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Methodology of uncertainty analysis prediction based on multi-well data fusion

机译:基于多孔数据融合的不确定性分析预测方法

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During drilling activities, geological parameters of a well to be drilled (target well) can be predicted within a limited interval based on multi-well data fusion which aims at ensuring a drilling safety, enhancement of drilling efficiency, reduction of drilling cost as well as acquiring accurate measurements in respect to Oil and Gas protection layers. This work presents a method of uncertainty analysis prediction of pressures using fusion data (formation pressures) from adjacent multi-well. The Eaton method, effective stress theory, and mathematical confidence interval were the various methods used to establish the formation pressure matrix of the target well. The results revealed that due to the complexity and variability of the formations, data interpretation errors of the geological parameters were inevitable. Therefore, the probability density distribution function was established through stratigraphy, probability statistics, and information diffusion. Moreover, the real value of the wells’ formation pressure (target well) was within the distribution interval of multi-well data fusion. Hence, the developed method cannot only effectively reduce the interval of geological parameter of the target well but also enhance the accuracy of parameters prediction.
机译:在钻井活动期间,可以在基于多孔数据融合的有限间隔内预测钻井(目标井)的地质参数,其旨在确保钻井安全性,提高钻井效率,降低钻井成本对石油和天然气保护层采集准确的测量。该工作介绍了使用来自相邻多孔的融合数据(地层压力)的压力的不确定度分析预测方法。伊顿方法,有效应力理论和数学置信区间是用于建立靶阱的形成压力基质的各种方法。结果表明,由于地层的复杂性和可变性,地质参数的数据解释误差是不可避免的。因此,通过地层,概率统计和信息扩散建立了概率密度分布函数。此外,井的形成压力(目标井)的实际值在多孔数据融合的分布间隔内。因此,开发方法不能有效地降低目标井的地质参数的间隔,而且还提高了参数预测的准确性。

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