Missing data are a problem in geophysical surveys, and interpolation and reconstruction of missing data is part of the data processing and interpretation. Based on the sparseness of the geophysical data or the transfo...Missing data are a problem in geophysical surveys, and interpolation and reconstruction of missing data is part of the data processing and interpretation. Based on the sparseness of the geophysical data or the transform domain, we can improve the accuracy and stability of the reconstruction by transforming it to a sparse optimization problem. In this paper, we propose a mathematical model for the sparse reconstruction of data based on the LO-norm minimization. Furthermore, we discuss two types of the approximation algorithm for the LO- norm minimization according to the size and characteristics of the geophysical data： namely, the iteratively reweighted least-squares algorithm and the fast iterative hard thresholding algorithm. Theoretical and numerical analysis showed that applying the iteratively reweighted least-squares algorithm to the reconstruction of potential field data exploits its fast convergence rate, short calculation time, and high precision, whereas the fast iterative hard thresholding algorithm is more suitable for processing seismic data, moreover, its computational efficiency is better than that of the traditional iterative hard thresholding algorithm.展开更多
Identification of reservoir types in deep carbonates has always been a great challenge due to complex logging responses caused by the heterogeneous scale and distribution of storage spaces.Traditional cross-plot analy...Identification of reservoir types in deep carbonates has always been a great challenge due to complex logging responses caused by the heterogeneous scale and distribution of storage spaces.Traditional cross-plot analysis and empirical formula methods for identifying reservoir types using geophysical logging data have high uncertainty and low efficiency,which cannot accurately reflect the nonlinear relationship between reservoir types and logging data.Recently,the kernel Fisher discriminant analysis(KFD),a kernel-based machine learning technique,attracts attention in many fields because of its strong nonlinear processing ability.However,the overall performance of KFD model may be limited as a single kernel function cannot simultaneously extrapolate and interpolate well,especially for highly complex data cases.To address this issue,in this study,a mixed kernel Fisher discriminant analysis(MKFD)model was established and applied to identify reservoir types of the deep Sinian carbonates in central Sichuan Basin,China.The MKFD model was trained and tested with 453 datasets from 7 coring wells,utilizing GR,CAL,DEN,AC,CNL and RT logs as input variables.The particle swarm optimization(PSO)was adopted for hyper-parameter optimization of MKFD model.To evaluate the model performance,prediction results of MKFD were compared with those of basic-kernel based KFD,RF and SVM models.Subsequently,the built MKFD model was applied in a blind well test,and a variable importance analysis was conducted.The comparison and blind test results demonstrated that MKFD outperformed traditional KFD,RF and SVM in the identification of reservoir types,which provided higher accuracy and stronger generalization.The MKFD can therefore be a reliable method for identifying reservoir types of deep carbonates.展开更多
In this paper we discuss the edge-preserving regularization method in the reconstruction of physical parameters from geophysical data such as seismic and ground-penetrating radar data. In the regularization method a p...In this paper we discuss the edge-preserving regularization method in the reconstruction of physical parameters from geophysical data such as seismic and ground-penetrating radar data. In the regularization method a potential function of model parameters and its corresponding functions are introduced. This method is stable and able to preserve boundaries, and protect resolution. The effect of regularization depends to a great extent on the suitable choice of regularization parameters. The influence of the edge-preserving parameters on the reconstruction results is investigated and the relationship between the regularization parameters and the error of data is described.展开更多
