Field investigation and seismic section explanation showed that the Longmen Mountain Thrust Belt has obvious differential deformation: zonation, segmentation and stratification. Zonation means that, from NW to NE, th...Field investigation and seismic section explanation showed that the Longmen Mountain Thrust Belt has obvious differential deformation: zonation, segmentation and stratification. Zonation means that, from NW to NE, the Longmen Mountain Thrust Belt can be divided into the Songpan- Garz~ Tectonic Belt, ductile deformation belt, base involved thrust belt, frontal fold-thrust belt, and foreland depression. Segmentation means that it can be divided into five segments from north to south: the northern segment, the Anxian Transfer Zone, the center segment, the Guanxian Transfer Zone and the southern segment. Stratification means that the detachment layers partition the structural styles in profile. The detachment layers in the Longmen Mountain Thrust Belt can be classified into three categories: the deep-level detachment layers, including the crust-mantle system detachment layer, intracrustal detachment layer, and Presinian system basal detachment layer; the middle-level detachment layers, including Cambrian-Ordovician detachment layer, Silurian detachment layer, etc.; and shallow-level detachment layers, including Upper Triassic Xujiahe Formation detachment layer and the Jurassic detachment layers. The multi-level detachment layers have a very important effect on the shaping and evolution of Longmen Mountain Thrust Belt.展开更多
Vertical differential structural deformation(VDSD),one of the most significant structural characteristics of strike-slip fault zones(SSFZs)in the Shunbei area,is crucial for understanding deformation in the SSFZ and i...Vertical differential structural deformation(VDSD),one of the most significant structural characteristics of strike-slip fault zones(SSFZs)in the Shunbei area,is crucial for understanding deformation in the SSFZ and its hydrocarbon accumulation significance.Based on drilling data and high-precision 3-D seismic data,we analyzed the geometric and kinematic characteristics of the SSFZs in the Shunbei area.Coupled with the stratification of the rock mechanism,the structural deformations of these SSFZs in different formations were differentiated and divided into four deformation layers.According to comprehensive structural interpretations and comparisons,three integrated 3-D structural models could describe the VDSD of these SSFZs.The time-space coupling of the material basis(rock mechanism stratification),changing dynamic conditions(e.g.,changing stress-strain states),and special deformation mechanism of the en echelon normal fault array uniformly controlled the formation of the VDSD in the SSFZs of the Shunbei area.The VDSD of the SSFZs in this area controlled the entire hydrocarbon accumulation process.Multi-stage structural superimposing deformation influenced the hydrocarbon migration,accumulation,distribution,preservation,and secondary adjustments.展开更多
The traditional pipeline for non-rigid registration is to iteratively update the correspondence and alignment such that the transformed source surface aligns well with the target surface.Among the pipeline,the corresp...The traditional pipeline for non-rigid registration is to iteratively update the correspondence and alignment such that the transformed source surface aligns well with the target surface.Among the pipeline,the correspondence construction and iterative manner are key to the results,while existing strategies might result in local optima.In this paper,we adopt the widely used deformation graph-based representation,while replacing some key modules with neural learning-based strategies.Specifically,we design a neural network to predict the correspondence and its reliability confidence rather than the strategies like nearest neighbor search and pair rejection.Besides,we adopt the GRU-based recurrent network for iterative refinement,which is more robust than the traditional strategy.The model is trained in a self-supervised manner and thus can be used for arbitrary datasets without ground-truth.Extensive experiments demonstrate that our proposed method outperforms the state-of-the-art methods by a large margin.展开更多
基金support from:National Natural Science Foundation of China (Grant no.40672143,40472107,40172076)National Major Fundamental Research and Development Project (Grant no.2005CB422107,G1999043305)+1 种基金Development Foundation of Key Laboratory for Hydrocarbon Accumulation of Education Ministry (Grant no.2003-01)Project of Southern Exploration and Development Division Company,SINOPEC (2003-04).
文摘Field investigation and seismic section explanation showed that the Longmen Mountain Thrust Belt has obvious differential deformation: zonation, segmentation and stratification. Zonation means that, from NW to NE, the Longmen Mountain Thrust Belt can be divided into the Songpan- Garz~ Tectonic Belt, ductile deformation belt, base involved thrust belt, frontal fold-thrust belt, and foreland depression. Segmentation means that it can be divided into five segments from north to south: the northern segment, the Anxian Transfer Zone, the center segment, the Guanxian Transfer Zone and the southern segment. Stratification means that the detachment layers partition the structural styles in profile. The detachment layers in the Longmen Mountain Thrust Belt can be classified into three categories: the deep-level detachment layers, including the crust-mantle system detachment layer, intracrustal detachment layer, and Presinian system basal detachment layer; the middle-level detachment layers, including Cambrian-Ordovician detachment layer, Silurian detachment layer, etc.; and shallow-level detachment layers, including Upper Triassic Xujiahe Formation detachment layer and the Jurassic detachment layers. The multi-level detachment layers have a very important effect on the shaping and evolution of Longmen Mountain Thrust Belt.
基金financially supported by the China Petroleum&Chemical Corporation(SINOPEC)(Grant No.P18047-2)the National Natural Science Foundation of China(Grant No.U19B6003-01)the National Key Research and Development Program of China(Grant No.2017YFC0601405)。
文摘Vertical differential structural deformation(VDSD),one of the most significant structural characteristics of strike-slip fault zones(SSFZs)in the Shunbei area,is crucial for understanding deformation in the SSFZ and its hydrocarbon accumulation significance.Based on drilling data and high-precision 3-D seismic data,we analyzed the geometric and kinematic characteristics of the SSFZs in the Shunbei area.Coupled with the stratification of the rock mechanism,the structural deformations of these SSFZs in different formations were differentiated and divided into four deformation layers.According to comprehensive structural interpretations and comparisons,three integrated 3-D structural models could describe the VDSD of these SSFZs.The time-space coupling of the material basis(rock mechanism stratification),changing dynamic conditions(e.g.,changing stress-strain states),and special deformation mechanism of the en echelon normal fault array uniformly controlled the formation of the VDSD in the SSFZs of the Shunbei area.The VDSD of the SSFZs in this area controlled the entire hydrocarbon accumulation process.Multi-stage structural superimposing deformation influenced the hydrocarbon migration,accumulation,distribution,preservation,and secondary adjustments.
基金supported by National Natural Science Foundation of China(No.62122071)the Youth Innovation Promotion Association CAS(No.2018495)“the Fundamental Research Funds for the Central Universities”(No.WK3470000021).
文摘The traditional pipeline for non-rigid registration is to iteratively update the correspondence and alignment such that the transformed source surface aligns well with the target surface.Among the pipeline,the correspondence construction and iterative manner are key to the results,while existing strategies might result in local optima.In this paper,we adopt the widely used deformation graph-based representation,while replacing some key modules with neural learning-based strategies.Specifically,we design a neural network to predict the correspondence and its reliability confidence rather than the strategies like nearest neighbor search and pair rejection.Besides,we adopt the GRU-based recurrent network for iterative refinement,which is more robust than the traditional strategy.The model is trained in a self-supervised manner and thus can be used for arbitrary datasets without ground-truth.Extensive experiments demonstrate that our proposed method outperforms the state-of-the-art methods by a large margin.