This is a case study of the application of pre-stack inverted elastic parameters to tight-sand reservoir prediction. With the development of oil and gas exploration, pre-stack data and inversion results are increasing...This is a case study of the application of pre-stack inverted elastic parameters to tight-sand reservoir prediction. With the development of oil and gas exploration, pre-stack data and inversion results are increasingly used for production objectives. The pre-stack seismic property studies include not only amplitude verse offset （AVO） but also the characteristics of other elastic property changes. In this paper, we analyze the elastic property parameters characteristics of gas- and wet-sands using data from four gas-sand core types. We found that some special elastic property parameters or combinations can be used to identify gas sands from water saturated sand. Thus, we can do reservoir interpretation and description using different elastic property data from the pre-stack seismic inversion processing. The pre- stack inversion method is based on the simplified Aki-Richard linear equation. The initial model can be generated from well log data and seismic and geologic interpreted horizons in the study area. The input seismic data is angle gathers generated from the common reflection gathers used in pre-stack time or depth migration. The inversion results are elastic property parameters or their combinations. We use a field data example to examine which elastic property parameters or combinations of parameters can most easily discriminate gas sands from background geology and which are most sensitive to pore-fluid content. Comparing the inversion results to well data, we found that it is useful to predict gas reservoirs using λ, λρ, λ/μ, and K/μ properties, which indicate the gas characteristics in the study reservoir.展开更多
Engineering seismic exploration aims at shallow imaging which is confused by statics if the surface is uneven. Direct pre-stack depth migration （DPDM） is based on accurate elevations of sources and receivers, by whi...Engineering seismic exploration aims at shallow imaging which is confused by statics if the surface is uneven. Direct pre-stack depth migration （DPDM） is based on accurate elevations of sources and receivers, by which static correction is completely abandoned before migration and surely the imaging quality is remarkably improved. To obtain some artificial shot gathers, high-order staggered-grid finite-difference （FD） method is adapted to model acoustic wave propagation. Since the shot gathers are always disturbed by regular interferences, the statics still must be applied to supporting the interference elimination by apparent velocity filtering method. Then all the shot gathers should be removed back to their original positions by reverse statics. Finally, they are migrated by pre-stack reverse-time depth migration and imaged. The numerical experiments show that the DPDM can ideally avoid the mistakes caused by statics and increase imaging precision.展开更多
Seismic texture attributes are closely related to seismic facies and reservoir characteristics and are thus widely used in seismic data interpretation.However,information is mislaid in the stacking process when tradit...Seismic texture attributes are closely related to seismic facies and reservoir characteristics and are thus widely used in seismic data interpretation.However,information is mislaid in the stacking process when traditional texture attributes are extracted from poststack data,which is detrimental to complex reservoir description.In this study,pre-stack texture attributes are introduced,these attributes can not only capable of precisely depicting the lateral continuity of waveforms between different reflection points but also reflect amplitude versus offset,anisotropy,and heterogeneity in the medium.Due to its strong ability to represent stratigraphies,a pre-stack-data-based seismic facies analysis method is proposed using the selforganizing map algorithm.This method is tested on wide azimuth seismic data from China,and the advantages of pre-stack texture attributes in the description of stratum lateral changes are verified,in addition to the method＇s ability to reveal anisotropy and heterogeneity characteristics.The pre-stack texture classification results effectively distinguish different seismic reflection patterns,thereby providing reliable evidence for use in seismic facies analysis.展开更多
The major storage space types in the carbonate reservoir in the Ordovician in the TZ45 area are secondary dissolution caves.For the prediction of caved carbonate reservoir,post-stack methods are commonly used in the o...The major storage space types in the carbonate reservoir in the Ordovician in the TZ45 area are secondary dissolution caves.For the prediction of caved carbonate reservoir,post-stack methods are commonly used in the oilfield at present since pre-stack inversion is always limited by poor seismic data quality and insufficient logging data.In this paper,based on amplitude preserved seismic data processing and rock-physics analysis,pre-stack inversion is employed to predict the caved carbonate reservoir in TZ45 area by seriously controlling the quality of inversion procedures.These procedures mainly include angle-gather conversion,partial stack,wavelet estimation,low-frequency model building and inversion residual analysis.The amplitude-preserved data processing method can achieve high quality data based on the principle that they are very consistent with the synthetics.Besides,the foundation of pre-stack inversion and reservoir prediction criterion can be established by the connection between reservoir property and seismic reflection through rock-physics analysis.Finally,the inversion result is consistent with drilling wells in most cases.It is concluded that integrated with amplitude-preserved processing and rock-physics,pre-stack inversion can be effectively applied in the caved carbonate reservoir prediction.展开更多
