In this paper, we built upon the estimating primaries by sparse inversion （EPSI） method. We use the 3D curvelet transform and modify the EPSI method to the sparse inversion of the biconvex optimization and Ll-norm r...In this paper, we built upon the estimating primaries by sparse inversion （EPSI） method. We use the 3D curvelet transform and modify the EPSI method to the sparse inversion of the biconvex optimization and Ll-norm regularization, and use alternating optimization to directly estimate the primary reflection coefficients and source wavelet. The 3D curvelet transform is used as a sparseness constraint when inverting the primary reflection coefficients, which results in avoiding the prediction subtraction process in the surface-related multiples elimination （SRME） method. The proposed method not only reduces the damage to the effective waves but also improves the elimination of multiples. It is also a wave equation- based method for elimination of surface multiple reflections, which effectively removes surface multiples under complex submarine conditions.展开更多
In this paper,an uncertainty propagation analysis method is developed based on an extended sparse grid technique and maximum entropy principle,aiming at improving the solving accuracy of the high-order moments and hen...In this paper,an uncertainty propagation analysis method is developed based on an extended sparse grid technique and maximum entropy principle,aiming at improving the solving accuracy of the high-order moments and hence the fitting accuracy of the probability density function(PDF)of the system response.The proposed method incorporates the extended Gauss integration into the uncertainty propagation analysis.Moreover,assisted by the Rosenblatt transformation,the various types of extended integration points are transformed into the extended Gauss-Hermite integration points,which makes the method suitable for any type of continuous distribution.Subsequently,within the sparse grid numerical integration framework,the statistical moments of the system response are obtained based on the transformed points.Furthermore,based on the maximum entropy principle,the obtained first four-order statistical moments are used to fit the PDF of the system response.Finally,three numerical examples are investigated to demonstrate the effectiveness of the proposed method,which includes two mathematical problems with explicit expressions and an engineering application with a black-box model.展开更多
Oil and gas seismic exploration have to adopt irregular seismic acquisition due to the increasingly complex exploration conditions to adapt to complex geological conditions and environments.However,the irregular seism...Oil and gas seismic exploration have to adopt irregular seismic acquisition due to the increasingly complex exploration conditions to adapt to complex geological conditions and environments.However,the irregular seismic acquisition is accompanied by the lack of acquisition data,which requires high-precision regularization.The sparse signal feature in the transform domain in compressed sensing theory is used in this paper to recover the missing signal,involving sparse transform base optimization and threshold modeling.First,this paper analyzes and compares the effects of six sparse transformation bases on the reconstruction accuracy and efficiency of irregular seismic data and establishes the quantitative relationship between sparse transformation and reconstruction accuracy and efficiency.Second,an adaptive threshold modeling method based on sparse coefficient is provided to improve the reconstruction accuracy.Test results show that the method has good adaptability to different seismic data and sparse transform bases.The f-x domain reconstruction method of effective frequency samples is studied to address the problem of low computational efficiency.The parallel computing strategy of curvelet transform combined with OpenMP is further proposed,which substantially improves the computational efficiency under the premise of ensuring the reconstruction accuracy.Finally,the actual acquisition data are used to verify the proposed method.The results indicate that the proposed method strategy can solve the regularization problem of irregular seismic data in production and improve the imaging quality of the target layer economically and efficiently.展开更多
基金supported by the National Science and Technology Major Project (No.2011ZX05023-005-008)
文摘In this paper, we built upon the estimating primaries by sparse inversion （EPSI） method. We use the 3D curvelet transform and modify the EPSI method to the sparse inversion of the biconvex optimization and Ll-norm regularization, and use alternating optimization to directly estimate the primary reflection coefficients and source wavelet. The 3D curvelet transform is used as a sparseness constraint when inverting the primary reflection coefficients, which results in avoiding the prediction subtraction process in the surface-related multiples elimination （SRME） method. The proposed method not only reduces the damage to the effective waves but also improves the elimination of multiples. It is also a wave equation- based method for elimination of surface multiple reflections, which effectively removes surface multiples under complex submarine conditions.
基金the National Science Fund for Distinguished Young Scholars(Grant No.51725502)the major program of the National Natural Science Foundation of China(Grant No.51490662)the National Key Research and Development Project of China(Grant No.2016YFD0701105).
文摘In this paper,an uncertainty propagation analysis method is developed based on an extended sparse grid technique and maximum entropy principle,aiming at improving the solving accuracy of the high-order moments and hence the fitting accuracy of the probability density function(PDF)of the system response.The proposed method incorporates the extended Gauss integration into the uncertainty propagation analysis.Moreover,assisted by the Rosenblatt transformation,the various types of extended integration points are transformed into the extended Gauss-Hermite integration points,which makes the method suitable for any type of continuous distribution.Subsequently,within the sparse grid numerical integration framework,the statistical moments of the system response are obtained based on the transformed points.Furthermore,based on the maximum entropy principle,the obtained first four-order statistical moments are used to fit the PDF of the system response.Finally,three numerical examples are investigated to demonstrate the effectiveness of the proposed method,which includes two mathematical problems with explicit expressions and an engineering application with a black-box model.
基金supported by the National Science and Technology Major project(No.2016ZX05024001003)the Innovation Consortium Project of China Petroleum,and the Southwest Petroleum University(No.2020CX010201).
文摘Oil and gas seismic exploration have to adopt irregular seismic acquisition due to the increasingly complex exploration conditions to adapt to complex geological conditions and environments.However,the irregular seismic acquisition is accompanied by the lack of acquisition data,which requires high-precision regularization.The sparse signal feature in the transform domain in compressed sensing theory is used in this paper to recover the missing signal,involving sparse transform base optimization and threshold modeling.First,this paper analyzes and compares the effects of six sparse transformation bases on the reconstruction accuracy and efficiency of irregular seismic data and establishes the quantitative relationship between sparse transformation and reconstruction accuracy and efficiency.Second,an adaptive threshold modeling method based on sparse coefficient is provided to improve the reconstruction accuracy.Test results show that the method has good adaptability to different seismic data and sparse transform bases.The f-x domain reconstruction method of effective frequency samples is studied to address the problem of low computational efficiency.The parallel computing strategy of curvelet transform combined with OpenMP is further proposed,which substantially improves the computational efficiency under the premise of ensuring the reconstruction accuracy.Finally,the actual acquisition data are used to verify the proposed method.The results indicate that the proposed method strategy can solve the regularization problem of irregular seismic data in production and improve the imaging quality of the target layer economically and efficiently.
