基于最大熵谱估计的沉积旋回划分方法探讨

Division of sedimentary cycle sequences based on maximum entropy spectrum estimation

为了提高测井曲线划分沉积旋回的精度和可靠性,采用最大熵谱估计原理对测井数据进行了预测误差的估计,并在此基础上计算了预测误差趋势曲线。采用对称和非对称理论模型对该方法进行了试验,结果表明:预测误差曲线可以较好地识别沉积旋回界面,预测误差趋势曲线可以识别旋回内部的半旋回。利用该方法对实际测井数据进行了沉积旋回的划分,取得了较好的应用效果。因此,该方法可作为测井沉积旋回划分的辅助分析手段。

In order to improve the division accuracy of sedimentary cycles by log,this paper estimated the prediction error of well log data by using maximum entropy spectrum estimation,and then obtained the prediction error trend curve.Symmetric and asymmetric models were applied to verify this method.The result shows that prediction error curve can be used to identify sedimentary cyclic interface well,and prediction error trend curve can be used to identify half cyclic sequences.This method was applied to divide the cyclic sequences of real well log data,and good results have been obtained.