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[Assistant] Now, if this is our property in plan view, this is in section view, we can also use the property filter. Again, go to the same place. The settings for the properties folder, the filter tab, make sure use index filter is not checked. Make sure use value filter is checked. Come down here and check a property. Then on the right side, click use filter.


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[Assistant] Color this pink not only here in this window, but also in our 3D grid. And now when we look in plan view.


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[Assistant] This is only porosity above 15% in section view. This is only porosity above 15%.


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[Assistant] Now we can also get statistics on them and we can even use the filter to make sure we only get the values that we want. So bring up the settings for whatever property we want to get the


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[Assistant] We bring up the settings for porosity, go to the statistics tab.


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[Assistant] This button right here, if it is, does not have an orange background, it's not using this filter, so you're getting statistics for all of these zones. If you click this so it has an orange background, then the numbers here will change and you will only be getting statistics depending on what the filter has been set right here. Similarly, this right here, the zone of interest.


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[Assistant] If you check that box, you can put in just what zone you want to see. If this is not checked, it's going to show you the statistics on all the zones in your project.


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[Assistant] This button right here will allow you to copy all of this information to the Microsoft Clipboard and paste it into Excel or some other application.


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[Assistant] Since we're working with properties, click this middle one of the five players, because that's the property player. Then, down here at the bottom, weeds.


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[Assistant] Then, since we have the property player, we can filter it in just the IJ or K direction by clicking on one of these. And that looks like this over here to the left. The I direction just filters in one I direction cell.


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[Assistant] One J direction or one K. Whichever one is up, then we can use these arrows to move back and forth in our model and so we can see what our property looks like throughout the entire model.


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[Assistant] Uhm, again, you both are amazing chefs. And, uh, Harold, I love working with you, man. So, you're my choice.


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[Assistant] Harold, he opened it up to us. It becomes more of a team challenge.


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[Assistant] I respect Tiffany for that, I was like, wow. Go girl, you know? So do we.


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[Assistant] Get to this place without the support of his coworkers and his castmates.


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[Assistant] There's four of us and we're damn near close to being in the finals. I don't feel an overwhelming obligation to be the closest of friends with the other people in this house.


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[Assistant] I didn't see that coming. We're going to Napa and truffles and this unbelievable Schaeffer wine. The chefs that we were going to be cooking for was a treat that was reserved for the people who had made it to the top four.


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[Assistant] There's only so much you can kick yourself in the ass for what you've done. And uhm, I just didn't have the time.


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[Assistant] And then all those are paired together with a lamb peri-jour sauce.


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[Assistant] My time management today was not spectacular. My technique suffered because of my time management. But uhm, I stand by my food. I stand by what it was in the time that was allotted and the resources that I was given.


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[Assistant] And the wine, it was fine to me in my head. Uhm, I went back and tasted it again and...


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[Assistant] It was a bit of a shocker that Leanne and I were together at that table. I think going in, everyone expected Dave to be in the bottom two.


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[Assistant] I've been absolutely true to myself through this entire competition and what that means is that I bring


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[Assistant] My food's been good all the way through this competition and I stand behind my food. I'm very proud of the things that I've done here. So for those reasons, I think that I've earned my ticket to Vegas.


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[Assistant] Leanne and I have very, very different philosophies. I get knocked for being...


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[Assistant] And the thing is, I'm a good person. I'm a nice person. And I don't feel like that's what I came here to prove. I came here to prove that I can cook. And that's what I did.


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[Assistant] I think so too, I like that. If you're gonna do risotto, I think.


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[Assistant] Dragons Love Tacos by Adam Rubin Illustrated by Daniel Salmieri


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[Assistant] Hey kid, did you know that dragons love tacos?


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[Assistant] They love beef tacos and chicken tacos. They love really big gigantic tacos and tiny little baby tacos as well.


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[Assistant] Why do dragons love tacos? Maybe it's the smell from the sizzling pan. Maybe it's the crunch of the crispy tortillas. Maybe it's a secret.


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[Assistant] Either way, if you want to make friends with dragons, tacos are key. Hey dragon, why do you guys love tacos so much? They are super delicious! But wait!


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[Assistant] As much as dragons love tacos, they hate spicy salsa even more.


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[Assistant] They hate spicy green salsa and spicy red salsa. They hate spicy chunky salsa and spicy smooth salsa. If the salsa is spicy at all, dragons can't stand it.


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[Assistant] Just one drop of hot sauce makes a dragon's ears smoke.


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[Assistant] Just one single speck of hot pepper makes a dragon snort sparks.


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[Assistant] Spicy salsa gives dragons the tummy troubles. And when dragons get the tummy troubles, oh boy.


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[Assistant] If you want to make tacos for dragons, keep the toppings mild. Tomatoes, check. Lettuce, check. Cheese, check. These are all good toppings for tacos for dragons.


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[Assistant] Hey dragon, how do you feel about spicy taco toppings?


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[Assistant] Dragons love parties. They like costume parties. And pool parties.


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[Assistant] They like big gigantic parties with accordions and tiny little parties with charades.


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[Assistant] The only thing dragons love more than parties or tacos is taco parties. Taco parties are parties with lots of tacos.


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[Assistant] If you wanna have some dragons over for a taco party, you'll need buckets of tacos. Pantloads of tacos.


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[Assistant] The best way to judge is get a boat and fill the boat with tacos.


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[Assistant] That's about how many tacos dragons need for a taco party. After all, dragons love tacos. Hey dragon, are you excited for the big taco party? Oh my gosh, I can't wait, I'm so excited!


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[Assistant] Just remember, dragons hate spicy salsa.


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[Assistant] Before you host your taco party with dragons, get rid of all the spicy salsa. In fact, bury the spicy salsa in the backyard so the dragons can't find it.


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[Assistant] These dragons love your taco party. They love the music.


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[Assistant] They love the decorations. They especially love the tacos. Congratulations!


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[Assistant] It's a good thing you got rid of all that spicy- Wait a second. What are all those little green things in the salsa? You didn't read the fine print?


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[Assistant] Those little green specks in the salsa, those are jalapeno peppers. They are super spicy!


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[Assistant] I know you love tacos, dragons, but you are not gonna love those tacos. Attention! Do not let those dragons eat those tacos! Crunch. Crunch. Crunch.


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[Assistant] Why would dragons help you rebuild your house? Maybe they're good samaritans. Maybe they feel bad for wrecking it. Maybe they're just in it for the taco breaks.


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[Assistant] Hey guys, thanks for watching. We hope you love this story. Dragons love tacos. It's one of our favorites. If you did, please click the thumbs up button, share this with your friends, and don't forget to subscribe. Thanks.


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[Assistant] I don't know, what type of seaweed. It's like a chili paste. I'm gonna go with chili paste next.


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[Assistant] I thought it was risky, but, you know, I'm a strong believer in going with the best available products. And the tutorial was gorgeous. And I thought, you know what, maybe we can educate some people along the way while we're out there.


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[Assistant] It was a little emotional when we found out Lisa was going home. I mean, she's like the mom of the house.


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[Assistant] Might have definitely brought it together. That jicama sounds crunchy and delicious.


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[Assistant] This couple is going through a model house now. The husband apparently isn't very keen about it all, but his wife is entranced by such convenient features as the sturdy built-in ironing board.


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[Assistant] Four days of rioting, looting, and arson rocked the city of Detroit in the worst outbreak of urban racial violence this year.


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[Assistant] I'm a ballerina by Sue Fleece. Illustrated by Joey Chu. Ballet lessons. Time to go. We head for the studio.


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[Assistant] First, we balance on the bar, leaning over, reaching far, stretching arms and legs out long.


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[Assistant] Ballet dancers must be strong.


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[Assistant] We've been working hard all year. Our recitals finally here. Last rehearsal for the show. Get it right from head to toe. Twist my hair up in a bun. Getting dressed is half the fun. Tutu, tights, a crown, some bows. Mom puts powder on my nose.


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[Assistant] Ballet slippers for my feet. Now my costume is complete. My recital starts at eight. Hurry up. We can't be late. The music is about to start. What if I forget my part? Take some deep breaths. You'll be great. I breathe in and stand up straight.


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[Assistant] Fix my tutu. Tug my tights. My instructor dims the lights. We hope our show will be a hit. Curtains open. This is it. That's my number. Here I go. I can't believe I'm in a show.


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[Assistant] Gracefully we bend and rise.


