Ocean temperature is an important physical variable in marine ecosystems,and ocean temperature prediction is an important research objective in ocean-related fields.Currently,one of the commonly used methods for ocean...Ocean temperature is an important physical variable in marine ecosystems,and ocean temperature prediction is an important research objective in ocean-related fields.Currently,one of the commonly used methods for ocean temperature prediction is based on data-driven,but research on this method is mostly limited to the sea surface,with few studies on the prediction of internal ocean temperature.Existing graph neural network-based methods usually use predefined graphs or learned static graphs,which cannot capture the dynamic associations among data.In this study,we propose a novel dynamic spatiotemporal graph neural network(DSTGN)to predict threedimensional ocean temperature(3D-OT),which combines static graph learning and dynamic graph learning to automatically mine two unknown dependencies between sequences based on the original 3D-OT data without prior knowledge.Temporal and spatial dependencies in the time series were then captured using temporal and graph convolutions.We also integrated dynamic graph learning,static graph learning,graph convolution,and temporal convolution into an end-to-end framework for 3D-OT prediction using time-series grid data.In this study,we conducted prediction experiments using high-resolution 3D-OT from the Copernicus global ocean physical reanalysis,with data covering the vertical variation of temperature from the sea surface to 1000 m below the sea surface.We compared five mainstream models that are commonly used for ocean temperature prediction,and the results showed that the method achieved the best prediction results at all prediction scales.展开更多
Accurate prediction of formation pore pressure is essential to predict fluid flow and manage hydrocarbon production in petroleum engineering.Recent deep learning technique has been receiving more interest due to the g...Accurate prediction of formation pore pressure is essential to predict fluid flow and manage hydrocarbon production in petroleum engineering.Recent deep learning technique has been receiving more interest due to the great potential to deal with pore pressure prediction.However,most of the traditional deep learning models are less efficient to address generalization problems.To fill this technical gap,in this work,we developed a new adaptive physics-informed deep learning model with high generalization capability to predict pore pressure values directly from seismic data.Specifically,the new model,named CGP-NN,consists of a novel parametric features extraction approach(1DCPP),a stacked multilayer gated recurrent model(multilayer GRU),and an adaptive physics-informed loss function.Through machine training,the developed model can automatically select the optimal physical model to constrain the results for each pore pressure prediction.The CGP-NN model has the best generalization when the physicsrelated metricλ=0.5.A hybrid approach combining Eaton and Bowers methods is also proposed to build machine-learnable labels for solving the problem of few labels.To validate the developed model and methodology,a case study on a complex reservoir in Tarim Basin was further performed to demonstrate the high accuracy on the pore pressure prediction of new wells along with the strong generalization ability.The adaptive physics-informed deep learning approach presented here has potential application in the prediction of pore pressures coupled with multiple genesis mechanisms using seismic data.展开更多
To solve the problems in restoring sedimentary facies and predicting reservoirs in loose gas-bearing sediment,based on seismic sedimentologic analysis of the first 9-component S-wave 3D seismic dataset of China,a four...To solve the problems in restoring sedimentary facies and predicting reservoirs in loose gas-bearing sediment,based on seismic sedimentologic analysis of the first 9-component S-wave 3D seismic dataset of China,a fourth-order isochronous stratigraphic framework was set up and then sedimentary facies and reservoirs in the Pleistocene Qigequan Formation in Taidong area of Qaidam Basin were studied by seismic geomorphology and seismic lithology.The study method and thought are as following.Firstly,techniques of phase rotation,frequency decomposition and fusion,and stratal slicing were applied to the 9-component S-wave seismic data to restore sedimentary facies of major marker beds based on sedimentary models reflected by satellite images.Then,techniques of seismic attribute extraction,principal component analysis,and random fitting were applied to calculate the reservoir thickness and physical parameters of a key sandbody,and the results are satisfactory and confirmed by blind testing wells.Study results reveal that the dominant sedimentary facies in the Qigequan Formation within the study area are delta front and shallow lake.The RGB fused slices indicate that there are two cycles with three sets of underwater distributary channel systems in one period.Among them,sandstones in the distributary channels of middle-low Qigequan Formation are thick and broad with superior physical properties,which are favorable reservoirs.The reservoir permeability is also affected by diagenesis.Distributary channel sandstone reservoirs extend further to the west of Sebei-1 gas field,which provides a basis to expand exploration to the western peripheral area.展开更多
The South Yellow Sea basin is filled with Mesozoic-Cenozoic continental sediments overlying pre-Palaeozoic and Mesozoic-Palaeozoic marine sediments.Conventional multi-channel seismic data cannot describe the velocity ...The South Yellow Sea basin is filled with Mesozoic-Cenozoic continental sediments overlying pre-Palaeozoic and Mesozoic-Palaeozoic marine sediments.Conventional multi-channel seismic data cannot describe the velocity structure of the marine residual basin in detail,leading to the lack of a deeper understanding of the distribution and lithology owing to strong energy shielding on the top interface of marine sediments.In this study,we present seismic tomography data from ocean bottom seismographs that describe the NEE-trending velocity distributions of the basin.The results indicate that strong velocity variations occur at shallow crustal levels.Horizontal velocity bodies show good correlation with surface geological features,and multi-layer features exist in the vertical velocity framework(depth:0–10 km).The analyses of the velocity model,gravity data,magnetic data,multichannel seismic profiles,and drilling data showed that high-velocity anomalies(>6.5 km/s)of small(thickness:1–2 km)and large(thickness:>5 km)scales were caused by igneous complexes in the multi-layer structure,which were active during the Palaeogene.Possible locations of good Mesozoic and Palaeozoic marine strata are limited to the Central Uplift and the western part of the Northern Depression along the wide-angle ocean bottom seismograph array.Following the Indosinian movement,a strong compression existed in the Northern Depression during the extensional phase that caused the formation of folds in the middle of the survey line.This study is useful for reconstructing the regional tectonic evolution and delineating the distribution of the marine residual basin in the South Yellow Sea basin.展开更多