Based on the sensitivity of geophysical response to gas hydrates contained in sediments, we studied the prediction of gas hydrates with seismic techniques, including seismic attributes analysis, AVO, inverted velocity...Based on the sensitivity of geophysical response to gas hydrates contained in sediments, we studied the prediction of gas hydrates with seismic techniques, including seismic attributes analysis, AVO, inverted velocity field construction for dipping formations, and pseudo-well constrained impedance inversion. We used an optimal integration of geophysical techniques results in a set of reliable and effective workflows to predict gas hydrates. The results show that the integrated analysis of the combination of reflectivity amplitude, instantaneous phase, interval velocity, relative impedance, absolute impedance, and AVO intercept is a valid combination of techniques for identifying the BSR （Bottom Simulated Reflector） from the lower boundary of the gas hydrates. Integration of seismic sections, relative and absolute impedance sections, and interval velocity sections can improve the validity of gas hydrates determination. The combination of instantaneous frequency, energy half attenuation time, interval velocity, AVO intercept, AVO product, and AVO fluid factor accurately locates the escaped gas beneath the BSR. With these conclusions, the combined techniques have been used to successfully predict the gas hydrates in the Dongsha Sea area.展开更多
The Qiantang Basin is now one of the topics of general interest in petroleum exploration in China. This paper reports a comprehensive study of geophysical and geological survey data recently obtained in this area and,...The Qiantang Basin is now one of the topics of general interest in petroleum exploration in China. This paper reports a comprehensive study of geophysical and geological survey data recently obtained in this area and, combined with INDEPTH-3 deep survey results, comes to the following conclusions： 1） The hydrocarbon source formations, reservoirs, and overlying strata and their association within the basin are quite good, local structures are developed, and, therefore, the region is favorable for forming and preserving oil and gas accumulations. Faults are not a fatal problem. The future main target strata are the middle-deep structural strata composed of Upper-Triassic and middle Jurassic rocks; 2） A new classification has been made for second-order tectonic sequences inside the basin to disavow the central Qingtang uplift. It is noted that the main structures at the surface are orientated NW-SE and the crustal structure can be described as three depressions, three risees, and one deep depression, of which the prospective zone with the most potential is the inner main subsided belt and its two sides; 3） Comparatively intensive interaction between the crust and mantle and volcanic and thermal activities in the northern basin play a very important role in petroleum evaluation. The southern deeper sedimentation and less thermal activity make this area a more perfect zone for oil exploration; 4） Currently, the most important objective is determining the physical properties of the deep strata, the status of oil and gas accumulations, the source of the hydrocarbons, and the relationship between the upper and lower structures; and 5） The Lunpola Tertiary basin may be favorable for oil accumulations because petroleum may migrate from marine strata on two sides.展开更多
The process of mass movements and their consequent turbidity currents in large submarine canyons has been widely reported, however, little attention was paid to that in small canyons. In this paper, we document mass m...The process of mass movements and their consequent turbidity currents in large submarine canyons has been widely reported, however, little attention was paid to that in small canyons. In this paper, we document mass movements in small submarine canyons in the northeast of Baiyun deepwater area, north of the South China Sea （SCS）, and their strong effects on the evolution of the canyons based on geophysical data. Submarine canyons in the study area arrange closely below the shelf break zone which was at the depth of -500 m. Within submarine canyons, seabed surface was covered with amounts of failure scars resulted from past small-sized landslides. A complex process of mass transportation in the canyons is indicated by three directions of mass movements. Recent mass movement deposits in the canyons exhibit translucent reflections or parallel reflections which represent the brittle deformation and the plastic deformation, respectively. The area of most landslides in the canyons is less than 3 km2. The trigger mechanisms for mass movements in the study area are gravitational overloading, slope angle and weak properties of soil. Geophysical data indicate that the genesis of submarine canyons is the erosion of mass movements and consequent turbidity currents. The significant effects of mass movements on canyon are incision and sediment transportation at the erosion phases and fillings supply at the fill phases. This research will be helpful for the geological risk assessments and understanding the sediment transportation in the northern margin of the SCS.展开更多