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[Assistant] Arms like wings of butterflies. Perfectly, I pirouette. But the show's not over yet. Glide and twirl. Leap and land. All the parents clap and stand. Time for me to take a bow. I'm a ballerina now.


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[Assistant] Pete the Cat put on his favorite shirt with four big, colorful, round, groovy buttons.


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[Assistant] He loved his buttons so much, he sang this song.


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[Assistant] One of the buttons popped off and rolled away.


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[Assistant] How many buttons are left?


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[Assistant] 4 minus 1 equals 3. Did Pete cry?


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[Assistant] Buttons come and buttons go.


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[Assistant] Another button popped off and rolled away.


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[Assistant] How many buttons are left?


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[Assistant] 3 minus 1 equals 2. Did Pete cry?


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[Assistant] Buttons come and buttons go. He kept on singing his song.


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[Assistant] Another button popped off and rolled away.


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[Assistant] How many buttons are left?


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[Assistant] Two minus one equals one. Did Pete cry?


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[Assistant] Buttons come and buttons go.


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[Assistant] He kept on singing his song.


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[Assistant] Oh no! The last button popped off and rolled away!


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[Assistant] How many buttons are left?


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[Assistant] 1 minus 1 equals 0. Did Pete cry?


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[Assistant] Buttons come and buttons go.


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[Assistant] And he kept on singing his song.


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[Assistant] I guess it simply goes to show that stuff will come and stuff will go. But do we cry? Goodness, no.


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[Assistant] You're just in time, Lily. Little pirate's ready to do his trick.


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[Assistant] Who caters a wedding out of a supermarket? That's unheard of. That's ridiculous. You have specialty purveyors that you go to. That specialize.


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[Assistant] Start filling some salmon, cleaning them up, get them ready. I wasn't happy with my salmon, you know, it was an Atlantic salmon. It doesn't have the color, it's not meaty, it's not sweet.


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[Assistant] You gotta, you gotta, you gotta, you gotta separate the two every once in a while though. Whatever Stephen's doing. I pulled him aside. Listen.


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[Assistant] You know, I think I threw the idea out there. I've used cake mix, you know, before and I've been satisfied with it.


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[Assistant] She did the right thing in a lot of different ways that, you know, people that weren't in the kitchen sat in the dining room couldn't feel. But from a, you know, cook's standpoint, uhm, you know, she definitely earned my respect.


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[Assistant] Written by Laura Numeral. Illustrated by Felicia Bogg.


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[Assistant] He'll ask for some sprinkles to go with it. Uh, can I have some sprinkles? When you give him the sprinkles, he might spill some on the floor. I'm so sorry. Cleaning up will make him hot. So, you'll have to give him a bathing suit. And take him to the beach. Time for swimming. He'll want to go in the water. Definitely. And build a sandcastle too.


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[Assistant] Can you help me with this? Then, he'll look for sea shells. Check these out!


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[Assistant] Dinosaurs! The T-Rex is awesome! Then, he'll visit the Hall of Eats!


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[Assistant] I wanna swing like they are. Can we stay a little longer?


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[Assistant] When you get home, he'll empty the sand from his shoes. He might spill some on the floor. I'm sorry about that.


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[Assistant] Yep, it's just you two, me and the deep blue sea lily. So we may as well enjoy it.


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[Assistant] It's a piece of cloth us sailors use to check the direction of the wind. Hold it up.


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[Assistant] Little Owl's Night by Divya Srinivasan Little Owl was having a wonderful night.


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[Assistant] He watched the funny possum family waddle along in a neat row. Hedgehog sniffed around the mushroom patch.


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[Assistant] Skunk was eating berries because he could find no snails.


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[Assistant] Turtle hid in her shell as fireflies danced all around.


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[Assistant] As they sat in the clover, fog rolled in and hovered just overhead.


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[Assistant] Moths flutter towards the moon. Silver dust fell from their wings.


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[Assistant] Little owl wanted to follow, but it was time to head home.


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[Assistant] Little owl sang, I want to show you the moon. But the bear kept snoring as usual. Little owl flew home to his tree gazing at the sky. He wondered if the bear had ever seen stars.


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[Assistant] Little Owl sat on his branch. How he loved the night forest!


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[Assistant] Frog gropes softly. Cricket chirps smartly.


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[Assistant] Little owl heard rustling at the foot of his tree. Fox had come to say hello.


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[Assistant] You're right buddy, my dear. We rabbit won't think to look for me here.


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[Assistant] You've just given me an idea. Clever girl.


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[Assistant] Hi, Lily. Hiyawee, Robbie. That's a pretty painting.


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[Assistant] It's the view from my tree house. We need to get as high as we can to see the starfish in the sky. Do you mean this starfish? We've come to the right place.


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[Assistant] Salty, I've been trying to see the starfish constellation. I've got as close as I can to this guy, but I still can't see anything.


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[Assistant] And I can show you the starfish constellation, dad.


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[Assistant] Today we're going to read a book about a mischievous little elf. It's called There's an Elf in Your Book by Tom Fletcher. Illustrated by Greg Abbott.


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[Assistant] Oh look, there's an elf in your book.


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[Assistant] Elf's here to do the nice list test with you.


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[Assistant] You need to be on the nice list if you want Santa to bring you Christmas presents.


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[Assistant] For you to pass the test, Elf will ask you to do some nice things. But, watch out. Elves can be a bit mischievous.


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[Assistant] Don't get tricked into being naughty. Okay?


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[Assistant] When you're ready to take the test, turn the page. Good luck.


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[Assistant] To see if you pass the test, turn the page.


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[Assistant] Good job! You passed the first test. Now, blow a Christmas kiss.


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[Assistant] What a lovely Christmas kiss. You passed the second test. What's next?


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[Assistant] Beautiful singing. You passed the third test. Now...


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[Assistant] Say, I'm a Weisenheimer sparkle butt.


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[Assistant] Wait a second. This sounds like a naughty trick. I think Elf is testing you.


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[Assistant] Don't say, I'm a Weisenheimer sparkle butt. Now turn the page.


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[Assistant] Phew! It was a trick. Thank goodness you didn't say it. You passed the fourth test.


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[Assistant] How is the nice list test going so far, elf?


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[Assistant] Name Santa's most famous reindeer.


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[Assistant] Rudolph, correct. You passed the fifth test. You're great at this. Now,


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[Assistant] Do your loudest, stinkiest pizza burp.


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[Assistant] Do you think this is another naughty elf trick?


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[Assistant] It was another trick. Good catch. Keep this up, and you'll be on the nice list in no time.


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[Assistant] To make Alf laugh, you'll have to tell a joke. Have a look in the Christmas Joke Book.


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[Assistant] The joke was a mischievous elf trick to make you say something naughty.


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[Assistant] Surely you can't be on the nice list if you've done something naughty.


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[Assistant] It looks as though Elf feels bad for tricking you. But rules are rules.


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[Assistant] Hang on a second. The test was to make Elf laugh. And you did. So... You passed the nice list test.


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[Assistant] Hooray, you are officially on the nice list. And look, what's this? Wow.


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[Assistant] It's your official Nice List Certificate. Make sure you leave this book out on Christmas Eve. Santa will want to check it.


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[Assistant] Until then, Merry Christmas. Stay nice. Bye, elf.


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[Assistant] I'm so glad you passed the elf's test. Remember to keep up your good behavior so you can stay on Santa's nice list. Subscribe to see more stories posted every week.


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[Assistant] Or find more books to read yourself at readbrightly.com. Bye!


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[Assistant] Well, you see, I know what to wear out at sea.


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[Assistant] It smells just dandy to me, Lily. No, no I really have to go.


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[Assistant] Moldering mudskippers, Lily. My honking haddock aftershave smells just fine. Will you please leave me in peace? Now, I'm having lunch with a very special hen.


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[Assistant] But not everyone is a sea dog's nose. Can you forgive me?


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[Assistant] And benign near-infrared light, go right through your hand. Just like this. This fact could enable better, faster and cheaper health care.


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[Assistant] Our translucence is key here.


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[Assistant] I'm going to show you how we use this key and a couple of other keys to see deep inside our bodies and brains. Okay, so first up,


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[Assistant] The light goes right through my hand, if we could bring the lights down, please, as I've already shown. But you can no longer see that laser spot. You see my hand glow. That's because the light spreads out. It scatters. I need you to understand what scattering is so I can show you how we get rid of it and see deep inside our bodies and brains. So I've got a piece of chicken back here.


