摘要
稀井网、大井距条件下进行地下砂体的刻画与表征是油气田开发初期的难点。以地震资料为主导,通过井震结合,利用波形指示反演技术,对鄂尔多斯盆地东缘临兴S区上石盒子组浅水三角洲分流河道砂体的边界及叠置关系进行识别,明确分流河道的叠置关系及其影响因素。研究表明:分流河道叠置类型受控于A/S值和河道能量,在地震剖面上识别出强能独立砂体、高能侧向切割砂体、垂向切叠砂体及高能叠置砂体4类高能叠置关系的砂体和低能叠置砂体、低侧向拼接砂体、低能孤立砂体3类低能叠置关系的砂体。与低能环境下发育的砂体相比,高能环境的砂体规模较大,物性较好,优质储层易发育。利用该方法进行砂体叠置关系识别,能有效地为砂体和气藏的预测提供依据,从而指导井网部署。
The research of characterization of underground sand bodies under the conditions of sparse well pattern and large well spacing is difficult in the initial stage of oil and gas field development. This paper takes seismic data as the leading factor,combines wells and earthquakes,and uses waveform indicator inversion technology to identify the boundary and superimposition relationship of the distributary channel sand bodies in the upper Shihezi Formation in the Linxing S area,and clarifies the superimposition of distributary channels,relationship and its influencing factors. The superimposed type of distributary channel is controlled by A/S and channel energy. Four types of high-energy independent sand bodies,high-energy laterally cut sand bodies,vertical tangentially stacked sand bodies,and high-energy superposed sand bodies are identified on the seismic profile. There are three types of low-energy superimposed sand bodies:Superposed sand bodies and low-energy superposed sand bodies,low lateral spliced sand bodies,and low-energy isolated sand bodies. Compared with sand bodies developed in low-energy environments,sand bodies in high-energy environments have a larger scale and better physical properties,and high-quality reservoirs are easy to develop. Using this method to identify the superposition relationship of sand bodies can effectively provide a basis for sand body and gas reservoir prediction and guide well pattern deployment.
作者
陈诚
齐宇
喻梓靓
王波
CHEN Cheng;QI Yu;YU Zi-liang;WANG Bo(CNOOC Research Institute,Beijing 100028,China)
出处
《天然气地球科学》
EI
CAS
CSCD
北大核心
2021年第5期772-779,共8页
Natural Gas Geoscience
关键词
河道叠置
浅水三角洲
波形指示反演
鄂尔多斯盆地
砂体预测
Superposition relationship of channels
Shallow water delta
SMI
Ordos Basin
Sand body prediction
