Accurate characte rization of the fault system is crucial for the exploration and development of fractu red reservoirs.The fault characterization technique based on multi-azimuth and multi-attribute fusion is a hotspo...Accurate characte rization of the fault system is crucial for the exploration and development of fractu red reservoirs.The fault characterization technique based on multi-azimuth and multi-attribute fusion is a hotspot.In this way,the fault structures of different scales can be identified and the characterization details of complex fault systems can be enriched by analyzing and fusing the fault-induced responses in multi-azimuth and multi-type seismic attributes.However,the current fusion methods are still in the stage of violent information stacking in utilizing fault information of multi-azimuth and multi-type seismic attributes,and the fault or fracture semantics in multi-type attributes are not fully considered and utilized.In this work,we propose a physic-guided multi-azimuth multi-type seismic attributes intelligent fusion method,which can mine fracture semantics from multi-azimuth seismic data and realize the effective fusion of fault-induced abnormal responses in multi-azimuth seismic coherence and curvature with the cooperation of the deep learning model and physical knowledge.The fused result can be used for multi-azimuth comprehensive characterization for multi-scale faults.The proposed method is successfully applied to an ultra-deep carbonate field survey.The results indicate the proposed method is superior to self-supervised-based,principal-component-analysis-based,and weighted-average-based fusion methods in fault characterization accuracy,and some medium-scale and microscale fault illusions in multi-azimuth seismic coherence and curvature can be removed in the fused result.展开更多
Sequential diagnosis is a very useful strategy for system-level fault identification because of its lower cost of hardware.In this paper,the characterization of sequentially t-diagnosable system is given,and a tmivers...Sequential diagnosis is a very useful strategy for system-level fault identification because of its lower cost of hardware.In this paper,the characterization of sequentially t-diagnosable system is given,and a tmiversal algorithm to seek faulty units in the system is developed.展开更多
During the late Miocene(~5.5 Ma), a large-scale submarine slide with an area of approximately 18000 km^2 and a maximum thickness of 930 m formed in the deep-water region of the Qiongdongnan Basin. The large-scale subm...During the late Miocene(~5.5 Ma), a large-scale submarine slide with an area of approximately 18000 km^2 and a maximum thickness of 930 m formed in the deep-water region of the Qiongdongnan Basin. The large-scale submarine slide has obvious features in seismic profile, with normal faults in the proximal region, escarpments at the lateral boundary, and a pronounced shear surface at the base. The internal seismic reflections are chaotic and enclosed by parallel and sub-parallel seismic events.The main direction of sediment transport was from south to north and the main sediment source was the southern region of the Qiongdongnan Basin, which is located in the east of the Indo-China Peninsula and the north of the Guangle uplift. In this region,late Miocene strike-slip reversal of the Red River Fault, uplift and increased erosion of the Indo-China Peninsula, and an abrupt rise in the rate of deposition in the western part of the South China Sea provided the basic conditions and triggering mechanism for the large-scale submarine slide. The discovery of the large-scale submarine slide provides sedimentological evidence for the tectonic event of late Miocene strike-slip reversal of the Red River Fault. It can also be inferred that the greatest tectonic activity during the process of the Red River Fault reversal occurred at ~5.5 Ma from the age of top surface of the submarine slide.展开更多
基金sponsorship of the National Natural Science Foundation of China (42430809, 42030103)the Basic Research Funds for Northeast Petroleum University in Heilongjiang Province (2025GPL-01)。
文摘Accurate characte rization of the fault system is crucial for the exploration and development of fractu red reservoirs.The fault characterization technique based on multi-azimuth and multi-attribute fusion is a hotspot.In this way,the fault structures of different scales can be identified and the characterization details of complex fault systems can be enriched by analyzing and fusing the fault-induced responses in multi-azimuth and multi-type seismic attributes.However,the current fusion methods are still in the stage of violent information stacking in utilizing fault information of multi-azimuth and multi-type seismic attributes,and the fault or fracture semantics in multi-type attributes are not fully considered and utilized.In this work,we propose a physic-guided multi-azimuth multi-type seismic attributes intelligent fusion method,which can mine fracture semantics from multi-azimuth seismic data and realize the effective fusion of fault-induced abnormal responses in multi-azimuth seismic coherence and curvature with the cooperation of the deep learning model and physical knowledge.The fused result can be used for multi-azimuth comprehensive characterization for multi-scale faults.The proposed method is successfully applied to an ultra-deep carbonate field survey.The results indicate the proposed method is superior to self-supervised-based,principal-component-analysis-based,and weighted-average-based fusion methods in fault characterization accuracy,and some medium-scale and microscale fault illusions in multi-azimuth seismic coherence and curvature can be removed in the fused result.
文摘Sequential diagnosis is a very useful strategy for system-level fault identification because of its lower cost of hardware.In this paper,the characterization of sequentially t-diagnosable system is given,and a tmiversal algorithm to seek faulty units in the system is developed.
基金supported by the National Natural Science Foundation of China (Grant Nos. 41576049, 91228208, 91028007 & 91428309)
文摘During the late Miocene(~5.5 Ma), a large-scale submarine slide with an area of approximately 18000 km^2 and a maximum thickness of 930 m formed in the deep-water region of the Qiongdongnan Basin. The large-scale submarine slide has obvious features in seismic profile, with normal faults in the proximal region, escarpments at the lateral boundary, and a pronounced shear surface at the base. The internal seismic reflections are chaotic and enclosed by parallel and sub-parallel seismic events.The main direction of sediment transport was from south to north and the main sediment source was the southern region of the Qiongdongnan Basin, which is located in the east of the Indo-China Peninsula and the north of the Guangle uplift. In this region,late Miocene strike-slip reversal of the Red River Fault, uplift and increased erosion of the Indo-China Peninsula, and an abrupt rise in the rate of deposition in the western part of the South China Sea provided the basic conditions and triggering mechanism for the large-scale submarine slide. The discovery of the large-scale submarine slide provides sedimentological evidence for the tectonic event of late Miocene strike-slip reversal of the Red River Fault. It can also be inferred that the greatest tectonic activity during the process of the Red River Fault reversal occurred at ~5.5 Ma from the age of top surface of the submarine slide.
