Fan Wu, Jingye Li, Xiaohong Chen, W. Geng, Wei Tang
{"title":"基于岩石物理模型的正交各向异性储层孔隙长径比和毛细管压力系数估算S波速度","authors":"Fan Wu, Jingye Li, Xiaohong Chen, W. Geng, Wei Tang","doi":"10.1080/08123985.2022.2117602","DOIUrl":null,"url":null,"abstract":"Accurate prediction of S-wave velocity is of great significance in many aspects, such as inversion, migration, brittleness index calculation, etc. Under normal circumstances, the more types of known input parameters there are, the more accurate the rock’s specific situation, and the more accurate the predicted S-wave velocity. However, considering the actual situation, the types of parameters obtained through logging curves are relatively limited. Some parameters cannot be measured and calculated, which limits the accuracy of S-wave prediction. Therefore, if the parameters can be predicted, a more accurate underground situation is able to described by these parameters. Through rockphysical analysis, the pore aspect ratio and capillary pressure coefficient can affect the velocity. In this way, a new orthorhombic (ORT) rockphysical modeling process considering the pore aspect ratio and capillary pressure coefficient is proposed. The model consists of VTI anisotropy from compaction or textural alignment of minerals, and HTI anisotropy from high-angle fractures caused by stratum pressure, thus showing ORT anisotropy. The inputs of the model can be multiple minerals. And the pore structure and the modulus of the mixed fluids in the pores are considered. We use inverse theory (quantum genetic algorithms) to obtain the pore aspect ratio and capillary pressure coefficient and finally calculate the S-wave velocity through the above parameters. The calculation results in a shale reservoir show that the predicted S-wave velocity is in good agreement with the real logging data. This shows that the proposed rockphysical modeling process and inverse algorithm method are effective.","PeriodicalId":0,"journal":{"name":"","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Estimation of pore aspect ratio and capillary pressure coefficient to predict S-wave velocity based on rockphysics modeling in orthorhombic anisotropic reservoirs\",\"authors\":\"Fan Wu, Jingye Li, Xiaohong Chen, W. 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In this way, a new orthorhombic (ORT) rockphysical modeling process considering the pore aspect ratio and capillary pressure coefficient is proposed. The model consists of VTI anisotropy from compaction or textural alignment of minerals, and HTI anisotropy from high-angle fractures caused by stratum pressure, thus showing ORT anisotropy. The inputs of the model can be multiple minerals. And the pore structure and the modulus of the mixed fluids in the pores are considered. We use inverse theory (quantum genetic algorithms) to obtain the pore aspect ratio and capillary pressure coefficient and finally calculate the S-wave velocity through the above parameters. The calculation results in a shale reservoir show that the predicted S-wave velocity is in good agreement with the real logging data. 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Estimation of pore aspect ratio and capillary pressure coefficient to predict S-wave velocity based on rockphysics modeling in orthorhombic anisotropic reservoirs
Accurate prediction of S-wave velocity is of great significance in many aspects, such as inversion, migration, brittleness index calculation, etc. Under normal circumstances, the more types of known input parameters there are, the more accurate the rock’s specific situation, and the more accurate the predicted S-wave velocity. However, considering the actual situation, the types of parameters obtained through logging curves are relatively limited. Some parameters cannot be measured and calculated, which limits the accuracy of S-wave prediction. Therefore, if the parameters can be predicted, a more accurate underground situation is able to described by these parameters. Through rockphysical analysis, the pore aspect ratio and capillary pressure coefficient can affect the velocity. In this way, a new orthorhombic (ORT) rockphysical modeling process considering the pore aspect ratio and capillary pressure coefficient is proposed. The model consists of VTI anisotropy from compaction or textural alignment of minerals, and HTI anisotropy from high-angle fractures caused by stratum pressure, thus showing ORT anisotropy. The inputs of the model can be multiple minerals. And the pore structure and the modulus of the mixed fluids in the pores are considered. We use inverse theory (quantum genetic algorithms) to obtain the pore aspect ratio and capillary pressure coefficient and finally calculate the S-wave velocity through the above parameters. The calculation results in a shale reservoir show that the predicted S-wave velocity is in good agreement with the real logging data. This shows that the proposed rockphysical modeling process and inverse algorithm method are effective.