发表机构
Scripps Institution of Oceanography, University of California, San Diego; Computational Geosciences Group, Lawrence Livermore National Laboratory（斯克里普斯海洋研究所，加利福尼亚大学圣地亚哥分校; 计算地球科学组，劳伦斯利弗莫尔国家实验室）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
提出ES-MDA-A2方法，在统一三步框架下通过追赶机制平衡精度与效率，仅需目标精度和最大同化次数两个输入，在多个实验中实现精确反演。
AI 中文摘要
带有多次数据同化的集合平滑器（ES-MDA）是一种基于集合的逆问题求解算法框架，应用于油藏工程（及其他领域）。ES-MDA逐步将先验集合过渡到后验集合。这一过渡（即“多次数据同化”）的具体实现方式决定了ES-MDA的精度和计算成本。我们表明，许多流行的自适应ES-MDA变体可以在一个简单的三步框架内理解：膨胀提议、分析前修正和分析后修正。这三个步骤相互作用，以解决ES-MDA固有的精度（多次同化，小更新）与效率（少数同化，大更新）之间的权衡。随后，我们提出了一种新的自适应且精度感知的方法ES-MDA-A2，它结合了大更新与一种“追赶”机制，该机制在精度较低时减小更新大小，从而允许额外的同化。ES-MDA-A2仅需两个输入：目标精度和最大数据同化次数。我们在系统数值实验中测试了现有和新的ES-MDA变体，实验包括一个玩具模型、两个带现场数据的电磁反演以及一个地下流动油藏模拟。我们发现，ES-MDA-A2以不同于现有方法的方式解决了精度-效率权衡，在所有实验中均以合理的计算成本实现了精确的反演。
英文摘要
The ensemble smoother with multiple data assimilation (ES-MDA) is an algorithmic framework for the ensemble-based solution of inverse problems in reservoir engineering (and beyond). ES-MDA gradually transitions a prior ensemble to a posterior ensemble. The details of how this transition, or "multiple data assimilation," is implemented defines the accuracy and computational cost of ES-MDA. We show that many popular, adaptive variants of ES-MDA can be understood within a simple three-step framework: inflation proposal, pre-analysis revision, and post-analysis revision. The three steps interact to resolve a trade-off between accuracy (many assimilations with small updates) and efficiency (few assimilations with large updates), inherent to ES-MDA. We then present a new adaptive and accuracy-aware method, ES-MDA-A2, that combines large updates with a "catch-up" mechanism that decreases the update size allowing for additional assimilations if the accuracy is low. ES-MDA-A2 requires only two inputs: a targeted accuracy and a maximum number of data assimilations. We test existing and new ES-MDA variants in systematic numerical experiments with a toy model, two electromagnetic inversions with field data, and a subsurface flow reservoir simulation. We find that ES-MDA-A2 resolves the accuracy-efficiency trade-off differently from existing methods, leading to accurate inversions at a reasonable computational cost in all experiments.
CommentsSubmitted to Computational Geosciences. 26 pages, 7 figures. Includes supplementary material
