Conventional AVO inversion utilizes the trace amplitudes of CMP gathers. There are three main factors affecting the accuracy of the inversion. First, CMP gathers are based on the hypothesis of horizontal layers but mo...Conventional AVO inversion utilizes the trace amplitudes of CMP gathers. There are three main factors affecting the accuracy of the inversion. First, CMP gathers are based on the hypothesis of horizontal layers but most real layers are not horizontal. Greater layer dip results in a greater difference between the observed CMP gathers and their real location. Second, conventional processing flows such as NMO, DMO, and deconvolution will distort amplitudes. Third, the formulation of reflection coefficient is related to incidence angles and it is difficult to get the relationship between amplitude and incidence angle. Wave equation prestack depth migration has the ability of imaging complex media and steeply dipping layers. It can reduce the errors of conventional processing and move amplitudes back to their real location. With true amplitude migration, common angle gathers abstraction, and AVO inversion, we suggest a method of AVO inversion from common shot gathers in order to reduce the effect of the above factors and improve the accuracy of AVO inversion.展开更多
An important research topic for prospecting seismology is to provide a fast accurate velocity model from pre-stack depth migration. Aiming at such a problem, we propose a quadratic precision generalized nonlinear glob...An important research topic for prospecting seismology is to provide a fast accurate velocity model from pre-stack depth migration. Aiming at such a problem, we propose a quadratic precision generalized nonlinear global optimization migration velocity inversion. First we discard the assumption that there is a linear relationship between residual depth and residual velocity and propose a velocity model correction equation with quadratic precision which enables the velocity model from each iteration to approach the real model as quickly as possible. Second, we use a generalized nonlinear inversion to get the global optimal velocity perturbation model to all traces. This method can expedite the convergence speed and also can decrease the probability of falling into a local minimum during inversion. The synthetic data and Mamlousi data examples show that our method has a higher precision and needs only a few iterations and consequently enhances the practicability and accuracy of migration velocity analysis （MVA） in complex areas.展开更多
Recently we have developed an eigenvector method (EVM) which can achieve the blind deconvolution (BD) for MIMO systems. One of attractive features of the proposed algorithm is that the BD can be achieved by calculatin...Recently we have developed an eigenvector method (EVM) which can achieve the blind deconvolution (BD) for MIMO systems. One of attractive features of the proposed algorithm is that the BD can be achieved by calculating the eigenvectors of a matrix relevant to it. However, the performance accuracy of the EVM depends highly on computational results of the eigenvectors. In this paper, by modifying the EVM, we propose an algorithm which can achieve the BD without calculating the eigenvectors. Then the pseudo-inverse which is needed to carry out the BD is calculated by our proposed matrix pseudo-inversion lemma. Moreover, using a combination of the conventional EVM and the modified EVM, we will show its performances comparing with each EVM. Simulation results will be presented for showing the effectiveness of the proposed methods.展开更多
Full-waveform inversion(FWI)utilizes optimization methods to recover an optimal Earth model to best fit the observed seismic record in a sense of a predefined norm.Since FWI combines mathematic inversion and full-wave...Full-waveform inversion(FWI)utilizes optimization methods to recover an optimal Earth model to best fit the observed seismic record in a sense of a predefined norm.Since FWI combines mathematic inversion and full-wave equations,it has been recognized as one of the key methods for seismic data imaging and Earth model building in the fields of global/regional and exploration seismology.Unfortunately,conventional FWI fixes background velocity mainly relying on refraction and turning waves that are commonly rich in large offsets.By contrast,reflections in the short offsets mainly contribute to the reconstruction of the high-resolution interfaces.Restricted by acquisition geometries,refractions and turning waves in the record usually have limited penetration depth,which may not reach oil/gas reservoirs.Thus,reflections in the record are the only source that carries the information of these reservoirs.Consequently,it is meaningful to develop reflection-waveform inversion(RWI)that utilizes reflections to recover background velocity including the deep part of the model.This review paper includes:analyzing the weaknesses of FWI when inverting reflections;overviewing the principles of RWI,including separation of the tomography and migration components,the objective functions,constraints;summarizing the current status of the technique of RWI;outlooking the future of RWI.展开更多
