首页|3D rock physics template-based probabilistic estimation of tight sandstone reservoir properties

3D rock physics template-based probabilistic estimation of tight sandstone reservoir properties

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Quantitative prediction of reservoir properties(e.g.,gas saturation,porosity,and shale content)of tight reservoirs is of great significance for resource evaluation and well placements.However,the complex pore structures,poor pore connectivity,and uneven fluid distribution of tight sandstone reservoirs make the correlation between reservoir parameters and elastic properties more complicated and thus pose a major challenge in seismic reservoir characterization.We have developed a partially connected double porosity model to calculate elastic properties by considering the pore structure and connectivity,and to analyze these factors'influences on the elastic behaviors of tight sandstone reservoirs.The modeling results suggest that the bulk modulus is likely to be affected by the pore connectivity coefficient,while the shear modulus is sensitive to the volumetric fraction of stiff pores.By comparing the model pre-dictions with the acoustic measurements of the dry and saturated quartz sandstone samples,the volumetric fraction of stiff pores and the pore connectivity coefficient can be determined.Based on the calibrated model,we have constructed a 3D rock physics template that accounts for the reservoir properties'impacts on the P-wave impedance,S-wave impedance,and density.The template combined with Bayesian inverse theory is used to quantify gas saturation,porosity,clay content,and their corre-sponding uncertainties from elastic parameters.The application of well-log and seismic data demon-strates that our 3D rock physics template-based probabilistic inversion approach performs well in predicting the spatial distribution of high-quality tight sandstone reservoirs in southwestern China.

Tight sandstonesPore structure3D rock physics templateSeismic inversionReservoir property estimation

Hao-Jie Pan、Chao Wei、Xin-Fei Yan、Xiao-Ming Li、Zhi-Fang Yang、Zhi-Xian Gui、Shu-Xian Liu

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College of Geophysics and Petroleum Resources,Yangtze University,Wuhan,430100,Hubei,China

Research Institute of Petroleum Exploration and Department,Petrochina,Beijing,100083,China

2024

石油科学(英文版)
中国石油大学(北京)

石油科学(英文版)

EI
影响因子:0.88
ISSN:1672-5107
年,卷(期):2024.21(5)