Ensemble-based decision-support workflow for operational geosteering

S. Alyaev, E. Suter, R. Bratvold, E. H. Vefring, N. Jahani
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引用次数: 1

Abstract

Summary We present a systematic geosteering workflow for decision support under uncertainty. The uncertainty is captured in an earth model represented as an ensemble of realizations of the geology. The realizations are updated each time new real-time measurements become available. Thereafter, the up-to-date ensemble of realizations is used as input for decision support optimization. The optimization algorithm evaluates the well path for the complete drilling operation under uncertainty and proposes a decision that maximizes the expected well value, calculated based on selected objectives. The workflow combines the near-bit information produced from look around with the pre-drill knowledge in realtime to suggest a decision that results in statistically optimal steering. We illustrate this by applying the workflow to two cases; the same initial geomodel is updated in accordance with two different synthetic true models. In both scenarios the workflow successfully augments look-around information with pre-drill knowledge to produce good steering decisions under uncertainty.
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基于集成的操作地质导向决策支持工作流
本文提出了一种系统的地质导向工作流程,用于不确定条件下的决策支持。不确定性被捕获在一个地球模型中,该模型表示为地质实现的集合。每次新的实时测量可用时,实现都会更新。然后,最新的实现集成被用作决策支持优化的输入。优化算法在不确定的情况下评估整个钻井作业的井眼轨迹,并根据选定的目标计算出最大的预期井眼价值。该工作流程结合了实时的钻前知识和近钻头信息,提出了一个决策,从而实现统计上的最佳转向。我们通过将工作流应用于两个案例来说明这一点;根据两种不同的合成真模型更新相同的初始地质模型。在这两种情况下,工作流都成功地利用预钻知识增加了周围信息,从而在不确定的情况下产生良好的转向决策。
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