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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.

Direct inversion for sensitive elastic parameters of deep reservoirs

Li Shengjun, Gui Jinyong, Gao Jianhu, Wang Shangxu, Li Hailiang

Acta Geophysica

2019

Vol. 67, no. 5

1329--1340

The deep reservoir is usually a type of tight reservoir with high pressure, high stress, low permeability and low porosity. The elastic parameters including Poisson’s ratio and Young’s modulus are important sensitive parameters to the tight reservoir, and the Gassmann fuid term is frequently used in the feld of fuid identifcation as a highly sensitive fuid factor. Such parameters can be obtained by the common prestack seismic inversion method, but not directly. It must frst invert for other elastic parameters and then convert them into the Poisson’s ratio, Young’s modulus and Gassmann fuid term by some formula. The errors will be accumulated in the conversion step, and the inversion results will have a large deviation. We propose a one-step inversion method to solve this problem. Firstly, a new form of P-wave refection coefcient equation in terms of Poisson’s ratio, Young’s modulus and Gassmann fuid term is derived which can directly establish the functional relationship between the P-wave refection coefcient and these elastic parameters. Considering seismic data of deep reservoir generally have a lower signal-to-noise ratio (S/N) and the partial angle stack gather has a higher S/N than single angle gather, we then derive a stack impedance equation which is suitable for the partial angle stack gather. By using three stacked impedance inversion data with diferent angle stack ranges, we can directly get the Poisson’s ratio, Young’s modulus and Gassmann fuid term simultaneously. Model and real data tests both prove that the one-step direct inversion method can reduce the cumulative errors efectively and has higher inversion accuracy.