This paper introduces an internal multiple prediction method based on imaging profile prediction and Kirchhoff demigration.First,based on an inputted prestack time migration profile,the method predicts the prestack ti...This paper introduces an internal multiple prediction method based on imaging profile prediction and Kirchhoff demigration.First,based on an inputted prestack time migration profile,the method predicts the prestack time migration profile that only includes internal multiples by inverse scattering series method.Second,the method uses velocity-weighted Kirchhoff demigration to create shot gathers that contains only internal multiples.Internal multiple prediction based on the prestack time migration profile effectively reduces the computational cost of multiple predictions,and the internal-multiple shot gathers created by Kirchhoff demigration remarkably reduces the complexity of the practical problem.Internal multiple elimination can be conducted through the combined adaptive multiple subtraction based on event tracing.Synthetic and field data tests show that the method effectively predicts internal multiples and possesses considerable potential in field data processing,particularly in areas where internal multiples develop seriously.展开更多
With the development of computational power, there has been an increased focus on data-fitting related seismic inversion techniques for high fidelity seismic velocity model and image, such as full-waveform inversion a...With the development of computational power, there has been an increased focus on data-fitting related seismic inversion techniques for high fidelity seismic velocity model and image, such as full-waveform inversion and least squares migration. However, though more advanced than conventional methods, these data fitting methods can be very expensive in terms of computational cost. Recently, various techniques to optimize these data-fitting seismic inversion problems have been implemented to cater for the industrial need for much improved efficiency. In this study, we propose a general stochastic conjugate gradient method for these data-fitting related inverse problems. We first prescribe the basic theory of our method and then give synthetic examples. Our numerical experiments illustrate the potential of this method for large-size seismic inversion application.展开更多
To reduce the dependence of EM inversion on the choice of initial model and to obtain the global minimum, we apply transdimensional Bayesian inversion to time-domain airborne electromagnetic data. The transdimensional...To reduce the dependence of EM inversion on the choice of initial model and to obtain the global minimum, we apply transdimensional Bayesian inversion to time-domain airborne electromagnetic data. The transdimensional Bayesian inversion uses the Monte Carlo method to search the model space and yields models that simultaneously satisfy the acceptance probability and data fitting requirements. Finally, we obtain the probability distribution and uncertainty of the model parameters as well as the maximum probability. Because it is difficult to know the height of the transmitting source during flight, we consider a fixed and a variable flight height. Furthermore, we introduce weights into the prior probability density function of the resistivity and adjust the constraint strength in the inversion model by changing the weighing coefficients. This effectively solves the problem of unsatisfactory inversion results in the middle high-resistivity layer. We validate the proposed method by inverting synthetic data with 3% Gaussian noise and field survey data.展开更多
In this paper,we consider the use of blind deconvolution for optoacoustic(photoacoustic)imaging and investigate the performance of the method as means for increasing the resolution of the reconstructed image beyond th...In this paper,we consider the use of blind deconvolution for optoacoustic(photoacoustic)imaging and investigate the performance of the method as means for increasing the resolution of the reconstructed image beyond the physical restrictions of the system.The method is demonstrated with optoacoustic measurement obtained from six-day-old mice,imaged in the near-infrared using a broadband hydrophone in a circular scanning configuration.Wefind that estimates of the unknown point spread function,achieved by blind deconvolution,improve the resolution and contrast in the images and show promise for enhancing optoacoustic images.展开更多
Offshore carbon dioxide(CO_(2)) storage is an effective method for reducing greenhouse gas emissions. However, when using traditional seismic wave methods to monitor the migration of sequestration CO_(2) plumes, the c...Offshore carbon dioxide(CO_(2)) storage is an effective method for reducing greenhouse gas emissions. However, when using traditional seismic wave methods to monitor the migration of sequestration CO_(2) plumes, the characteristics of wave velocity changes tend to become insignificant beyond a certain limit. In contrast, the controllable source electromagnetic method(CSEM) remains highly sensitive to resistivity changes. By simulating different CO_(2) plume migration conditions, we established the relevant models and calculated the corresponding electric field response characteristic curves, allowing us to analyze the CSEM's ability to monitor CO_(2) plumes. We considered potential scenarios for the migration and diffusion of offshore CO_(2) storage, including various burial depths, vertical extension diffusion, lateral extension diffusion,multiple combinations of lateral intervals, and electric field components. We also obtained differences in resistivity inversion imaging obtained by CSEM to evaluate its feasibility in monitoring and to analyze all the electric field(Ex, Ey, and Ez) response characteristics. CSEM has great potential in monitoring CO_(2) plume migration in offshore saltwater reservoirs due to its high sensitivity and accuracy. Furthermore, changes in electromagnetic field response reflect the transport status of CO_(2) plumes, providing an important basis for monitoring and evaluating CO_(2)transport behavior during storage processes.展开更多
