Research output: Contribution to journal › Article › peer-review
Boolean Spectral Analysis in Categorical Reservoir Modeling. / Ismagilov, Niyaz; Borovitskiy, Viacheslav; Lifshits, Mikhail; Platonova, Mariia.
In: Mathematical Geosciences, Vol. 53, No. 3, 04.2021, p. 305-324.Research output: Contribution to journal › Article › peer-review
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TY - JOUR
T1 - Boolean Spectral Analysis in Categorical Reservoir Modeling
AU - Ismagilov, Niyaz
AU - Borovitskiy, Viacheslav
AU - Lifshits, Mikhail
AU - Platonova, Mariia
N1 - Funding Information: Research was partially supported by Russian Science Foundation Grant 19-71-30002. Publisher Copyright: © 2021, International Association for Mathematical Geosciences. Copyright: Copyright 2021 Elsevier B.V., All rights reserved.
PY - 2021/4
Y1 - 2021/4
N2 - This work introduces a new method for simulating facies distribution with two categories based on Fourier analysis of Boolean functions. According to this method, two categories of facies distributed along vertical wells are encoded as Boolean functions taking two values. The subsequent simulation process is divided into three consecutive steps. First, Boolean functions of the well data are decomposed into a binary version of a Fourier series. Decomposition coefficients are then simulated over the two-dimensional area as stationary random fields. Finally, synthetic data in the interwell space are reconstructed from simulated coefficients. The described method was implemented experimentally in software and tested on a case of a real oil field and on a case of a synthetic oil field model. Simulations on the synthetic model were used to test the performance of the method for two different bases in the Fourier expansion (Walsh functions and Haar wavelets). The simulation results were compared to those obtained on the same synthetic model via the classical sequential indicator simulation. It was shown that, for both bases, the new method reproduces statistical parameters of the well data better than sequential indicator simulation.
AB - This work introduces a new method for simulating facies distribution with two categories based on Fourier analysis of Boolean functions. According to this method, two categories of facies distributed along vertical wells are encoded as Boolean functions taking two values. The subsequent simulation process is divided into three consecutive steps. First, Boolean functions of the well data are decomposed into a binary version of a Fourier series. Decomposition coefficients are then simulated over the two-dimensional area as stationary random fields. Finally, synthetic data in the interwell space are reconstructed from simulated coefficients. The described method was implemented experimentally in software and tested on a case of a real oil field and on a case of a synthetic oil field model. Simulations on the synthetic model were used to test the performance of the method for two different bases in the Fourier expansion (Walsh functions and Haar wavelets). The simulation results were compared to those obtained on the same synthetic model via the classical sequential indicator simulation. It was shown that, for both bases, the new method reproduces statistical parameters of the well data better than sequential indicator simulation.
KW - Boolean functions
KW - Categorical simulation
KW - Reservoir modeling
KW - Spectral analysis
UR - http://www.scopus.com/inward/record.url?scp=85100073867&partnerID=8YFLogxK
UR - https://www.mendeley.com/catalogue/1e967251-6da3-31c8-b5d0-30620816e51f/
U2 - 10.1007/s11004-021-09919-z
DO - 10.1007/s11004-021-09919-z
M3 - Article
AN - SCOPUS:85100073867
VL - 53
SP - 305
EP - 324
JO - Mathematical Geosciences
JF - Mathematical Geosciences
SN - 1874-8961
IS - 3
ER -
ID: 75053013