Joint PP–PS inversion offers better accuracy and resolution than conventional P-wave inversion. P-and S-wave elastic moduli determined through data inversions are key parameters for reservoir evaluation and fluid cha...Joint PP–PS inversion offers better accuracy and resolution than conventional P-wave inversion. P-and S-wave elastic moduli determined through data inversions are key parameters for reservoir evaluation and fluid characterization. In this paper, starting with the exact Zoeppritz equation that relates P-and S-wave moduli, a coefficient that describes the reflections of P-and converted waves is established. This method effectively avoids error introduced by approximations or indirect calculations, thus improving the accuracy of the inversion results. Considering that the inversion problem is ill-posed and that the forward operator is nonlinear, prior constraints on the model parameters and modified low-frequency constraints are also introduced to the objective function to make the problem more tractable. This modified objective function is solved over many iterations to continuously optimize the background values of the velocity ratio, which increases the stability of the inversion process. Tests of various models show that the method effectively improves the accuracy and stability of extracting P and S-wave moduli from underdetermined data. This method can be applied to provide inferences for reservoir exploration and fluid extraction.展开更多
The extensive application of pre-stack depth migration has produced huge volumes of seismic data,which allows for the possibility of developing seismic inversions of reservoir properties from seismic data in the depth...The extensive application of pre-stack depth migration has produced huge volumes of seismic data,which allows for the possibility of developing seismic inversions of reservoir properties from seismic data in the depth domain.It is difficult to estimate seismic wavelets directly from seismic data due to the nonstationarity of the data in the depth domain.We conduct a velocity transformation of seismic data to make the seismic data stationary and then apply the ridge regression method to estimate a constant seismic wavelet.The estimated constant seismic wavelet is constructed as a set of space-variant seismic wavelets dominated by velocities at different spatial locations.Incorporating the weighted superposition principle,a synthetic seismogram is generated by directly employing the space-variant seismic wavelets in the depth domain.An inversion workflow based on the model-driven method is developed in the depth domain by incorporating the nonlinear conjugate gradient algorithm,which avoids additional data conversions between the time and depth domains.The impedance inversions of the synthetic and field seismic data in the depth domain show good results,which demonstrates that seismic inversion in the depth domain is feasible.The approach provides an alternative for forward numerical analyses and elastic property inversions of depth-domain seismic data.It is advantageous for further studies concerning the stability,accuracy,and efficiency of seismic inversions in the depth domain.展开更多
Anisotropy correction is necessary during the processing of converted PS- wave seismic data to achieve accurate structural imaging, reservoir prediction, and fracture detection. To effectively eliminate the adverse ef...Anisotropy correction is necessary during the processing of converted PS- wave seismic data to achieve accurate structural imaging, reservoir prediction, and fracture detection. To effectively eliminate the adverse effects of S-wave splitting and to improve PS- wave imaging quality, we tested methods for pre-stack migration imaging and anisotropic correction of PS-wave data. We based this on the propagation rules of seismic waves in a horizontal transverse isotropy medium, which is a fractured medium model that reflects likely subsurface conditions in the field. We used the radial （R） and transverse （T） components of PS-wave data to separate the fast and slow S-wave components, after which their propagation moveout was effectively extracted. Meanwhile, corrections for the energies and propagation moveouts of the R and T components were implemented using mathematical rotation. The PS-wave imaging quality was distinctly improved, and we demonstrated the reliability of our methods through numerical simulations. Applying our methods to three-dimensional and three-component seismic field data from the Xinchang-Hexingchang region of the Western Sichuan Depression in China, we obtained high-quality seismic imaging with continuous reflection wave groups, distinct structural features, and specific stratigraphic contact relationships. This study provides an effective and reliable approach for data processing that will improve the exploration of complex, hidden lithologic gas reservoirs.展开更多
