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大庆油田由于其特殊的地质因素影响,进入高含水期以后,储层平面、层间、层内非均质性严重,剩余油在空间上分布状况较为复杂,薄差储层发育。在调整开发阶段,开采对象从主力厚油层转向薄差层。常规测井解释薄差层水淹级别误差较大。因此,建立一种针对大庆油田薄差层水淹级别识别技术:首先,计算测井曲线的分形维数,然后通过研究区内关键井研究,选取对薄差层水淹特征敏感的测井曲线及其分形维数作为判别分量,建立标准样本集,最后利用Fisher判别方法实现薄差层水淹级别的自动划分。将该方法应用于大庆油田两口井实际资料处理,并将处理结果与岩心分析结果对比,其符合率达到73.5%。该方法对油田开发中后期薄差层水淹解释是有效的,其精度达到油田现场要求,有助于对薄差层井下状况准确勘测和研究,提高薄差层产量。
Due to its special geologic factors, Daqing Oilfield entered the high water cut period, resulting in serious heterogeneity in the plane, interlayer and intra-layer of reservoirs. The distribution of remaining oil in space is more complicated with the development of thin-margin reservoirs. In the period of adjustment and development, the target of mining turned from the main thick oil layer to the thin difference layer. Conventional well logging explained that the difference of water level of thin difference layer was larger. Therefore, we establish a water level discrimination technique for thin difference layer in Daqing Oilfield. Firstly, we calculate the fractal dimension of well logging curve. Then, by studying the key wells in the area, we select well logging curves that are sensitive to water flooding characteristics And its fractal dimension as the discriminant component, a standard sample set is established. Finally, Fisher’s discriminant method is used to automatically classify the flooding level of the thin layer. The method was applied to the actual data processing of two wells in Daqing Oilfield, and the result was compared with the result of core analysis. The coincidence rate reached 73.5%. The method is effective for the interpretation of water thinning of thin difference layer in the middle and late stage of oilfield development. The accuracy of the method meets the field requirements of the oilfield, which is helpful for the accurate survey and study of the downhole condition of the thin difference layer and the increase of thin difference layer yield.