Abstract

Abstract —The paper presents the results of the development and use of numerical methods for interpreting logging data in the Bazhenov Formation interval (Upper Jurassic). We consider the example of wells located in the central and southeastern regions of Western Siberia. Based on the machine learning method (artificial neural networks), and taking into account the results of detailed lithological and geochemical core studies, a computational algorithm has been developed and tested to evaluate the material composition of the Bazhenov Formation rocks. In our studies, we employ the classification of the Bazhenov Formation lithotypes, which is centered on the modern concept of rock-forming mineral and mineraloid components distribution. In the examined borehole sections, the lithological composition of the Bazhenov Formation rocks has been determined, along with revealing the features of its lateral change in the central part of the Salym field, in the Surgut arch region, and in the southeast of Western Siberia.

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