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塔里木油田吉南地区三叠系储层具有典型的砂泥岩互层特征,砂岩的声波阻抗和泥岩的声波阻抗存在较大范围的重叠,利用声波阻抗很难区分砂岩和泥岩。相对于声波阻抗,弹性阻抗包含有更多的储层岩性和物性信息。在精细层位标定的基础上,利用叠前弹性阻抗反演得到10o、20o、30o的弹性阻抗数据体。利用PNN神经网络建立弹性阻抗与泥质含量之间的非线性统计关系,利用该非线性映射关系,由弹性阻抗预测储层泥质含量,进而对储层的含油气特征进行描述和预测。
The Triassic reservoirs in the Ji’nan area of Tarim Oilfield have typical characteristics of interbedded sand and mudstone. There is a large overlap between the acoustic impedance of sandstone and the acoustic impedance of mudstone. It is hard to distinguish between sandstone and mudstone using acoustic impedance. Relative to the acoustic impedance, the elastic impedance contains more reservoir lithology and physical properties. On the basis of fine horizon calibration, the elastic impedance data body of 10o, 20o and 30o is obtained by prestack elastic impedance inversion. The PNN neural network is used to establish the nonlinear statistical relationship between the elastic impedance and the mud content. By using the nonlinear mapping relationship, the elastic impedance is used to predict the shale content of the reservoir, and then the hydrocarbon-bearing characteristics of the reservoir are described and predicted.