New Method of Oil Reservoir Rock Heterogeneity Quantitative Estimation from X-ray MCT Data

Irena Viktorovna Yazynina, Evgeny Vladimirovich Shelyago, Andrey Andreevich Abrosimov and Vladimir Stanislavovich Yakushev
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Irena Viktorovna Yazynina: Department of Oil Field Development and Operation, Gubkin Russian State University of Oil and Gas (National Research University), 65 Leninsky Prospekt, 119991 Moscow, Russia
Evgeny Vladimirovich Shelyago: Department of Oil Field Development and Operation, Gubkin Russian State University of Oil and Gas (National Research University), 65 Leninsky Prospekt, 119991 Moscow, Russia
Andrey Andreevich Abrosimov: Department of Oil Field Development and Operation, Gubkin Russian State University of Oil and Gas (National Research University), 65 Leninsky Prospekt, 119991 Moscow, Russia
Vladimir Stanislavovich Yakushev: Department of Gas and Gas Condensate Field Development and Operation, Gubkin Russian State University of Oil and Gas (National Research University), 65 Leninsky Prospekt, 119991 Moscow, Russia

Energies, 2021, vol. 14, issue 16, 1-8

Abstract: This paper considers a new method for “pore scale” oil reservoir rock quantitative estimation. The method is based on core sample X-ray tomography data analysis and can be directly used to both classify rocks by heterogeneity and assess representativeness of the core material collection. The proposed heterogeneity criteria consider the heterogeneity of pore size and heterogeneity of pore arrangement in the sample void and can thus be related to the drainage effectiveness. The classification of rocks by heterogeneity at the pore scale is also proposed when choosing a reservoir engineering method and may help us to find formations that are similar at pore scale. We analyzed a set of reservoir rocks of different lithologies using the new method that considers only tomographic images and clearly distributes samples over the structure of their pore space.

Keywords: reservoir rock; heterogeneity; tomography (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
References: View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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