储层横向预测的多元地质统计方法
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摘要
本文应用多元统计方法，利用地震属性并辅以钻井、测井资料对某地区某层段砂岩的厚度和孔隙率进行了横向预测。在多元统计方法中，主要应用了有效数计算、逐步回归分析和Krig插值等方法。有效数可以定量判定哪些地震属性能进行储层预测，从而筛选出地震属性；逐步回归分析是利用已筛选后的地震属性计算储层参数，用它可以提高预测效率和精度，但计算结果仍与建模井点处的真值存在误差；再利用剩余误差的结构性进行Krig插值，可使误差进一步减小。用本方法对陆相薄互层的计算结果表明，其精度可以达到勘探甚至开发阶段储层描述的要求。
The horizontal prediction of thickness and porosity of a sand member in a region was made by applying multivariate statistical method to seismic attribute,drilling and logging data. The multivariate statistical method mainly involves significant figure calculation, stepped regressive analysis and Krig interpolation. Significant figure determines which seismic attribute may be applied to reservoir prediction, and useful seismic attribute can be thus chosen properly. The stepped regressive analysis uses the chosen seismic attribute to estimate reservoir parameter,by which efficiency and accuracy of prediction can be improved obviously. However, the estimation result slightly deviates from real result at the borehole point where model is constructed. The deviation will be reduced further by doing Krig interpolation according to the structural property of residual deviation. Its computation result of a land-facies thin interbed shows that the accuracy meets the requirements of exploration or development phase.
The horizontal prediction of thickness and porosity of a sand member in a region was made by applying multivariate statistical method to seismic attribute,drilling and logging data. The multivariate statistical method mainly involves significant figure calculation, stepped regressive analysis and Krig interpolation. Significant figure determines which seismic attribute may be applied to reservoir prediction, and useful seismic attribute can be thus chosen properly. The stepped regressive analysis uses the chosen seismic attribute to estimate reservoir parameter,by which efficiency and accuracy of prediction can be improved obviously. However, the estimation result slightly deviates from real result at the borehole point where model is constructed. The deviation will be reduced further by doing Krig interpolation according to the structural property of residual deviation. Its computation result of a land-facies thin interbed shows that the accuracy meets the requirements of exploration or development phase.
引文
1 Schultz P S et al.Seismic-guided estimation of log properties.The Lading Edge,1994,13(5):305～315
2 Dumay J et al. Multivariate statistical analyses applied to seismic facies recognition. Geophysics, 1988, 53(9): 1151～1168
3 于崇文.教学地质方法与应用,地质出版社,1982
4 汪荣鑫.数理统计,西安交通大学出版社,1993
2 Dumay J et al. Multivariate statistical analyses applied to seismic facies recognition. Geophysics, 1988, 53(9): 1151～1168
3 于崇文.教学地质方法与应用,地质出版社,1982
4 汪荣鑫.数理统计,西安交通大学出版社,1993
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