Based on the seismic response characteristics of space frame structures,a new type of seismic isolation bearing defined as a three-dimensional seismic isolation bearing(3DSIB) is developed in this paper.The bearing ...Based on the seismic response characteristics of space frame structures,a new type of seismic isolation bearing defined as a three-dimensional seismic isolation bearing(3DSIB) is developed in this paper.The bearing offers excellent properties such as multi-dimensional seismic isolation,reasonable rotation capability,good ability to resist lifting load,uncoupled stiffness in horizontal and vertical directions,etc.In the 3DSIB,the horizontal dimension is designed by combining the Teflon sliding device and helical spring,while the vertical dimension is developed by introducing disk springs or helical springs.The mathematical model of the 3DSIB was established and its performance with the critical parameters was tested on a shaking table.Furthermore,the 3DSIB was applied in a 120 m span hangar structure and simulated using SAP2000 software to evaluate its performance in practical structures.The performance of the structures with and without 3DSIB was compared.It is shown that the hangar structure with 3D bearings achieves a better performance.The axial force and acceleration response of the structures with 3DSIB are effectively reduced,while the displacement response of the bearing is within the predetermined range.展开更多
The parameters that influence slope stability and their criteria of failure are fairly understood but over-conservative design approaches are often preferred,which can result in excessive overburden removal that may j...The parameters that influence slope stability and their criteria of failure are fairly understood but over-conservative design approaches are often preferred,which can result in excessive overburden removal that may jeopardize profitability in the context of open pit mining.Numerical methods such as finite element and discrete element modelling are instrumental to identify specific zones of stability,but they remain approximate and do not pinpoint the critical factors that influence stability without extensive parametric studies.A large number of degrees of freedom and input parameters may make the outcome of numerical modelling insufficient compared to analytical solutions.Existing analytical approaches have not tackled the stability of slopes using non-linear plasticity criteria and threedimensional failure mechanisms.This paper bridges this gap by using the yield design theory and the Hoek-Brown criterion.Moreover,the proposed model includes the effect of seismic forces,which are not always taken into account in slope stability analyses.The results are presented in the form of rigorous mathematical expressions and stability charts involving the loading conditions and the rock mass properties emanating from the plasticity criterion.展开更多
Probabilistic analysis is a rational approach for engineering design because it provides more insight than traditional deterministic analysis. Probabilistic evaluation on seismic stability of three dimensional (3D) sl...Probabilistic analysis is a rational approach for engineering design because it provides more insight than traditional deterministic analysis. Probabilistic evaluation on seismic stability of three dimensional (3D) slopes is studied in this paper. The slope safety factor is computed by combining the kinematic approach of limit analysis using a three-dimensional rotational failure mechanism with the pseudo-dynamic approach. The variability of input parameters, including six pseudo-dynamic parameters and two soil shear strength parameters, are taken into account by means of Monte-Carlo Simulations (MCS) method. The influences of pseudo-dynamic input variables on the computed failure probabilities are investigated and discussed. It is shown that the obtained failure probabilities increase with the pseudo-dynamic input variables and the pseudo-dynamic approach gives more conservative failure probability estimates compared with the pseudo-static approach.展开更多
In order to solve the so-called "bull-eye" problem caused by using a simple bilinear interpolation as an observational mapping operator in the cost function in the multigrid three-dimensional variational (3DVAR) d...In order to solve the so-called "bull-eye" problem caused by using a simple bilinear interpolation as an observational mapping operator in the cost function in the multigrid three-dimensional variational (3DVAR) data assimilation scheme, a smoothing term, equivalent to a penalty term, is introduced into the cost function to serve as a means of troubleshooting. A theoretical analysis is first performed to figure out what on earth results in the issue of "bull-eye", and then the meaning of such smoothing term is elucidated and the uniqueness of solution of the multigrid 3DVAR with the smoothing term added is discussed through the theoretical deduction for one-dimensional (1D) case, and two idealized data assimilation experiments (one- and two-dimensional (2D) cases). By exploring the relationship between the smoothing term and the recursive filter theoretically and practically, it is revealed why satisfied analysis results can be achieved by using such proposed solution for the issue of the multigrid 3DVAR.展开更多
This paper presents the study of a three-dimensional(3D) isolation system.Firstly,the authors investigated the effects of an innovative 3D isolator,which was composed of a connecting plate,a rubber pad for vibration i...This paper presents the study of a three-dimensional(3D) isolation system.Firstly,the authors investigated the effects of an innovative 3D isolator,which was composed of a connecting plate,a rubber pad for vibration isolation in the vertical direction and a horizontal rubber bearing for seismic isolation in both horizontal directions.Secondly,the authors designed such a vibration isolation system and installed it underneath two specific residential buildings which were built directly over an existing subway communication hub platform in Beijing.These buildings required good performance vibration and seismic isolation system to reduce the impact from the running of nearby subway trains.Finally,in situ tests were conducted for both the isolated and the non-isolated buildings for the purpose of comparison.The test results showed that the maximum acceleration response level of the isolated superstructure is reduced by 10% as compared to that of the platform.The maximum attenuation of vibration reaches up to 25 dB.The 3D system explored in this paper is very effective in control and suppression of building vibration induced by earthquakes or running of trains.展开更多
The Solomon Sea Basin is a Cenozoic back-arc spreading basin within the convergence system of the Pacific and Indo-Australian plates.Against the background of subduction polarity reversal,the current Solomon Sea Basin...The Solomon Sea Basin is a Cenozoic back-arc spreading basin within the convergence system of the Pacific and Indo-Australian plates.Against the background of subduction polarity reversal,the current Solomon Sea Basin gradually formed a rhombic morphology with the subduction of the basin along the New Britain Trench and the Trobriand Trough.By analyzing the vertical gravity gradient,natural earthquake and seismic reflection data,this study determines the structural characteristics of the Solomon Sea Basin.It was found that the tectonics of the basin are characterized by the original expansion structure within the central part in addition to the structure induced by the latest subduction along the basin margin.The original spreading structure of the basin presented an east–west linear graben and horst controlled by normal faults during the basin expansion period.As a result of the subduction and slab-pull of the Solomon Sea Basin,extensional structure belts parallel to the New Britain Trench formed along the basin margin.展开更多
