【摘要】 延长油田低孔隙度低渗透率储层气水层测井响应特征不明显,采用常规的测井流体性质识别方法不易区分气水层。在灰色识别方法的基础上,引入最大信息熵理论,消除了不确定性对流体性质识别的影响。该方法克服了因测试层不多、样本数较少而在某些识别方法如模糊识别、神经网络等造成分辨率低的问题,为小样本的流体识别提供了新途径。通过对延长地区实际资料的应用表明,该方法的判别效果好,判别精度高,且方法简便,适合于测试层数少的油田新区流体性质识别。更多还原

【Abstract】 In view of lowporosity and lowpermeability reservoir of Yanchang oilfield,log response characteristics of gaswater layer are not obvious.It is difficult to distinguish the characteristics of gaswater layer by conventional recognition methods.Based on the gray recognition method,introduced is the maximum entropy theory to eliminate uncertainty which influences the accuracy of fluid property identification.Some recognition methods such as fuzzy recognition,neural network can not work well when there are few test zones and samples.Gray recognition model based on maximum entropy theory provides a new method for fluid identification to reservoir with few samples.Application in Yanchang oilfield shows that this method works well in gaswater layer identification with high precision,and it is easy to operate.This method is suitable to recognize fluid property about few test zones in newly developed area.更多还原