【摘要】 目前地震属性分析技术已成为油气勘探和开发工作中必不可少的常规方法,但地震属性的种类不断增多,对储层预测精度的要求也越来越高,这使得地震属性的提取、优化及应用成为了关键。以胜利油田单56区块馆陶组下段砂体储层为目标,首先在岩石物理统计及属性敏感性分析的基础上提取合适的地震属性,然后采用K-L变换对多种地震属性进行降维处理,最后基于人工神经网络的识别技术对目标层的含油饱和度等储层参数进行了预测,预测的效果较好,为该工区的剩余油开发提供了依据。更多还原

【Abstract】 At present,seismic attribute analysis technology has become an indispensable method in oil and gas exploration and development.Because of the growing variety of seismic attributes and the increasingly high demands for reservoir prediction accuracy,the seismic attribute extraction,optimization and application became the key factors.First by taking the sandbody reservoir in Guantao Formation of Wellblock Shan 56 in Shengli Oilfield as an object of study,the suitable attributes were attracted on the basis of the rock physical statistics and attributes sensitivity analysis,and then the K-L transform was used for the dimension reduction of multiple seismic attributes.Finally the target zone oil saturation parameters are predicted based on artificial neural network identification technology.The effect of prediction is good,and it provides a basis for remaining oil development in the operation area.更多还原