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[Assistant] Put on some gloves. It's got the same optical properties as human flesh.


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[Assistant] So, here's the chicken. Put it in on the light. Can you see the light goes right through?


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[Assistant] I also implanted a tumor in that chicken. Can you see it?


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[Assistant] So this means, using red light and infrared light, we can see tumors in human flesh. But there's a catch. When I throw another piece of chicken on it, the light still goes through, but you can no longer see the tumor. That's because the light scatters.


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[Assistant] So we have to do something about the scatter so we can see the tumor. We have to de-scatter the light. So ...


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[Assistant] A technology I spent the early part of my career on enables de-scattering. It's called holography.


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[Assistant] And it won the Nobel Prize in Physics in the 70s because of the fantastic things it enables you to do with light. This is a hologram. It captures


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[Assistant] All of the light, all of the rays, all of the photons at all of the positions and all of the angles simultaneously. It's amazing. To see what we can do with holography


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[Assistant] You see these marbles? Look at these marbles bouncing off of the barriers as an analogy to light being scattered by our bodies.


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[Assistant] They're chaotic. They're scattering and bouncing everywhere.


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[Assistant] If we record a hologram at the bottom inside of the screen, we can record the position and angle of each marble exiting the maze. And then we can bring in marbles from below.


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[Assistant] And have the hologram direct each marble to exactly the right position and angle, such as they emerge in a line at the top of the scatter matrix. We're going to do that with this. This is optically similar to human brain. I'm going to switch to green light now.


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[Assistant] Because green light is brighter to your eyes than red or infrared, and I really need you to see this. So we're going to put a hologram in front of this brain and make a stream of light come out of it.


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[Assistant] No one's done this before. You're the first public audience to ever see this.


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[Assistant] What this means is that we can focus deep into tissue. Our translucency is the first key.


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[Assistant] Holography enabling de-scattering is the second key to enable us to see deep inside of our bodies and brains. You're probably thinking, sounds good, but what about skull and bones? How are you going to see through the brain without seeing through bone? Well, this is real human skull.


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[Assistant] No kidding. But we treat this skull with great respect at our lab and here at TED. And as you can see, the red light goes right through it.


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[Assistant] Goes through our bones, so we can go through skull and bones and flesh with just red light.


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[Assistant] Gamma rays and x-rays do that too, but they cause tumors. Red light is all around us. So ...


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[Assistant] Using that, I'm going to come back here and show you something more useful than making a brainless.


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[Assistant] We challenged ourselves to see how fine we could focus through brain tissue. Focusing through this brain


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[Assistant] It was such a fine focus, we put a bare camera die in front of it. And the bare camera die


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[Assistant] That means that spot focus, full width, half max, is six to eight microns. To give you an idea of what that means,


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[Assistant] That's the diameter of the smallest neuron in the human brain. So that means we can focus through skull and brain to a neuron.


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[Assistant] Just to give an idea, like that's not just 50 marbles, that's billions, trillions of photons all falling in line as directed by the hologram to ricochet through densely scattering brain and emerge as a focus. So, it's pretty cool. We're excited about it.


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[Assistant] So this is an MRI machine. It's a few million dollars. It fills a room. Many people have probably been in one, have spent a lot of time in one. It has a focus of about a millimeter. Kind of chunky compared to what I just showed you.


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[Assistant] So a system based on our technology could enable dramatically lower cost, higher resolution and smaller medical imaging. So that's what we've started to do. My team and I have built a rig, a lab rig, to scan out tissue. And here it is in action. We wanted to see how good we could do. We've built this over the last year.


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[Assistant] In this sample, 70 millimeters deep, the light going in here.


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[Assistant] Half a millimeter resolution, and that's the tumor it found. So, you're probably looking at this, and it's like, sounds good.


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[Assistant] But that's kind of a big system. It's smaller than a honking big MRI machine.


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[Assistant] The last two decades, inventing, prototype, developing and then shipping.


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[Assistant] Billions of dollars of consumer electronics with full custom chips on the hairy edge of optical physics. So my team and I built the big lab rig to


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[Assistant] Perfect our architecture and test the corner cases and really fine-tune our chip designs before spending the millions of dollars to fabricate each chip.


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[Assistant] Our new chip inventions slimmed down the system.


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[Assistant] Speed it up and enable rapid scanning and de-scattering of light to see deep into our bodies. So this is the third key to enable better, faster and cheaper health care.


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[Assistant] of something that can replace the functionality of a multimillion-dollar MRI machine.


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[Assistant] Into a consumer electronics price point that you could wear as a bandage, line a ski hat, put inside a pillow. That's what we're building. Oh thanks.


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[Assistant] So you're probably thinking, I get the light going through our bodies. You can get the holography de-scattering the light.


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[Assistant] But how do we use these new chip inventions, exactly, to do the scanning? Well, we have a sound approach. No, literally, we use sound.


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[Assistant] So here, these three disks represent the integrated circuits that we've designed that massively reduce the size of our current bulky system.


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[Assistant] One of the spots, one of the chips emits a sonic ping, and it focuses down, and then we turn red light on.


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[Assistant] And the red light that goes through that sonic spot changes color slightly.


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[Assistant] There's this other thing about holography I haven't told you yet, but you need to know.


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[Assistant] Only two beams of exactly the same color can make a hologram. So ...


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[Assistant] From that hologram, we can extract information just about that sonic spot, because we filter out all of the red light.


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[Assistant] Then we can optionally focus the light back down into the brain to stimulate a neuron or part of the brain. And then we move on to


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[Assistant] Shift the sonic focus to another spot, and that way, spot by spot, we scan out the brain.


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[Assistant] Our chips decode holograms a bit like Rosalind Franklin decoded this iconic image of X-ray diffraction to reveal the structure of DNA for the first time.


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[Assistant] We're doing that electronically with our chips, recording the image and decoding the information in a millionth of a second. We scan fast.


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[Assistant] Our system may be extraordinary at finding blood. And that's because blood absorbs red light and infrared light. Blood is red. Here's a beaker of blood I'm going to show you.


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[Assistant] And here's our laser going right through it. It really is a laser. You can see it on the, there it is. In comparison to my pound of flesh, where you can see the light goes everywhere. So let's see that again. Blood. This is really key. Blood absorbs light. Flesh scatters light.


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[Assistant] This is significant because every tumor bigger than a cubic millimeter or two has five times the amount of blood as normal flesh.


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[Assistant] So with our system, you can imagine detecting cancers early when intervention is easy.


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[Assistant] Or tracking the size of your tumor as it grows or shrinks.


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[Assistant] Our system also should be extraordinary at finding out where blood isn't, like a clogged artery.


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[Assistant] Or the color change in blood as it carries oxygen versus not carrying oxygen, which is a way to measure neural activity.


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[Assistant] There's a saying that sunlight is the best disinfectant. It's literally true.


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[Assistant] Researchers are killing pneumonia in lungs by shining light deep inside of lungs. Our system could enable this non-invasively.


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[Assistant] And let me give you three more examples of what this technology can do. One, stroke. There's two major kinds of stroke.


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[Assistant] The one caused by clogs and another caused by rupture. If you can determine the type of stroke within an hour or two,


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[Assistant] You can give medication to massively reduce the damage to the brain. Get the drug wrong, and the patient dies.


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[Assistant] Today that means access to an MRI scanner within an hour or two of a stroke.


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[Assistant] Tomorrow, with compact, portable, inexpensive imaging,


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[Assistant] Every ambulance in every clinic can decode the type of stroke and get the right therapy on time.


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[Assistant] Compact, portable, inexpensive medical imaging can save countless lives. And three, brain-computer communication.


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[Assistant] I've shown here on stage our system focusing through skull and brain to the diameter of the smallest neuron.


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[Assistant] Using light and sound, you can activate or inhibit neurons. And simultaneously, we can match spec by spec the resolution of an fMRI scanner, which measures oxygen use in the brain.


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[Assistant] We do that by looking at the color change in the blood rather than using a two-ton magnet. So, you can imagine


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[Assistant] We can decode the imagined words, images and dreams of those being scanned.


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[Assistant] We're working on a system that puts all three of these capabilities into the same system. Neural read and write with light and sound, while simultaneously mapping oxygen use in the brain.


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[Assistant] Altogether, in a non-invasive portable that can enable brain-computer communication, no implants, no surgery, no optional brain surgery required, this can do enormous good.