This study adopted the Euler deconvolution method to conduct an inversion and interpretation of the depth and spatial distribution pattern of field source that lead to gravity variation. For this purpose, mobile gravi...This study adopted the Euler deconvolution method to conduct an inversion and interpretation of the depth and spatial distribution pattern of field source that lead to gravity variation. For this purpose, mobile gravity data from four periods in the Hexi region between 2011 and 2015 were obtained from an observation network. With a newly established theoretical model, we acquired the optimum inversion parameters and conducted calculation and analysis with the actual data. The results indicate that one is the appropriate value of the structure index for the inversion of the mobile gravity data. The inversion results of the actual data showed a comparable spatial distribution of the field source and a consistent structural trend with observations from the Qilian-Haiyuan Fault zone between 2011 and 2015. The distribution was in a blocking state at the epicenter of the Menyuan earthquake in 2016. Our quantitative study of the field source provides new insights into the inversion and interpretation of signals of mobile gravity variation.展开更多
In this paper, we propose a novel seismic blind deconvolution approach based on the Spearman’s rho in the case of band-limited seismic data with a low dominant frequency and short data records. The Spearman’s rho is...In this paper, we propose a novel seismic blind deconvolution approach based on the Spearman’s rho in the case of band-limited seismic data with a low dominant frequency and short data records. The Spearman’s rho is a measure of the dependence between two continuous random variables without the influence of the marginal distributions, by which a new criterion for blind deconvolution is constructed. The optimization program for new criterion of blind deconvolution is performed by applying Neidell’s wavelet model to the inverse filter. The noise-free and noisy synthetic data, onshore seismic trace in the Ordos Basin, and offshore stacked section in the Bohai Bay Basin examples show good results of the method.展开更多
The Yutu-2 rover onboard the Chang’E-4 mission performed the first lunar penetrating radar detection on the farside of the Moon.The high-frequency channel presented us with many unprecedented details of the subsurfac...The Yutu-2 rover onboard the Chang’E-4 mission performed the first lunar penetrating radar detection on the farside of the Moon.The high-frequency channel presented us with many unprecedented details of the subsurface structures within a depth of approximately 50 m.However,it was still difficult to identify finer layers from the cluttered reflections and scattering waves.We applied deconvolution to improve the vertical resolution of the radar profile by extending the limited bandwidth associated with the emissive radar pulse.To overcome the challenges arising from the mixed-phase wavelets and the problematic amplification of noise,we performed predictive deconvolution to remove the minimum-phase components from the Chang’E-4 dataset,followed by a comprehensive phase rotation to rectify phase anomalies in the radar image.Subsequently,we implemented irreversible migration filtering to mitigate the noise and diminutive clutter echoes amplified by deconvolution.The processed data showed evident enhancement of the vertical resolution with a widened bandwidth in the frequency domain and better signal clarity in the time domain,providing us with more undisputed details of subsurface structures near the Chang’E-4 landing site.展开更多
The propagation of seismic waves in viscous media,such as the loess plateau and shallow gas regions,alters their amplitude,frequency,and phase due to absorption attenuation,resulting in reductions in the resolution an...The propagation of seismic waves in viscous media,such as the loess plateau and shallow gas regions,alters their amplitude,frequency,and phase due to absorption attenuation,resulting in reductions in the resolution and fidelity of seismic profiles and the inaccurate identification of subtle structure and lithology.Q modeling and Q migration techniques proposed in this paper are used to compensate for the energy and frequency attenuation of seismic waves,obtain high-quality depth imaging results,and further enhance structural imaging to address the aforementioned problem.First,various prior information is utilized to construct an initial Q model.Q tomography techniques are employed to further optimize the precision of the initial Q model and build a high-precision Q model.Subsequently,Q prestack depth migration technology is employed to compensate for absorption and attenuation in the three-dimensional space along the seismic wave propagation path and correct the travel times,realizing the purposes of amplitude compensation,frequency recovery,and phase correction,which can help improve the wave group characteristics while enhancing the resolution.Model data and practical application results demonstrate that high-precision Q modeling and Q migration techniques can substantially improve the imaging quality of underground structures and formations in the loess plateau region with extremely complex surface and near-surface conditions.The resolution and fidelity of seismic data,as well as the capability to identify reservoirs,can be improved using these techniques.展开更多