Classical multi-channel technology can significantly reduce the pre-stack seismic inversion uncertainty, especially for complex geology such as high dipping structures. However, due to the consideration of complex str...Classical multi-channel technology can significantly reduce the pre-stack seismic inversion uncertainty, especially for complex geology such as high dipping structures. However, due to the consideration of complex structure or reflection features, the existing multi-channel inversion methods have to adopt the highly time-consuming strategy of arranging seismic data trace-by-trace, limiting its wide application in pre-stack inversion. A fast pre-stack multi-channel inversion constrained by seismic reflection features has been proposed to address this issue. The key to our method is to re-characterize the reflection features to directly constrain the pre-stack inversion through a Hadamard product operator without rearranging the seismic data. The seismic reflection features can reflect the distribution of the stratum reflection interface, and we obtained them from the post-stack profile by searching the shortest local Euclidean distance between adjacent seismic traces. Instead of directly constructing a large-size reflection features constraint operator advocated by the conventional methods, through decomposing the reflection features along the vertical and horizontal direction at a particular sampling point, we have constructed a computationally well-behaved constraint operator represented by the vertical and horizontal partial derivatives. Based on the Alternating Direction Method of Multipliers (ADMM) optimization, we have derived a fast algorithm for solving the objective function, including Hadamard product operators. Compared with the conventional reflection features constrained inversion, the proposed method is more efficient and accurate, proved on the Overthrust model and a field data set.展开更多
With the development of exploration of oil and gas resources,the requirements for seismic inversion results are getting more accurate.In particular,it is hoped that the distribution patterns of oil and gas reservoirs ...With the development of exploration of oil and gas resources,the requirements for seismic inversion results are getting more accurate.In particular,it is hoped that the distribution patterns of oil and gas reservoirs can be finely characterized,and the seismic inversion results can clearly characterize the location of stratigraphic boundaries and meet the needs of accurate geological description.Specifically,for pre-stack AVO inversion,it is required to be able to distinguish smaller geological targets in the depth or time domain,and clearly depict the vertical boundaries of the geological objects.In response to the above requirements,we introduce the preprocessing regularization of the adaptive edge-preserving smooth filter into the pre-stack AVO elastic parameter inversion to clearly invert the position of layer boundary and improve the accuracy of the inversion results.展开更多
Strong fluctuation of seabed,abrupt variation in depth and dip of seabed bring seismic imaging problems,such as irregular reflection waves,obvious multiple waves,serious lateral wave development,poor imaging on base s...Strong fluctuation of seabed,abrupt variation in depth and dip of seabed bring seismic imaging problems,such as irregular reflection waves,obvious multiple waves,serious lateral wave development,poor imaging on base surface and depression structure,low signal-to-noise ratio of middle and deep layers.In this paper,Gaussian beam migration imaging method is used to analyze the imaging effect of rugged seabed in deep water area,and the ray tracing method of wavefront construction method is used to analyze the kinematic characteristics of seismic waves.By improving the design of seismic data acquisition and observation system,imaging quality of fine structures is improved.展开更多
Pre-stack seismic inversion is used to calculate elastic parameters,including P-wave and S-wave velocities,as well as densities.These parameters play an integral role in the characterization of reservoirs,thereby enha...Pre-stack seismic inversion is used to calculate elastic parameters,including P-wave and S-wave velocities,as well as densities.These parameters play an integral role in the characterization of reservoirs,thereby enhancing the exploration and production process.Deep learning-based seismic inversion does not need a known physical system and can give satisfactory results with sufficient training data.The acquisition of such datasets for seismic inversion poses a significant challenge due to the exorbitant costs associated with drilling activities.Integrating domain knowledge,physical systems,and well log data into a deep learning-based seismic inversion framework is crucial for improving its efficiency and effectiveness.Nevertheless,existing data-driven approaches do not adequately exploit such information,thereby constraining their overall performance and applicability.Therefore,we develop a double dual neural network structure built upon the closed-loop neural network framework,which incorporates both physics and model information to mitigate the dependency on extensive labeled datasets.The information from the different domains is linked through a loss function,where one dual network is responsible for constraining the inversion results using physics information to ensure the physics consistency of the predictions,and the other dual network is responsible for constraining the inversion results using a priori model information to enhance the reliability of the predictions.The method makes full use of well-log data for network training when wells are available,as well as providing unsupervised learning and inversion under well-free conditions.The integration of qualitative and quantitative analyses proves instrumental in demonstrating the effectiveness of the proposed methodology through the use of synthetic and field pre-stack examples.展开更多