Sea state bias(SSB)is an important component of errors for the radar altimeter measurements of sea surface height(SSH).However,existing SSB estimation methods are almost all based on single-task learning(STL),where on...Sea state bias(SSB)is an important component of errors for the radar altimeter measurements of sea surface height(SSH).However,existing SSB estimation methods are almost all based on single-task learning(STL),where one model is built on the data from only one radar altimeter.In this paper,taking account of the data from multiple radar altimeters available,we introduced a multi-task learning method,called trace-norm regularized multi-task learning(TNR-MTL),for SSB estimation.Corresponding to each individual task,TNR-MLT involves only three parameters.Hence,it is easy to implement.More importantly,the convergence of TNR-MLT is theoretically guaranteed.Compared with the commonly used STL models,TNR-MTL can effectively utilize the shared information between data from multiple altimeters.During the training of TNR-MTL,we used the JASON-2 and JASON-3 cycle data to solve two correlated SSB estimation tasks.Then the optimal model was selected to estimate SSB on the JASON-2 and the HY-270-71 cycle intersection data.For the JSAON-2 cycle intersection data,the corrected variance(M)has been reduced by 0.60 cm^2 compared to the geophysical data records(GDR);while for the HY-2 cycle intersection data,M has been reduced by 1.30 cm^2 compared to GDR.Therefore,TNR-MTL is proved to be effective for the SSB estimation tasks.展开更多
Episodes of tectonic activities since Archaean time in one of the oldest craton,the eastern Yilgarn Craton of Western Australia,have left a complex pattern in the architectural settings.Insights of the crustal scale a...Episodes of tectonic activities since Archaean time in one of the oldest craton,the eastern Yilgarn Craton of Western Australia,have left a complex pattern in the architectural settings.Insights of the crustal scale architectural settings of the Craton have been made through geophysical data modelling and imaging using high resolution aeromagnetic and Bouguer gravity data.The advanced technique of image processing using pseudocolour composition,hill-shading and the multiple data layers compilation in the hue,saturation and intensity(HSI)space has been used for image based analysis of potential field data.Geophysical methods of anomaly enhancement technique along with the imaging technique are used to delineate several regional and as well as local structures.Multiscale analysis in geophysical data processing with the application of varying upward continuation levels,and also anomaly enhancement techniques using spatial derivatives are used delineating major shear zones and regional scale structures.A suitable data based interpretation of basement architecture of the study area is given.展开更多
New methods are presented for processing and interpretation of shallow marine differential magnetic data, including constructing maps of offshore total magnetic anomalies with an extremely high reso- lution of up to 1...New methods are presented for processing and interpretation of shallow marine differential magnetic data, including constructing maps of offshore total magnetic anomalies with an extremely high reso- lution of up to 1-2 nT, mapping weak anomalies of 5-10 nT caused by mineralization effects at the contacts of hydrocarbons with host rocks, estimating depths to upper and lower boundaries of anom- alous magnetic sources, and estimating thickness of magnetic layers and boundaries of tectonic blocks. Horizontal dimensions of tectonic blocks in the so-called ＂seismic gap＂ region in the central Kuril Arc vary from 10 to 100 km, with typical dimensions of 25-30 km. The area of the ＂seismic gap＂ is a zone of intense tectonic activity and recent volcanism. Deep sources causing magnetic anomalies in the area are similar to the ＂magnetic belt＂ near Hokkaido. In the southern and central parts of Barents Sea, tectonic blocks with widths of 30-100 kin, and upper and lower boundaries of magnetic layers ranging from depths of 10 to 5 km and 18 to 30 km are calculated. Models of the magnetic layer underlying the Mezen Basin in an inland part of the White Sea-Barents Sea paleorift indicate depths to the lower boundary of the layer of 12-30 km. Weak local magnetic anomalies of 2-5 nT in the northern and central Caspian Sea were identified using the new methods, and drilling confirms that the anomalies are related to concentrations of hydrocarbon. Two layers causing magnetic anomalies are identified in the northern Caspian Sea from magnetic anomaly spectra. The upper layer lies immediately beneath the sea bottom and the lower layer occurs at depths between 30-40 m and 150-200 m.展开更多