Current data-driven deep learning(DL)methods typically reconstruct subsurface velocity models directly from pre-stack seismic records.However,these purely data-driven methods are often less robust and produce results ...Current data-driven deep learning(DL)methods typically reconstruct subsurface velocity models directly from pre-stack seismic records.However,these purely data-driven methods are often less robust and produce results that are less physically interpretative.Here,the authors propose a new method that uses migration images as input,combined with convolutional neural networks to construct high-resolution velocity models.Compared to directly using pre-stack seismic records as input,the nonlinearity between migration images and velocity models is significantly reduced.Additionally,the advantage of using migration images lies in its ability to more comprehensively capture the reflective properties of the subsurface medium,including amplitude and phase information,thereby to provide richer physical information in guiding the reconstruction of the velocity model.This approach not only improves the accuracy and resolution of the reconstructed velocity models,but also enhances the physical interpretability and robustness.Numerical experiments on synthetic data show that the proposed method has superior reconstruction performance and strong generalization capability when dealing with complex geological structures,and shows great potential in providing efficient solutions for the task of reconstructing high-wavenumber components.展开更多
Based on the absolute and relative gravity observations in North China from 2009 to 2014,spatial dynamic variations of the regional gravity field are obtained. We employed the Euler deconvolution method and the theore...Based on the absolute and relative gravity observations in North China from 2009 to 2014,spatial dynamic variations of the regional gravity field are obtained. We employed the Euler deconvolution method and the theoretical model to get the best estimates of parameters. Gravity field change caused by the depth and distribution in North China is calculated by back analysis. The results show the structural index that equals 1 is suitable for inversion of the gravity variation data. The inversion results indicate that the depths of anomaly field sources are spread over the Hetao fault. The research method of this paper can be used in the quantitative study on the field source and may shed new light on the interpretations of gravity change, and also provide quantitative basis for earthquake prediction index criterions based on the gravity change.展开更多
A new concept, the generalized inverse group (GIG) of signal, is firstly proposed and its properties, leaking coefficients and implementation with neural networks are presented. Theoretical analysis and computational ...A new concept, the generalized inverse group (GIG) of signal, is firstly proposed and its properties, leaking coefficients and implementation with neural networks are presented. Theoretical analysis and computational simulation have shown that (1) there is a group of finite length of generalized inverse signals for any given finite signal, which forms the GIG; (2) each inverse group has different leaking coefficients, thus different abnormal states; (3) each GIG can be implemented by a grouped and improved single-layer perceptron which appears with fast convergence. When used in deconvolution, the proposed GIG can form a new parallel finite length of filtering deconvolution method. On off-line processing, the computational time is reduced to O(N) from O(N2). And the less the leaking coefficient is, the more reliable the deconvolution will be.展开更多
基金This project is sponsored by the "Pre-Cenozoic Marine Oil and Gas Resource Research around the Bohai Area" of the Knowledge Innovation Project of The Chinese Academy of Sciences (No. KZCX1-SW-18)
文摘Conventional AVO inversion utilizes the trace amplitudes of CMP gathers. There are three main factors affecting the accuracy of the inversion. First, CMP gathers are based on the hypothesis of horizontal layers but most real layers are not horizontal. Greater layer dip results in a greater difference between the observed CMP gathers and their real location. Second, conventional processing flows such as NMO, DMO, and deconvolution will distort amplitudes. Third, the formulation of reflection coefficient is related to incidence angles and it is difficult to get the relationship between amplitude and incidence angle. Wave equation prestack depth migration has the ability of imaging complex media and steeply dipping layers. It can reduce the errors of conventional processing and move amplitudes back to their real location. With true amplitude migration, common angle gathers abstraction, and AVO inversion, we suggest a method of AVO inversion from common shot gathers in order to reduce the effect of the above factors and improve the accuracy of AVO inversion.
