4.6 Article

3-dimensional magnetotelluric inversion including topography using deformed hexahedral edge finite elements and direct solvers parallelized on symmetric multiprocessor computers - Part II: direct data-space inverse solution

Journal

GEOPHYSICAL JOURNAL INTERNATIONAL
Volume 204, Issue 1, Pages 94-110

Publisher

OXFORD UNIV PRESS
DOI: 10.1093/gji/ggv411

Keywords

Numerical solutions; Inverse theory; Electrical properties; Magnetotellurics; Volcanic arc processes; Explosive volcanism

Funding

  1. U.S. Department of Energy [DE-EE0002750]
  2. U.S. National Science Foundation [AES-1443522, ARC-0934721, DMS-1413454]
  3. MIPRS award through Monash University
  4. MGS award through Monash University
  5. Royal Society of New Zealand Marsden Fund [ASL-1301]

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Following the creation described in Part I of a deformable edge finite-element simulator for 3-D magnetotelluric (MT) responses using direct solvers, in Part II we develop an algorithm named HexMT for 3-D regularized inversion of MT data including topography. Direct solvers parallelized on large-RAM, symmetric multiprocessor (SMP) workstations are used also for the Gauss-Newton model update. By exploiting the data-space approach, the computational cost of the model update becomes much less in both time and computer memory than the cost of the forward simulation. In order to regularize using the second norm of the gradient, we factor the matrix related to the regularization term and apply its inverse to the Jacobian, which is done using the MKL PARDISO library. For dense matrix multiplication and factorization related to the model update, we use the PLASMA library which shows very good scalability across processor cores. A synthetic test inversion using a simple hill model shows that including topography can be important; in this case depression of the electric field by the hill can cause false conductors at depth or mask the presence of resistive structure. With a simple model of two buried bricks, a uniform spatial weighting for the norm of model smoothing recovered more accurate locations for the tomographic images compared to weightings which were a function of parameter Jacobians. We implement joint inversion for static distortion matrices tested using the Dublin secret model 2, for which we are able to reduce nRMS to similar to 1.1 while avoiding oscillatory convergence. Finally we test the code on field data by inverting full impedance and tipper MT responses collected around Mount St Helens in the Cascade volcanic chain. Among several prominent structures, the north-south trending, eruption-controlling shear zone is clearly imaged in the inversion.

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