Application of artificial neural network in fracture pressure prediction - Nguyen Van Hung; Dang Huu Minh (Petrovietnam Journal, 2019)
Prediction of formation fracture pressure is an essential task in designing safer drilling operations and economical well planning, allowing effective control, operation and stimulation. Errors in fracture pressure prediction can lead to several serious problems such as lost circulation and kick, and even blowout. This paper presents an overview on application of artificial intelligent in the petroleum industry. Then an artificial neural network model will be used with depth, overburden stress, Poisson’s ration, and pore pressure as the input data and fracture pressure as the output data of one well in Nam Con Son basin for predicting formation fracture pressure. The results obtained from the model are compared with those obtained from conventional method. The comparison shows that the ANN method is promising and under some circumstances it is superior to the available techniques.