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ARTICLE

Method of complex interpretation of spectral decomposition for seismic facies analysis and parametrization of lithological traps

ALBINA BELAEVA* ,  DAMIR MURTAZIN
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1 Department of Informatics and Information Technologies, Federal State Budgetary Educational Establishment of Higher Education “Bashkir State Agrarian University”, Ufa 450001, Russian Federation,
2 Gazpromnrft STC, Saint Petersburg 190000, Russian Federation,
JSE 2022, 31(3), 239–251;
Submitted: 16 November 2021 | Accepted: 18 January 2022 | Published: 1 June 2022
© 2022 by the Authors. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution -Noncommercial 4.0 International License (CC-by the license) ( https://creativecommons.org/licenses/by-nc/4.0/ )
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Abstract

Belaeva, A. and Murtazin, D., 2022. Method of complex interpretation of spectral decomposition for seismic facies analysis and parametrization of lithological traps. Journal of Seismic Exploration, 31: 239-251. The study aims at creating a method for complex interpretation of spectral decomposition for seismic facies analysis, parametrization of potential lithological traps, prediction of effective reservoir thicknesses in the inter-well space and risk reduction in the assessment of reserves and resources. The method of spectral decomposition using the Wavelet transform was applied during the research. This method of seismic route decomposition was used as part of the proposed methodology. Many clustering methods from the Sklern Python library were used. The study placed a premium on the KMeans methods. Correlation analysis and qualitative interpretation of the obtained seismic images were used to link geological and seismic information. The developed method of sorting the centres of spectral curves clusters allowed a joint analysis of wells data and clustering results. The developed approach was applied to comprehensively study the paleochannel systems of the West Siberian, Timan-Pechora and Volga-Ural oil and gas provinces. The advantages of the proposed technology over attribute analysis, spectral characteristics analysis and RGB blending were proved by comparing the deposits of the above-mentioned provinces. Various geological objects in the wavefield were identified using qualitative interpretation and then linked with wells data. This technology proved to be the best when using quantitative interpretation. High correlation coefficients between the effective thicknesses in wells and the results of spectral curves clustering were obtained.

Keywords
3D seismic measurements
dynamic interpretation
RGB Blending
spectral decomposition
clustering of amplitude-frequency spectra
terrigenous deposits
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Journal of Seismic Exploration, Print ISSN: 0963-0651, Published by AccScience Publishing
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