Abstract:

Optimal approaches to solving many problems are required in many areas. One of these areas is the determination of the occurrence of gravity anomalies in oil and gas fields. In this paper is proposed a new approach for determining the source of gravity anomalies in an oil and gas fields by estimating the gravity parameters associated with simple-shaped bodies such as a homogeneous sphere, a horizontal prism, and a vertical step. The approach was implemented in the computational module of the GeoM information system for optimizing the solution of a series of direct gravimetry problems using a genetic algorithm (GA). Approach is based on solving the direct gravimetry problem to minimize the discrepancy of gravity variations by the genetic algorithm. The method allows to select values simultaneously for several parameters of the studied environment. The task is realized through successive approximations based on a given initial approximation of the medium. The paper indicates the initial calculation parameters and criteria for finding optimal solutions for models of the geological environment. The calculations were carried out for such models of the environment as a homogeneous sphere, a horizontal prism and a vertical ledge. For calculations, the results of gravimetric monitoring at one of the Kazakh oil and gas fields were used. The paper demonstrates the operation of the algorithm and presents the results of modeling for three available field profiles. The obtained results of the system showed an acceptable accuracy of the algorithm up to 10-11. The genetic algorithm made it possible to significantly increase the reliability of the model and reduce the working time for analyzing the measured gravitational field Supporting Agency This work is a continuation of the project study "Development of a geographic information system for solving the problem of gravimetric monitoring of the state of the subsoil of oil and gas regions of Kazakhstan based on high-performance computing in a limited amount of experimental data" No. AP05135158 (grant funding for scientific projects of the Ministry of Education and Science of the Republic of Kazakhstan for 2018-2020). The authors also express their special gratitude to the Scientific-Productional Centre "Geoken" for providing gravimetric monitoring data, carried out over 7 cycles of observations, for scientific research. Author Biographies Assem Nazirova, Almaty University of Power Engineering and Telecommunications named after Gumarbek Daukeyev; Satbayev University Master, Doctoral Student Department of Information Technology Engineering Department of Software Engineering

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