At present,the acquisition of seismic data is developing toward high-precision and high-density methods.However,complex natural environments and cultural factors in many exploration areas cause difficulties in achievi...At present,the acquisition of seismic data is developing toward high-precision and high-density methods.However,complex natural environments and cultural factors in many exploration areas cause difficulties in achieving uniform and intensive acquisition,which makes complete seismic data collection impossible.Therefore,data reconstruction is required in the processing link to ensure imaging accuracy.Deep learning,as a new field in rapid development,presents clear advantages in feature extraction and modeling.In this study,the convolutional neural network deep learning algorithm is applied to seismic data reconstruction.Based on the convolutional neural network algorithm and combined with the characteristics of seismic data acquisition,two training strategies of supervised and unsupervised learning are designed to reconstruct sparse acquisition seismic records.First,a supervised learning strategy is proposed for labeled data,wherein the complete seismic data are segmented as the input of the training set and are randomly sampled before each training,thereby increasing the number of samples and the richness of features.Second,an unsupervised learning strategy based on large samples is proposed for unlabeled data,and the rolling segmentation method is used to update(pseudo)labels and training parameters in the training process.Through the reconstruction test of simulated and actual data,the deep learning algorithm based on a convolutional neural network shows better reconstruction quality and higher accuracy than compressed sensing based on Curvelet transform.展开更多
Based on data collected by deep seismic sounding carried out in 1999, a three-dimensional P wave velocity structure is determined with tomographic inversion. The tomographic result shows that there is a P wave low vel...Based on data collected by deep seismic sounding carried out in 1999, a three-dimensional P wave velocity structure is determined with tomographic inversion. The tomographic result shows that there is a P wave low velocity zone (LVZ) in the upper crust beneath the Tengchong volcanic area. The LVZ is in the depth of 7~8 km and may be a smgma chamber or a partial melting body. The result also shows that the LVZ is in the northeastern side of the Rehai hydrothermal field, which is located in another LVZ near the surface. The shallow LVZ may represent a well-developed fracture zone. The strong hydrothermal activity in Rehai area can attribute to the existence of fractures between two LVZs. These fractures are the channels for going upwards of the deep hot fluid.展开更多
Paleostress plays a significant role in controlling the formation, accumulation, and distribution of reservoirs, and this could be an important factor in controlling the production of hydrocarbons from the unconventio...Paleostress plays a significant role in controlling the formation, accumulation, and distribution of reservoirs, and this could be an important factor in controlling the production of hydrocarbons from the unconventional reservoirs. In this study, we will use 3D seismic reflection data to perform the slip-tendency-based stress inversion to determine the stress field in the basement of the northern slope area in the Bongor Basin. The dataset for this technique is easily available in the oil and gas companies. The stress inversion results from the basement of the northern slope area of Bongor basin show that the maximum principal stress axis (σ1) is oriented vertically, the intermediate principal stress axis (σ2) is oriented N18° and the minimum principal stress axis (σ3) is oriented N105°, and σ2/σ1 = 0.60 and σ3/σ1 = 0.29. The findings of this paper provide significant information to understand the fault reactivation at the critical stage of hydrocarbon accumulation and the regional tectonic evolution.展开更多
The Kuiyang-ST2000 deep-towed high-resolution multichannel seismic system was designed by the First Institute of Oceanography,Ministry of Natural Resources(FIO,MNR).The system is mainly composed of a plasma spark sour...The Kuiyang-ST2000 deep-towed high-resolution multichannel seismic system was designed by the First Institute of Oceanography,Ministry of Natural Resources(FIO,MNR).The system is mainly composed of a plasma spark source(source level:216 dB,main frequency:750 Hz,frequency bandwidth:150-1200 Hz)and a towed hydrophone streamer with 48 channels.Because the source and the towed hydrophone streamer are constantly moving according to the towing configuration,the accurate positioning of the towing hydrophone array and the moveout correction of deep-towed multichannel seismic data processing before imaging are challenging.Initially,according to the characteristics of the system and the towing streamer shape in deep water,travel-time positioning method was used to construct the hydrophone streamer shape,and the results were corrected by using the polynomial curve fitting method.Then,a new data-processing workflow for Kuiyang-ST2000 system data was introduced,mainly including float datum setting,residual static correction,phase-based moveout correction,which allows the imaging algorithms of conventional marine seismic data processing to extend to deep-towed seismic data.We successfully applied the Kuiyang-ST2000 system and methodology of data processing to a gas hydrate survey of the Qiongdongnan and Shenhu areas in the South China Sea,and the results show that the profile has very high vertical and lateral resolutions(0.5 m and 8 m,respectively),which can provide full and accurate details of gas hydrate-related and geohazard sedimentary and structural features in the South China Sea.展开更多
In response to the construction needs of “Real 3D China”, the system structure, functional framework, application direction and product form of block level augmented reality three-dimensional map is designed. Those ...In response to the construction needs of “Real 3D China”, the system structure, functional framework, application direction and product form of block level augmented reality three-dimensional map is designed. Those provide references and ideas for the later large-scale production of augmented reality three-dimensional map. The augmented reality three-dimensional map is produced based on skyline software. Including the map browsing, measurement and analysis and so on, the basic function of three-dimensional map is realized. The special functional module including housing management, pipeline management and so on is developed combining the need of residential quarters development, that expands the application fields of augmented reality three-dimensional map. Those lay the groundwork for the application of augmented reality three-dimensional map. .展开更多
