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用马尔可夫─贝叶斯方法预测孔隙度的分布 被引量:3

Markov-Bayes method in its estimation of porosity distribution
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摘要 用地震资料预测储层参数可以为勘探和开发提供有价值的信息,可以提高钻井的成功率和布井的准确性。但地震所提供的信息存在着局限性,一般来说其精度较低。因此,要有效地预测储层参数,必须把地震、测井及地质学家的经验和推测结合起来。马尔可夫-贝叶斯方法就是这样一种方法。此方法不仅可以预测控制井点较少的区域,而且在没有井的区域,通过地质学家对点散图的解释,仍然可以得到区域储层参数的分布。本文用此方法仅做了孔隙度的估算,其它储层参数的估算道理相同。 By predicting reservoir parameters with seismic data we can have valuable information for exploration and development,which is beneficial to increase the success rate of drilling and the accuracy of well distribution. However,seismic data has their limitation;Generally speaking, their accuracy is relatively low. So, in order to predict rescrvoir parameters effectively we must use seismic, logging, geologists'experiences and guesses jointly, which is just the idea of MarkovBayes method. By this method we can predict reservoir parameter distribution in an area with avery limited numbet of well control points,even in an area with no well points at all.In the latter case,we can get help from geologists who interpret the concerned scatter diagrams. In this paper,we only introduce the estimation of porosity using Markov-Bayes method,but we can dcal with the other roservoir parameters in the same way.
出处 《石油物探》 EI CSCD 北大核心 1995年第4期33-41,共9页 Geophysical Prospecting For Petroleum
关键词 马尔可夫假设 地震勘探 孔隙度 预测 储集层 Hard Data, Soft Data, Prior Information, Posterior Information, Markov Hypothesis
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  • 1陆大(纟金).随机过程及其应用[M]清华大学出版社,1986.

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