基金This work is supported by National Natural Science Foundation of China （Grant No.40839905）.
文摘An important research topic for prospecting seismology is to provide a fast accurate velocity model from pre-stack depth migration. Aiming at such a problem, we propose a quadratic precision generalized nonlinear global optimization migration velocity inversion. First we discard the assumption that there is a linear relationship between residual depth and residual velocity and propose a velocity model correction equation with quadratic precision which enables the velocity model from each iteration to approach the real model as quickly as possible. Second, we use a generalized nonlinear inversion to get the global optimal velocity perturbation model to all traces. This method can expedite the convergence speed and also can decrease the probability of falling into a local minimum during inversion. The synthetic data and Mamlousi data examples show that our method has a higher precision and needs only a few iterations and consequently enhances the practicability and accuracy of migration velocity analysis （MVA） in complex areas.
文摘Recently we have developed an eigenvector method (EVM) which can achieve the blind deconvolution (BD) for MIMO systems. One of attractive features of the proposed algorithm is that the BD can be achieved by calculating the eigenvectors of a matrix relevant to it. However, the performance accuracy of the EVM depends highly on computational results of the eigenvectors. In this paper, by modifying the EVM, we propose an algorithm which can achieve the BD without calculating the eigenvectors. Then the pseudo-inverse which is needed to carry out the BD is calculated by our proposed matrix pseudo-inversion lemma. Moreover, using a combination of the conventional EVM and the modified EVM, we will show its performances comparing with each EVM. Simulation results will be presented for showing the effectiveness of the proposed methods.
基金supported by National Key R&D Program of China(No.2018YFA0702502)NSFC(Grant No.41974142)Science Foundation of China University of petroleum,Beijing(No.2462019YJRC005).
文摘Full-waveform inversion(FWI)utilizes optimization methods to recover an optimal Earth model to best fit the observed seismic record in a sense of a predefined norm.Since FWI combines mathematic inversion and full-wave equations,it has been recognized as one of the key methods for seismic data imaging and Earth model building in the fields of global/regional and exploration seismology.Unfortunately,conventional FWI fixes background velocity mainly relying on refraction and turning waves that are commonly rich in large offsets.By contrast,reflections in the short offsets mainly contribute to the reconstruction of the high-resolution interfaces.Restricted by acquisition geometries,refractions and turning waves in the record usually have limited penetration depth,which may not reach oil/gas reservoirs.Thus,reflections in the record are the only source that carries the information of these reservoirs.Consequently,it is meaningful to develop reflection-waveform inversion(RWI)that utilizes reflections to recover background velocity including the deep part of the model.This review paper includes:analyzing the weaknesses of FWI when inverting reflections;overviewing the principles of RWI,including separation of the tomography and migration components,the objective functions,constraints;summarizing the current status of the technique of RWI;outlooking the future of RWI.
