Systems and methods for real-time risk prediction during drilling operations using real-time data from an uncompleted well, a trained coarse layer model and a trained fine layer model for each respective layer of the trained coarse layer model. In addition to using the systems and methods for real-time risk prediction, the systems and methods may also be used to monitor other uncompleted wells and to perform a statistical analysis of the duration of each risk level for the monitored well.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A method for predicting a risk during drilling operations of a well, which comprises: a) defining a course layer model and a fine layer model for each layer of the course layer model based on a model type for the well; b) training the coarse layer model and each fine layer model using a computer processor, the model type and at least one of segmented historical data and one or more extracted features representing each respective historical data segment; c) repeating steps a)-b) with another model type until the course layer model and each fine layer model are acceptable; and d) predicting the predetermined risk for the well using an acceptable course layer model, each acceptable fine layer model and real-time data for the well. 2. The method of claim 1, wherein the model type is fuzzy mapping or static mapping. 3. The method of claim 2, wherein the fuzzy mapping includes a fuzzy inference system model and a rules base, which calculate, using the at least one of the segmented historical data and the one or more extracted features representing each respective historical data segment, a best number of layers for the course layer model representing different risk zones with a best respective incremental time and a best number of layers for each fine layer model representing different classification levels with a best respective incremental time within a respective risk zone totaling the best incremental time of the respective risk zone. 4. The method of claim 2, wherein the static mapping uses multiple model parameters, which include a forecasting horizon, a coarse layer model segment number, a fine layer model segment number and a warning interval. 5. The method of claim 4, wherein the coarse layer model segment number represents a number of layers for the coarse layer model, which represent different risk zones with the same incremental time totaling the forecasting horizon and the fine layer model segment number represents a number of layers for each fine layer model, which represent different classification levels with the same incremental time within a respective risk zone totaling the incremental time of the respective risk zone. 6. The method of claim 2, wherein a realization of the predetermined risk is labeled with at least one of a time stamp and a depth stamp in the at least one of the segmented historical data and the one or more extracted features representing each respective historical data segment. 7. The method of claim 6, wherein one or more risk attributes are labeled with at least one of a time stamp and a depth stamp as safe, potential risk or the realized predetermined risk in the at least one of the segmented historical data and the one or more extracted features representing each respective historical data segment. 8. The method of claim 7, wherein the at least one of the segmented historical data and the one or more extracted features representing each respective historical data segment are mapped to a most appropriate layer of the coarse layer model representing a risk zone or a safe zone and a most appropriate layer of the fine layer model representing a classification level within the respective risk zone of the coarse layer model using the labeled realized predetermined risk and the one or more labeled risk attributes. 9. The method of claim 8, wherein predicting the predetermined risk for the real-time data for the well comprises: comparing to the real-time data for the well to the acceptable coarse layer model and each acceptable fine layer model, which classifies he real-time data in a safe zone, or a risk zone and a classification level within the respective risk zone; repeating step d) in claim 1 as the real-time data for the well is received during the drilling operations; and displaying the predicted predetermined risk for the well during the drilling operations at a predetermined warning interval. 10. A non-transitory program carrier device tangibly carrying computer executable instructions for predicting a risk during drilling operations of a well, the instructions being executable to implement: a) defining a course layer model and a fine layer model for each layer of the course layer model based on a model type for the well; b) training the coarse layer model and each fine layer model using the model type and at least one of segmented historical data and one or more extracted features representing each respective historical data segment; c) repeating steps a)-b) with another model type until the course layer model and each fine layer model are acceptable; and d) predicting the predetermined risk for the well using an acceptable course layer model, each acceptable fine layer model and real-time data for the well. 11. The program device of claim 10, wherein the model type is fuzzy mapping or static mapping. 12. The program device of claim 11, wherein the fuzzy mapping includes a fuzzy inference system model and a rules base, which calculate, using the at least one of the segmented historical data and the one or more extracted features representing each respective historical data segment, a best number of layers for the course layer model representing different risk zones with a best respective incremental time and a best number of layers for each fine layer model representing different classification levels with a best respective incremental time within a respective risk zone totaling the best incremental time of the respective risk zone. 13. The program device of claim 11, wherein the static mapping uses multiple model parameters, which include a forecasting horizon, a coarse layer model segment number, a fine layer model segment number and a warning interval. 14. The program device of claim 13, wherein the coarse layer model segment number represents a number of layers for the coarse layer model, which represent different risk zones with the same incremental time totaling the forecasting horizon and the fine layer model segment number represents a number of layers for each fine layer model, which represent different classification levels with the same incremental time within a respective risk zone totaling the incremental time of the respective risk zone. 15. The program device of claim 11, wherein a realization of the predetermined risk is labeled with at least one of a time stamp and a depth stamp in the at least one of the segmented historical data and the one or more extracted features representing each respective historical data segment. 16. The program device of claim 15, wherein one or more risk attributes are labeled with at least one of a time stamp and a depth stamp as safe, potential risk or the realized predetermined risk in the at least one of the segmented historical data and the one or more extracted features representing each respective historical data segment. 17. The program device of claim 16, wherein the at least one of the segmented historical data and the one or more extracted features representing each respective historical data segment are mapped to a most appropriate layer of the coarse layer model representing a risk zone or a safe zone and a most appropriate layer of the fine layer model representing a classification level within the respective risk zone of the coarse layer model using the labeled realized predetermined risk and the one or more labeled risk attributes. 18. The program device of claim 17, wherein predicting the predetermined risk for the real-time data for the well comprises: comparing to the real-time data for the well to the acceptable coarse layer model and each acceptable fine layer model, which classifies he real-time data in a safe zone, or a risk zone and a classification level within the respective risk zone; repeating step d) in claim 1 as the real-time data for the well is received during the drilling operations; and displaying the predicted predetermined risk for the well during the drilling operations at a predetermined warning interval. 19. A non-transitory program carrier device tangibly carrying computer executable instructions for predicting a risk during drilling operations of a well, the instructions being executable to implement: defining a course layer model and a fine layer model for each layer of the course layer model based on a model type for the well; training the coarse layer model and each fine layer model using the model type and at least one of segmented historical data and one or more extracted features representing each respective historical data segment; and predicting the predetermined risk for the well using the course layer model, each fine layer model and real-time data for the well. 20. The program device of claim 19, wherein the model type is fuzzy mapping or static mapping.