Quality over quantity: on workflow and model space exploration of 3D inversion of MT data

Abstract

3D inversions of magnetotelluric data are now almost standard, with computational power now allowing an inversion to be performed in a matter of days (or hours) rather than weeks. However, when compared to 2D inversions, these are still very computationally demanding. As a result, 3D inversions are generally not subjected to as rigorous testing as a 1D or 2D inversion would be, which has implications when these models are used for geological interpretation. In this study, we explore the parameter space for inversion of continent-scale datasets. The generalisations made regarding the effects of each parameter should also be scalable to smaller surveys and will enable MT practitioners to optimise their results. We have performed testing on a subset of the South Australian component of the eventual Australia-wide AusLAMP (Australian Lithospheric Architecture Magnetotelluric Project). The subset was inverted with different parameters, model setup and data subsets. Specifically, results from testing of the model covariance, the resistivity of the prior model, the inclusion of 'known' information into the prior model, the model cell size, the data components inverted for and the damping parameter were all investigated. In our testing of the 3D inversion software, ModEM3DMT, we found that the resistivity of the starting/prior model had significant effect on the final model. Careful selection of initial value can aid in reducing computational time whilst having a negligible effect on the resultant model, whilst large covariance values and model cell sizes enhanced conductive features at depth.

Bifurcated Crustal Channel Flow and Seismogenic Structures of Intraplate Earthquakes in Western Yunnan, China as Revealed by Three‐Dimensional Magnetotelluric Imaging

“…It has been known that when using the nonlinear conjugate gradient algorithm, different starting models may yield different inversion results with the same level of data fitting (Robertson et al, 2020). We further investigated the nonuniqueness of the 3‐D inversion results using different half‐space starting models with uniform resistivity values of 20, 50, 100, and 300 Ωm.…”

Modeling Geoelectric Fields Induced by Geomagnetic Disturbances in 3D Subsurface Geology, an Example From Southeastern Australia

“…The AusLAMP MT array in southeastern Australia consisted of 96 sites in Victoria (Duan & Kyi, 2018) and 400 sites in South Australia (Robertson et al, 2018, 2020) (Figure 7). These AusLAMP data have a 1‐s sampling rate (c.f.…”

Geolectric field measurement, modelling and validation during geomagnetic storms in the UK

“…Approach (c) requires significant effort to create a large-scale 3D model (e.g. Robertson et al, 2020), which may be made from information gathered from MT surveys and other sources, but may have larger uncertainties in regions without ground measurements. Finally, approach (b) is based on incomplete knowledge of lithological and deep crustal conductivity acquired from geological surveys but is feasibly to construct from readily-available information (see Beamish, 2013, and references therein).…”