Porosity estimation based on the shear modulus inversion of seismic shear wave

被引:0
作者
Dai, Fucai [1 ,2 ]
Zhang, Feng [2 ,3 ]
Li, Xiangyang [3 ]
Xu, Yong [1 ]
机构
[1] Zhoukou Normal Univ, Sch Comp Sci & Technol, Zhoukou, Peoples R China
[2] China Univ Petr, State Key Lab Petr Resources & Prospecting, Beijing, Peoples R China
[3] China Univ Petr, CNPC Key Lab Geophys Explorat, Beijing, Peoples R China
关键词
WELL-LOG DATA; ROCK-PHYSICS; MULTIATTRIBUTE TRANSFORMS; PREDICTION; DENSITY; VELOCITY; FLUID; ATTRIBUTES; SATURATION; RESERVOIR;
D O I
10.1190/GEO2023-0618.1
中图分类号
P3 [地球物理学]; P59 [地球化学];
学科分类号
0708 ; 070902 ;
摘要
Reliable estimation of subsurface porosity is necessary for hydrocarbon reservoir characterization and fluid identification. Porosity estimations from seismic data can provide the lateral distribution of subsurface porosity, but the results may be highly nonunique because subsurface elastic properties (such as velocity and density) can be affected by porosity and pore fluids. Because shear modulus is insensitive to pore fluid content, it can be effectively used to estimate porosity. We develop a novel porosity estimation method using the reflected SH wave (SH-SH wave), whose propagation characteristics depend mainly on shear modulus and S-wave velocity. We derive a new analytical expression for the SH-SH-wave reflection coefficient, which acts as a function of shear modulus and Swave velocity in its natural logarithm form. This new approximation has high accuracy, and both coefficients corresponding to shear modulus and S-wave velocity are " model-parameter independent"; " ; thus, there is no need for prior estimation of any model parameter during inversion. Numerical analysis indicates that shear modulus inverted from the SH-SH wave has lower uncertainty, the problem is better conditioned, and the method requires data with fewer incidence angles than algorithms that invert for the shear modulus from the PP wave. Furthermore, the highly correlated rock-physics relationships between porosity and shear modulus facilitate accurate porosity estimation. A field data application indicates that high-resolution porosity of fine structures can be reliably recovered using our method.
引用
收藏
页码:M123 / M135
页数:13
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