基于BISQ模型的储层物性参数贝叶斯反演方法

doi:10.13810/j.cnki.issn.1000-7210.2023.04.019

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Abstract For problems with multiple solutions such as the physical property inversion, common methods are usually difficult to obtain optimal solutions with high efficiency and accuracy. Therefore, according to the Bayesian statistics, we use the Gaussian prior model to introduce the constraints from well-log data and develop a Bayesian inversion method for reservoir physical properties to overcome the multi-solution problem. Next, a petrophysical forward model is developed based on the BISQ and effective fluid theories, which can reflect the multiple physical effects of solids and fluid in the porous medium and finely characterize the propagation process of seismic waves in the reservoir, thus enhancing the reliability of inversion results. In addition, because deterministic optimization algorithms usually have only local convergence capability and fail to converge to the global optimal solution of the inversion problem, hybrid genetic algorithms with global convergence capability are introduced to improve the accuracy and efficiency of the inversion method. Finally, the proposed inversion method is used to predict the porosity and water saturation in oil field A in eastern China, and positive results are obtained.

Key words： BISQ model Bayesian inversion reservoir elastic parameters reservoir physical properties

Received: 18 July 2022

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P631

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	Articles by authors
	QU Zhipeng
	WEN Jin
	HAN Hongwei
	BU Fan
	WANG Xingmou
	ZHU Jianbing

Cite this article:

QU Zhipeng,WEN Jin,HAN Hongwei等. Bayesian inversion based on BISQ model for reservoir physical properties[J]. OGP, 2023, 58(4): 942-948.

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http://www.ogp-cn.com/EN/10.13810/j.cnki.issn.1000-7210.2023.04.019 OR http://www.ogp-cn.com/EN/Y2023/V58/I4/942

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