基于集成的地质导向测井解释及不确定性量化
Ensemble-Based Well Log Interpretation and Uncertainty Quantification for Geosteering
摘要：
海上钻井的成本很高，碳氢化合物通常位于复杂的储层中。为了有效地从这些储层中生产并降低成本，实时优化布井（地质导向）至关重要。地质导向通常通过随钻测井解释获得的更新的地层评价来辅助。一个可靠的，计算效率高，强大的工作流程，实时解释测井和捕捉不确定性是必要的，这种应用。一种基于迭代集成的方法，即近似Levenberg Marquardt形式的Ensemble随机极大似然（LM-EnRML）集成在我们的地层评价工作流程中。我们估计模型参数，电阻率和密度，除了边界位置，以及相关的不确定性，通过减少从测井工具的测量值和正演工具模拟器的理论测量值之间的统计失配。对几种测井曲线的综合实例分析表明，该方法能较好地估计模型参数。通过比较CPU时间，我们得出结论，所提出的方法具有至少约10- 125倍的计算时间相比，一个常见的统计方法，如Metropolis-Hastings蒙特卡罗。此外，基于集成的方法可以在多个CPU上并行运行。在一个实际油田的实例上测试该方法也得到了准确的地层评价。因此，所提出的基于集成的方法已被证明是鲁棒的和计算有效的估计岩石物理地层属性，层边界和它们的不确定性，这表明它是适合地质导向。
英文摘要：
The costs for drilling offshore wells are high and hydrocarbons are often located in complex reservoir formations. To effectively produce from such reservoirs and reduce costs, optimized well placement in real-time (geosteering) is crucial. Geosteering is usually assisted by an updated formation evaluation obtained by well-log interpretation while drilling. A reliable, computationally efficient, and robust workflow to interpret well logs and capture uncertainties in real-time is necessary for this application. An iterative ensemble-based method, namely the approximate Levenberg Marquardt form of the Ensemble Randomized Maximum Likelihood (LM-EnRML) is integrated in our formation evaluation workflow. We estimate model parameters, resistivity and density in addition to boundary locations, and related uncertainties by reducing the statistical misfit between the measurements from the well logging tools and the theoretical measurements from the forward tool simulators. The results of analyzing several synthetic cases with several types of logs verified that the proposed method can give good estimate of model parameters. By comparing the CPU time, we conclude that the proposed method has at least about 10--125 times lower computational time compare to a common statistical method, such as Metropolis-Hastings Monte Carlo. In addition, the ensemble-based method can run in parallel on multiple CPUs. Testing the method on a case inspired from a real field also yielded accurate formation evaluation. Thus, the proposed ensemble-based method has been proven robust and computationally efficient to estimate petrophysical formation properties, layer boundaries and their uncertainties, indicating that it is suitable for geosteering.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
