摘要
深水水道型储层蕴含了丰富的油气资源,但海上油气勘探往往由于井数量不足导致地下储层预测困难。基于对深水水道的地质认识,构建了不同成因类型的水道概念模型,设计了井点处砂体叠置样式,并通过正演模型分析地震响应特征及地震属性敏感性,结合多种敏感地震属性进行聚类分析及概率神经网络预测。将该方法应用于西非X油藏,预测结果符合率达到87.5%,能够有效预测该油藏的砂体展布特征。预测结果结合地震沉积学综合研究认为,目的层内砂体主要分布于水道中部,两端分布较少,其主要受控于沉积环境和弯曲段流态变化。
Deep-water channel sand bodies are good reservoir for oil and gas accumulation.However,the prediction of such a reservoir is difficult since usually no sufficient wells are available offshore.Following the geological characteristics of deep-water channels,this paper constructed some models for different types of channels and proposed some sand body superposition patterns at the well point using forward model analysis,the seismic response characteristics and sensitive seismic attributes as tools.Cluster analysis and probabilistic neural network(PNN)prediction are carried out based on sensitive seismic attributes.The X reservoir in West Africa is selected as a case for application,and the coincidence rate of the prediction results reached as high as 87.5%,which is efficient enough to predict the sand body distribution pattern for oil and gas exploration.Combined with the integrated study of seismic sedimentology,it is concluded that the sand bodies in the target layer are mainly distributed in the middle of the channel but few in both ends under the control of the sedimentary environment and the change in flow regime in the curved part of channel.
作者
杨希濮
张栋
陈筱
宋来明
黎孟承
刘飞
冯潇飞
YANG Xipu;ZHANG Dong;CHEN Xiao;SONG Laiming;LI Mengcheng;LIU Fei;FENG Xiaofei(China National Offshore Oil International Co.,Ltd.,Beijing 100028,China;School of Geoscience and Technology,Southwest Petroleum University,Chengdu 610500,China;CNOOC Research Institute Co.,Ltd.,Beijing 100028,China)
出处
《海洋地质前沿》
CSCD
北大核心
2021年第10期70-77,共8页
Marine Geology Frontiers
基金
中海石油(中国)有限公司科技项目“西非水道型浊积储层连续性及井网适应性研究”(YXKY-2019-ZY-07)。
关键词
深水水道
地震属性
砂体构型
砂体预测
神经网络
deep-water channel
seismic attributes
sand body architecture
sand body prediction
neural network