SeisGuard, a system for analyzing earthquake precursory data, is a software platform to search for earthquake precursory information by processing geophysical data from different sources to establish automatically an ...SeisGuard, a system for analyzing earthquake precursory data, is a software platform to search for earthquake precursory information by processing geophysical data from different sources to establish automatically an earthquake forecasting model. The main function of this system is to analyze and process the deformation, fluid, electromagnetic and other geophysical field observing data from ground-based observation, as well as space-based observation. Combined station and earthquake distributions, geological structure and other information, this system can provide a basic software platform for earthquake forecasting research based on spatiotemporal fusion. The hierarchical station tree for data sifting and the interaction mode have been innovatively developed in this SeisGuard system to improve users’ working efficiency. The data storage framework designed according to the characteristics of different time series can unify the interfaces of different data sources, provide the support of data flow, simplify the management and usage of data, and provide foundation for analysis of big data. The final aim of this development is to establish an effective earthquake forecasting model combined all available information from ground-based observations to space-based observations.展开更多
基金supported by the National Natural Science Foundation of China (Grant No.41074133)
文摘Missing data are a problem in geophysical surveys, and interpolation and reconstruction of missing data is part of the data processing and interpretation. Based on the sparseness of the geophysical data or the transform domain, we can improve the accuracy and stability of the reconstruction by transforming it to a sparse optimization problem. In this paper, we propose a mathematical model for the sparse reconstruction of data based on the LO-norm minimization. Furthermore, we discuss two types of the approximation algorithm for the LO- norm minimization according to the size and characteristics of the geophysical data： namely, the iteratively reweighted least-squares algorithm and the fast iterative hard thresholding algorithm. Theoretical and numerical analysis showed that applying the iteratively reweighted least-squares algorithm to the reconstruction of potential field data exploits its fast convergence rate, short calculation time, and high precision, whereas the fast iterative hard thresholding algorithm is more suitable for processing seismic data, moreover, its computational efficiency is better than that of the traditional iterative hard thresholding algorithm.
基金supported by the National Natural Science Foundation of China(No.U21B2062)the Natural Science Foundation of Hubei Province(No.2023AFB307)。
文摘Identification of reservoir types in deep carbonates has always been a great challenge due to complex logging responses caused by the heterogeneous scale and distribution of storage spaces.Traditional cross-plot analysis and empirical formula methods for identifying reservoir types using geophysical logging data have high uncertainty and low efficiency,which cannot accurately reflect the nonlinear relationship between reservoir types and logging data.Recently,the kernel Fisher discriminant analysis(KFD),a kernel-based machine learning technique,attracts attention in many fields because of its strong nonlinear processing ability.However,the overall performance of KFD model may be limited as a single kernel function cannot simultaneously extrapolate and interpolate well,especially for highly complex data cases.To address this issue,in this study,a mixed kernel Fisher discriminant analysis(MKFD)model was established and applied to identify reservoir types of the deep Sinian carbonates in central Sichuan Basin,China.The MKFD model was trained and tested with 453 datasets from 7 coring wells,utilizing GR,CAL,DEN,AC,CNL and RT logs as input variables.The particle swarm optimization(PSO)was adopted for hyper-parameter optimization of MKFD model.To evaluate the model performance,prediction results of MKFD were compared with those of basic-kernel based KFD,RF and SVM models.Subsequently,the built MKFD model was applied in a blind well test,and a variable importance analysis was conducted.The comparison and blind test results demonstrated that MKFD outperformed traditional KFD,RF and SVM in the identification of reservoir types,which provided higher accuracy and stronger generalization.The MKFD can therefore be a reliable method for identifying reservoir types of deep carbonates.
基金supported in part by the National Natural Science Foundation of China under Grant-in-Aid 40574053the Program for New Century Excellent Talents in University of China (NCET-06-0602)the National 973 Key Basic Research Development Program (No.2007CB209601)
文摘In this paper we discuss the edge-preserving regularization method in the reconstruction of physical parameters from geophysical data such as seismic and ground-penetrating radar data. In the regularization method a potential function of model parameters and its corresponding functions are introduced. This method is stable and able to preserve boundaries, and protect resolution. The effect of regularization depends to a great extent on the suitable choice of regularization parameters. The influence of the edge-preserving parameters on the reconstruction results is investigated and the relationship between the regularization parameters and the error of data is described.
基金National Gas Hydrates Integral Appraisal Project (GZH200200203-05).
