We present a 3D inversion algorithm that solves for subsurface DC conductivity over a large computational domain, and using large DC voltage datasets. Our algorithm is efficient in computation time and memory, which enables our method to be used for monitoring sites with densely sampled electrode-borehole locations. We achieve efficiency by exploiting matrix-vector multiplication of sparse matrices. Hence, we never explicitly store or approximate the Jacobian of the data. Moreover, our algorithm is independent of the discretization method used in the forward model. In order to visualize apparent resistivities of borehole DC data, we present a physics-based method for obtaining pseudo-locations in 3D space. We present field data results within the scope of the project Guided Injection Remediation Monitoring (GIRem), acquired with an in-house DCIP measuring instrument called Adapt.
3D inversion and visualization of DC data acquired at dense borehole locations
Domenzain, Diego, Liu, Lichao, Kristian Kuhl, Anders, Vest Christiansen, Anders, and Iván Yélamos Vela. "3D inversion and visualization of DC data acquired at dense borehole locations." Paper presented at the SEG/AAPG International Meeting for Applied Geoscience & Energy, Houston, Texas, USA, August 2022. doi: https://doi.org/10.1190/image2022-3742200.1
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