In the Baikouquan Formation of the Shawan Depression,there exist thin,high-quality conglomerate reservoirs with low porosity and low permeability.Only the underwater gray-green conglomerate with medium porosity is con...In the Baikouquan Formation of the Shawan Depression,there exist thin,high-quality conglomerate reservoirs with low porosity and low permeability.Only the underwater gray-green conglomerate with medium porosity is considered a high-quality reservoir.Due to the overlapping wave impedance between these thin highquality reservoirs and tight layers,traditional post-stack inversion and pre-stack simultaneous inversion methods are ineffective in predicting such thin reservoirs.Pre-stack geostatistical inversion,which combines the advantages of simultaneous inversion and geostatistical inversion,has proven to be effective in this context.This study integrates core,logging,and test data to construct petrophysical charts using P-impedance and V_(p)/V_(s) ratios,idengtify key reservoir parameters,and apply pre-stack geostatistical inversion to predict thin high-quality conglomerate reservoirs.The results show that pre-stack geostatistical inversion can accurately identify thin high-quality reservoirs,providing a reliable basis for further exploration and development.展开更多
Seismic low-frequency component included more fluid information,which was still a focus in geophysics.Seismic pre-stack data contained more fluid information,but signal to noise ratio(SNR)was low.By comparison,seismic...Seismic low-frequency component included more fluid information,which was still a focus in geophysics.Seismic pre-stack data contained more fluid information,but signal to noise ratio(SNR)was low.By comparison,seismic post-stack data had a high SNR,but some fluid information was lost during data processing.Different angel stacks reflected different fluid seismic amplitude,compared with nearangle stacks.Far angle stacks had more low frequency components,which were more benefit for fluid identification.Based on this principle,combined with the pre-stacks and post-stacks seismic data,more fluid information would be included.In this study,a new fluid identification method was proposed.This method combined the post-stack seismic and pre-stack seismic data,it took into consideration high SNR of the post-stack seismic data and the large fluid amplitude differences of the pre-stack different angles.Field testing indicated this method was quite effective in detecting fluids.展开更多
基金supported by the National Basic Priorities Program "973" Project (Grant No.2007CB209600)China Postdoctoral Science Foundation Funded Project
文摘This is a case study of the application of pre-stack inverted elastic parameters to tight-sand reservoir prediction. With the development of oil and gas exploration, pre-stack data and inversion results are increasingly used for production objectives. The pre-stack seismic property studies include not only amplitude verse offset （AVO） but also the characteristics of other elastic property changes. In this paper, we analyze the elastic property parameters characteristics of gas- and wet-sands using data from four gas-sand core types. We found that some special elastic property parameters or combinations can be used to identify gas sands from water saturated sand. Thus, we can do reservoir interpretation and description using different elastic property data from the pre-stack seismic inversion processing. The pre- stack inversion method is based on the simplified Aki-Richard linear equation. The initial model can be generated from well log data and seismic and geologic interpreted horizons in the study area. The input seismic data is angle gathers generated from the common reflection gathers used in pre-stack time or depth migration. The inversion results are elastic property parameters or their combinations. We use a field data example to examine which elastic property parameters or combinations of parameters can most easily discriminate gas sands from background geology and which are most sensitive to pore-fluid content. Comparing the inversion results to well data, we found that it is useful to predict gas reservoirs using λ, λρ, λ/μ, and K/μ properties, which indicate the gas characteristics in the study reservoir.
文摘Engineering seismic exploration aims at shallow imaging which is confused by statics if the surface is uneven. Direct pre-stack depth migration （DPDM） is based on accurate elevations of sources and receivers, by which static correction is completely abandoned before migration and surely the imaging quality is remarkably improved. To obtain some artificial shot gathers, high-order staggered-grid finite-difference （FD） method is adapted to model acoustic wave propagation. Since the shot gathers are always disturbed by regular interferences, the statics still must be applied to supporting the interference elimination by apparent velocity filtering method. Then all the shot gathers should be removed back to their original positions by reverse statics. Finally, they are migrated by pre-stack reverse-time depth migration and imaged. The numerical experiments show that the DPDM can ideally avoid the mistakes caused by statics and increase imaging precision.