The picking efficiency of seismic first breaks(FBs)has been greatly accelerated by deep learning(DL)technology.However,the picking accuracy and efficiency of DL methods still face huge challenges in low signal-to-nois...The picking efficiency of seismic first breaks(FBs)has been greatly accelerated by deep learning(DL)technology.However,the picking accuracy and efficiency of DL methods still face huge challenges in low signal-to-noise ratio(SNR)situations.To address this issue,we propose a regression approach to pick FBs based on bidirectional long short-term memory(Bi LSTM)neural network by learning the implicit Eikonal equation of 3D inhomogeneous media with rugged topography in the target region.We employ a regressive model that represents the relationships among the elevation of shots,offset and the elevation of receivers with their seismic traveltime to predict the unknown FBs,from common-shot gathers with sparsely distributed traces.Different from image segmentation methods which automatically extract image features and classify FBs from seismic data,the proposed method can learn the inner relationship between field geometry and FBs.In addition,the predicted results by the regressive model are continuous values of FBs rather than the discrete ones of the binary distribution.The picking results of synthetic data shows that the proposed method has low dependence on label data,and can obtain reliable and similar predicted results using two types of label data with large differences.The picking results of9380 shots for 3D seismic data generated by vibroseis indicate that the proposed method can still accurately predict FBs in low SNR data.The subsequent stacked profiles further illustrate the reliability and effectiveness of the proposed method.The results of model data and field seismic data demonstrate that the proposed regression method is a robust first-break picker with high potential for field application.展开更多
The Pennsylvanian unconformity,which is a detrital surface,separates the beds of the Permian-aged strata from the Lower Paleozoic in the Central Basin Platform.Seismic data interpretation indicates that the unconformi...The Pennsylvanian unconformity,which is a detrital surface,separates the beds of the Permian-aged strata from the Lower Paleozoic in the Central Basin Platform.Seismic data interpretation indicates that the unconformity is an angular unconformity,overlying multiple normal faults,and accompanied with a thrust fault which maximizes the region's structural complexity.Additionally,the Pennsylvanian angular unconformity creates pinch-outs between the beds above and below.We computed the spectral decomposition and reflector convergence attributes and analyzed them to characterize the angular unconformity and faults.The spectral decomposition attribute divides the broadband seismic data into different spectral bands to resolve thin beds and show thickness variations.In contrast,the reflector convergence attribute highlights the location and direction of the pinch-outs as they dip south at angles between 2° and 6°.After reviewing findings from RGB blending of the spectrally decomposed frequencies along the Pennsylvanian unconformity,we observed channel-like features and multiple linear bands in addition to the faults and pinch-outs.It can be inferred that the identified linear bands could be the result of different lithologies associated with the tilting of the beds,and the faults may possibly influence hydrocarbon migration or act as a flow barrier to entrap hydrocarbon accumulation.The identification of this angular unconformity and the associated features in the study area are vital for the following reasons:1)the unconformity surface represents a natural stratigraphic boundary;2)the stratigraphic pinch-outs act as fluid flow connectivity boundaries;3)the areal extent of compartmentalized reservoirs'boundaries created by the angular unconformity are better defined;and 4)fault displacements are better understood when planning well locations as faults can be flow barriers,or permeability conduits,depending on facies heterogeneity and/or seal effectiveness of a fault,which can affect hydrocarbon production.The methodology utilized in this study is a further step in the characterization of reservoirs and can be used to expand our knowledge and obtain more information about the Goldsmith Field.展开更多
In order to realize visualization of three-dimensional data field (TDDF) in instrument, two methods of visualization of TDDF and the usual manner of quick graphic and image processing are analyzed. And how to use Op...In order to realize visualization of three-dimensional data field (TDDF) in instrument, two methods of visualization of TDDF and the usual manner of quick graphic and image processing are analyzed. And how to use OpenGL technique and the characteristic of analyzed data to construct a TDDF, the ways of reality processing and interactive processing are described. Then the medium geometric element and a related realistic model are constructed by means of the first algorithm. Models obtained for attaching the third dimension in three-dimensional data field are presented. An example for TDDF realization of machine measuring is provided. The analysis of resultant graphic indicates that the three-dimensional graphics built by the method developed is featured by good reality, fast processing and strong interaction展开更多
Irregular seismic data causes problems with multi-trace processing algorithms and degrades processing quality. We introduce the Projection onto Convex Sets (POCS) based image restoration method into the seismic data...Irregular seismic data causes problems with multi-trace processing algorithms and degrades processing quality. We introduce the Projection onto Convex Sets (POCS) based image restoration method into the seismic data reconstruction field to interpolate irregularly missing traces. For entire dead traces, we transfer the POCS iteration reconstruction process from the time to frequency domain to save computational cost because forward and reverse Fourier time transforms are not needed. In each iteration, the selection threshold parameter is important for reconstruction efficiency. In this paper, we designed two types of threshold models to reconstruct irregularly missing seismic data. The experimental results show that an exponential threshold can greatly reduce iterations and improve reconstruction efficiency compared to a linear threshold for the same reconstruction result. We also analyze the anti- noise and anti-alias ability of the POCS reconstruction method. Finally, theoretical model tests and real data examples indicate that the proposed method is efficient and applicable.展开更多
Seismic data contain random noise interference and are affected by irregular subsampling. Presently, most of the data reconstruction methods are carried out separately from noise suppression. Moreover, most data recon...Seismic data contain random noise interference and are affected by irregular subsampling. Presently, most of the data reconstruction methods are carried out separately from noise suppression. Moreover, most data reconstruction methods are not ideal for noisy data. In this paper, we choose the multiscale and multidirectional 2D curvelet transform to perform simultaneous data reconstruction and noise suppression of 3D seismic data. We introduce the POCS algorithm, the exponentially decreasing square root threshold, and soft threshold operator to interpolate the data at each time slice. A weighing strategy was introduced to reduce the reconstructed data noise. A 3D simultaneous data reconstruction and noise suppression method based on the curvelet transform was proposed. When compared with data reconstruction followed by denoizing and the Fourier transform, the proposed method is more robust and effective. The proposed method has important implications for data acquisition in complex areas and reconstructing missing traces.展开更多
基金The National Key R&D Program of China under contract No.2021YFC3101603.
