TY - JOUR
T1 - Utilisation of probabilistic magnetotelluric modelling to constrain magnetic data inversion
T2 - proof-of-concept and field application
AU - Giraud, Jérémie
AU - Seillé, Hoël
AU - Lindsay, Mark D.
AU - Visser, Gerhard
AU - Ogarko, Vitaliy
AU - Jessell, Mark W.
N1 - Funding Information:
Jérémie Giraud, Mark D. Lindsay, and Mark W. Jessell were supported, in part, by Loop – 25 Enabling Stochastic 3D Geological Modelling (LP170100985) and the Mineral Exploration Cooperative Research Centre, whose activities are funded by the Australian Government's Cooperative Research Centre Program. This is MinEx CRC Document 2021/36. Mark D. Lindsay was supported by ARC DECRA DE190100431. Hoël Seillé and Gerhard Visser were supported by the CSIRO Deep Earth Imaging Future Science Platform. We acknowledge the developers of the ModEM code for making it available. Jérémie Giraud has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement no. 101032994.
Funding Information:
This research has been supported by the Department of Industry, Science, Energy and Resources of the Australian Government (grant no. GA22270). Australia Research Council (grant DE190100431), and European Commission (grant no. 101032994).
Publisher Copyright:
© 2023 Jérémie Giraud et al.
PY - 2023/1/18
Y1 - 2023/1/18
N2 - We propose, test and apply a methodology integrating 1D magnetotelluric (MT) and magnetic data inversion, with a focus on the characterisation of the cover-basement interface. It consists of a cooperative inversion workflow relying on standalone inversion codes. Probabilistic information about the presence of rock units is derived from MT and passed on to magnetic inversion through constraints combining structural constraints with petrophysical prior information. First, we perform the 1D probabilistic inversion of MT data for all sites and recover the respective probabilities of observing the cover-basement interface, which we interpolate to the rest of the study area. We then calculate the probabilities of observing the different rock units and partition the model into domains defined by combinations of rock units with non-zero probabilities. Third, we combine these domains with petrophysical information to apply spatially varying, disjoint interval bound constraints (DIBC) to least-squares magnetic data inversion using the alternating direction method of multipliers (or ADMM). We demonstrate the proof-of-concept using a realistic synthetic model reproducing features from the Mansfield area (Victoria, Australia) using a series of uncertainty indicators. We then apply the workflow to field data from the prospective mining region of Cloncurry (Queensland, Australia). Results indicate that our integration methodology efficiently leverages the complementarity between separate MT and magnetic data modelling approaches and can improve our capability to image the cover-basement interface. In the field application case, our findings also suggest that the proposed workflow may be useful to refine existing geological interpretations and to infer lateral variations within the basement.
AB - We propose, test and apply a methodology integrating 1D magnetotelluric (MT) and magnetic data inversion, with a focus on the characterisation of the cover-basement interface. It consists of a cooperative inversion workflow relying on standalone inversion codes. Probabilistic information about the presence of rock units is derived from MT and passed on to magnetic inversion through constraints combining structural constraints with petrophysical prior information. First, we perform the 1D probabilistic inversion of MT data for all sites and recover the respective probabilities of observing the cover-basement interface, which we interpolate to the rest of the study area. We then calculate the probabilities of observing the different rock units and partition the model into domains defined by combinations of rock units with non-zero probabilities. Third, we combine these domains with petrophysical information to apply spatially varying, disjoint interval bound constraints (DIBC) to least-squares magnetic data inversion using the alternating direction method of multipliers (or ADMM). We demonstrate the proof-of-concept using a realistic synthetic model reproducing features from the Mansfield area (Victoria, Australia) using a series of uncertainty indicators. We then apply the workflow to field data from the prospective mining region of Cloncurry (Queensland, Australia). Results indicate that our integration methodology efficiently leverages the complementarity between separate MT and magnetic data modelling approaches and can improve our capability to image the cover-basement interface. In the field application case, our findings also suggest that the proposed workflow may be useful to refine existing geological interpretations and to infer lateral variations within the basement.
UR - http://www.scopus.com/inward/record.url?scp=85147250626&partnerID=8YFLogxK
U2 - 10.5194/se-14-43-2023
DO - 10.5194/se-14-43-2023
M3 - Article
AN - SCOPUS:85147250626
SN - 1869-9510
VL - 14
SP - 43
EP - 68
JO - Solid Earth
JF - Solid Earth
IS - 1
ER -