基金supported by the Scientific Research Staring Foundation of University of Electronic Science and Technology of China(No.ZYGX2015KYQD049)
文摘Seismic texture attributes are closely related to seismic facies and reservoir characteristics and are thus widely used in seismic data interpretation.However,information is mislaid in the stacking process when traditional texture attributes are extracted from poststack data,which is detrimental to complex reservoir description.In this study,pre-stack texture attributes are introduced,these attributes can not only capable of precisely depicting the lateral continuity of waveforms between different reflection points but also reflect amplitude versus offset,anisotropy,and heterogeneity in the medium.Due to its strong ability to represent stratigraphies,a pre-stack-data-based seismic facies analysis method is proposed using the selforganizing map algorithm.This method is tested on wide azimuth seismic data from China,and the advantages of pre-stack texture attributes in the description of stratum lateral changes are verified,in addition to the method＇s ability to reveal anisotropy and heterogeneity characteristics.The pre-stack texture classification results effectively distinguish different seismic reflection patterns,thereby providing reliable evidence for use in seismic facies analysis.
基金supported by National Basic Research Program(2006CB202304)of Chinaco-supported by the National Basic Research Program of China(Grant No.2011CB201103)the National Science and Technology Major Project of China(Grant No.2011ZX05004003)
文摘The major storage space types in the carbonate reservoir in the Ordovician in the TZ45 area are secondary dissolution caves.For the prediction of caved carbonate reservoir,post-stack methods are commonly used in the oilfield at present since pre-stack inversion is always limited by poor seismic data quality and insufficient logging data.In this paper,based on amplitude preserved seismic data processing and rock-physics analysis,pre-stack inversion is employed to predict the caved carbonate reservoir in TZ45 area by seriously controlling the quality of inversion procedures.These procedures mainly include angle-gather conversion,partial stack,wavelet estimation,low-frequency model building and inversion residual analysis.The amplitude-preserved data processing method can achieve high quality data based on the principle that they are very consistent with the synthetics.Besides,the foundation of pre-stack inversion and reservoir prediction criterion can be established by the connection between reservoir property and seismic reflection through rock-physics analysis.Finally,the inversion result is consistent with drilling wells in most cases.It is concluded that integrated with amplitude-preserved processing and rock-physics,pre-stack inversion can be effectively applied in the caved carbonate reservoir prediction.
基金supported by the National Science and Technology Major Project(No.2016ZX05047-002-001)
文摘Joint PP–PS inversion offers better accuracy and resolution than conventional P-wave inversion. P-and S-wave elastic moduli determined through data inversions are key parameters for reservoir evaluation and fluid characterization. In this paper, starting with the exact Zoeppritz equation that relates P-and S-wave moduli, a coefficient that describes the reflections of P-and converted waves is established. This method effectively avoids error introduced by approximations or indirect calculations, thus improving the accuracy of the inversion results. Considering that the inversion problem is ill-posed and that the forward operator is nonlinear, prior constraints on the model parameters and modified low-frequency constraints are also introduced to the objective function to make the problem more tractable. This modified objective function is solved over many iterations to continuously optimize the background values of the velocity ratio, which increases the stability of the inversion process. Tests of various models show that the method effectively improves the accuracy and stability of extracting P and S-wave moduli from underdetermined data. This method can be applied to provide inferences for reservoir exploration and fluid extraction.
基金supported by the National Natural Science Foundation of China(No.41574130,41874143 and 41374134)the National Science and Technology Major Project of China(No.2016ZX05014-001-009)the Sichuan Provincial Youth Science&Technology Innovative Research Group Fund(No.2016TD0023)
文摘The extensive application of pre-stack depth migration has produced huge volumes of seismic data,which allows for the possibility of developing seismic inversions of reservoir properties from seismic data in the depth domain.It is difficult to estimate seismic wavelets directly from seismic data due to the nonstationarity of the data in the depth domain.We conduct a velocity transformation of seismic data to make the seismic data stationary and then apply the ridge regression method to estimate a constant seismic wavelet.The estimated constant seismic wavelet is constructed as a set of space-variant seismic wavelets dominated by velocities at different spatial locations.Incorporating the weighted superposition principle,a synthetic seismogram is generated by directly employing the space-variant seismic wavelets in the depth domain.An inversion workflow based on the model-driven method is developed in the depth domain by incorporating the nonlinear conjugate gradient algorithm,which avoids additional data conversions between the time and depth domains.The impedance inversions of the synthetic and field seismic data in the depth domain show good results,which demonstrates that seismic inversion in the depth domain is feasible.The approach provides an alternative for forward numerical analyses and elastic property inversions of depth-domain seismic data.It is advantageous for further studies concerning the stability,accuracy,and efficiency of seismic inversions in the depth domain.
