Seismic wavelet estimation is an important part of seismic data processing and interpretation, whose preciseness is directly related to the results of deconvolution and inversion. Wavelet estimation based on higher-or...Seismic wavelet estimation is an important part of seismic data processing and interpretation, whose preciseness is directly related to the results of deconvolution and inversion. Wavelet estimation based on higher-order spectra is an important new method. However, the higher-order spectra often have phase wrapping problems, which lead to wavelet phase spectrum deviations and thereby affect mixed-phase wavelet estimation. To solve this problem, we propose a new phase spectral method based on conformal mapping in the bispectral domain. The method avoids the phase wrapping problems by narrowing the scope of the Fourier phase spectrum to eliminate the bispectral phase wrapping influence in the original phase spectral estimation. The method constitutes least-squares wavelet phase spectrum estimation based on conformal mapping which is applied to mixed-phase wavelet estimation with the least-squares wavelet amplitude spectrum estimation. Theoretical model and actual seismic data verify the validity of this method. We also extend the idea of conformal mapping in the bispectral wavelet phase spectrum estimation to trispectral wavelet phase spectrum estimation.展开更多
China＇s continental deposition basins are characterized by complex geological structures and various reservoir lithologies. Therefore, high precision exploration methods are needed. High density spatial sampling is a...China＇s continental deposition basins are characterized by complex geological structures and various reservoir lithologies. Therefore, high precision exploration methods are needed. High density spatial sampling is a new technology to increase the accuracy of seismic exploration. We briefly discuss point source and receiver technology, analyze the high density spatial sampling in situ method, introduce the symmetric sampling principles presented by Gijs J. O. Vermeer, and discuss high density spatial sampling technology from the point of view of wave field continuity. We emphasize the analysis of the high density spatial sampling characteristics, including the high density first break advantages for investigation of near surface structure, improving static correction precision, the use of dense receiver spacing at short offsets to increase the effective coverage at shallow depth, and the accuracy of reflection imaging. Coherent noise is not aliased and the noise analysis precision and suppression increases as a result. High density spatial sampling enhances wave field continuity and the accuracy of various mathematical transforms, which benefits wave field separation. Finally, we point out that the difficult part of high density spatial sampling technology is the data processing. More research needs to be done on the methods of analyzing and processing huge amounts of seismic data.展开更多
Presented here is a new adaptive state filtering algorithm for systems with multiplicative noise. This algorithm estimates the vector state of the system and the statistics of noise when all the statistics of noise ar...Presented here is a new adaptive state filtering algorithm for systems with multiplicative noise. This algorithm estimates the vector state of the system and the statistics of noise when all the statistics of noise are unknown. This filtering algorithm is a simple recursive structure. A simulation example is presented which demonstrates the effectiveness of this filtering algorithm.展开更多
An analysis of a passive seismic method for subsurface imaging is presented in which ambient seismic noise is employed as the source of illumination of subsurface scatterers. The imaging algorithm can incorporate new ...An analysis of a passive seismic method for subsurface imaging is presented in which ambient seismic noise is employed as the source of illumination of subsurface scatterers. The imaging algorithm can incorporate new data into the image in a recursive fashion which causes image background noise to diminish over time. Under the assumption of spatially-incoherent ambient noise, an analytical expression for the point-spread function of the imaging algorithm is derived. The point-spread function （PSF） characterizes the resolution of the image, which is a function of the receiving array length and the ambient bandwidth.展开更多
Aiming at the characteristics of the seismic exploration signals, the paper studies the image coding technology, the coding standard and algorithm, brings forward a new scheme of admixing coding for seismic data compr...Aiming at the characteristics of the seismic exploration signals, the paper studies the image coding technology, the coding standard and algorithm, brings forward a new scheme of admixing coding for seismic data compression. Based on it, a set of seismic data compression software has been developed.展开更多
