论文标题
具有可扩展的雅各布方法的加速3D电阻率断层扫描
Accelerated 3D Electrical Resistivity Tomography with a Scalable Jacobian-free Approach
论文作者
论文摘要
提出了一种无雅可比的反转方法，以加速电阻层扫描（ERT）以进行浅水含水层表征。 ERT问题通常会实现伴随状态方法，以在反转过程中有效计算Jacobian。但是，伴随状态方法需要侵入性的远期模型代码更改，并且在许多观察结果上可能无法计算可扩展，尤其是当一个人执行具有密集多电极阵列的3D ERT调查时。在这里，主要成分地统计方法（PCGA）是一种快速且可扩展的无雅可比逆逆建模方法，用于解决高维数据密集型ERT问题。 PNNL的ERT仿真软件E4D链接到Python接口PYPCGA而没有侵入性代码更改，并且示例代码在公共存储库中上传。这项研究的结果表明，高分辨率3D地下表征在计算上是可行的，这将在实践中具有巨大的实施潜力。
A Jacobian-free inversion method is presented to accelerate Electrical Resistivity Tomography (ERT) for shallow aquifer characterization. The ERT problem typically implements the adjoint state method to efficiently compute Jacobian during the inversion. However, the adjoint state method needs intrusive forward model code changes and may not be computationally scalable with many observations especially when one performs 3D ERT surveys with dense multi-electrode arrays. Here the Principal Component Geostatistical Approach (PCGA), a fast and scalable Jacobian-free inverse modeling method, is applied to solve a high dimensional data-intensive ERT problem. The PNNL's ERT simulation software E4D was linked to the python interface pyPCGA without intrusive code change and the example code is upload in a public repository. The result in this study shows that high-resolution 3D subsurface characterization is computationally feasible, which would have a great potential for implementations in practice.
