The present disclosure generally relates to synthetic logging for reservoir stimulation. A synthetic logging method for stimulating a reservoir includes: training a machine learning algorithm using historical or exploratory data; and generating a synthetic elastic property log of the reservoir by supplying the trained machine learning algorithm with data acquired from a production wellbore.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A synthetic logging method for stimulating a reservoir, comprising: training a machine learning algorithm (MLA) using historical or exploratory data; and generating a synthetic elastic property log of the reservoir by supplying the trained MLA with data acquired from a production wellbore. 2. The method of claim 1, wherein the data is acquired from the production wellbore using one or more logging tools selected from a group consisting of: passive nuclear logging tools and nonnuclear logging tools. 3. The method of claim 2, wherein: the data is acquired from the production wellbore during drilling thereof, and the passive/nonnuclear logging tools are assembled as part of a bottomhole assembly of a drill string. 4. The method of claim 3, wherein the production wellbore has a deviated lower portion traversing the reservoir. 5. The method of claim 2, wherein the passive/nonnuclear logging tools comprise one or more of: a passive gamma sonde, a resistivity sonde, a caliper sonde, and an annulus temperature sonde. 6. The method of claim 1, wherein the data is acquired from the production wellbore during drilling thereof by: mud logging drilling returns; and measuring drilling parameters. 7. The method of claim 1, wherein the historical or exploratory data is measured by an induced nuclear logging tool. 8. The method of claim 7, wherein the historical or exploratory data is measured by logging a vertical exploratory wellbore traversing the reservoir using the induced nuclear logging tool. 9. The method of claim 7, wherein the induced nuclear logging tool is a pulsed neutron capture sonde. 10. The method of claim 1, further comprising generating a stimulation plan by supplying the elastic property log to a reservoir model. 11. The method of claim 10, further comprising stimulating the reservoir using the stimulation plan. 12. The method of claim 11, wherein the stimulation is hydraulic fracturing. 13. The method of claim 10, wherein the stimulation plan comprises a number of zones and a depth of each zone. 14. The method of claim 13, wherein the stimulation plan further comprises a fracture pressure of each zone. 15. The method of claim 1, wherein the MLA is a neural network. 16. A synthetic logging method for analyzing a reservoir, comprising: supplying a trained machine learning algorithm (MLA) with data acquired from a wellbore traversing the reservoir; and generating a synthetic log of the reservoir using the trained MLA and the supplied data, wherein the synthetic log is selected from a group consisting of: an elastic property log, a density log, a porosity log, and a sonic velocity log. 17. The method of claim 16, wherein the data is acquired by logging the reservoir from the wellbore using one or more logging tools selected from a group consisting of: passive nuclear logging tools and nonnuclear logging tools. 18. The method of claim 16, further comprising training the MLA using data measured by a pulsed neutron capture sonde. 19. A synthetic logging method for determining properties of a formation, comprising: training a machine learning algorithm (MLA) using historical or exploratory data; and generating a synthetic elastic property log of the formation by supplying the trained MLA with data acquired from a wellbore traversing the formation.