基金supported by the National Natural Science Foundation of China(Grant No.41574099)the National Key Science and Technology Special Projects(grant No.2016ZX05002004-005)
文摘Anisotropy correction is necessary during the processing of converted PS- wave seismic data to achieve accurate structural imaging, reservoir prediction, and fracture detection. To effectively eliminate the adverse effects of S-wave splitting and to improve PS- wave imaging quality, we tested methods for pre-stack migration imaging and anisotropic correction of PS-wave data. We based this on the propagation rules of seismic waves in a horizontal transverse isotropy medium, which is a fractured medium model that reflects likely subsurface conditions in the field. We used the radial （R） and transverse （T） components of PS-wave data to separate the fast and slow S-wave components, after which their propagation moveout was effectively extracted. Meanwhile, corrections for the energies and propagation moveouts of the R and T components were implemented using mathematical rotation. The PS-wave imaging quality was distinctly improved, and we demonstrated the reliability of our methods through numerical simulations. Applying our methods to three-dimensional and three-component seismic field data from the Xinchang-Hexingchang region of the Western Sichuan Depression in China, we obtained high-quality seismic imaging with continuous reflection wave groups, distinct structural features, and specific stratigraphic contact relationships. This study provides an effective and reliable approach for data processing that will improve the exploration of complex, hidden lithologic gas reservoirs.
基金We would like to acknowledge the sponsorship of the National Natural Science Foundation of China(42004092,42030103,41974119)Marine S&T Fund of Shandong Province for Pilot National Laboratory for Marine Science and Technology(Qingdao)(Grant No.2021QNLM020001-6)Young Elite Scientists Sponsorship Program by CAST(2021QNRC001).
文摘Classical multi-channel technology can significantly reduce the pre-stack seismic inversion uncertainty, especially for complex geology such as high dipping structures. However, due to the consideration of complex structure or reflection features, the existing multi-channel inversion methods have to adopt the highly time-consuming strategy of arranging seismic data trace-by-trace, limiting its wide application in pre-stack inversion. A fast pre-stack multi-channel inversion constrained by seismic reflection features has been proposed to address this issue. The key to our method is to re-characterize the reflection features to directly constrain the pre-stack inversion through a Hadamard product operator without rearranging the seismic data. The seismic reflection features can reflect the distribution of the stratum reflection interface, and we obtained them from the post-stack profile by searching the shortest local Euclidean distance between adjacent seismic traces. Instead of directly constructing a large-size reflection features constraint operator advocated by the conventional methods, through decomposing the reflection features along the vertical and horizontal direction at a particular sampling point, we have constructed a computationally well-behaved constraint operator represented by the vertical and horizontal partial derivatives. Based on the Alternating Direction Method of Multipliers (ADMM) optimization, we have derived a fast algorithm for solving the objective function, including Hadamard product operators. Compared with the conventional reflection features constrained inversion, the proposed method is more efficient and accurate, proved on the Overthrust model and a field data set.
基金support of China national key project 41904130 and key research project 041020080060.
文摘With the development of exploration of oil and gas resources,the requirements for seismic inversion results are getting more accurate.In particular,it is hoped that the distribution patterns of oil and gas reservoirs can be finely characterized,and the seismic inversion results can clearly characterize the location of stratigraphic boundaries and meet the needs of accurate geological description.Specifically,for pre-stack AVO inversion,it is required to be able to distinguish smaller geological targets in the depth or time domain,and clearly depict the vertical boundaries of the geological objects.In response to the above requirements,we introduce the preprocessing regularization of the adaptive edge-preserving smooth filter into the pre-stack AVO elastic parameter inversion to clearly invert the position of layer boundary and improve the accuracy of the inversion results.
