Neftyanaya Provintsiya
electronic peer-reviewed scholarly publication
Neftyanaya provintsiya No. 3(47), 2026

Identification and integration of facies barriers in geology and development

Y.K. Zinchenko
DOI: https://doi.org/10.25689/NP.2026.3.23-36

Abstract


This paper presents a comprehensive methodology for identifying and integrating facies barriers into geological and hydrodynamic models of the Jurassic formations in Western Siberia. Conventional approaches overlook silicate‑filled channels, leading to errors in structural mapping and drilling failures. A five‑stage approach has been implemented, combining seismofacies analysis, GIS data, GDIS results, and machine‑learning techniques based on Kohonen maps. The constructed probability cube of the collector and the discrete regional cube allowed for the incorporation of facies barriers, justification of blocks with varying VNK and reservoir pressure, and improved the accuracy of hydrodynamic model adaptation by 10 %. Practical application of the method prevented drilling into non‑collector zones, increased the production rate of new wells by 3.5‑fold, and confirmed the feasibility of scaling the approach.

Key words:

facies barriers, seismic facies analysis and wavefield spectral decomposition, machine learning, IP-Seismic, differential compaction, reservoir simulation (hydrodynamic modeling), Western Siberia, Jurassic deposits, bottomhole pressure gauges and well testing, water-oil contact (WOC) and hydrodynamic regions

References

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Authors

Y.K. Zinchenko, Lead Specialist, RN-Geology Research Development LLC
79/1 Osiypenko St., Tyumen, 625002, Russian Federation
E‑mail: ykzinchenko@tnnc.rosneft.ru

For citation:

Y.K. Zinchenko Vyyavleniye i integratsiya fatsial'nykh bar'yerov v geologiyu i razrabotku [Identification and integration of facies barriers in geology and development]. Neftyanaya Provintsiya, No. 3(47), 2026. pp. 23-36. DOI https://doi.org/10.25689/NP.2026.3.23-36. EDN SEBWGF (in Russian)

© Non-governmental organization Volga-Kama Regional Division of the Russian Academy of Natural Science, 2015-2026 All the materials of the journal are available under the Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/)