Artificial Neural Networks in Drilling Troubles Prediction

Abstract Drilling of oil and gas wells is a basic process in production of hydrocarbons. Up to now drilling projects are often being designed on the base of segmental data and primary analysis of drilling experience, which is ineffective under modern drilling conditions. A possible solution of this problem consists in computer analysis of data on earlier drilled wells with the use of modern information technologies. Authors propose methods for prediction of probable troubles occurring while drilling new wells on the base of information on well stock of the oilfield using efficient data mining tools – artificial neural networks. Structural and parametric identification of a neural network solving the formalized problem of functions approximation has been conducted. Results of computational experiments on real data show effectiveness of software developed.