Geoelectric Models of Lower Cretaceous Deposits of the Latitudinal Ob Region Based on the Results of Multilayer Inversion of Electrical Logging Data

The article considers the results of applying a multi-layer approach to the quantitative interpretation of electrical and induction logging data in vertical wells for formation evaluation of the Achimov formation in the central part of Western Siberia. Interpretation of electrical logging data by conventional methods often leads to errors in estimating the oil saturation of thin reservoirs due to the complex apparent resistivity logs, which are significantly influenced by the high-contrast invaded zones and shoulder beds. The approach proposed at Institute of Petroleum Geology and Geophysics of the Siberian Branch of the Russian Academy of Sciences is based on joint multilayer 2D inversion of signals from a complex of galvanic and induction probes. The signals are calculated using a verified finite element algorithm. This naturally takes into account changes in the well diameter and drilling mud resistivity, radial and vertical distribution of electrical properties in the section, different sensitivity of the signals to various elements of the environment around the logging tool, as well as design parameters of the most common Russian electrical logging tools. The approach has been tested on logging data provided under an agreement with SNIIGGiMS. Geoelectric models of Lower Cretaceous deposits were built for several dozen wells, typical examples of which are given in the article.

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Journal
Georesursy
Published
2024-12-30
DOI
https://doi.org/10.18599/grs.2024.4.19
Primary Topic
Geophysical and Geoelectrical Methods
Type
article
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article

Geoelectric Models of Lower Cretaceous Deposits of the Latitudinal Ob Region Based on the Results of Multilayer Inversion of Electrical Logging Data

S. A. Primakov, К. В. Сухорукова, D.S. Lezhnin, M. I. Epov
Georesursy
Geophysical and Geoelectrical Methods
article

Geoelectric Models of Lower Cretaceous Deposits of the Latitudinal Ob Region Based on the Results of Multilayer Inversion of Electrical Logging Data

S. A. Primakov, К. В. Сухорукова, D.S. Lezhnin, M. I. Epov
article en

Abstract

The article considers the results of applying a multi-layer approach to the quantitative interpretation of electrical and induction logging data in vertical wells for formation evaluation of the Achimov formation in the central part of Western Siberia. Interpretation of electrical logging data by conventional methods often leads to errors in estimating the oil saturation of thin reservoirs due to the complex apparent resistivity logs, which are significantly influenced by the high-contrast invaded zones and shoulder beds. The approach proposed at Institute of Petroleum Geology and Geophysics of the Siberian Branch of the Russian Academy of Sciences is based on joint multilayer 2D inversion of signals from a complex of galvanic and induction probes. The signals are calculated using a verified finite element algorithm. This naturally takes into account changes in the well diameter and drilling mud resistivity, radial and vertical distribution of electrical properties in the section, different sensitivity of the signals to various elements of the environment around the logging tool, as well as design parameters of the most common Russian electrical logging tools. The approach has been tested on logging data provided under an agreement with SNIIGGiMS. Geoelectric models of Lower Cretaceous deposits were built for several dozen wells, typical examples of which are given in the article.

GeoresursyVol. 26(4)
Institute of Petroleum Geology and Geophysics (RU), Siberian Branch of the Russian Academy of Sciences (RU), Siberian Research Institute of Geology, Geophysics and Mineral Resources (RU)
Openalex Percentile: Top 74%
Geophysical and Geoelectrical Methods
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Geoelectric Models of Lower Cretaceous Deposits of the Latitudinal Ob Region Based on the Results of Multilayer Inversion of Electrical Logging Data — S. A. Primakov, К. В. Сухорукова, et al. · Georesursy (2024) | TGRS Research Map | TGRS