基金Supported by projects of National Natural Science Foundation of China (No. 42074150)National Key R&D Program of China (No. 2017YFC0601305)。
文摘Strong fluctuation of seabed,abrupt variation in depth and dip of seabed bring seismic imaging problems,such as irregular reflection waves,obvious multiple waves,serious lateral wave development,poor imaging on base surface and depression structure,low signal-to-noise ratio of middle and deep layers.In this paper,Gaussian beam migration imaging method is used to analyze the imaging effect of rugged seabed in deep water area,and the ray tracing method of wavefront construction method is used to analyze the kinematic characteristics of seismic waves.By improving the design of seismic data acquisition and observation system,imaging quality of fine structures is improved.
基金supported in part by the National Natural Science Foundation of China under Grant 42204108,42374166 and42374149in part by National Key Laboratory of Petroleum Resources and Engineering,China University of Petroleum,Beijing under Grant PRE/open-2305in part by Research on Fine Exploration and Surrounding Rock Classification Technology for Deep Buried Long Tunnels Driven by Horizontal Directional Drilling and Magnetotelluric Methods Based on Deep Learning under Grant E202408010。
文摘Pre-stack seismic inversion is used to calculate elastic parameters,including P-wave and S-wave velocities,as well as densities.These parameters play an integral role in the characterization of reservoirs,thereby enhancing the exploration and production process.Deep learning-based seismic inversion does not need a known physical system and can give satisfactory results with sufficient training data.The acquisition of such datasets for seismic inversion poses a significant challenge due to the exorbitant costs associated with drilling activities.Integrating domain knowledge,physical systems,and well log data into a deep learning-based seismic inversion framework is crucial for improving its efficiency and effectiveness.Nevertheless,existing data-driven approaches do not adequately exploit such information,thereby constraining their overall performance and applicability.Therefore,we develop a double dual neural network structure built upon the closed-loop neural network framework,which incorporates both physics and model information to mitigate the dependency on extensive labeled datasets.The information from the different domains is linked through a loss function,where one dual network is responsible for constraining the inversion results using physics information to ensure the physics consistency of the predictions,and the other dual network is responsible for constraining the inversion results using a priori model information to enhance the reliability of the predictions.The method makes full use of well-log data for network training when wells are available,as well as providing unsupervised learning and inversion under well-free conditions.The integration of qualitative and quantitative analyses proves instrumental in demonstrating the effectiveness of the proposed methodology through the use of synthetic and field pre-stack examples.
文摘In the Baikouquan Formation of the Shawan Depression,there exist thin,high-quality conglomerate reservoirs with low porosity and low permeability.Only the underwater gray-green conglomerate with medium porosity is considered a high-quality reservoir.Due to the overlapping wave impedance between these thin highquality reservoirs and tight layers,traditional post-stack inversion and pre-stack simultaneous inversion methods are ineffective in predicting such thin reservoirs.Pre-stack geostatistical inversion,which combines the advantages of simultaneous inversion and geostatistical inversion,has proven to be effective in this context.This study integrates core,logging,and test data to construct petrophysical charts using P-impedance and V_(p)/V_(s) ratios,idengtify key reservoir parameters,and apply pre-stack geostatistical inversion to predict thin high-quality conglomerate reservoirs.The results show that pre-stack geostatistical inversion can accurately identify thin high-quality reservoirs,providing a reliable basis for further exploration and development.
文摘Seismic low-frequency component included more fluid information,which was still a focus in geophysics.Seismic pre-stack data contained more fluid information,but signal to noise ratio(SNR)was low.By comparison,seismic post-stack data had a high SNR,but some fluid information was lost during data processing.Different angel stacks reflected different fluid seismic amplitude,compared with nearangle stacks.Far angle stacks had more low frequency components,which were more benefit for fluid identification.Based on this principle,combined with the pre-stacks and post-stacks seismic data,more fluid information would be included.In this study,a new fluid identification method was proposed.This method combined the post-stack seismic and pre-stack seismic data,it took into consideration high SNR of the post-stack seismic data and the large fluid amplitude differences of the pre-stack different angles.Field testing indicated this method was quite effective in detecting fluids.