The optimization inversion method based on derivatives is an important inversion technique in seismic data processing,where the key problem is how to compute the Jacobian matrix.The computation precision of the Jacobi...The optimization inversion method based on derivatives is an important inversion technique in seismic data processing,where the key problem is how to compute the Jacobian matrix.The computation precision of the Jacobian matrix directly influences the success of the optimization inversion method.Currently,all AVO(Amplitude Versus Offset) inversion techniques are based on approximate expressions of Zoeppritz equations to obtain derivatives.As a result,the computation precision and application range of these AVO inversions are restricted undesirably.In order to improve the computation precision and to extend the application range of AVO inversions,the partial derivative equation(Jacobian matrix equation(JME) for the P-and S-wave velocities inversion) is established with Zoeppritz equations,and the derivatives of each matrix entry with respect to Pand S-wave velocities are derived.By solving the JME,we obtain the partial derivatives of the seismic wave reflection coefficients(RCs) with respect to P-and S-wave velocities,respectively,which are then used to invert for P-and S-wave velocities.To better understand the behavior of the new method,we plot partial derivatives of the seismic wave reflection coefficients,analyze the characteristics of these curves,and present new understandings for the derivatives acquired from in-depth analysis.Because only a linear system of equations is solved in our method,the computation of Jacobian matrix is not only of high precision but also is fast and efficient.Finally,the theoretical foundation is established so that we can further study inversion problems involving layered structures(including those with large incident angle) and can further improve computational speed and precision.展开更多
The alternating electromagnetic(EM) field is one of the most sensitive physical fields related to earthquakes. There have been a number of publications reporting EM anomalies associated with earthquakes. With increasi...The alternating electromagnetic(EM) field is one of the most sensitive physical fields related to earthquakes. There have been a number of publications reporting EM anomalies associated with earthquakes. With increasing applications and research of artificial-source extremely low frequency EM and satellite EM technologies in earthquake studies, the amount of observed data from the alternating EM method increases rapidly and exponentially, so it is imperative to develop suitable and effective methods for processing and analyzing the influx of big data. This paper presents research on the self-adaptive filter and wavelet techniques and their applications to analyzing EM data obtained from ground measurements and satellite observations, respectively. Analysis results show that the self-adaptive filter method can identify both natural- and artificial-source EM signals, and enhance the ratio between signal and noise of EM field spectra, apparent resistivity, and others. The wavelet analysis is capable of detecting possible correlation between EM anomalies and seismic events. These techniques are effective in processing and analyzing massive data obtained from EM observations.展开更多
基金supported by National 973 Program (No. 2007CB209600)
文摘Seismic wavelet estimation is an important part of seismic data processing and interpretation, whose preciseness is directly related to the results of deconvolution and inversion. Wavelet estimation based on higher-order spectra is an important new method. However, the higher-order spectra often have phase wrapping problems, which lead to wavelet phase spectrum deviations and thereby affect mixed-phase wavelet estimation. To solve this problem, we propose a new phase spectral method based on conformal mapping in the bispectral domain. The method avoids the phase wrapping problems by narrowing the scope of the Fourier phase spectrum to eliminate the bispectral phase wrapping influence in the original phase spectral estimation. The method constitutes least-squares wavelet phase spectrum estimation based on conformal mapping which is applied to mixed-phase wavelet estimation with the least-squares wavelet amplitude spectrum estimation. Theoretical model and actual seismic data verify the validity of this method. We also extend the idea of conformal mapping in the bispectral wavelet phase spectrum estimation to trispectral wavelet phase spectrum estimation.
文摘China＇s continental deposition basins are characterized by complex geological structures and various reservoir lithologies. Therefore, high precision exploration methods are needed. High density spatial sampling is a new technology to increase the accuracy of seismic exploration. We briefly discuss point source and receiver technology, analyze the high density spatial sampling in situ method, introduce the symmetric sampling principles presented by Gijs J. O. Vermeer, and discuss high density spatial sampling technology from the point of view of wave field continuity. We emphasize the analysis of the high density spatial sampling characteristics, including the high density first break advantages for investigation of near surface structure, improving static correction precision, the use of dense receiver spacing at short offsets to increase the effective coverage at shallow depth, and the accuracy of reflection imaging. Coherent noise is not aliased and the noise analysis precision and suppression increases as a result. High density spatial sampling enhances wave field continuity and the accuracy of various mathematical transforms, which benefits wave field separation. Finally, we point out that the difficult part of high density spatial sampling technology is the data processing. More research needs to be done on the methods of analyzing and processing huge amounts of seismic data.
