Joint PP‐ and PSV‐wave amplitudes versus offset and azimuth inversion for fracture compliances in horizontal transversely isotropic media

Chen, Huaizhen; Zhang, Guangzhi; Chen, Tiansheng; Yin, Xingyao

doi:10.1111/1365-2478.12567

Cited by 10 publications

(2 citation statements)

References 44 publications

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“…The physical property parameter prediction method based on linearized rock physics inversion applies to linear or slightly nonlinear rock physical models (Zhang et al, 2020b;Pan et al, 2021). For the highly nonlinear rock physical model, the empirical formula method is used to predict the porosity (Zong and Yin, 2017;Chen et al, 2017;Pan et al, 2017;. It is to obtain a statistical empirical relationship between porosity and rock elastic parameters (such as P-wave velocity, S-wave velocity, density, and elastic impedance) by using rock physics test data and logging data and then use this statistical empirical relationship to convert the elastic parameters obtained by seismic inversion into porosity parameters.…”

Section: Porosity Inversionmentioning

confidence: 99%

Rock Physical Modeling of Tight Sandstones Based on Digital Rocks and Reservoir Porosity Prediction From Seismic Data

et al. 2022

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Digital rock physics (DRP) has become an important tool to analyze the characteristics of pore structures and minerals and reveal the relationships between microscopic structures and the physical properties of reservoirs. However, it is greatly difficult to upscale the rock physical parameters, such as P-wave velocity, S-wave velocity, and elastic moduli, from DRP to large-scale boreholes and reservoirs. On the other hand, theoretical rock physical modeling can establish the internal relationship between the elastic properties and physical parameters of tight sandstones, which provides a theoretical basis for seismic inversion and seismic forward modeling. Therefore, the combination of digital rock physics and rock physical modeling can guide the identification and evaluation of the gas reservoir’s “sweet spot.” In this study, the CT images are used to analyze the mineral and pore characteristics. After that, the V-R-H model is used to calculate the equivalent elastic moduli of rocks containing only the mineral matrix, and then, the differential equivalent medium (DEM) model is used to obtain the elastic moduli of dry rocks containing minerals and pores. Subsequently, the homogeneous saturation model is used to fill the fluids in the pores and the Gassmann equation is used to calculate the equivalent elastic moduli of the saturated rock of tight sandstones. Rock physical modeling is calibrated, and the reliability of the rock physical model is verified by comparing those with the logging data. Afterward, the empirical relationship of rock porosity established from CT images and rock elastic moduli is obtained, and then, the elastic parameters obtained by seismic data inversion are converted into porosity parameters by using this empirical relationship. Finally, the porosity prediction of large-scale reservoirs in the study area is realized to figure out the distribution of gas reservoirs with high porosity. The results show that the H3b and H3c sections of the study area exhibit higher porosity than H3a. For the H3b reservoir, the northeast and middle areas of the gas field are potential targets since their porosity is larger than that of others, from 10% to 20%. Because of the effects of the provenance from the east direction, the southeast region of the H3c reservoir exhibits higher porosity than others.

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Section: Porosity Inversionmentioning

confidence: 99%

Rock Physical Modeling of Tight Sandstones Based on Digital Rocks and Reservoir Porosity Prediction From Seismic Data

et al. 2022

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“…Rocks located in areas with high values of strain energy density are more prone to produce ruptures. Therefore, this parameter can be used to determine the probability of internal ruptures in rocks [68]- [70].…”

Section: Sweet Spot Prediction a Strain Energy Density Distributionmentioning

confidence: 99%

Numerical Study on the Prediction of “Sweet Spots” in a Low Efficiency-Tight Gas Sandstone Reservoir Based on a 3D Strain Energy Model

Yin

Gao

2019

IEEE Access

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The study of the construction of a micro-scale rupture parameter from the perspective of rock stress and strain is a frontier in geoscience. The strain energy density (U) can quantitatively characterize the probability of internal micro-scale ruptures in different types of rock. Based on this, in this paper, a systematic forecasting method for tight sandstone sweet spots in a low-amplitude tectonic zone based on U-value calculations was proposed. The specific steps are as follows. First, a geological model of the target layer was created, and a new rock mechanics parameter assignment method based on sedimentary facies control principle was proposed. Then, the palaeo-tectonic stress field of the target layer in the Yanshanian period was recovered through the boundary loading. Finally, the strain energy density distribution of the target layer was obtained based on energy conservation principle. The simulation results of the paleo-tectonic stress field show that, the distribution of horizontal stress is mainly affected by lithology and local structure, and the vertical stress is mainly affected by the burial depth. Stress diffusion occurs in some areas, which are mainly affected by lithologic mutations or complex structures. The U values of the target layers have a band-like distribution and are mainly distributed between 0.12 and 0.30 J•m −3. The relationship between strain energy density and productivity of tight sandstone reservoirs was analyzed, and the criteria for distinguishing sweet spot areas based on U values were proposed. This method is applicable to strongly heterogeneous tight sandstone reservoirs in the low-amplitude tectonic zone of the Ordos Basin and have reference values for similar types of reservoirs around the world. INDEX TERMS Tight gas sandstone, strain energy model, finite element method, tectonic stress field.

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A Comparative Study of Pre-Stack Fracture Prediction Methods for Coal Bed Methane

Zhang,

Jiang

et al. 2024

Springer Series in Geomechanics and Geoengineering

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Joint PP‐ and PSV‐wave amplitudes versus offset and azimuth inversion for fracture compliances in horizontal transversely isotropic media

Cited by 10 publications

References 44 publications

Rock Physical Modeling of Tight Sandstones Based on Digital Rocks and Reservoir Porosity Prediction From Seismic Data

Rock Physical Modeling of Tight Sandstones Based on Digital Rocks and Reservoir Porosity Prediction From Seismic Data

Numerical Study on the Prediction of “Sweet Spots” in a Low Efficiency-Tight Gas Sandstone Reservoir Based on a 3D Strain Energy Model

A Comparative Study of Pre-Stack Fracture Prediction Methods for Coal Bed Methane

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