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Studying the direction of hydraulic fracture in carbonate reservoirs:Using machine learning to determine reservoir pressure

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Petroleum Research 2023年第2期8卷 226-233页

作者： Dmitriy A.Martyushev Inna N.Ponomareva Evgenii V.Filippov Department of Oil and Gas Technologies Perm National Research Polytechnic UniversityPerm614990Russia Department of Oil and Gas Fields Development LLC《LUKOIL-PERM》Perm614068Russia

Hydraulic fracturing(HF)is an effective way to intensify oil production,which is currently widely used in various conditions,including complex carbonate *** the conditions of the field under consideration,the hydraulic fracturing leads to a significant differentiation of technological efficiency indicators,which makes it expedient to study the patterns of crack formation in *** were carried out for all wells,which were considered as the objects of impact,to assess the spatial orientation of the cracks *** developed indirect method was used for this purpose,the reliability of which was confirmed by geophysical *** the analysis,it was found that in all cases,the crack is oriented in the direction of the section of the development system element characterized by the maximum reservoir *** the same time,the reservoir pressure values for all wells were determined at one point in time(at the beginning of HF)using machine learning *** reliability of the machine learning methods used is confirmed by the high convergence with the actual(historical)reservoir pressures obtained during hydrodynamic studies of *** obtained conclusion about the influence of the reservoir pressure on the patterns of fracture formation should be taken into account when planning hydraulic fracturing under the conditions studied.

关键词： Hydraulic fracturing direction Machine learning Actual field data Correlation coefficient well flow rate well geophysical studies Carbonate reservoir

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