Prediction of geophysical properties of rocks on rare well data and attributes of seismic waves by machine learning methods on the example of the Achimov formation

2021/06/24 by Dmitry Ivlev, Ivlev, Dmitry
Computer Science · Earth and Planetary Sciences · Engineering · #FOS: Computer and information sciences #FOS: Physical sciences #Geochemistry and Geologic Mapping #Geological Studies and Exploration #Geophysics (physics.geo-ph) #Hydrocarbon exploration and reservoir analysis #Machine Learning (cs.LG) #Reservoir Engineering and Simulation Methods

paper · pdf · doi:10.48550/arxiv.2106.13274

openalex publication_date 2021/06/24 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

Purpose of this research is to forecast the development of sand bodies in productive sediments based on well log data and seismic attributes. The object of the study is the productive intervals of Achimov sedimentary complex in the part of oil field located in Western Siberia. The research shows a technological stack of machine learning algorithms, methods for enriching the source data with synthetic ones and algorithms for creating new features. The result was the model of regression relationship between the values of natural radioactivity of rocks and seismic wave field attributes with an acceptable prediction quality. Acceptable quality of the forecast is confirmed both by model cross validation, and by the data obtained following the results of new well.

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