Известия Томского политехнического университета: Инжиниринг георесурсов (Jul 2021)

SPECIFIC FEATURES OF PETROPHYSICAL PROPERTIES OF COMPLEX CARBONATE RESERVOIR BY COMPLEX GEOPHYSICAL DATA

  • Kristina Yu. Chuchalina,
  • Mikhail O. Korovin

DOI
https://doi.org/10.18799/24131830/2021/7/3268
Journal volume & issue
Vol. 332, no. 7
pp. 107 – 113

Abstract

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The relevance of the research is determined by the need to predict the lateral variability of lithological rock types, which affects the development and economic evaluation of the field. Very often, oil companies have a limited set of geological and geophysical information, in this relation the difficulties arise in predicting promising areas, which contributes to increase in uncertainties in the study of the field. The main aim of the research is isolation and statistical justification of the facies structure according to the geological and geophysical information on the example of one of the deposits of the Tomsk region, confined to the Paleozoic basement of Western Siberia. The object of the study is deposits of the Paleozoic basement of the southeastern part of the West Siberian Plate – complex carbonate reservoir, the study window that covers a rock volume of 40 m is selected based on the conditions for constructing a seismic facies map. Methods of the research are based on the use of integrated data analysis – a statistical comparison of geophysical surveys and core material. This analysis helps to reduce uncertainties in the process of assessing and forecasting the geological environment. The paper notes that the use of a wide range of information affects the assessment and forecast of the distribution of geological bodies in space. A technique is proposed for comparing acoustic properties obtained from the original source – seismic data, with the calculated acoustic properties from core data. The authors have revealed the interconnections between seismic, geophysical information and core research. The justification of the obtained seismic facies map based on the data integration allows us to effectively predict the geological distribution of facies in space and time, but also to reduce uncertainties in the construction of the geological model.

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