In studies on gas hydrate,bottom-simulating reflectors(BSR)are used to determine the potential hydrate-bearing sedimentary layers.Usually,BSR detection is performed manually by experienced interpreters.Therefore,a met...In studies on gas hydrate,bottom-simulating reflectors(BSR)are used to determine the potential hydrate-bearing sedimentary layers.Usually,BSR detection is performed manually by experienced interpreters.Therefore,a method for implementing an auto-matic BSR detection process should be established.In this study,we develop a novel architecture for BSR characterization using the convolutional neural network(CNN)technique.We propose the use of Stokes’transform(ST)to obtain a time-frequency spectrum for the input of CNN.ST fully uses the frequency content of the seismic data,and a part of the 3D seismic data collected from the Blake Ridge is utilized to train the CNN.Synthetic seismic records with variable signal-to-noise ratios(SNR),as well as Blake Ridge seismic data,were used to validate the detection effect of the CNN.Results show that the CNN trained by this method exhibits excellent performance in noise-resistant testing and achieves an accuracy of more than 89% in field seismic data detection.展开更多
The chirp sub-bottom profiler,for its high resolution,easy accessibility and cost-effectiveness,has been widely used in acoustic detection.In this paper,the acoustic impedance and grain size compositions were obtained...The chirp sub-bottom profiler,for its high resolution,easy accessibility and cost-effectiveness,has been widely used in acoustic detection.In this paper,the acoustic impedance and grain size compositions were obtained based on the chirp sub-bottom profiler data collected in the Chukchi Plateau area during the 11th Arctic Expedition of China.The time-domain adaptive search matching algorithm was used and validated on our established theoretical model.The misfit between the inversion result and the theoretical model is less than 0.067%.The grain size was calculated according to the empirical relationship between the acoustic impedance and the grain size of the sediment.The average acoustic impedance of sub-seafloor strata is 2.5026×10^(6) kg(s m^(2))^(-1)and the average grain size(θvalue)of the seafloor surface sediment is 7.1498,indicating the predominant occurrence of very fine silt sediment in the study area.Comparison of the inversion results and the laboratory measurements of nearby borehole samples shows that they are in general agreement.展开更多
Studying the Arctic sea ice contributes to a comprehensive understanding of the climate system in polar regions and offers valuable insights into the interplay between polar climate change and the global climate and e...Studying the Arctic sea ice contributes to a comprehensive understanding of the climate system in polar regions and offers valuable insights into the interplay between polar climate change and the global climate and environment.One of the key research aspects is the investigation of the temperature,salinity,and density parameters of sea ice to obtain essential insights.During the 11th Chinese National Arctic Research Expedition,acoustic velocity was measured on an ice core at a short-term ice station,however,temperature,salinity,and density were not measured.In the present work,we utilized a genetic algorithm to invert these obtained acoustic velocity data to sea ice temperature,salinity,and density parameters on the basis of the relationship between acoustic velocity and the physical properties of Arctic summer sea ice.We validated the effectiveness of this inversion procedure by comparing its findings with those of other researchers.The results indicate that within the normalized depth range of 0.43-0.94,the ranges for temperature,salinity,and density are -0.48--0.29℃,1.63-3.35,and 793.1-904.1 kg m^(-3),respectively.展开更多
The Ying-Qiong Basin is located on the northwestern margin of the South China Sea and at the junction of the South China Block and the Indochina Block.It is characterized by complex geological structures.The existing ...The Ying-Qiong Basin is located on the northwestern margin of the South China Sea and at the junction of the South China Block and the Indochina Block.It is characterized by complex geological structures.The existing seismic data in the study area is sparse due to the lack of earthquake activities.Because of the limited source energy and poor coverage of seismic data,the knowledge of deep structures in the area,including the spatial distribution of deep faults,is incomplete.Contrarily,satellite gravity data cover the entire study area and can reveal the spatial distribution of faults.Based on the wavelet multi-scale decomposition method,the Bouguer gravity field in the Ying-Qiong Basin was decomposed and reconstructed to obtain the detailed images of the first-to sixth-order gravitational fields.By incorporating the known geological features,the gravitational field responses of the main faults in the Ying-Qiong Basin were identified in the detailed fields,and the power spectrum analysis yielded the depths of 1.4,8,15,26.5,and 39 km for the average burial depths of the bottom surfaces from the first-to fifth-order detailed fields,respectively.The four main faults in the Yinggehai Basin all have a large active depth range:fault A(No.1)is between 5 and 39 km,fault B is between 26.5 and 39 km,and faults C and D are between 15 and 39 km.However,the depth of active faults in the Qiongdongnan Basin is relatively shallow,mainly between 8 and 26.5 km.展开更多
基金supported by the Fundamental Research Funds for the Central Universities(No.202262012)the National Natural Science Foundation of China(No.42076224)the National Key R&D Program of China(No.2021YFC2801200).
