Abstract
Imaging the Earth's thermochemical structure is crucial for understanding its dynamics and evolution. Moreover, the increased demand for critical minerals and geothermal energy driven by the energy transition has intensified the need for reliable subsurface models. Multi-Observable Thermochemical Tomography (MTT) is a simulation-based, probabilistic inversion platform designed to harness the combined sensitivities of multiple geophysical data sets and thermodynamic modeling. It produces internally consistent estimates of the Earth's interior as probability distributions, offering a powerful means for uncertainty quantification. Here, we present an updated MTT formalism and assess its benefits and limitations to image the thermochemical structure of the lithosphere-asthenosphere system. Individual and combined sensitivities of different observables to parameters of interest (e.g., temperature, composition, crustal architecture) are explored using challenging synthetic models. Our findings demonstrate that a judicious combination of observables can retrieve complex thermochemical structures relevant to greenfields exploration. We then apply MTT to study two cratonic regions of geological and economic significance. In the Superior Craton, we jointly invert receiver functions, gravity anomalies, gravity gradients, geoid anomalies, Rayleigh-wave dispersion curves, absolute elevation and surface heat flow. In the North Australian Craton, we incorporate new data from the AusArray and add teleseismic P- and S-phase travel times to the data sets. The imaged lithospheric architectures provide new insights into the tectonic evolution of these two regions and the physical meaning of geophysical signatures. Additionally, these models offer unique proxies to guide exploration efforts for clean energy and critical minerals and serve as reference models for future high-resolution studies.
| Original language | English |
|---|---|
| Article number | e2025JB031939 |
| Journal | Journal of Geophysical Research: Solid Earth |
| Volume | 131 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - Jan 2026 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
Keywords
- n/a OA procedure
- Markov chain Monte Carlo
- North Australian craton
- regional geology
- superior craton
- geophysical inversion
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