The analysis technology of Amplitude Variation with Offset(AVO)is one of the important methods for oil and gas reservoir prediction.Zoeppritz equation and its approximations are the theoretical basis of AVO analysis,w...The analysis technology of Amplitude Variation with Offset(AVO)is one of the important methods for oil and gas reservoir prediction.Zoeppritz equation and its approximations are the theoretical basis of AVO analysis,which assumes that the upper and lower media of a horizontal interface are single-phase media.Limited by this assumption,AVO analysis has limited prediction and identification accuracy for complex porous reservoirs.In view of this,the first-order approximate analytical expressions of oblique elastic wave at an interface of porous media are derived.Firstly,the incident and scattering characteristics of various waves at the interface of porous media are analyzed,and the displacement vectors generated by these elastic waves are described by exponential function.Secondly,the kinematic and dynamic boundary conditions at the interface of porous media are discussed.Thirdly,by substituting the displacement vectors of incident and scattered waves into boundary conditions,the exact analytical equation is derived.Then,considering the symmetry of scattering matrix in the equation,the exact analytical expressions of each scattered wave are obtained.Furthermore,under the assumptions of small incident angle,weak elasticity at an interface of porous media,and ignoring the second-and higherorder terms,the first-order approximate analytical expressions are derived.Establishing a model of sandstone porous media with different porosity in upper and lower media,the correctness of the approximate analytical expressions is verified,and the elastic wave response characteristics of lithology and pore fluids are analyzed.展开更多
In order to solve the black-box modeling problem and improve the prediction accuracy of model,two distinguished models for tensile strength(Ts)and yield strength(Ys)of hot-rolled strip steel are established based on t...In order to solve the black-box modeling problem and improve the prediction accuracy of model,two distinguished models for tensile strength(Ts)and yield strength(Ys)of hot-rolled strip steel are established based on the industrial hot-rolled data and the algorithm of gene expression programming(GEP).Firstly,the industrial data of hot-rolled strip steel are preprocessed using the Pauta criterion,so as to eliminate outliers.The key input variables that affect Ys and Ts are selected by using the method of the maximal information coefficient(MIC).Secondly,the explicit prediction models of Ys and Ts are established using GEP.Subsequently,the model results based on GEP are compared with those based on the support vector regression(SVR)and the back propagation neural network(BPNN).Finally,the mathematical expression models for Ys and Ts obtained by GEP are used to further analyse the specific relationships between the chemical composition and mechanical property.It is shown that the errors of Ys and Ts based on GEP are less than 4%,and the coefficient of determination(R^(2))of Ys and Ts based on GEP is above 0.9,which has strong prediction performance.The prediction accuracy of GEP can achieve the same level with SVR and BPNN.It is worth mentioning that the proposed model can not only show the explicit relationship between the chemical composition,production process,and mechanical property of strip steel,but also occupy high prediction accuracy,which can make reliable reference for strip steel product design and optimisation.展开更多
基金financially supported by the National Natural Science Foundation of China(Grant No.42104131)the Natural Science Foundation of Sichuan Province of China(Grant No.2022NSFSC1140)Open Fund(PLC20211101)of State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation
文摘The analysis technology of Amplitude Variation with Offset(AVO)is one of the important methods for oil and gas reservoir prediction.Zoeppritz equation and its approximations are the theoretical basis of AVO analysis,which assumes that the upper and lower media of a horizontal interface are single-phase media.Limited by this assumption,AVO analysis has limited prediction and identification accuracy for complex porous reservoirs.In view of this,the first-order approximate analytical expressions of oblique elastic wave at an interface of porous media are derived.Firstly,the incident and scattering characteristics of various waves at the interface of porous media are analyzed,and the displacement vectors generated by these elastic waves are described by exponential function.Secondly,the kinematic and dynamic boundary conditions at the interface of porous media are discussed.Thirdly,by substituting the displacement vectors of incident and scattered waves into boundary conditions,the exact analytical equation is derived.Then,considering the symmetry of scattering matrix in the equation,the exact analytical expressions of each scattered wave are obtained.Furthermore,under the assumptions of small incident angle,weak elasticity at an interface of porous media,and ignoring the second-and higherorder terms,the first-order approximate analytical expressions are derived.Establishing a model of sandstone porous media with different porosity in upper and lower media,the correctness of the approximate analytical expressions is verified,and the elastic wave response characteristics of lithology and pore fluids are analyzed.
基金supported by the National Natural Science Foundation of China(Grant Nos.52074187 and 52274388)Liaoning Province Artificial Intelligence Innovation and Development Plan Project(Major Science and Technology Project)(2023JH26-10100002)the National Key Research and Development Program of China(No.2022YFB3304800).
文摘In order to solve the black-box modeling problem and improve the prediction accuracy of model,two distinguished models for tensile strength(Ts)and yield strength(Ys)of hot-rolled strip steel are established based on the industrial hot-rolled data and the algorithm of gene expression programming(GEP).Firstly,the industrial data of hot-rolled strip steel are preprocessed using the Pauta criterion,so as to eliminate outliers.The key input variables that affect Ys and Ts are selected by using the method of the maximal information coefficient(MIC).Secondly,the explicit prediction models of Ys and Ts are established using GEP.Subsequently,the model results based on GEP are compared with those based on the support vector regression(SVR)and the back propagation neural network(BPNN).Finally,the mathematical expression models for Ys and Ts obtained by GEP are used to further analyse the specific relationships between the chemical composition and mechanical property.It is shown that the errors of Ys and Ts based on GEP are less than 4%,and the coefficient of determination(R^(2))of Ys and Ts based on GEP is above 0.9,which has strong prediction performance.The prediction accuracy of GEP can achieve the same level with SVR and BPNN.It is worth mentioning that the proposed model can not only show the explicit relationship between the chemical composition,production process,and mechanical property of strip steel,but also occupy high prediction accuracy,which can make reliable reference for strip steel product design and optimisation.