基金support of the NSFC-Shandong Joint Fund for Marine Science Research Centers (No. U1606401)the National Natural Science Foundation of China (Nos. 41704114 and 41574105)+3 种基金the National Science and Technology Major Project of China (No. 2016Z X05027-002)the Scientific and Technological Innovation Project financially supported by Qingdao National Laboratory for Marine Science and Technology (No. 2016 ASKJ13)Taishan Scholar Project Funding (No. tspd2016 1007)the Latitudinal Project of Algorithm Research of Internal Multiple Prediction financially supported by CNOOC
文摘This paper introduces an internal multiple prediction method based on imaging profile prediction and Kirchhoff demigration.First,based on an inputted prestack time migration profile,the method predicts the prestack time migration profile that only includes internal multiples by inverse scattering series method.Second,the method uses velocity-weighted Kirchhoff demigration to create shot gathers that contains only internal multiples.Internal multiple prediction based on the prestack time migration profile effectively reduces the computational cost of multiple predictions,and the internal-multiple shot gathers created by Kirchhoff demigration remarkably reduces the complexity of the practical problem.Internal multiple elimination can be conducted through the combined adaptive multiple subtraction based on event tracing.Synthetic and field data tests show that the method effectively predicts internal multiples and possesses considerable potential in field data processing,particularly in areas where internal multiples develop seriously.
基金partially supported by the National Natural Science Foundation of China (No.41230318)
文摘With the development of computational power, there has been an increased focus on data-fitting related seismic inversion techniques for high fidelity seismic velocity model and image, such as full-waveform inversion and least squares migration. However, though more advanced than conventional methods, these data fitting methods can be very expensive in terms of computational cost. Recently, various techniques to optimize these data-fitting seismic inversion problems have been implemented to cater for the industrial need for much improved efficiency. In this study, we propose a general stochastic conjugate gradient method for these data-fitting related inverse problems. We first prescribe the basic theory of our method and then give synthetic examples. Our numerical experiments illustrate the potential of this method for large-size seismic inversion application.
基金This paper was financially supported by the Key National Research Project of China （Nos. 2017YFC0601900 and 2016YFC0303100）, and the Key Program of National Natural Science Foundation of China （No. 41530320） and Surface Project （No. 41774125）.
文摘To reduce the dependence of EM inversion on the choice of initial model and to obtain the global minimum, we apply transdimensional Bayesian inversion to time-domain airborne electromagnetic data. The transdimensional Bayesian inversion uses the Monte Carlo method to search the model space and yields models that simultaneously satisfy the acceptance probability and data fitting requirements. Finally, we obtain the probability distribution and uncertainty of the model parameters as well as the maximum probability. Because it is difficult to know the height of the transmitting source during flight, we consider a fixed and a variable flight height. Furthermore, we introduce weights into the prior probability density function of the resistivity and adjust the constraint strength in the inversion model by changing the weighing coefficients. This effectively solves the problem of unsatisfactory inversion results in the middle high-resistivity layer. We validate the proposed method by inverting synthetic data with 3% Gaussian noise and field survey data.
文摘In this paper,we consider the use of blind deconvolution for optoacoustic(photoacoustic)imaging and investigate the performance of the method as means for increasing the resolution of the reconstructed image beyond the physical restrictions of the system.The method is demonstrated with optoacoustic measurement obtained from six-day-old mice,imaged in the near-infrared using a broadband hydrophone in a circular scanning configuration.Wefind that estimates of the unknown point spread function,achieved by blind deconvolution,improve the resolution and contrast in the images and show promise for enhancing optoacoustic images.