文摘Based on the sensitivity of geophysical response to gas hydrates contained in sediments, we studied the prediction of gas hydrates with seismic techniques, including seismic attributes analysis, AVO, inverted velocity field construction for dipping formations, and pseudo-well constrained impedance inversion. We used an optimal integration of geophysical techniques results in a set of reliable and effective workflows to predict gas hydrates. The results show that the integrated analysis of the combination of reflectivity amplitude, instantaneous phase, interval velocity, relative impedance, absolute impedance, and AVO intercept is a valid combination of techniques for identifying the BSR （Bottom Simulated Reflector） from the lower boundary of the gas hydrates. Integration of seismic sections, relative and absolute impedance sections, and interval velocity sections can improve the validity of gas hydrates determination. The combination of instantaneous frequency, energy half attenuation time, interval velocity, AVO intercept, AVO product, and AVO fluid factor accurately locates the escaped gas beneath the BSR. With these conclusions, the combined techniques have been used to successfully predict the gas hydrates in the Dongsha Sea area.
文摘The Qiantang Basin is now one of the topics of general interest in petroleum exploration in China. This paper reports a comprehensive study of geophysical and geological survey data recently obtained in this area and, combined with INDEPTH-3 deep survey results, comes to the following conclusions： 1） The hydrocarbon source formations, reservoirs, and overlying strata and their association within the basin are quite good, local structures are developed, and, therefore, the region is favorable for forming and preserving oil and gas accumulations. Faults are not a fatal problem. The future main target strata are the middle-deep structural strata composed of Upper-Triassic and middle Jurassic rocks; 2） A new classification has been made for second-order tectonic sequences inside the basin to disavow the central Qingtang uplift. It is noted that the main structures at the surface are orientated NW-SE and the crustal structure can be described as three depressions, three risees, and one deep depression, of which the prospective zone with the most potential is the inner main subsided belt and its two sides; 3） Comparatively intensive interaction between the crust and mantle and volcanic and thermal activities in the northern basin play a very important role in petroleum evaluation. The southern deeper sedimentation and less thermal activity make this area a more perfect zone for oil exploration; 4） Currently, the most important objective is determining the physical properties of the deep strata, the status of oil and gas accumulations, the source of the hydrocarbons, and the relationship between the upper and lower structures; and 5） The Lunpola Tertiary basin may be favorable for oil accumulations because petroleum may migrate from marine strata on two sides.
基金The National Science and Technology Major Project under contract No.2011ZX05056-001-02
文摘The process of mass movements and their consequent turbidity currents in large submarine canyons has been widely reported, however, little attention was paid to that in small canyons. In this paper, we document mass movements in small submarine canyons in the northeast of Baiyun deepwater area, north of the South China Sea （SCS）, and their strong effects on the evolution of the canyons based on geophysical data. Submarine canyons in the study area arrange closely below the shelf break zone which was at the depth of -500 m. Within submarine canyons, seabed surface was covered with amounts of failure scars resulted from past small-sized landslides. A complex process of mass transportation in the canyons is indicated by three directions of mass movements. Recent mass movement deposits in the canyons exhibit translucent reflections or parallel reflections which represent the brittle deformation and the plastic deformation, respectively. The area of most landslides in the canyons is less than 3 km2. The trigger mechanisms for mass movements in the study area are gravitational overloading, slope angle and weak properties of soil. Geophysical data indicate that the genesis of submarine canyons is the erosion of mass movements and consequent turbidity currents. The significant effects of mass movements on canyon are incision and sediment transportation at the erosion phases and fillings supply at the fill phases. This research will be helpful for the geological risk assessments and understanding the sediment transportation in the northern margin of the SCS.
基金This work was supported by the Major Project for New Generation of AI(No.2018AAA0100400)the National Natural Science Foundation of China(No.41706010)+1 种基金the Joint Fund of the Equipments Pre-Research and Ministry of Education of China(No.6141A020337)and the Fundamental Research Funds for the Central Universities of China.
