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Petrophysical properties prediction of deep dolomite reservoir considering pore structure

Gui Jinyong, Yin Xingyao, Jianhu Gao, Li Shengjun, Liu Bingyang

Acta Geophysica

2022

Vol. 70, no 4

1507--1518

Prediction of petrophysical properties of deep dolomite reservoir using elastic parameter data is challenging and of great uncertainty. Changes in the petrophysical properties generally induce perturbations in elastic properties. Rock-physics model, which plays a role as a bridge between petrophysical properties and elastic properties, determines the accuracy of inversion for petrophysical properties using elastic properties. Different pore structures lead to variations of rock-physics relationships, and in dolomite reservoir, the influence of pore structure on elastic properties is larger than that of petrophysical properties. We first propose a statistical rock-physics model, in which we consider the effect of pore structure on the nonlinear rockphysical relationship between petrophysical properties and elastic properties of dolomite reservoirs. Then, we propose a Bayesian inversion approach of using elastic properties to predict petrophysical properties and use weight factors to address the difference in accuracy of the input elastic properties in the Bayesian inversion framework. Examples illustrate the proposed approach may produce petrophysical properties of high accuracy for deep dolomite reservoirs.

Multi sparsity based spectral attributes for discontinuity detection

Wang Tieyi, Yuan Sanyi, Yang Shan, Liu Bingyang, Wang Shangxu

Acta Geophysica

2019

Vol. 67, no. 4

1059--1069

Structural and stratigraphic discontinuities, such as faults and channels, generally contribute to the construction of traps and reservoirs. Spectral decomposition can utilize the sensitivities of different frequency components to different geological conditions to identify these geological anomalies. The sparse inverse spectral decomposition (SISD) involves a sparse constraint of time–frequency spectra, and one critical parameter is the sparsity which determines the time–frequency resolution. A small sparsity gives a low temporal resolution result that cannot be used for thin-bed detection. Conversely, a large sparsity provides a high-resolution result, but it may lose weak refection signals. The complex geological conditions in the subsurface will lead to some difficulties in detecting the discontinuities by using the SISD method with a fixed sparsity. To address this issue, we propose multi-sparsity-based spectral attributes by fusing the amplitude spectra results of three different sparsities to detect subsurface discontinuities. Compared with the fixed sparsity, the multi-sparsity-based spectral attributes can detect more geological details and highlight geological edges more clearly. The application on a 3D real data with an area of 230 km2 from deep formation in Northwest China exhibits its effectiveness in discontinuity detection. The proposed method can detect the weak or small hidden geological details more and better than the fixed sparsity method, suggesting that it may serve as a future tool for detecting the distribution of geological abnormalities in subsurface.