4.7 Article

Pore and Microfracture Characterization in Tight Gas Sandstone Reservoirs with a New Rock-Physics-Based Seismic Attribute

期刊

REMOTE SENSING
卷 15, 期 2, 页码 -

出版社

MDPI
DOI: 10.3390/rs15020289

关键词

pore-microfracture indicator (PMI); tight gas sandstone reservoir; double-porosity model; microfracture porosity prediction; quantitative seismic interpretation

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This study proposes a rock-physics-based approach to compute the pore-microfracture indicator (PMI) from elastic properties for pore structure evaluation in tight sandstones. Seismic characterization of pores and microfractures provides valuable information in predicting high-quality tight gas sandstone reservoirs. The computed PMI using seismic data can predict permeable zones and provide valuable information for sweet spot characterization in tight gas sandstone reservoirs.
Pores and microfractures provide storage spaces and migration pathways for gas accumulation in tight sandstones with low porosity and permeability, acting as one of the controlling factors of gas production. The development of a rational rock physics model is essential for better understanding the elastic responses of tight sandstone with complex pore structures. Accordingly, seismic characterization of pores and microfractures based on the rock physics model provides valuable information in predicting high-quality tight gas sandstone reservoirs. This paper proposes a rock-physics-based approach to compute the pore-microfracture indicator (PMI) from elastic properties for pore structure evaluation in tight sandstones. The PMI is achieved based on the axis rotation of the elastic parameter space using well-log data. The rotation angle is determined by finding the maximum correlation between the linearized combination of the elastic parameters and the introduced factor associated with total porosity and microfracture porosity. The microfracture porosity is then estimated with an inversion scheme based on the double-porosity model. Finally, the optimized rotation angle is employed to compute the PMI with seismic data. The obtained results are of great benefit in predicting the permeable zones, providing valuable information for sweet spot characterization in tight gas sandstone reservoirs.

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