Алгоритм выбора скважин-кандидатов для зарезки боковых стволов в условиях неопределенности геолого-промысловой информации

V.Sh. Mukhametshin; R.A. Gilyazetdinov; D.S. Saduakassov; A.B. Bakiyeva

doi:10.46698/VNC.2026.25.10.001

V.Sh. Mukhametshin Institute of Oil and Gas, Ufa State Petroleum Technological University (Oktyabrsky Branch), 54а Devonskaya Str., Oktyabrsky 452607, Russian Federation
R.A. Gilyazetdinov Institute of Oil and Gas, Ufa State Petroleum Technological University (Oktyabrsky Branch), 54а Devonskaya Str., Oktyabrsky 452607, Russian Federation
D.S. Saduakassov Yesenov University, Aktau 130000, Republic of Kazakhstan
A.B. Bakiyeva Branch of KMG Engineering LLP “KazNIPImunaigasˮ, Aktau 130000, Republic of Kazakhstan

DOI: https://doi.org/10.46698/VNC.2026.25.10.001

Keywords: sidetracking, pattern recognition methods, Tournaisian carbonate reservoirs, Wald procedure, geological-statistical modeling, productivity index, information content of geological and production parameters

Abstract

Relevance. The work is devoted to the development of an algorithm for selecting candidate wells for sidetracking in conditions of uncertainty of geological and field information. The lack of relevant well selection methods during long-term development of Tournaisian carbonate reservoirs of the Volga-Ural oil and gas province reduces the effectiveness of management decisions and geological and technical measures. Aim. To develop an algorithm for selecting candidate wells for the effective implementation of sidetracking based on a comprehensive analysis of geological and technological indicators. Methods. The object of the study is the deposits of carbonate reservoirs of the Tournaisian stage. The wells were divided based on the productivity value to identify hidden patterns. Results. Parameter change dependencies were constructed for various well groups, and an algorithm for assessing the information content of criteria and predictive models for sidetracking efficiency were developed, based on the relationship between oil flow rate increment and a set of indicators. The potential of the algorithm for optimizing oil production processes and increasing the efficiency of sidetracking is demonstrated.

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Algorithm for selecting candidate wells for sidetracking under conditions of uncertain geological and field data

Abstract

References