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[Assistant] For the two billion people that suffer globally with brain disease.


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[Assistant] So people ask me how deep we can go, and the answer is the whole body is in reach. But here's another way to look at it.


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[Assistant] What's truly scary is not knowing about our bodies, our brains and our diseases so we can effectively treat them. This technology can help. Thank you.


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[Assistant] Atsy, Atsy, can you take me up to Lord Stagg's castle please? I'm doing some break dancing at his very interesting thing show. Break dancing?


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[Assistant] Our dear Hatsy, we've all realized that we've asked you to do too much. Aye.


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[Assistant] We watched it for a few seconds, then it shot away incredibly quickly. Even as a kid, I got angry. It was ignoring the laws of physics.


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[Assistant] We ran inside to tell the grown-ups and they were skeptical. You'd be skeptical too, right?


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[Assistant] Extraterrestrial civilizations could have started in the summer months. Imagine a summer civilization


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[Assistant] More advanced and hostile neighbor. There'll be worlds where, for whatever reason, civilizations either stay silent or don't spend long trying to communicate.


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[Assistant] Some say a summer civilization did colonize the galaxy and seeded Earth with life.


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[Assistant] Others that were living in a cosmic wilderness preserve, a zoo. Yet others that were living in a simulation. Programmers just haven't revealed the aliens yet.


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[Assistant] The outcome of that crash could have been a quite different Earth-Moon system. We ended up with a large moon.


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[Assistant] Vogue factors influence climate, and the suggestion is that they've helped moderate climate change. Great for us, right?


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[Assistant] Complex life forms must arise. A thousand becomes one.


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[Assistant] To reach the stars, there'll have to be social creatures capable of discussing abstract concepts with each other, using a complex grammar. One planet in a billion galaxies.


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[Assistant] And they have to avoid disaster, not just self-inflicted, but from the skies too. That planet around Proxima Centauri, last year it got blasted by a flare. One planet in a trillion galaxies, just those in the visible universe.


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[Assistant] Shush, bovin'. Help me open this here chest.


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[Assistant] I, and in all my years it's never lost a minute. Land ho!


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[Assistant] There you are, young lily. You've just missed Hatsy. That hay never stops.


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[Assistant] I did, Lily. It was in your toy box all the time.


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[Assistant] You know how people tell you, if you get nervous when on stage, picture people in the audience naked. Like it's this thing that's supposed to make you feel better.


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[Assistant] But I was thinking, picturing all of you naked in 2018 feels kind of weird and wrong. Like, we're working really hard on moving past stuff like that. So we need a new method of dealing with if you get nervous on stage. And I realized that what I'd really like


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[Assistant] Is that I can look at you as much as you're looking at me. Just to like even things out a little bit. So if I had way more eyeballs, then we'd all be really comfortable, right?


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[Assistant] So in preparation for this talk, I made myself a shirt.


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[Assistant] It took me 14 hours and 227 googly eyes to make this shirt. And being able to look at you as much as you're looking at me, it's actually only half of the reason I made this. The other half is being able to do this.


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[Assistant] Uh, I call it the toothbrush helmet.


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[Assistant] So my toothbrush helmet is recommended by zero out of 10 dentists, and it definitely did not revolutionize the world of dentistry. But it did completely change my life.


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[Assistant] Because I finished making this tube-thrush helmet three years ago, and after I finished making it, I went into my living room and I put up a camera, and I filmed a seven-second clip of it working.


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[Assistant] And by now, this is a pretty standard modern-day fairy tale of girl posting on the internet. The internet takes the girl by storm. Thousands of men voyage into the comments sections to ask for her hand in marriage. She ignores all of them, starts a YouTube channel and keeps on building robots.


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[Assistant] Since then, I've carved out this little niche for myself on the internet as an inventor of useless machines. Because as we all know, the easiest way to be at the top of your field is to choose a very small field.


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[Assistant] As an engineer, I did not study engineering in school, but I was a super ambitious student growing up. In middle school and high school, I had straight A's and I graduated at the top of my year. On the flip side of that, I struggled with very severe performance anxiety.


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[Assistant] Here's an email I sent to my brother around that time. You won't understand how difficult it is for me to tell you, to confess this. I'm so freaking embarrassed. I don't want people to think that I'm stupid. Now I'm starting to cry too. Damn.


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[Assistant] Beautiful time indeed. But moreover, I got interested in building robots, and I wanted to teach myself about hardware.


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[Assistant] But building things with hardware, especially if you're teaching yourself, is something that's really difficult to do. It has a high likelihood of failure, and moreover, it has a high likelihood of making you feel stupid. And that was my biggest fear at the time.


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[Assistant] So I came up with a setup that would guarantee success 100 percent of the time. With my setup, it would be nearly impossible to fail. And that was that instead of trying to succeed, I was going to try to build things that would fail.


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[Assistant] And even though I didn't realize it at the time, building stupid things was actually quite smart.


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[Assistant] Because as I kept on learning about hardware, for the first time in my life, I did not have to deal with my performance anxiety.


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[Assistant] And as soon as I removed all pressure and expectations from myself, that pressure quickly got replaced by enthusiasm, and it allowed me to just play.


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[Assistant] So as an inventor, I'm interested in things that people struggle with. It can be small things or big things or medium-sized things. And something like giving a TED talk presents this whole new set of problems that I can solve. And identifying a problem is the first step in my process of building a useless machine.


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[Assistant] So before I came here, I sat down and I thought of some of the potential problems I might have in giving this talk. Forgetting what to say, that people won't laugh, that's you, or even worse, that you'll laugh at the wrong things. That was an OK part to laugh at, thank you.


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[Assistant] Or that when I get nervous, my hands start shaking, and I'm really self-conscious about it. Or that my fly has been open this entire time, and all of you noticed, but I didn't. But it's close, so we're all good on that one.


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[Assistant] But one thing I'm actually really nervous about is my hands shaking. I remember when I was a kid, giving presentations in school, I would have my notes on a piece of paper, and I would put a notebook behind the paper, so that people wouldn't be able to see the paper covering. And I give a lot of talks.


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[Assistant] Uhm, I know that about half of you in the audience are probably like,


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[Assistant] Building useless machines is really fun, but how is this in any way or form a business? And giving talks is a part of it.


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[Assistant] And the arrangers always put out a glass of water for you on stage so you have something to drink if you get thirsty. And I always so badly want to drink that water, but I don't dare to pick the glass up because then people might be able to see that my hands are shaking.


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[Assistant] So what about a machine that hands you a glass of water? Sold to the nervous girl in the googly eye shirt. Actually, I need to take this off, because I have a thing.


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[Assistant] I still don't know what to call this, but I think some sort of like head orbit device, because it rotates this platform around you, and you can put anything on it. You can have like a camera, you can get photos of your entire head. Like it's really, it's a very versatile machine.


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[Assistant] Still need to work on this machine a little bit because I still need to pick up the glass and put it on the platform. But if your hands are shaking a little bit, nobody's going to notice because you're wearing a very mesmerizing piece of equipment. So it's, we're all good. Okay. Ayayayaya. Oh no, get stuck.


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[Assistant] So as much as my machines can seem like simple engineering slapstick, I realized that I stumbled on something bigger than that.


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[Assistant] It's this expression of joy and humility that often gets lost in engineering. And for me, it was a way to learn about hardware without having my performance anxiety get in the way.


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[Assistant] And I often get asked if I think I'm ever going to build something useful. And maybe someday I will.


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[Assistant] But the way I see it, I already have, because I've built myself this job.


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[Assistant] It's something that I could never have planned for, instead it happened just because I was enthusiastic about what I was doing, and I was sharing that enthusiasm with other people.


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[Assistant] To me, there's a true beauty of making useless things, because it's this acknowledgement that you don't always know what the best answer is.


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[Assistant] And it turns off that voice in your head that tells you that you know exactly how the world works. And maybe a toothbrush helmet isn't the answer, but at least you're asking the question. Thank you.


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[Assistant] And he grabbed that bolt actually went shh shh and I watched the rifle shell go in the barrel and.


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[Assistant] He lunged it towards me and hit me right here.


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[Assistant] To start off with, click on this icon over here in the utilities area of one of the ribbons. It's called Make Polygons is what the tooltips is.


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[Assistant] If you would like to replace a file that's already out there, a line file, highlight its name and put it in here in results.