文摘Presented here is a new adaptive state filtering algorithm for systems with multiplicative noise. This algorithm estimates the vector state of the system and the statistics of noise when all the statistics of noise are unknown. This filtering algorithm is a simple recursive structure. A simulation example is presented which demonstrates the effectiveness of this filtering algorithm.
文摘An analysis of a passive seismic method for subsurface imaging is presented in which ambient seismic noise is employed as the source of illumination of subsurface scatterers. The imaging algorithm can incorporate new data into the image in a recursive fashion which causes image background noise to diminish over time. Under the assumption of spatially-incoherent ambient noise, an analytical expression for the point-spread function of the imaging algorithm is derived. The point-spread function （PSF） characterizes the resolution of the image, which is a function of the receiving array length and the ambient bandwidth.
文摘Aiming at the characteristics of the seismic exploration signals, the paper studies the image coding technology, the coding standard and algorithm, brings forward a new scheme of admixing coding for seismic data compression. Based on it, a set of seismic data compression software has been developed.
基金supported by Funding Project for Academic Human Resources Development in Institutions of Higher Learning (Grant No. PHR(20117145))National Natural Science Foundation of China (Grant No. 10705049)
文摘The optimization inversion method based on derivatives is an important inversion technique in seismic data processing,where the key problem is how to compute the Jacobian matrix.The computation precision of the Jacobian matrix directly influences the success of the optimization inversion method.Currently,all AVO(Amplitude Versus Offset) inversion techniques are based on approximate expressions of Zoeppritz equations to obtain derivatives.As a result,the computation precision and application range of these AVO inversions are restricted undesirably.In order to improve the computation precision and to extend the application range of AVO inversions,the partial derivative equation(Jacobian matrix equation(JME) for the P-and S-wave velocities inversion) is established with Zoeppritz equations,and the derivatives of each matrix entry with respect to Pand S-wave velocities are derived.By solving the JME,we obtain the partial derivatives of the seismic wave reflection coefficients(RCs) with respect to P-and S-wave velocities,respectively,which are then used to invert for P-and S-wave velocities.To better understand the behavior of the new method,we plot partial derivatives of the seismic wave reflection coefficients,analyze the characteristics of these curves,and present new understandings for the derivatives acquired from in-depth analysis.Because only a linear system of equations is solved in our method,the computation of Jacobian matrix is not only of high precision but also is fast and efficient.Finally,the theoretical foundation is established so that we can further study inversion problems involving layered structures(including those with large incident angle) and can further improve computational speed and precision.
基金supported by the National Natural Science Foundation of China(Grant Nos.41374077,41074047)CEA-NASCC Dragon Project Ⅲ(Grant No.10671)Special Public Benefit Program for Earthquake Study(Grant No.200808010)
文摘The alternating electromagnetic(EM) field is one of the most sensitive physical fields related to earthquakes. There have been a number of publications reporting EM anomalies associated with earthquakes. With increasing applications and research of artificial-source extremely low frequency EM and satellite EM technologies in earthquake studies, the amount of observed data from the alternating EM method increases rapidly and exponentially, so it is imperative to develop suitable and effective methods for processing and analyzing the influx of big data. This paper presents research on the self-adaptive filter and wavelet techniques and their applications to analyzing EM data obtained from ground measurements and satellite observations, respectively. Analysis results show that the self-adaptive filter method can identify both natural- and artificial-source EM signals, and enhance the ratio between signal and noise of EM field spectra, apparent resistivity, and others. The wavelet analysis is capable of detecting possible correlation between EM anomalies and seismic events. These techniques are effective in processing and analyzing massive data obtained from EM observations.