基金Supported by Key Special Project for Introduced Talents Team of Southern Marine Science and Engineering Guangdong Laboratory (2019BT02H594)Sanya Technology Innovation Special Project (2022KJCX08)。
文摘Offshore carbon dioxide(CO_(2)) storage is an effective method for reducing greenhouse gas emissions. However, when using traditional seismic wave methods to monitor the migration of sequestration CO_(2) plumes, the characteristics of wave velocity changes tend to become insignificant beyond a certain limit. In contrast, the controllable source electromagnetic method(CSEM) remains highly sensitive to resistivity changes. By simulating different CO_(2) plume migration conditions, we established the relevant models and calculated the corresponding electric field response characteristic curves, allowing us to analyze the CSEM's ability to monitor CO_(2) plumes. We considered potential scenarios for the migration and diffusion of offshore CO_(2) storage, including various burial depths, vertical extension diffusion, lateral extension diffusion,multiple combinations of lateral intervals, and electric field components. We also obtained differences in resistivity inversion imaging obtained by CSEM to evaluate its feasibility in monitoring and to analyze all the electric field(Ex, Ey, and Ez) response characteristics. CSEM has great potential in monitoring CO_(2) plume migration in offshore saltwater reservoirs due to its high sensitivity and accuracy. Furthermore, changes in electromagnetic field response reflect the transport status of CO_(2) plumes, providing an important basis for monitoring and evaluating CO_(2)transport behavior during storage processes.
基金funded by Science and Technology Project of Shanxi Province (2014K13-04)the National Science Foundation of China (41274083)+1 种基金the Special Fund for Earthquake Scientific Research of China (201308009)the Youth Seismic Regime Tracking Project in the Year of 2016, China Earthquake Administration (2016010222)
文摘This study adopted the Euler deconvolution method to conduct an inversion and interpretation of the depth and spatial distribution pattern of field source that lead to gravity variation. For this purpose, mobile gravity data from four periods in the Hexi region between 2011 and 2015 were obtained from an observation network. With a newly established theoretical model, we acquired the optimum inversion parameters and conducted calculation and analysis with the actual data. The results indicate that one is the appropriate value of the structure index for the inversion of the mobile gravity data. The inversion results of the actual data showed a comparable spatial distribution of the field source and a consistent structural trend with observations from the Qilian-Haiyuan Fault zone between 2011 and 2015. The distribution was in a blocking state at the epicenter of the Menyuan earthquake in 2016. Our quantitative study of the field source provides new insights into the inversion and interpretation of signals of mobile gravity variation.
文摘In this paper, we propose a novel seismic blind deconvolution approach based on the Spearman’s rho in the case of band-limited seismic data with a low dominant frequency and short data records. The Spearman’s rho is a measure of the dependence between two continuous random variables without the influence of the marginal distributions, by which a new criterion for blind deconvolution is constructed. The optimization program for new criterion of blind deconvolution is performed by applying Neidell’s wavelet model to the inverse filter. The noise-free and noisy synthetic data, onshore seismic trace in the Ordos Basin, and offshore stacked section in the Bohai Bay Basin examples show good results of the method.
基金supported by the National Natural Science Foundation of China(Grant Nos.42325406 and 42304187)the China Postdoctoral Science Foundation(Grant No.2023M733476)+3 种基金the CAS Project for Young Scientists in Basic Research(Grant No.YSBR082)the National Key R&D Program of China(Grant No.2022YFF0503203)the Key Research Program of the Institute of Geology and GeophysicsChinese Academy of Sciences(Grant Nos.IGGCAS-202101 and IGGCAS-202401).
文摘The Yutu-2 rover onboard the Chang’E-4 mission performed the first lunar penetrating radar detection on the farside of the Moon.The high-frequency channel presented us with many unprecedented details of the subsurface structures within a depth of approximately 50 m.However,it was still difficult to identify finer layers from the cluttered reflections and scattering waves.We applied deconvolution to improve the vertical resolution of the radar profile by extending the limited bandwidth associated with the emissive radar pulse.To overcome the challenges arising from the mixed-phase wavelets and the problematic amplification of noise,we performed predictive deconvolution to remove the minimum-phase components from the Chang’E-4 dataset,followed by a comprehensive phase rotation to rectify phase anomalies in the radar image.Subsequently,we implemented irreversible migration filtering to mitigate the noise and diminutive clutter echoes amplified by deconvolution.The processed data showed evident enhancement of the vertical resolution with a widened bandwidth in the frequency domain and better signal clarity in the time domain,providing us with more undisputed details of subsurface structures near the Chang’E-4 landing site.