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[Assistant] Or, if you want to just make one with a specific name, put a check mark in the box in front of name, type in the name that you want to create here.


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[Assistant] We're going to pick rectangles. So this is alright. Make 16 points in the circles, make it a constant radius. We could make it oval shaped if we want. And it's going to be a radius of 100. This is a meters project. This 100 is in meters. If this is a feet project, this 100 is in feet.


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[Assistant] Turn them on only in that folder, we can see yes. Just those in that folder are inside that polygon. Repeat this procedure with the other two polygons. Right click, move wells inside this, choose which wells you want to move. The second folder is created.


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[Assistant] And once again we can display and make sure only the correct ones are inside it. Same with the third. Move wells inside the polygon. Choose the wells.


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[Assistant] I suppose I could set it up for you. That would save you some money. If you get the forms, I'll prepare them for you, nearly free of charge. I'd only ask three beers apiece for each of my co-workers.


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[Assistant] Coworkers, get him, that's rich, ain't it? I think a man working outdoors feels more like a man if he can have a bottle of suds. That's only my opinion. Sir.


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[Assistant] Want a cold one, Andy? No, thanks. I came up drinking.


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[Assistant] People gave him shit. That's how he put it. So, one night like a joke.


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[Assistant] Today, we are going to show you different ways to reveal deepwater sediments from seismic using Petrel 2014. As you all know,


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[Assistant] Deep water sediments such as turbidites or mass flows can be a reservoir for hydrocarbon.


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[Assistant] But they are often very difficult to find and evaluate from seismic.


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[Assistant] Is to interpret manually the major sequences to delineate compartments.


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[Assistant] And describe the internal architecture of the bodies.


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[Assistant] The challenge here is to be able to do this more efficiently and accurately in one platform.


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[Assistant] It is exactly what you are going to see today. First, we will show you the 3D seismic and the reconnaissance of it to find and see the deep water sediments.


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[Assistant] Then, we will show you the major seismic sequences delineated and defining the level of compartmentalization.


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[Assistant] Finally, you will see the description of the internal architecture of the identified bodies.


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[Assistant] Now let's move to Petrel and see how using all the knowledge and the new capabilities of 2014, it can help you reveal the Deepwater Sediments from Seismic.


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[Assistant] Here is displayed a 2D seismic survey in the campus basin offshore Brazil.


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[Assistant] The seabed and the myosin-oligosin and conformity has been interpreted.


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[Assistant] Petrel can be directly connected to Geofacets database from Elsevier.


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[Assistant] Accessing more than 350,000 references.


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[Assistant] Here, we are searching all the relevant content referring to lobes in the campus basin.


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[Assistant] It displays directly all the content geolocalized, like this map of the main loop systems.


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[Assistant] Preserving all the information of the original publication, saving you time and effort.


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[Assistant] The map can be found quickly in the project using the new search tool.


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[Assistant] Draping it onto the horizon interpreted from the 2D shows better the extension of the lobes at the level of interest, just above the inconformity interpreted.


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[Assistant] Only the unique combination of Petrel and Elsevier through studio environment provides you the right insight to carry on your interpretation confidently.


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[Assistant] Now that we have confirmed the trend and the shape of the lobes, let's have a look at the 3D seismic and try to reveal these mass flows.


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[Assistant] When doing a reconnaissance of the 3D seismic, the first thing that the interpreter often does is an attribute computation. We will show you something more advanced. The decomposition of the seismic signal


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[Assistant] Such as a frequency extraction to identify geological features. But as you may know,


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[Assistant] It is difficult to choose which range of frequencies to extract To help you screening your seismic content


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[Assistant] Here, looking at the bandwidth over the potential turbidites, you can see the dominant frequency range.


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[Assistant] Now choosing the right frequency to extract become easy.


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[Assistant] On the right are the envelope of the three frequencies extracted from the volume attribute.


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[Assistant] See how the response of the channel and other features are different in the three cases.


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[Assistant] Looking at them separately is inadequate.


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[Assistant] By RGB blending the three frequencies together using the GeoBody interpretation tool in Petrel, it allows us to recognize and highlight clearly stratigraphical features such as channels.


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[Assistant] But some features on the side are still unclear.


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[Assistant] To have a full definition of the environment, a frequency decomposition is not enough.


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[Assistant] Wouldn't be good to be able to combine it with an edge attribute?


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[Assistant] Let me show you the result of a structural decomposition based on an edge detection approach.


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[Assistant] On the right, you can see the RGB blending of three amplitude contrast attributes with different vertical operators.


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[Assistant] This rendering provides a sharp image of the structural and stratigraphical edges in the area.


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[Assistant] While panning through the volume using the new players, you can recognize the channel content on the left with a bright response of the frequency.


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[Assistant] And there are clear edges on the right from the amplitude contrast in white.


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[Assistant] Even more obvious, the SPLAY features that were not highlighted in the frequency decomposition.


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[Assistant] are completely revealed in the structural decomposition blending. It is simply stunning, thanks to the new visualization technology of Petrel.


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[Assistant] Down at the level of interest, it is now possible to completely see the turbidite system. With the presence of a low body on the left,


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[Assistant] Cut by two channels in the middle and on the right. Clearly defined in both views.


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[Assistant] This powerful combination of signal and structural decomposition provides you the right insight to start confidently the interpretation.


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[Assistant] Now the reconnaissance is done, we would like to share these seismic cubes with our interpreters team to help them start delineating the compartments.


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[Assistant] As you might have experienced in the past, sharing this kind of data is often difficult due to the size of the seismic.


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[Assistant] To solve this issue, we have enabled, in Petrel, the seismic compression to reduce drastically the size of the volumes.


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[Assistant] Controlled by a signal to noise ratio, the seismic can be compressed from 2.6 to 270 times of the original size, for example.


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[Assistant] This seismic was compressed from approximately 500 megabytes to 200 megabytes using the higher quality ratio.


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[Assistant] Petrel will read it and decompress it on the fly, which will speed up the process of visualization, calculations, and interpretation, especially through weak networks.


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[Assistant] So far, we have shown you the 3D seismic and how you are able to relate your work to external knowledge directly into your project for a better understanding of the geology of the area using Elsevier and Studio.


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[Assistant] And how linked to the best science of Petrel, it helps you to do an accurate reconnaissance using frequency spectrum, seismic attribute, and the best in-class core rendering volumes.


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[Assistant] Now let's see how all of these drive to a precise delineation and interpretation of the different compartments or bodies.


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[Assistant] As you see here on this blended frequency horizon, the deep water sediments are obvious.


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[Assistant] The challenge now is to be able to interpret the seismic sequences that defines the compartments.


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[Assistant] Let me select the right perspective to complete this task.


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[Assistant] Using the 2D interpretation as guide, some seismic sequences has been interpreted in 3D, as you can see here, displayed in Restrict View, on the inline and crossline.


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[Assistant] It looks good. However, we would like to quality control this interpretation.


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[Assistant] On the top left is the 3D view. On the bottom left, the classical base map.


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[Assistant] And on the right, a conventional 2D section with the seismic sequences.


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[Assistant] The best way to QC the interpretation would be to reconstruct these sequences at the initial depositional space using a geomechanical engine.


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[Assistant] You can see how the different sequences has been flattened.


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[Assistant] And separated from each other by simply running the reconstruction using the mini toolbar directly from the section.


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[Assistant] The 2D reconstruction tool respects geological rules, such as in conformity.


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[Assistant] Which provides you a realistic reconstruction of the environment.


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[Assistant] And update the reconstruction to understand the boundary of the bays.


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[Assistant] Now you can clearly see that the blue reflector is truncated by the red.


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[Assistant] The lobe compartment has been now accurately delineated.


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[Assistant] The quick access of the interpretation tools using the tool palette and the mini toolbar of the new user experience of Petrel 2014.


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[Assistant] Definitely increase the workflow productivity and help you focus on the data.


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[Assistant] Now, back to the 3D view. The lope has been picked in the traditional way, line by line.


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[Assistant] The challenge for the seismic interpreters is to fill the gaps using all the tools available.


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[Assistant] Let's use the new tracking tool that allows us to have a live trace while picking the horizon.


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[Assistant] This gives us much more control in areas with dipping reflectors. We will change the window.


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[Assistant] An orientation to track properly in the slope.


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[Assistant] Conventionally, tracking tools only work with amplitude priorities. By selecting the proximity, we constrain even more the tracking.