文摘Sea state bias(SSB)is an important component of errors for the radar altimeter measurements of sea surface height(SSH).However,existing SSB estimation methods are almost all based on single-task learning(STL),where one model is built on the data from only one radar altimeter.In this paper,taking account of the data from multiple radar altimeters available,we introduced a multi-task learning method,called trace-norm regularized multi-task learning(TNR-MTL),for SSB estimation.Corresponding to each individual task,TNR-MLT involves only three parameters.Hence,it is easy to implement.More importantly,the convergence of TNR-MLT is theoretically guaranteed.Compared with the commonly used STL models,TNR-MTL can effectively utilize the shared information between data from multiple altimeters.During the training of TNR-MTL,we used the JASON-2 and JASON-3 cycle data to solve two correlated SSB estimation tasks.Then the optimal model was selected to estimate SSB on the JASON-2 and the HY-270-71 cycle intersection data.For the JSAON-2 cycle intersection data,the corrected variance(M)has been reduced by 0.60 cm^2 compared to the geophysical data records(GDR);while for the HY-2 cycle intersection data,M has been reduced by 1.30 cm^2 compared to GDR.Therefore,TNR-MTL is proved to be effective for the SSB estimation tasks.
基金supported by Spaceage Geoconsulting,a research oriented consulting firm.
文摘Episodes of tectonic activities since Archaean time in one of the oldest craton,the eastern Yilgarn Craton of Western Australia,have left a complex pattern in the architectural settings.Insights of the crustal scale architectural settings of the Craton have been made through geophysical data modelling and imaging using high resolution aeromagnetic and Bouguer gravity data.The advanced technique of image processing using pseudocolour composition,hill-shading and the multiple data layers compilation in the hue,saturation and intensity(HSI)space has been used for image based analysis of potential field data.Geophysical methods of anomaly enhancement technique along with the imaging technique are used to delineate several regional and as well as local structures.Multiscale analysis in geophysical data processing with the application of varying upward continuation levels,and also anomaly enhancement techniques using spatial derivatives are used delineating major shear zones and regional scale structures.A suitable data based interpretation of basement architecture of the study area is given.
基金supported by the Russian Fund of Fundamental Research(Grant No.11-05-00280)
文摘New methods are presented for processing and interpretation of shallow marine differential magnetic data, including constructing maps of offshore total magnetic anomalies with an extremely high reso- lution of up to 1-2 nT, mapping weak anomalies of 5-10 nT caused by mineralization effects at the contacts of hydrocarbons with host rocks, estimating depths to upper and lower boundaries of anom- alous magnetic sources, and estimating thickness of magnetic layers and boundaries of tectonic blocks. Horizontal dimensions of tectonic blocks in the so-called ＂seismic gap＂ region in the central Kuril Arc vary from 10 to 100 km, with typical dimensions of 25-30 km. The area of the ＂seismic gap＂ is a zone of intense tectonic activity and recent volcanism. Deep sources causing magnetic anomalies in the area are similar to the ＂magnetic belt＂ near Hokkaido. In the southern and central parts of Barents Sea, tectonic blocks with widths of 30-100 kin, and upper and lower boundaries of magnetic layers ranging from depths of 10 to 5 km and 18 to 30 km are calculated. Models of the magnetic layer underlying the Mezen Basin in an inland part of the White Sea-Barents Sea paleorift indicate depths to the lower boundary of the layer of 12-30 km. Weak local magnetic anomalies of 2-5 nT in the northern and central Caspian Sea were identified using the new methods, and drilling confirms that the anomalies are related to concentrations of hydrocarbon. Two layers causing magnetic anomalies are identified in the northern Caspian Sea from magnetic anomaly spectra. The upper layer lies immediately beneath the sea bottom and the lower layer occurs at depths between 30-40 m and 150-200 m.
文摘SeisGuard, a system for analyzing earthquake precursory data, is a software platform to search for earthquake precursory information by processing geophysical data from different sources to establish automatically an earthquake forecasting model. The main function of this system is to analyze and process the deformation, fluid, electromagnetic and other geophysical field observing data from ground-based observation, as well as space-based observation. Combined station and earthquake distributions, geological structure and other information, this system can provide a basic software platform for earthquake forecasting research based on spatiotemporal fusion. The hierarchical station tree for data sifting and the interaction mode have been innovatively developed in this SeisGuard system to improve users’ working efficiency. The data storage framework designed according to the characteristics of different time series can unify the interfaces of different data sources, provide the support of data flow, simplify the management and usage of data, and provide foundation for analysis of big data. The final aim of this development is to establish an effective earthquake forecasting model combined all available information from ground-based observations to space-based observations.
