论文详情
环渤中凹陷低速泥岩识别与预测
断块油气田
2019年 26卷 第05期
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Title
Identification and prediction of low?鄄speed mudstone in Bozhong Sag and surrounding areas
单位
中海石油(中国)有限公司天津分公司,天津 300459)
Organization
Tianjin Branch of CNOOC Ltd., Tianjin 300459, China)
摘要
在欠压实型超压地层预测中,准确识别低速泥岩的速度以预测孔隙压力,是井身结构设计和钻井液配置的重要参考依据。常规速度分析方法,如剩余速度分析、网格层析等,在精度和效率上难以同时满足快速勘探的需求。经统计发现,环渤中凹陷低速泥岩的速度与厚度、埋深满足线性关系。文中以特征频率和随机介质厚度的关系为基础,通过小波包特征频率自动优选,构建已钻井低速泥岩特征频率和厚度的关系式,进而根据低速泥岩速度、厚度、埋深的统计关系预测设计钻井速度。研究成果在曹妃甸18构造进行了成功应用,钻探结果表明,特征频率重构剖面对于低速泥岩的空间位置刻画准确,预测的低速泥岩速度与测井曲线吻合程度较好,为钻井工程安全提供了可靠保障。
Abstract
In the under?鄄compacting overpressure prediction, accurately identifying the velocity of low?鄄speed mudstone to predict the core pressure is an important reference for well structure design and drilling fluid configuration. Conventional velocity analysis methods, such as residual velocity analysis, grid tomography, etc., are difficult to meet the requirements of rapid exploration in both accuracy and efficiency. According to statistics, the velocity, thickness and depth of the low?鄄speed mudstone in the Bozhong Sag and surrounding areas are in a linear relationship. Based on the relationship between the characteristic frequency and the thickness of the random medium, the relationship between the characteristic frequency and thickness of the well?鄄drilled low?鄄speed mudstone is automatically optimized by characteristic frequency based on the wavelet packet decomposition. The low velocity mudstone velocity of the design well is predicted according to the relationship between the velocity, thickness and depth of the low velocity mudstone. The results were applied to the Caofeidian 18 structure. The results show that the characteristic frequency reconstruction profile is accurate for the spatial location of the low?鄄speed mudstone, and the predicted low?鄄speed mudstone velocity is in good agreement with the logging curve, which effectively guarantees the safety of drilling.
关键词:
低速泥岩;
特征频率;
识别与预测;
反射特征;
渤中凹陷;
Keywords:
low?鄄speed mudstone;
characteristic frequency;
recognition and prediction;
reflection characteristics;
Bozhong Sag;
DOI
10.6056/dkyqt201905009