文摘Ocean temperature is an important physical variable in marine ecosystems,and ocean temperature prediction is an important research objective in ocean-related fields.Currently,one of the commonly used methods for ocean temperature prediction is based on data-driven,but research on this method is mostly limited to the sea surface,with few studies on the prediction of internal ocean temperature.Existing graph neural network-based methods usually use predefined graphs or learned static graphs,which cannot capture the dynamic associations among data.In this study,we propose a novel dynamic spatiotemporal graph neural network(DSTGN)to predict threedimensional ocean temperature(3D-OT),which combines static graph learning and dynamic graph learning to automatically mine two unknown dependencies between sequences based on the original 3D-OT data without prior knowledge.Temporal and spatial dependencies in the time series were then captured using temporal and graph convolutions.We also integrated dynamic graph learning,static graph learning,graph convolution,and temporal convolution into an end-to-end framework for 3D-OT prediction using time-series grid data.In this study,we conducted prediction experiments using high-resolution 3D-OT from the Copernicus global ocean physical reanalysis,with data covering the vertical variation of temperature from the sea surface to 1000 m below the sea surface.We compared five mainstream models that are commonly used for ocean temperature prediction,and the results showed that the method achieved the best prediction results at all prediction scales.
基金funded by the National Natural Science Foundation of China(General Program:No.52074314,No.U19B6003-05)National Key Research and Development Program of China(2019YFA0708303-05)。
文摘Accurate prediction of formation pore pressure is essential to predict fluid flow and manage hydrocarbon production in petroleum engineering.Recent deep learning technique has been receiving more interest due to the great potential to deal with pore pressure prediction.However,most of the traditional deep learning models are less efficient to address generalization problems.To fill this technical gap,in this work,we developed a new adaptive physics-informed deep learning model with high generalization capability to predict pore pressure values directly from seismic data.Specifically,the new model,named CGP-NN,consists of a novel parametric features extraction approach(1DCPP),a stacked multilayer gated recurrent model(multilayer GRU),and an adaptive physics-informed loss function.Through machine training,the developed model can automatically select the optimal physical model to constrain the results for each pore pressure prediction.The CGP-NN model has the best generalization when the physicsrelated metricλ=0.5.A hybrid approach combining Eaton and Bowers methods is also proposed to build machine-learnable labels for solving the problem of few labels.To validate the developed model and methodology,a case study on a complex reservoir in Tarim Basin was further performed to demonstrate the high accuracy on the pore pressure prediction of new wells along with the strong generalization ability.The adaptive physics-informed deep learning approach presented here has potential application in the prediction of pore pressures coupled with multiple genesis mechanisms using seismic data.
基金Supported by the CNPC Science and Technology Projects(2022-N/G-47808,2023-N/G-67014)RIPED International Cooperation Project(19HTY5000008).
文摘To solve the problems in restoring sedimentary facies and predicting reservoirs in loose gas-bearing sediment,based on seismic sedimentologic analysis of the first 9-component S-wave 3D seismic dataset of China,a fourth-order isochronous stratigraphic framework was set up and then sedimentary facies and reservoirs in the Pleistocene Qigequan Formation in Taidong area of Qaidam Basin were studied by seismic geomorphology and seismic lithology.The study method and thought are as following.Firstly,techniques of phase rotation,frequency decomposition and fusion,and stratal slicing were applied to the 9-component S-wave seismic data to restore sedimentary facies of major marker beds based on sedimentary models reflected by satellite images.Then,techniques of seismic attribute extraction,principal component analysis,and random fitting were applied to calculate the reservoir thickness and physical parameters of a key sandbody,and the results are satisfactory and confirmed by blind testing wells.Study results reveal that the dominant sedimentary facies in the Qigequan Formation within the study area are delta front and shallow lake.The RGB fused slices indicate that there are two cycles with three sets of underwater distributary channel systems in one period.Among them,sandstones in the distributary channels of middle-low Qigequan Formation are thick and broad with superior physical properties,which are favorable reservoirs.The reservoir permeability is also affected by diagenesis.Distributary channel sandstone reservoirs extend further to the west of Sebei-1 gas field,which provides a basis to expand exploration to the western peripheral area.
基金The National Natural Science Foundation of China under contract No.41806048the Open Fund of the Hubei Key Laboratory of Marine Geological Resources under contract No.MGR202009+2 种基金the Fund from the Key Laboratory of Deep-Earth Dynamics of Ministry of Natural Resource,Institute of Geology,Chinese Academy of Geological Sciences under contract No.J1901-16the Aoshan Science and Technology Innovation Project of Pilot National Laboratory for Marine Science and Technology(Qingdao)under contract No.2015ASKJ03-Seabed Resourcesthe Fund from the Korea Institute of Ocean Science and Technology(KIOST)under contract No.PE99741.
文摘The South Yellow Sea basin is filled with Mesozoic-Cenozoic continental sediments overlying pre-Palaeozoic and Mesozoic-Palaeozoic marine sediments.Conventional multi-channel seismic data cannot describe the velocity structure of the marine residual basin in detail,leading to the lack of a deeper understanding of the distribution and lithology owing to strong energy shielding on the top interface of marine sediments.In this study,we present seismic tomography data from ocean bottom seismographs that describe the NEE-trending velocity distributions of the basin.The results indicate that strong velocity variations occur at shallow crustal levels.Horizontal velocity bodies show good correlation with surface geological features,and multi-layer features exist in the vertical velocity framework(depth:0–10 km).The analyses of the velocity model,gravity data,magnetic data,multichannel seismic profiles,and drilling data showed that high-velocity anomalies(>6.5 km/s)of small(thickness:1–2 km)and large(thickness:>5 km)scales were caused by igneous complexes in the multi-layer structure,which were active during the Palaeogene.Possible locations of good Mesozoic and Palaeozoic marine strata are limited to the Central Uplift and the western part of the Northern Depression along the wide-angle ocean bottom seismograph array.Following the Indosinian movement,a strong compression existed in the Northern Depression during the extensional phase that caused the formation of folds in the middle of the survey line.This study is useful for reconstructing the regional tectonic evolution and delineating the distribution of the marine residual basin in the South Yellow Sea basin.
