Abstract: System and methods for event prediction during drilling operations are provided. Regression data associated with coefficients of a predictive model are retrieved for a downhole event during a drilling operation along a planned path of a wellbore. The regression data includes a record of changes in historical coefficient values associated with prior occurrences of the event. As the wellbore is drilled over different stages of the operation, a value of an operating variable is estimated based on values of the coefficients and real-time data acquired during each stage. A percentage change in coefficient values adjusted between successive stages of the operation is tracked. An occurrence of the downhole event is estimated, based on a correlation between the percentage change tracked for at least one coefficient and a corresponding change in the historical coefficient values. The path of the wellbore is adjusted, based on the estimated occurrence of the event.

Abstract: System and methods for event prediction during drilling operations are provided. Regression data associated with coefficients of a predictive model are retrieved for a downhole event during a drilling operation along a planned path of a wellbore. The regression data includes a record of changes in historical coefficient values associated with prior occurrences of the event. As the wellbore is drilled over different stages of the operation, a value of an operating variable is estimated based on values of the coefficients and real-time data acquired during each stage. A percentage change in coefficient values adjusted between successive stages of the operation is tracked. An occurrence of the downhole event is estimated, based on a correlation between the percentage change tracked for at least one coefficient and a corresponding change in the historical coefficient values. The path of the wellbore is adjusted, based on the estimated occurrence of the event.

Abstract: A system and method can be used for implementing self-adapting digital twins. The system may include operations for estimate a state matrix characterizing behavior of a hydrocarbon recovery process implemented by a hydrocarbon recovery tool. Observed values of one or more sensors for at least one process parameter may be obtained from sensors deployed throughout the drilling environment. These sensors may be physical sensors acquiring information about physical changes within the drilling environment; and processes monitoring output of system functions and/or other processes. A data assimilation tool may be applied to the estimated state matrix and the observed values to produce an updated state matrix. The updated state matrix may be used as the previous state matrix in a subsequent time step, thus implementing a self-adapting digital twin model.