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[Assistant] Almost everybody can do a good tracking, but what we always want to do is to check the result of it and evaluate the quality.


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[Assistant] To measure how well the tracker was, let's display the confidence factor.


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[Assistant] It is obvious here that some area outside of the original interpretation has less confidence. So we will filter it out.


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[Assistant] See now how the lobe interpretation is accurate.


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[Assistant] We've showed you so far two fantastic ways to ensure the accuracy of the interpretation.


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[Assistant] One by using the live trace of the auto tracking tool and the other one filtering the attributes.


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[Assistant] Let me show you an approach to quality control all the previous step by flattening the entire 3D volume.


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[Assistant] Before computing the flattened cube, we will apply some transparency to see the sequence beneath to be flattened.


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[Assistant] The flattened cube is displayed on the right window. It is a virtual volume.


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[Assistant] Let's compute a variance attribute cube using the quick access to the processes in the mini toolbar.


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[Assistant] To verify the edges of the lobe in the flattened mode.


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[Assistant] The new user experience of Petrel allows you to work directly from your data, searching results without even going to the input or process pane, reducing the amount of clicks and the time spent finding data.


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[Assistant] Now see how the edges of the lobe and channel are clearly defined on the time slice of the variance cube, which definitely validate the interpretation.


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[Assistant] The next challenge will be to understand the internal architecture of these features.


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[Assistant] But first, let's come back to Powerpond to wrap up everything.


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[Assistant] So far, we have shown you how using the full capabilities of the seismic interpretation of Petrel, you are able to interpret seismic sequences using 2D reconstruction. Delineate them accurately with the auto-tracking capabilities such as live trace and proximity tracking.


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[Assistant] And QC it by flattening the entire volume. All of this into a brand new user experience that increases your workflow productivity.


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[Assistant] Now the compartments has been delineated, let's see how to describe the internal architecture of the loops seen previously.


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[Assistant] In order to do a proper fascist model for accurate volume estimation, it is obvious that geoscientists need to have a good understanding of the sedimentology.


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[Assistant] But what happens when the area have a limited amount of well as control points? The geoscientists can then only rely on the seismic.


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[Assistant] Here is the map of the top of the lobe, and the thickness of it.


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[Assistant] Obviously, using conventional surface attributes such as RMS, it is possible to start looking at the potential seismic fascist distribution.


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[Assistant] Let us show you a waveform classification workflow that helps getting more insight on the internal architecture.


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[Assistant] It slices the seismic from top to the bottom of the lobe.


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[Assistant] And extract the amplitude values as you can see here displayed sequentially.


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[Assistant] Take a look now to the four waveform extracted on the right.


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[Assistant] They were generated inside each compartment of the lobe.


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[Assistant] ...represented as a small seismic cube in the 3D view.


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[Assistant] Now we are going to show you the probability maps associated to each class.


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[Assistant] The final output of this workflow is a waveform classification map.


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[Assistant] Where, here, the colors are the type of waveform.


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[Assistant] You can recognize a different class's distribution. And even more important, you can estimate similar pattern across the different isolated compartments of the lobe. Very powerful.


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[Assistant] What we would like to do now is to extract the bodies of the classes from the seismic.


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[Assistant] Here you can see the frequencies blend with the stunning render of the GeoBody Interpretation tool of Petrel.


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[Assistant] Filtering the frequencies allows the isolation of a type of class that can be related to waveform showed before.


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[Assistant] Once we got the body, we will now extract it in full resolution, which gives you a very detailed and sharp chair body.


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[Assistant] Here you can see how the class 3 on the surface can be related to the geobody extracted in the lobe and the intersecting channel.


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[Assistant] The unique integration between these two advanced geophysical methods in one platform provide us enough insight to describe and extract the internal constitution of the deepwater sediments formation.


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[Assistant] The examples presented so far have shown some techniques to reveal deep water sediments from seismic using Petra 2014.


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[Assistant] The first thing that you have seen is how it is possible to do a fast and accurate reconnaissance of a large amount of data using a combination of the best sense in Petrel for signal and structural decomposition such as frequencies extraction and amplitude contrast attribute to identify the turbidites. The second thing that we have shown you


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[Assistant] Is how compartments can be delineated using a combination of 2D reconstruction with a geomechanical engine and auto tracking using live traces and proximity priorities.


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[Assistant] All of this driving to a validation of your interpretation of the seismic sequences.


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[Assistant] Then, we described the internal architecture of the lobe through waveform classification workflow and geobody extraction. Finally,


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[Assistant] We believe that in the years to come, the amount of data and techniques to work with INT will increase expansionally.


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[Assistant] To address this, the new user experience delivers a unique way to increase the day to day productivity, helping you focus on your customized workflow to gain critical insight from your data faster than ever before.


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[Assistant] And all of this in our shared earth platform, Petrel.


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[Assistant] Welcome to Brightly Storytime. I'm Miss Linda.


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[Assistant] Today we're going to read a book about new experiences and how they can be both exciting and overwhelming sometimes. It's called Oh the Places You'll Go by Dr. Seuss.


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[Assistant] Congratulations! Today is your day. You're off to great places. You're off and away. You have brains in your head. You have feet in your shoes.


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[Assistant] You can steer yourself any direction you choose. You're on your own. And you know what you know.


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[Assistant] And you are the guy who'll decide where to go.


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[Assistant] You'll look up and down streets. Look them over with care. About some you will say, I don't choose to go there.


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[Assistant] With your head full of brains and your shoes full of feet.


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[Assistant] You're too smart to go down any not so good street.


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[Assistant] And you may not find any you'll want to go down. In that case, of course, you'll head straight out of town. It's opener there in the wide open air.


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[Assistant] Out there, things can happen, and frequently do.


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[Assistant] To people as brainy and footsy as you. And when things start to happen, don't worry. Don't stew. Just go right along. You'll start happening too.


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[Assistant] You'll be on your way up. You'll be seeing great sights.


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[Assistant] You'll join the high flyers who soar to high heights. You won't lag behind because you'll have the speed.


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[Assistant] You'll pass the whole gang, and you'll soon take the lead.


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[Assistant] Wherever you fly, you'll be best of the best. Wherever you go, you will top all the rest.


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[Assistant] Except when you don't. Because sometimes you won't.


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[Assistant] I'm sorry to say so, but sadly it's true that bang-ups and hang-ups can happen to you.


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[Assistant] You can get all hung up in a prickly perch. And your gang will fly on. You'll be left in a lurch.


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[Assistant] You'll come down from the lurch with an unpleasant bump. And the chances are then that you'll be in a slump. And when you're in a slump, you're not in for much fun.


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[Assistant] Unslumping yourself is not easily done.


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[Assistant] You will come to a place where the streets are not marked. Some windows are lighted, but mostly they're darked.


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[Assistant] And if you go in, should you turn left or right?


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[Assistant] Or right and three quarters. Or maybe not quite.


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[Assistant] Or go around back and sneak in from behind.


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[Assistant] For a mind maker upper to make up his mind.


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[Assistant] You can get so confused that you'll start in to race down long wiggled roads at a break-necking pace.


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[Assistant] And grind on for miles across weirdish wild space, headed, I fear, toward a most useless place, the waiting place.


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[Assistant] For people just waiting. Waiting for a train to go, or a bus to come, or a plane to go, or the mail to come, or the rain to go, or the phone to ring, or the snow to snow.


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[Assistant] Or waiting around for a yes or no. Or waiting for their hair to grow. Everyone is just waiting. Waiting for the fish to bite. Or waiting for wind to fly a kite. Or waiting around for Friday night. Or waiting, perhaps, for their Uncle Jake. Or a pot to boil. Or a better break.


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[Assistant] Or a string of pearls, or a pair of pants, or a wig with curls, or another chance. Everyone is just waiting.


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[Assistant] No, that's not for you. Somehow you'll escape all that waiting and staying. You'll find the bright places where boom bands are playing.


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[Assistant] With banner flip flapping, once more you'll ride high. Ready for anything under the sky. Ready.


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[Assistant] Because you're that kind of a guy.


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[Assistant] Oh, the places you'll go. There is fun to be done. There are points to be scored. There are games to be won.


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[Assistant] Will make you the winningest winner of all. Fame. You'll be famous as famous can be.


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[Assistant] With the whole wide world watching, you win on TV.


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[Assistant] Except when they don't, because sometimes they won't.