基金National Natural Science Foundation of China under Grant No. 50778006,51278008Doctoral Fund of Ministry of Education of China under Grant No.20121103110021+1 种基金Beijing Natural Science Foundation under Grant No.8112005the Funding of the Jurisdiction of Beijing Municipality 2011
文摘Based on the seismic response characteristics of space frame structures,a new type of seismic isolation bearing defined as a three-dimensional seismic isolation bearing(3DSIB) is developed in this paper.The bearing offers excellent properties such as multi-dimensional seismic isolation,reasonable rotation capability,good ability to resist lifting load,uncoupled stiffness in horizontal and vertical directions,etc.In the 3DSIB,the horizontal dimension is designed by combining the Teflon sliding device and helical spring,while the vertical dimension is developed by introducing disk springs or helical springs.The mathematical model of the 3DSIB was established and its performance with the critical parameters was tested on a shaking table.Furthermore,the 3DSIB was applied in a 120 m span hangar structure and simulated using SAP2000 software to evaluate its performance in practical structures.The performance of the structures with and without 3DSIB was compared.It is shown that the hangar structure with 3D bearings achieves a better performance.The axial force and acceleration response of the structures with 3DSIB are effectively reduced,while the displacement response of the bearing is within the predetermined range.
文摘The parameters that influence slope stability and their criteria of failure are fairly understood but over-conservative design approaches are often preferred,which can result in excessive overburden removal that may jeopardize profitability in the context of open pit mining.Numerical methods such as finite element and discrete element modelling are instrumental to identify specific zones of stability,but they remain approximate and do not pinpoint the critical factors that influence stability without extensive parametric studies.A large number of degrees of freedom and input parameters may make the outcome of numerical modelling insufficient compared to analytical solutions.Existing analytical approaches have not tackled the stability of slopes using non-linear plasticity criteria and threedimensional failure mechanisms.This paper bridges this gap by using the yield design theory and the Hoek-Brown criterion.Moreover,the proposed model includes the effect of seismic forces,which are not always taken into account in slope stability analyses.The results are presented in the form of rigorous mathematical expressions and stability charts involving the loading conditions and the rock mass properties emanating from the plasticity criterion.
文摘Probabilistic analysis is a rational approach for engineering design because it provides more insight than traditional deterministic analysis. Probabilistic evaluation on seismic stability of three dimensional (3D) slopes is studied in this paper. The slope safety factor is computed by combining the kinematic approach of limit analysis using a three-dimensional rotational failure mechanism with the pseudo-dynamic approach. The variability of input parameters, including six pseudo-dynamic parameters and two soil shear strength parameters, are taken into account by means of Monte-Carlo Simulations (MCS) method. The influences of pseudo-dynamic input variables on the computed failure probabilities are investigated and discussed. It is shown that the obtained failure probabilities increase with the pseudo-dynamic input variables and the pseudo-dynamic approach gives more conservative failure probability estimates compared with the pseudo-static approach.
基金The National Basic Research Program of China under contract No. 2013CB430304the National High-Tech R&D Program of China under contract No. 2013AA09A505the National Natural Science Foundation of China under contract Nos 41030854,40906015,40906016,41106005 and 41176003
文摘In order to solve the so-called "bull-eye" problem caused by using a simple bilinear interpolation as an observational mapping operator in the cost function in the multigrid three-dimensional variational (3DVAR) data assimilation scheme, a smoothing term, equivalent to a penalty term, is introduced into the cost function to serve as a means of troubleshooting. A theoretical analysis is first performed to figure out what on earth results in the issue of "bull-eye", and then the meaning of such smoothing term is elucidated and the uniqueness of solution of the multigrid 3DVAR with the smoothing term added is discussed through the theoretical deduction for one-dimensional (1D) case, and two idealized data assimilation experiments (one- and two-dimensional (2D) cases). By exploring the relationship between the smoothing term and the recursive filter theoretically and practically, it is revealed why satisfied analysis results can be achieved by using such proposed solution for the issue of the multigrid 3DVAR.
基金Supported by the National Natural Science Foundation of China (Grant No. 51078098,90915007,90815027 and 50878124)the Key Laboratory of Seismic Control & Structure Safety Open FundInnovation Group Fund of Guangdong Province
文摘This paper presents the study of a three-dimensional(3D) isolation system.Firstly,the authors investigated the effects of an innovative 3D isolator,which was composed of a connecting plate,a rubber pad for vibration isolation in the vertical direction and a horizontal rubber bearing for seismic isolation in both horizontal directions.Secondly,the authors designed such a vibration isolation system and installed it underneath two specific residential buildings which were built directly over an existing subway communication hub platform in Beijing.These buildings required good performance vibration and seismic isolation system to reduce the impact from the running of nearby subway trains.Finally,in situ tests were conducted for both the isolated and the non-isolated buildings for the purpose of comparison.The test results showed that the maximum acceleration response level of the isolated superstructure is reduced by 10% as compared to that of the platform.The maximum attenuation of vibration reaches up to 25 dB.The 3D system explored in this paper is very effective in control and suppression of building vibration induced by earthquakes or running of trains.
