利用贝叶斯—克里金估计技术进行储展参数预测

在此之前，人们常单独利用地震或测井数据研究储层参数的空间分布，而把二者结合起来研究储层参数的空间变化还比较少见。本文把这两种参数有机地结合起来，利用贝叶斯-克里金估计技术进行储层参数预测。该项技术是把线性贝叶斯理论运用于克里金估计，其作法是构想一个模型，把用以进行空间估计的数据分为两类，即观测数据和猜测数据，然后用区域性变量理论研突这两类数据的空间变化特征。对具体的地震勘探和测井而言，把测井数据视为观测数据，把地震数据视为猜测数据，经对王居-曹家务地区实际资料进行砂岩厚度、孔隙率的预测，证明了该方法的正确性。

Reservoir parameter prediction using Bayes-Kriging estimation technique

The distributions of reservoir parameters are ascertained usually by using seismic data or logging data respectively, but they are analysed rarely by adopting both seismic data and logging data simultaneously. Here reservoir parameters are predicted by taking Bayse-Kriging estimation technique with simultaneous use of seismic and logging data. In this technique, linear Bayes theory is applied in Kriging estimation. It is achieved by first constructing a model to class the data needed in estimation into two types (observed data and guess data), then using areal variable theory to analyse the spacial variation of the two type data. As to practical seismic exploration and logging, logging data may be taken as observed data, and seismic data as guess data. The real prediction of thickness and porosity of sandstone in Wangju-Caojiawu area proves this technique feasible.