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[Assistant] I'm afraid that sometimes you'll play lonely games too. Games you can't win, cause you'll play against you.


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[Assistant] All alone. Whether you like it or not.


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[Assistant] Alone will be something you'll be quite a lot. And when you're alone there's a very good chance


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[Assistant] You'll meet things that scare you right out of your pants.


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[Assistant] Down the road between hither and yawn that can scare you so much you won't want to go on.


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[Assistant] But on you will go, though the weather be foul. On you will go, though your enemies prowl. On you will go, though the hack and cracks howl. Onward up many a frightening creek, Though your arms may get sore, and your sneakers may leak. On and on you will hike, and I know you'll hike far, And face up to your problems,


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[Assistant] You'll get mixed up, of course. As you already know.


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[Assistant] You'll get mixed up with many strange birds as you go. So be sure when you step. Step with care and great tact.


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[Assistant] And remember that life's a great balancing act.


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[Assistant] Just never forget to be dextrous and deft.


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[Assistant] And never mix up your right foot with your left.


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[Assistant] And will you succeed? Yes, you will indeed.


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[Assistant] 98 and 3 quarters percent guaranteed. Kid, you'll move mountains.


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[Assistant] Be your name Buxbaum or Bixby or Bray.


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[Assistant] Or Mordecai Alley Van Allen O'Shea. You're off to great places. Today is your day. Your mountain is waiting. So get on your way.


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[Assistant] Have you ever felt overwhelmed by something new? Maybe you moved somewhere or started a new school.


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[Assistant] Life is full of new experiences that can be scary at first.


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[Assistant] But if you keep going, I think you'll find they can be fun.


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[Assistant] And maybe you'll even make a new friend along the way.


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[Assistant] or find more books to read yourself at ReadBrightly.com Bye!


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[Assistant] Andy kept pretty much to himself at first. I guess he had a lot on his mind trying to adapt to life on the inside.


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[Assistant] As it turned out, that somebody was me.


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[Assistant] No? Wait a while. The way it gets around. Sisters have taken quite a liking to you.


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[Assistant] Well, it's soft and cosy and smells like squishy mud.


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[Assistant] Rick-a-chick-chicken away we go, away we go, away we go. Rick-a-chick-chicken away we go, hi-ho, hi-ho, hi-ho.


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[Assistant] Me? Oh, no. No, no flying for me. I'll stay here, thank you. Very well, Bull. Uhm, nah. Who will help me with my glider? Well, he won't be on my train.


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[Assistant] Please can I get this flying thing off me? It's making me nervous. Did you bring my goggles, Bull? No, you never mention goggles.


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[Assistant] For a moment there, I thought I was flying. Oh, eerie me.


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[Assistant] Often when you have well logs displayed in a well section, you want to color fill between the log and one side of the track or the other side of the track.


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[Assistant] The easiest way to do this is go to the Stratigraphy tab and click on the Edit Well Tops icon. This brings up the tool palette with the well correlation group active.


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[Assistant] The easiest way to bring up the template is clicking this icon right here. The template comes up, you click on the track and not the log. When you click on the gamma track and go to curve filling, you can see that the color goes from the gamma curve to about 150. If we wanted to go to a certain exact number, we can just type in that number, 150. And then we hit, when we hit apply,


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[Assistant] The curve will go from 0 to 150 on all the wells.


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[Assistant] The callout will change depending on which one of these icons you have set. Some of the different icons. Smooth the surface. If you click on that,


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[Assistant] Removing a peak. If you have a peak in your surface or a big spike for whatever reason, click on the remove peak icon and then click on the


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[Assistant] If you have contour lines displayed on your 2D surface, the contour lines will go away and you have to go into the settings of dialogue of that object to turn them back on.


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[Assistant] Look at those forks and spoons. All neat and straight.


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[Assistant] Just then, the garbage truck sneaks into a garage and then he comes.


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[Assistant] He digs out the west side. He digs out the east side. He digs out the whole city.


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[Assistant] The next morning, the trucks wonder about the mighty truck who saved them. Where could he be?


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[Assistant] We all know that saving is important and it's something that we should be doing. And yet overall, we're doing less and less of it.


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[Assistant] And that's what I'm here to teach you. Your savings behavior isn't a question of how smart you are or how much willpower you have.


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[Assistant] We ran a study in which in one group, we showed people their income on a monthly basis. In another group, we showed people their income on a weekly basis. And what we found was that people who saw their income on a weekly basis were able to budget better throughout the month.


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[Assistant] So I'm not gonna share tricks with you that you already know. I'm not gonna tell you how to open up a savings account or how to start saving for your retirement. What I am gonna share with you is how to bridge this gap from your intentions to save and your actions. Are you ready? Here's number one. Harness the power of pre-commitment.


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[Assistant] They wanted to save about 17% of their tax refund. But in the condition when we asked people before they even filed their taxes, savings rates increased from 17%


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[Assistant] For something that you know, today will be a little bit hard. Sign up for an app that lets you make savings decisions in advance. The trick is, you have to have that binding contract. We did an experiment with a website that helps older adults share their housing.


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[Assistant] We ran two ads on social media, targeted to the same population of 64 year olds. In one group we said, hey, you're getting older.


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[Assistant] Whether it's the start of a new year or even a new season, your motivation to act increases. So right now, put a meeting request on your calendar for the day before your next birthday. Identify the one financial thing you most want to do and commit yourself to it. The third and final trick.


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[Assistant] Get a handle on small, frequent purchases.


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[Assistant] We've run a few different studies and found that the number one purchase people say they regret after bank fees is eating out. It's a frequent purchase we make almost every day and is death by a thousand cuts. A coffee here, a burrito there, it adds up and decreases our ability to save.


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[Assistant] Back when I lived in New York City, I looked at my expenses and saw that I spent over $2,000 on ride sharing apps. It was more than my New York City rent. I vowed to make a change. And the next month, I spent $2,000 again.


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[Assistant] No change, because the information alone didn't change my behavior. I didn't change my environment.


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[Assistant] So now that I was $4,000 in the hole, I did two things. The first is that I unlinked my credit card from my card sharing apps. Instead, I linked a debit card that only had $300 a month. If I needed more, I had to go through the whole process of adding a new card.


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[Assistant] And we know that every click, every barrier, changes our behavior.


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[Assistant] We aren't machines. We don't carry around an abacus every day, adding up what we're spending in comparison to what we wanted. But what our brains are very good at?


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[Assistant] Is counting up the number of times we've done something. So I gave myself a limit. I can only use ride sharing apps three times a week. It forced me to ration my travels.


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[Assistant] I got a handle on my car sharing expenses to the benefit of my husband because of the environmental changes that I did. So get a handle on whatever that purchase is for you and change your environment to make it harder to do so. Those are my tips for you, but I want you to remember one thing.


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[Assistant] As human beings, we can be irrational when it comes to saving and spending and budgeting, but luckily we know this about ourselves and we can predict how we'll act under certain environments. Let's do that with saving. Let's change our environment to help our future selves.


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[Assistant] The sinking tree sounds pretty. It sounds like our sea treasure.


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[Assistant] And to make my music accessible to an audience who might be hard of hearing or deaf and otherwise might not be able to be included in my music.


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[Assistant] And it really wasn't until this collaboration that I had thought of the fact that though I work so much in diversity and inclusion, that my music may not be reaching as many people as it could be.


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[Assistant] I grew up in New York City playing the drums, listening to Nas, Lauryn Hill, Thebre Corporation, TV on the radio, the Spice Girls. And for me, music was truth.


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[Assistant] Into storytelling, into understanding how the world works.


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[Assistant] And yet at the same time, I felt like there was such a disconnect.


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[Assistant] Between the way that I understood my own very multidimensional sense of my gender identity and the very two-dimensional way that women and femmes were often portrayed in the media.


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[Assistant] I was the first ever data analyst at Interscope Records. I toured the world playing the drums for MIA.


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[Assistant] And I did my MBA at Harvard all with the intention of being able to make a difference in the music industry and move the needle on gender equality from the business side.


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[Assistant] When I ran the London Marathon, bleeding freely on my cycle, to combat the global menstrual stigma that women face every day all around the world, then I realized that I have a message.


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[Assistant] And why music? Because music caters to the emotions. Music is joyful. Music pulls you in with the beat and the rhythm and the melodies. The music pulls you in via the community aspect of it. And music allows you to access somebody else's truth.