基金supported by the National Natural Science Foundation of China(Grant Nos.91858215 and 41906048)。
文摘The Solomon Sea Basin is a Cenozoic back-arc spreading basin within the convergence system of the Pacific and Indo-Australian plates.Against the background of subduction polarity reversal,the current Solomon Sea Basin gradually formed a rhombic morphology with the subduction of the basin along the New Britain Trench and the Trobriand Trough.By analyzing the vertical gravity gradient,natural earthquake and seismic reflection data,this study determines the structural characteristics of the Solomon Sea Basin.It was found that the tectonics of the basin are characterized by the original expansion structure within the central part in addition to the structure induced by the latest subduction along the basin margin.The original spreading structure of the basin presented an east–west linear graben and horst controlled by normal faults during the basin expansion period.As a result of the subduction and slab-pull of the Solomon Sea Basin,extensional structure belts parallel to the New Britain Trench formed along the basin margin.
基金This study was supported by the National Natural Science Foundation of China under the project‘Research on the Dynamic Location of Receiver Points and Wave Field Separation Technology Based on Deep Learning in OBN Seismic Exploration’(No.42074140).
文摘At present,the acquisition of seismic data is developing toward high-precision and high-density methods.However,complex natural environments and cultural factors in many exploration areas cause difficulties in achieving uniform and intensive acquisition,which makes complete seismic data collection impossible.Therefore,data reconstruction is required in the processing link to ensure imaging accuracy.Deep learning,as a new field in rapid development,presents clear advantages in feature extraction and modeling.In this study,the convolutional neural network deep learning algorithm is applied to seismic data reconstruction.Based on the convolutional neural network algorithm and combined with the characteristics of seismic data acquisition,two training strategies of supervised and unsupervised learning are designed to reconstruct sparse acquisition seismic records.First,a supervised learning strategy is proposed for labeled data,wherein the complete seismic data are segmented as the input of the training set and are randomly sampled before each training,thereby increasing the number of samples and the richness of features.Second,an unsupervised learning strategy based on large samples is proposed for unlabeled data,and the rolling segmentation method is used to update(pseudo)labels and training parameters in the training process.Through the reconstruction test of simulated and actual data,the deep learning algorithm based on a convolutional neural network shows better reconstruction quality and higher accuracy than compressed sensing based on Curvelet transform.
基金State Natural Science Foundation of China (D49974020), Joint Seismological Science Foundation of China (199110) and Project (95-11-01-06) during Ninth Five-Year Plan from China Seismological Bureau.
文摘Based on data collected by deep seismic sounding carried out in 1999, a three-dimensional P wave velocity structure is determined with tomographic inversion. The tomographic result shows that there is a P wave low velocity zone (LVZ) in the upper crust beneath the Tengchong volcanic area. The LVZ is in the depth of 7~8 km and may be a smgma chamber or a partial melting body. The result also shows that the LVZ is in the northeastern side of the Rehai hydrothermal field, which is located in another LVZ near the surface. The shallow LVZ may represent a well-developed fracture zone. The strong hydrothermal activity in Rehai area can attribute to the existence of fractures between two LVZs. These fractures are the channels for going upwards of the deep hot fluid.
文摘Paleostress plays a significant role in controlling the formation, accumulation, and distribution of reservoirs, and this could be an important factor in controlling the production of hydrocarbons from the unconventional reservoirs. In this study, we will use 3D seismic reflection data to perform the slip-tendency-based stress inversion to determine the stress field in the basement of the northern slope area in the Bongor Basin. The dataset for this technique is easily available in the oil and gas companies. The stress inversion results from the basement of the northern slope area of Bongor basin show that the maximum principal stress axis (σ1) is oriented vertically, the intermediate principal stress axis (σ2) is oriented N18° and the minimum principal stress axis (σ3) is oriented N105°, and σ2/σ1 = 0.60 and σ3/σ1 = 0.29. The findings of this paper provide significant information to understand the fault reactivation at the critical stage of hydrocarbon accumulation and the regional tectonic evolution.
基金Supported by the National Key R&D Program of China(No.2016YFC0303900)the Laoshan Laboratory(Nos.MGQNLM-KF201807,LSKJ202203604)the National Natural Science Foundation of China(No.42106072)。
文摘The Kuiyang-ST2000 deep-towed high-resolution multichannel seismic system was designed by the First Institute of Oceanography,Ministry of Natural Resources(FIO,MNR).The system is mainly composed of a plasma spark source(source level:216 dB,main frequency:750 Hz,frequency bandwidth:150-1200 Hz)and a towed hydrophone streamer with 48 channels.Because the source and the towed hydrophone streamer are constantly moving according to the towing configuration,the accurate positioning of the towing hydrophone array and the moveout correction of deep-towed multichannel seismic data processing before imaging are challenging.Initially,according to the characteristics of the system and the towing streamer shape in deep water,travel-time positioning method was used to construct the hydrophone streamer shape,and the results were corrected by using the polynomial curve fitting method.Then,a new data-processing workflow for Kuiyang-ST2000 system data was introduced,mainly including float datum setting,residual static correction,phase-based moveout correction,which allows the imaging algorithms of conventional marine seismic data processing to extend to deep-towed seismic data.We successfully applied the Kuiyang-ST2000 system and methodology of data processing to a gas hydrate survey of the Qiongdongnan and Shenhu areas in the South China Sea,and the results show that the profile has very high vertical and lateral resolutions(0.5 m and 8 m,respectively),which can provide full and accurate details of gas hydrate-related and geohazard sedimentary and structural features in the South China Sea.
文摘In response to the construction needs of “Real 3D China”, the system structure, functional framework, application direction and product form of block level augmented reality three-dimensional map is designed. Those provide references and ideas for the later large-scale production of augmented reality three-dimensional map. The augmented reality three-dimensional map is produced based on skyline software. Including the map browsing, measurement and analysis and so on, the basic function of three-dimensional map is realized. The special functional module including housing management, pipeline management and so on is developed combining the need of residential quarters development, that expands the application fields of augmented reality three-dimensional map. Those lay the groundwork for the application of augmented reality three-dimensional map. .