文摘In studies on gas hydrate,bottom-simulating reflectors(BSR)are used to determine the potential hydrate-bearing sedimentary layers.Usually,BSR detection is performed manually by experienced interpreters.Therefore,a method for implementing an auto-matic BSR detection process should be established.In this study,we develop a novel architecture for BSR characterization using the convolutional neural network(CNN)technique.We propose the use of Stokes’transform(ST)to obtain a time-frequency spectrum for the input of CNN.ST fully uses the frequency content of the seismic data,and a part of the 3D seismic data collected from the Blake Ridge is utilized to train the CNN.Synthetic seismic records with variable signal-to-noise ratios(SNR),as well as Blake Ridge seismic data,were used to validate the detection effect of the CNN.Results show that the CNN trained by this method exhibits excellent performance in noise-resistant testing and achieves an accuracy of more than 89% in field seismic data detection.
基金supported by the National Key R&D Program of China (No.2021YFC2801202)the National Natural Science Foundation of China (No.42076224)the Fundamental Research Funds for the Central Universities (No.202262012)。
文摘The chirp sub-bottom profiler,for its high resolution,easy accessibility and cost-effectiveness,has been widely used in acoustic detection.In this paper,the acoustic impedance and grain size compositions were obtained based on the chirp sub-bottom profiler data collected in the Chukchi Plateau area during the 11th Arctic Expedition of China.The time-domain adaptive search matching algorithm was used and validated on our established theoretical model.The misfit between the inversion result and the theoretical model is less than 0.067%.The grain size was calculated according to the empirical relationship between the acoustic impedance and the grain size of the sediment.The average acoustic impedance of sub-seafloor strata is 2.5026×10^(6) kg(s m^(2))^(-1)and the average grain size(θvalue)of the seafloor surface sediment is 7.1498,indicating the predominant occurrence of very fine silt sediment in the study area.Comparison of the inversion results and the laboratory measurements of nearby borehole samples shows that they are in general agreement.
基金supported by the Fundamental Research Funds for the Central Universities(No.202262012)the National Natural Science Foundation of China(No.42076224)the National Key R&D Program of China(No.2021YFC2801200).
文摘Studying the Arctic sea ice contributes to a comprehensive understanding of the climate system in polar regions and offers valuable insights into the interplay between polar climate change and the global climate and environment.One of the key research aspects is the investigation of the temperature,salinity,and density parameters of sea ice to obtain essential insights.During the 11th Chinese National Arctic Research Expedition,acoustic velocity was measured on an ice core at a short-term ice station,however,temperature,salinity,and density were not measured.In the present work,we utilized a genetic algorithm to invert these obtained acoustic velocity data to sea ice temperature,salinity,and density parameters on the basis of the relationship between acoustic velocity and the physical properties of Arctic summer sea ice.We validated the effectiveness of this inversion procedure by comparing its findings with those of other researchers.The results indicate that within the normalized depth range of 0.43-0.94,the ranges for temperature,salinity,and density are -0.48--0.29℃,1.63-3.35,and 793.1-904.1 kg m^(-3),respectively.
基金sup-ported by the National Natural Science Foundation of China(Nos.41530963,91858215 and 41906048)the Fundamental Research Funds for the Central Universities(No.201964015)the Laboratory for Marine Mineral Resources,Qingdao National Laboratory for Marine Science and Technology(No.MMRZZ201801).
文摘The Ying-Qiong Basin is located on the northwestern margin of the South China Sea and at the junction of the South China Block and the Indochina Block.It is characterized by complex geological structures.The existing seismic data in the study area is sparse due to the lack of earthquake activities.Because of the limited source energy and poor coverage of seismic data,the knowledge of deep structures in the area,including the spatial distribution of deep faults,is incomplete.Contrarily,satellite gravity data cover the entire study area and can reveal the spatial distribution of faults.Based on the wavelet multi-scale decomposition method,the Bouguer gravity field in the Ying-Qiong Basin was decomposed and reconstructed to obtain the detailed images of the first-to sixth-order gravitational fields.By incorporating the known geological features,the gravitational field responses of the main faults in the Ying-Qiong Basin were identified in the detailed fields,and the power spectrum analysis yielded the depths of 1.4,8,15,26.5,and 39 km for the average burial depths of the bottom surfaces from the first-to fifth-order detailed fields,respectively.The four main faults in the Yinggehai Basin all have a large active depth range:fault A(No.1)is between 5 and 39 km,fault B is between 26.5 and 39 km,and faults C and D are between 15 and 39 km.However,the depth of active faults in the Qiongdongnan Basin is relatively shallow,mainly between 8 and 26.5 km.