基金supported by the China National Offshore Oil Corporation’s“14th Five-Year Plan”major scientific and technological project,“Key Technologies for Onshore Unconventional Natural Gas Exploration and Development”(KJGG2021-1000).
文摘The propagation of seismic waves in viscous media,such as the loess plateau and shallow gas regions,alters their amplitude,frequency,and phase due to absorption attenuation,resulting in reductions in the resolution and fidelity of seismic profiles and the inaccurate identification of subtle structure and lithology.Q modeling and Q migration techniques proposed in this paper are used to compensate for the energy and frequency attenuation of seismic waves,obtain high-quality depth imaging results,and further enhance structural imaging to address the aforementioned problem.First,various prior information is utilized to construct an initial Q model.Q tomography techniques are employed to further optimize the precision of the initial Q model and build a high-precision Q model.Subsequently,Q prestack depth migration technology is employed to compensate for absorption and attenuation in the three-dimensional space along the seismic wave propagation path and correct the travel times,realizing the purposes of amplitude compensation,frequency recovery,and phase correction,which can help improve the wave group characteristics while enhancing the resolution.Model data and practical application results demonstrate that high-precision Q modeling and Q migration techniques can substantially improve the imaging quality of underground structures and formations in the loess plateau region with extremely complex surface and near-surface conditions.The resolution and fidelity of seismic data,as well as the capability to identify reservoirs,can be improved using these techniques.
文摘Current data-driven deep learning(DL)methods typically reconstruct subsurface velocity models directly from pre-stack seismic records.However,these purely data-driven methods are often less robust and produce results that are less physically interpretative.Here,the authors propose a new method that uses migration images as input,combined with convolutional neural networks to construct high-resolution velocity models.Compared to directly using pre-stack seismic records as input,the nonlinearity between migration images and velocity models is significantly reduced.Additionally,the advantage of using migration images lies in its ability to more comprehensively capture the reflective properties of the subsurface medium,including amplitude and phase information,thereby to provide richer physical information in guiding the reconstruction of the velocity model.This approach not only improves the accuracy and resolution of the reconstructed velocity models,but also enhances the physical interpretability and robustness.Numerical experiments on synthetic data show that the proposed method has superior reconstruction performance and strong generalization capability when dealing with complex geological structures,and shows great potential in providing efficient solutions for the task of reconstructing high-wavenumber components.
基金funded by the Natural Science Foundation of China(61627824,41274083)the Youth Foundation of Earthquake Prediction(2017010227)
文摘Based on the absolute and relative gravity observations in North China from 2009 to 2014,spatial dynamic variations of the regional gravity field are obtained. We employed the Euler deconvolution method and the theoretical model to get the best estimates of parameters. Gravity field change caused by the depth and distribution in North China is calculated by back analysis. The results show the structural index that equals 1 is suitable for inversion of the gravity variation data. The inversion results indicate that the depths of anomaly field sources are spread over the Hetao fault. The research method of this paper can be used in the quantitative study on the field source and may shed new light on the interpretations of gravity change, and also provide quantitative basis for earthquake prediction index criterions based on the gravity change.
基金Supported partly by Natural Science Foundation of ChinaAviation Science Grant of China
文摘A new concept, the generalized inverse group (GIG) of signal, is firstly proposed and its properties, leaking coefficients and implementation with neural networks are presented. Theoretical analysis and computational simulation have shown that (1) there is a group of finite length of generalized inverse signals for any given finite signal, which forms the GIG; (2) each inverse group has different leaking coefficients, thus different abnormal states; (3) each GIG can be implemented by a grouped and improved single-layer perceptron which appears with fast convergence. When used in deconvolution, the proposed GIG can form a new parallel finite length of filtering deconvolution method. On off-line processing, the computational time is reduced to O(N) from O(N2). And the less the leaking coefficient is, the more reliable the deconvolution will be.