基金financially supported by the National Key R&D Program of China(2018YFA0702504)the National Natural Science Foundation of China(42174152)+1 种基金the Strategic Cooperation Technology Projects of China National Petroleum Corporation(CNPC)and China University of Petroleum-Beijing(CUPB)(ZLZX2020-03)the R&D Department of China National Petroleum Corporation(2022DQ0604-01)。
文摘The picking efficiency of seismic first breaks(FBs)has been greatly accelerated by deep learning(DL)technology.However,the picking accuracy and efficiency of DL methods still face huge challenges in low signal-to-noise ratio(SNR)situations.To address this issue,we propose a regression approach to pick FBs based on bidirectional long short-term memory(Bi LSTM)neural network by learning the implicit Eikonal equation of 3D inhomogeneous media with rugged topography in the target region.We employ a regressive model that represents the relationships among the elevation of shots,offset and the elevation of receivers with their seismic traveltime to predict the unknown FBs,from common-shot gathers with sparsely distributed traces.Different from image segmentation methods which automatically extract image features and classify FBs from seismic data,the proposed method can learn the inner relationship between field geometry and FBs.In addition,the predicted results by the regressive model are continuous values of FBs rather than the discrete ones of the binary distribution.The picking results of synthetic data shows that the proposed method has low dependence on label data,and can obtain reliable and similar predicted results using two types of label data with large differences.The picking results of9380 shots for 3D seismic data generated by vibroseis indicate that the proposed method can still accurately predict FBs in low SNR data.The subsequent stacked profiles further illustrate the reliability and effectiveness of the proposed method.The results of model data and field seismic data demonstrate that the proposed regression method is a robust first-break picker with high potential for field application.
文摘The Pennsylvanian unconformity,which is a detrital surface,separates the beds of the Permian-aged strata from the Lower Paleozoic in the Central Basin Platform.Seismic data interpretation indicates that the unconformity is an angular unconformity,overlying multiple normal faults,and accompanied with a thrust fault which maximizes the region's structural complexity.Additionally,the Pennsylvanian angular unconformity creates pinch-outs between the beds above and below.We computed the spectral decomposition and reflector convergence attributes and analyzed them to characterize the angular unconformity and faults.The spectral decomposition attribute divides the broadband seismic data into different spectral bands to resolve thin beds and show thickness variations.In contrast,the reflector convergence attribute highlights the location and direction of the pinch-outs as they dip south at angles between 2° and 6°.After reviewing findings from RGB blending of the spectrally decomposed frequencies along the Pennsylvanian unconformity,we observed channel-like features and multiple linear bands in addition to the faults and pinch-outs.It can be inferred that the identified linear bands could be the result of different lithologies associated with the tilting of the beds,and the faults may possibly influence hydrocarbon migration or act as a flow barrier to entrap hydrocarbon accumulation.The identification of this angular unconformity and the associated features in the study area are vital for the following reasons:1)the unconformity surface represents a natural stratigraphic boundary;2)the stratigraphic pinch-outs act as fluid flow connectivity boundaries;3)the areal extent of compartmentalized reservoirs'boundaries created by the angular unconformity are better defined;and 4)fault displacements are better understood when planning well locations as faults can be flow barriers,or permeability conduits,depending on facies heterogeneity and/or seal effectiveness of a fault,which can affect hydrocarbon production.The methodology utilized in this study is a further step in the characterization of reservoirs and can be used to expand our knowledge and obtain more information about the Goldsmith Field.
基金This project is supported by National Natural Science Foundation of China (No.50405009)
文摘In order to realize visualization of three-dimensional data field (TDDF) in instrument, two methods of visualization of TDDF and the usual manner of quick graphic and image processing are analyzed. And how to use OpenGL technique and the characteristic of analyzed data to construct a TDDF, the ways of reality processing and interactive processing are described. Then the medium geometric element and a related realistic model are constructed by means of the first algorithm. Models obtained for attaching the third dimension in three-dimensional data field are presented. An example for TDDF realization of machine measuring is provided. The analysis of resultant graphic indicates that the three-dimensional graphics built by the method developed is featured by good reality, fast processing and strong interaction
基金financially supported by National 863 Program (Grants No.2006AA 09A 102-09)National Science and Technology of Major Projects ( Grants No.2008ZX0 5025-001-001)
文摘Irregular seismic data causes problems with multi-trace processing algorithms and degrades processing quality. We introduce the Projection onto Convex Sets (POCS) based image restoration method into the seismic data reconstruction field to interpolate irregularly missing traces. For entire dead traces, we transfer the POCS iteration reconstruction process from the time to frequency domain to save computational cost because forward and reverse Fourier time transforms are not needed. In each iteration, the selection threshold parameter is important for reconstruction efficiency. In this paper, we designed two types of threshold models to reconstruct irregularly missing seismic data. The experimental results show that an exponential threshold can greatly reduce iterations and improve reconstruction efficiency compared to a linear threshold for the same reconstruction result. We also analyze the anti- noise and anti-alias ability of the POCS reconstruction method. Finally, theoretical model tests and real data examples indicate that the proposed method is efficient and applicable.
基金sponsored by the National Natural Science Foundation of China(Nos.41304097 and 41664006)the Natural Science Foundation of Jiangxi Province(No.20151BAB203044)+1 种基金the China Scholarship Council(No.201508360061)Distinguished Young Talent Foundation of Jiangxi Province(2017)
文摘Seismic data contain random noise interference and are affected by irregular subsampling. Presently, most of the data reconstruction methods are carried out separately from noise suppression. Moreover, most data reconstruction methods are not ideal for noisy data. In this paper, we choose the multiscale and multidirectional 2D curvelet transform to perform simultaneous data reconstruction and noise suppression of 3D seismic data. We introduce the POCS algorithm, the exponentially decreasing square root threshold, and soft threshold operator to interpolate the data at each time slice. A weighing strategy was introduced to reduce the reconstructed data noise. A 3D simultaneous data reconstruction and noise suppression method based on the curvelet transform was proposed. When compared with data reconstruction followed by denoizing and the Fourier transform, the proposed method is more robust and effective. The proposed method has important implications for data acquisition in complex areas and reconstructing missing traces.