检索规则说明:AND代表“并且”;OR代表“或者”;NOT代表“不包含”;(注意必须大写,运算符两边需空一格)
检 索 范 例 :范例一: (K=图书馆学 OR K=情报学) AND A=范并思 范例二:J=计算机应用与软件 AND (U=C++ OR U=Basic) NOT M=Visual
作 者:XIONG Lianqiao XIE Xiaojun ZHAO Zhao ZHANG Chunyu WANG Long LIAO Jihua CAI Lulu XU Wei
机构地区:[1]CNOOC Research Institute Co.,Ltd.,Beijing 100028,China
出 处:《Acta Geologica Sinica(English Edition)》2021年第1期248-258,共11页地质学报(英文版)
摘 要:Oil and gas shows are rich in drilling wells in Kaiping sag,however,large oilfield was still not found in this area.For a long time,it is thought that source rocks were developed in the middle-deep lacustrine facies in the Eocene Wenchang Formation,while there is no source rocks that in middle-deep lacustrine facies have been found in well.Thickness of Wenchang Formation is big and reservoirs with good properties could be found in this formation.Distribution and scale of source rock are significant for further direction of petroleum exploration.Distribution characterization of middle-deep lacustrine facies is the base for source rock research.Based on the sedimentary background,fault activity rate,seismic response features,and seismic attributes were analyzed.No limited classification method and multi-attributes neural network deep learning method were used for predicting of source rock distribution in Wenchang Formation.It is found that during the deposition of lower Wenchang Formation,activity rate of main fault controlling the sub sag sedimentation was bigger than 100 m/Ma,which formed development background for middle-deep lacustrine facies.Compared with the seismic response of middle-deep lacustrine source rocks developed in Zhu I depression,those in Kaiping sag are characterized in low frequency and good continuity.Through RGB frequency decomposition,areas with low frequency are main distribution parts for middle-deep lacustrine facies.Dominant frequency,instantaneous frequency,and coherency attributes of seismic could be used in no limited classification method for further identification of middle-deep lacustrine facies.Based on the limitation of geology knowledge,multi-attributes of seismic were analyzed through neural network deep learning method.Distribution of middle-deep lacustrine facies in the fourth member of Wenchang Formation is oriented from west to east and is the largest.Square of the middle-deep lacustrine facies in that member is 154 km^(2)and the volume is 50 km^(3).Achievements could be ba
关 键 词:neural network seismic classification middle-deep lacustrine facies EOCENE Wenchang Formation Kaiping sag
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在链接到云南高校图书馆文献保障联盟下载...
云南高校图书馆联盟文献共享服务平台 版权所有©
您的IP:216.73.216.117