Application of artificial intelligence methods for identifying and predicting complications in the construction of oil and gas wells: problems and solutions
Alexander D. Chernikov, N.A. Eremin, V.E. Stolyarov, Alexander Sboev, Olga K. Semenova-Chashchina, Leonid K. Fitsner
Abstract
This paper poses and solves the problem of using artificial intelligence methods for processing large 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, in particular, 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 multidimensional data volumes from various types of sensors used to measure parameters during 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.