Development of a Methodology for the Comprehensive Petrotyping of Terrigenous Reservoirs to Reduce Uncertainty in Assessing Reservoir Properties (Using the Minnibaevskaya Area of the Romashkinskoye Field as an Example)

Author details
  • TATNEFT named after V.D. Shashin, Almetyevsk, Russian Federation; Almetyevsk State Technological University "Higher School of Oil", Almetyevsk, Russian Federation
  • TatNIPIneft R&D Institute of the PJSC TATNEFT named after V.D. Shashin, Almetyevsk, Russian Federation
  • TatNIPIneft R&D Institute of the PJSC TATNEFT named after V.D. Shashin, Almetyevsk, Russian Federation
  • TatNIPIneft R&D Institute of the PJSC TATNEFT named after V.D. Shashin, Almetyevsk, Russian Federation; Almetyevsk State Technological University "Higher School of Oil", Almetyevsk, Russian Federation
  • TATNEFT named after V.D. Shashin, Almetyevsk, Russian Federation; Almetyevsk State Technological University "Higher School of Oil", Almetyevsk, Russian Federation
  • TatNIPIneft R&D Institute of the PJSC TATNEFT named after V.D. Shashin, Almetyevsk, Russian Federation
  • TatNIPIneft R&D Institute of the PJSC TATNEFT named after V.D. Shashin, Almetyevsk, Russian Federation
  • TatNIPIneft R&D Institute of the PJSC TATNEFT named after V.D. Shashin, Almetyevsk, Russian Federation
  • TatNIPIneft R&D Institute of the PJSC TATNEFT named after V.D. Shashin, Almetyevsk, Russian Federation
  • TatNIPIneft R&D Institute of the PJSC TATNEFT named after V.D. Shashin, Almetyevsk, Russian Federation
  • TatNIPIneft R&D Institute of the PJSC TATNEFT named after V.D. Shashin, Almetyevsk, Russian Federation; Almetyevsk State Technological University "Higher School of Oil", Almetyevsk, Russian Federation

Abstract

The subject of this study is the development of a petrotyping methodology for terrigenous reservoirs to improve the reliability of reservoir properties (RP) assessments in highly lithologically heterogeneous environments. This work integrates laboratory core data, well logging (WL) results, and modern machine learning methods to identify petrotypes in sediments of the Pashiysky and Timansky horizons of the Minnibayevskaya area of the Romashkinskoye field. The primary objective of the study was to develop a scientifically sound approach to reservoir differentiation that reduces errors in permeability and water saturation estimates compared to traditional averaged models. As a result of the studies, three petrotypes were identified: clayey siltstones with low RP, silty sandstones and siltstones with medium RP, and mixed- and medium-grained sandstones with high RP. Stable correlations were established between WL parameters and core characteristics. The application of the results includes optimizing geological and hydrodynamic modeling and reserve estimation at the Minnibayevskaya area, as well as adapting the methodology to other fields with similar terrigenous reservoirs. The proposed approach reduces permeability estimation errors and improves the accuracy of water saturation determination, especially in low-permeability intervals, enabling more reliable field development forecasting and rational management of recoverable reserves.

Keywords

petrotypificationterrigenous reservoirspermeabilitymachine learningK-means clusteringwell loggingcoreRomashkinskoye fieldpetrotypepetrophysical model

Bibliography

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Article information

Published
14 May 2026
Issue date
14 May 2026
Issue
Vol. 26, No. 2 (2026)
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