3D multinary inversion of CSEM data based on finite element method with unstructured mesh

Geophysics ◽  
2020 ◽  
pp. 1-60
Author(s):  
Hongzhu Cai ◽  
Zhidan Long ◽  
Wei Lin ◽  
Jianhui Li ◽  
Pinrong Lin ◽  
...  

In controlled-source electromagnetic (CSEM) inversion with conventional regularization, the reconstructed conductivity image is usually blurry and only has limited resolution. To effectively obtain more compact conductivity models, we apply the concept of multinary transformation to CSEM inversion based on the finite element (FE) method with unstructured tetrahedral mesh. Within the framework of multinary inversion, the model conductivities are only allowed to be clustered within the designed values which is usually obtained from other a priori information or the conventional inversion. The synthetic studies show that the multinary inversion produces conductivity images with clearer model boundaries comparing to both the maximum smoothness inversion and the focusing inversion for realistic geoelectric models. We further applied the developed method to a land CSEM survey for mineral exploration. The multinary inversion results are closer to the ground truth comparing to the conventional maximum smoothness inversion and the focusing inversion. The developed method and numerical algorithm provide a new approach and workflow for CSEM inversion when the models need to have clear boundaries and clustering model values. Such geoelectric models could be very useful for geological interpretation in oil and mineral exploration when the a priori information (such as the estimated conductivity values) of the exploration targets is known.

Geophysics ◽  
2013 ◽  
Vol 78 (3) ◽  
pp. D115-D127 ◽  
Author(s):  
Judith Robinson ◽  
Timothy Johnson ◽  
Lee Slater

There is a need to better characterize discrete fractures in contaminated hard rock aquifers to determine the fate of remediation injections away from boreholes and also to evaluate hydraulic fracturing performance. A synthetic cross-borehole electrical resistivity study was conducted assuming a discrete fracture model of an existing contaminated site with known fracture locations. Four boreholes and two discrete fracture zones, assumed to be the dominant electrical and hydraulically conductive pathways, were explicitly modeled within an unstructured tetrahedral mesh. We first evaluated different regularization constraints starting with an uninformed smoothness-constrained inversion, to which a priori information was incrementally added. We found major improvements when (1) smoothness regularization constraints were relaxed (or disconnected) along boreholes and fractures, (2) a homogeneous conductivity was assumed along boreholes, and (3) borehole conductivity constraints that could be determined from a specific conductance log were applied. We also evaluated the effect of including borehole packers on fracture zone model recovery. We found that the fracture zone conductivities with the inclusion of packers were comparable to similar trials excluding the use of packers regardless of electrical potential changes. The misplacement of fracture regularization disconnects (FRDs) can easily be misinterpreted as actual fracture locations. Conductivities within these misplaced disconnects were near the starting model value, and removing smoothing between boreholes and assumed fracture locations helped in identifying incorrectly located FRDs. We found that structural constraints used after careful evaluation of a priori information are critical to improve imaging of fracture electrical conductivities, locations, and orientations.


2000 ◽  
Vol 54 (5) ◽  
pp. 721-730 ◽  
Author(s):  
S. S. Kharintsev ◽  
D. I. Kamalova ◽  
M. Kh. Salakhov

The problem of improving the resolution of composite spectra with statistically self-similar (fractal) noise is considered within the framework of derivative spectrometry. An algorithm of the numerical differentiation of an arbitrary (including fractional) order of spectra is produced by the statistical regularization method taking into account a priori information on statistical properties of the fractal noise. Fractal noise is analyzed in terms of the statistical Hurst method. The efficiency and expedience of this algorithm are exemplified by treating simulated and experimental IR spectra.


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