小波变换与最大熵法联合计算薄层厚度  

Thin-layer thickness estimation using wavelet transform and maximum entropy method

作　　者：邵治龙[1] 贺振华[1] 黄德济[1] 

机构地区：[1]成都理工学院

出　　处：《石油地球物理勘探》1998年第2期204-213,共10页Oil Geophysical Prospecting

基　　金：国家自然科学基金

摘　　要：薄层、薄互层厚度的预测是储层横向预测的一个重要环节。常规计算薄层厚度的方法是在时间域或频率域上通过提取单参数来实现的。本文则利用小坡变换，在时一频域进行最大滴分析，并提取多种特征参数；然后利用对薄层厚度敏感的地震特征参数之间的非线性关系，使用神经网络算法，建立了一套计算薄层及薄互层厚度的方法。理论模型的正反演结果表明：该算法对薄层厚度及薄互层累积厚度的预测均有较好的效果，且具有一定的抗噪声能力。我们还利用本文所述方法对TZ地区DL－92－04测线部分剖面的石炭系I油组薄互层砂岩的累积厚度进行了预测，结果令人满意。The thickness prediction of thin layer or thin interbedded strata is an impor-tant part of lateral reservoir prediction. Conventional methods for thin-layer thick-ness estimation are achived by deriving single parameter from time-domain or fre-quency-domain seismic data. This method consists of following essential steps:. Do maximum entropy analysis in time-frequency domain by making wavelettransform.. Extract multiple characteristic parameters.. Compute thickness of thin layer or thin-interbedded strata by using nonlin-ear relations among seismic characteristic parameters which are sensitive to thin-layer thickness,and by taking neural network algorithm.The forward and inversion results of theoretic model show that this method,being of some noise resistant ability,brings good effects in predicting both thin-lay-er thickness and accumulative thickness of thin-interbedded strata- This method wasused to predict the accumulative thickness of thin-interbedded sand strata in Car- boniferous reservoir I of partial DL92－O4 seismic section In IZ area．The predic－ tion result is satisfactory．

关 键 词：小波变换 最大熵 地震特征 薄层 计算 地震勘探 

分 类 号：P631.443[天文地球—地质矿产勘探]