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[Assistant] In the music I listen to today, sometimes I'm like, wow, I love the rhythm so much, but the message is so misogynist, it's tough to work out to or run to or do whatever it is that I'm trying to do. I oftentimes say I'm not here trying to turn up to the sound of my own oppression. You feel me?


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[Assistant] In my work, I talk often about the notion that the future is female, that we can actually look to the femme archetype and derive alternative styles of leadership that might encourage instead collaboration.


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[Assistant] Emotional intelligence and building a world that is linked and not ranked.


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[Assistant] And so for anyone watching or listening and experiencing this talk today, I encourage you to consider the blind spots in your work.


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[Assistant] And what partnerships or collaborations you can do to be able to make your work have even greater of an impact.


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[Assistant] This next song is called Bad Habits, and it's about being an even better version of yourself.


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[Assistant] Good evening. Tonight, Voices is a little different because there are only two of us, Susan Sontag and myself, John Berger.


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[Assistant] Susan and I have quite a lot of things in common, I think. We both write essays, uh, about literature, about ideas.


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[Assistant] Susan has just come back from Rome where she's been making a film based on one of her own short stories. I've written film scenarios. We've both from time to time written quite a lot about photography, about the visual photographic image.


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[Assistant] And then finally, and perhaps most important of all for tonight, we both write fiction, novels and short stories. And tonight


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[Assistant] We are going to exchange views and experiences about this activity, somewhat mysterious really, this activity of telling stories.


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[Assistant] If I think of somebody telling a story, I see a group of people huddled together, and around them, a vast space, quite frightening.


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[Assistant] Maybe they are huddled against a wall. Maybe they're under fire.


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[Assistant] The shelter perhaps of the voyager, the traveler who has come home, who has lived to tell the story. Or the soldier who has come back, who has survived. So there is this almost physical sense of shelter where the story represents a kind of habitation, a kind of home. But then, inside the story, there's another kind of shelter.


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[Assistant] Because what the story narrates and tells is sheltered within the story from oblivion, forgetfulness, and daily indifference.


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[Assistant] Yes, I agree. But I'm not certain that something of that primitive origin doesn't remain. For instance, uh, when children hear stories, or when we were children, and uh, they told us stories, uh, when does it happen? In bed?


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[Assistant] In this strange no man's land between waking and sleep. And in that telling of a story or listening to a story there is something reassuring.


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[Assistant] I'm very curious, because the more exciting, the more threatening the story, the more reassuring it is. Why?


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[Assistant] Exists somewhere between fiction and truth. I agree. If I think now, straight away, of my own personal experience in telling stories, or writing stories, I think they begin off for me, and they have to begin off, as, as truth.


[User] Please transcribe this text

[Assistant] For instance, for instance, I won't tell you the whole story, but a little one. A man I knew in the village where I live, uh, a shepherd with about a hundred sheep.


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[Assistant] And he fell in love. Fell in love with a woman, married, uh, not from the village, from the town.


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[Assistant] Half of what he had at least, including a house. And, uh, then she, uh, she turned him out.


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[Assistant] And it is that displacement of place and time which makes something fiction it seems to me.


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[Assistant] It's immediate time or it's immediate place. And it's exactly that which makes it fiction. Uh, or what we call fiction.


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[Assistant] I think it's less, perhaps it's less sociological than that. Uhm, it doesn't really concern me whether


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[Assistant] That kind of story exists in literature or not. Um, if I'm very, very honest, I mean, it is because that life was lived, uh, I see a kind of meaning in it and, uh, I would like to retain it so that it is not lost, not forgotten. Um,


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[Assistant] I mean, whether we're telling stories in a city context or in a village, probably you'll agree that in fact stories begin at their end.


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[Assistant] I mean in life. I mean the story of Romeo and Juliet in a sense begins


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[Assistant] What does it tell us? I mean, you tell me. Uh, what is our need?


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[Assistant] If we take the experience of writing a story or of listening to one, uh, the story, it seems to me every story has its own subjectivity. And I emphasize that because I think this subjectivity is an area where


[User] Please transcribe this text

[Assistant] No, I mean a kind of subjectivity. Now, and it seems to me this subjectivity is a kind of amalgam of three elements or three people. The storyteller or the writer.


[User] Please transcribe this text

[Assistant] There is already a kind of cooperation between these three, which actually makes the subjectivity of that story.


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[Assistant] And who were you? You were yourself, you were the person telling you the story, and you were the characters, all mixed together in a rather reassuring way.


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[Assistant] This is a record player. Hand me that record, Lily.


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[Assistant] Oh, I wish I could, Lily. The other fellas moved away. I'm the only flat fish left. Oh!


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[Assistant] Why ho, young lily. I've come for one of Nona's cream buns.


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[Assistant] Oh has she now? That's not like our Nona. I'll see if she's okay.


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[Assistant] Now then, we need to get the sheep come out here into this shed.


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[Assistant] Hoho, warm sheep are happy sheep. Well done, sheep-baits. And just in time too.


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[Assistant] Right. No harm done. How we need to find that sheep is getting mighty chilly out here.


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[Assistant] The shepherd who commits suicide when he's thrown out by the woman he loves. I'm, I'm, I'm saying that you are trying to equate telling a story with writing a story.


[User] Please transcribe this text

[Assistant] In other words, you're saying writing is a kind of telling. Writing is the telling with art, so to speak. Uh, it's a, it's a transformation of oral telling. What I'm saying, and that, that I think is one, one of the points on which we disagree, is I think that once people began to write stories, they told different kinds of stories.


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[Assistant] In a written form, there are things you want to tell in a written form, which you couldn't tell in an oral form. For instance, I know in my own story writing,


[User] Please transcribe this text

[Assistant] Several stories going at the same time. The famous model is, uh, Griffith's intolerance.


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[Assistant] That's the kind of thing that you can't do, uh, orally.


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[Assistant] But a tremendous expansion and modification of storytelling that comes when you have the resources of print and when you are


[User] Please transcribe this text

[Assistant] Reading with the eyes as opposed to hearing with the ears.


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[Assistant] But isn't it just that you can't say everything? I mean, if you would tell the story of a day, not even a day, an hour in anyone's life, you could write a thousand pages.


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[Assistant] In storytelling, as in every other form of art, there's a process of selection. But if the person goes out the door and leaves the house and leaves the door, exits from the house and leaves the door open, and then you cut to the mad dog in the orchard, it's only two stories if you're going to follow the man.


[User] Please transcribe this text

[Assistant] Somewhere else. And then also tell a long story about the dog.


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[Assistant] The assumption is that the man and the dog will meet. That the dog in the orchard has something to do with the man. But you don't describe step by step.


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[Assistant] From one sentence to the next, you're featuring a different detail and in fact you're skipping time, you're skipping all sorts of things that you could be telling. The question is of course what kind of detail


[User] Please transcribe this text

[Assistant] Are we interested in telling? And there we have a very particular set of traditions that we're responsive to as writers.


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[Assistant] We look for the angular or the eccentric detail as illustrating what.


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[Assistant] I mean, I think that what happens in dreaming as in anything else is that once you have the narration, or once you have the event,


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[Assistant] Then you can always assign meaning to it, and you want to assign meaning to it, but I don't think the meaning resides.


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[Assistant] I don't think the dream exists, or as soon as it exists it doesn't exist. But what does exist is the already highly selective account.


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[Assistant] That you make of the dream to yourself, writing it out, or to someone else.


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[Assistant] Uh, and actually the chair in, in that room was a chair in the dormitory in the school that I went to when I was nine years old. And you begin to find associations. And I think that, that makes...


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[Assistant] The kind of meaning that we, on a very, that's a very simple level of meaning that we assign to dreams. And even in stories, I don't know that I would say that every detail has to be essential. I would say that every detail has to be powerful. Every detail has to be thrilling. And then after the fact,


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[Assistant] And perhaps it's that that we then say gives it some essential quality.


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[Assistant] The characters on whom they're based, of course, you have an experience which is extremely rare for a contemporary writer. When I write a story, I'm sure that


[User] Please transcribe this text

[Assistant] I don't have a privileged first audience in the sense that I'm not part of a small community in the way that you are. And, uh, I have, I'm not telling a story that people will


[User] Please transcribe this text

[Assistant] And know that part of his audience will be people who have been in those camps and will be judging his story.


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[Assistant] His story by the criteria of their own experience. It was really like that and at last this person is really telling the world how it was for us.