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Application of artificial intelligence methods for identifying and predicting complications in the construction of oil and gas wells: problems and solutions

A.D. Chernikov, N.A. Eremin, V.E. Stolyarov, A.G. Sboev, O.K. Semenova-Chaschina, L.K. Fitsner

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This paper poses and solves the problem of using artificial intelligence methods for processing Big volumes of geodata from geological and technological measurement stations in order to identify and predict complications during well drilling. Digital modernization of the life cycle of wells using artificial intelligence methods helps to improve the efficiency of drilling oil and gas wells. In the course of creating and training artificial neural networks, regularities were modeled with a given accuracy, hidden relationships between geological and geophysical, technical and technological parameters were revealed. The clustering of Big data volumes from various sources and types of sensors used to measure parameters while well drilling has been carried out. Artificial intelligence classification models have been developed to predict the operational results of the well construction. The analysis of these issues is carried out, and the main directions for their solution are determined.

artificial intelligence, machine learning methods, geological and technological research, neural network model, regression model, construction of oil and gas wells, identification and prediction of complications, prevention of emergency situations


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Alexander D. Chernikov
Oil and Gas Research Institute of the Russian Academy of Sciences
3, Gubkin st., Moscow, 119333, Russian Federation
Nikolai A. Eremin
Oil and Gas Research Institute of the Russian Academy of Sciences; Professor, National University of Oil and Gas «Gubkin University» (Gubkin University)
3, Gubkin st., Moscow, 119333, Russian Federation
Vladimir E. Stolyarov
Institute of Oil and Gas Problems of the Russian Academy of Sciences
3, Gubkin st., Moscow, 119333, Russian Federation
Alexander G. Sboev
National Research Center «Kurchatov Institute»
1, Ak. Kurchatov pl., Moscow, 123098, Russian Federation
Olga K. Semenova-Chashchina
Oil and Gas Research Institute of the Russian Academy of Sciences
3, Gubkin st., Moscow, 119333, Russian Federation
Leonid K. Fitsner
Oil and Gas Research Institute of the Russian Academy of Sciences
3, Gubkin st., Moscow, 119333, Russian Federation

For citation:

Chernikov A.D., Eremin N.A., Stolyarov V.E., Sboev A.G., Semenova-Chashchina O.K., Fitsner L.K. (2020). Application of artificial intelligence methods for identifying and predicting complications in the construction of oil and gas wells: problems and solutions. Georesursy = Georesources, 22(3), pp. 87–96. DOI: