Projects per year
Abstract
We introduce a methodology developed with the objective of exploiting complementary information between 1D magnetotelluric (MT) and gravity inversion. To maintain flexibility, we propose a cooperative workflow leveraging standalone inversions. We first perform 1D probabilistic MT inversion to obtain ensembles of models representative of the measurements. We then use the probabilities of presence of the different rock units derived from these ensembles to divide the studied area into domains characterized by positive probabilities to observe the different rock units. Thirdly, these domains are used to constrain the inversion of gravity data by restricting density values accordingly with the rock units of each domain obtained from MT-derived probabilities. We perform the synthetic proof-of-concept using a realistic model based on the framework of a region in the Mansfield area (Victoria, Australia). Results reveal that our methodology can improve subsurface imaging and can be applied to field data.
Original language | English |
---|---|
Title of host publication | 82nd EAGE Conference and Exhibition 2021 |
Place of Publication | Netherlands |
Publisher | European Association of Geoscientists and Engineers, EAGE |
Pages | 4943-4947 |
Number of pages | 5 |
ISBN (Electronic) | 9781713841449 |
Publication status | Published - 2021 |
Event | 82nd EAGE Conference and Exhibition 2021 - Amsterdam, Virtual, Netherlands Duration: 18 Oct 2021 → 21 Oct 2021 |
Publication series
Name | 82nd EAGE Conference and Exhibition 2021 |
---|---|
Volume | 7 |
Conference
Conference | 82nd EAGE Conference and Exhibition 2021 |
---|---|
Country/Territory | Netherlands |
City | Amsterdam, Virtual |
Period | 18/10/21 → 21/10/21 |
Fingerprint
Dive into the research topics of 'UTILISATION OF STOCHASTIC MT INVERSION RESULTS TO CONSTRAIN GRAVITY INVERSION'. Together they form a unique fingerprint.Projects
- 2 Finished
-
Optimising the use of geophysical data for modelling the Australian crust
Lindsay, M. (Chief Investigator)
ARC Australian Research Council
1/01/19 → 13/06/21
Project: Research
-
Enabling 3D stochastic geological modelling
Jessell, M. (Investigator 01), Lindsay, M. (Investigator 02), Aillères, L. (Investigator 03) & Armit, R. (Investigator 04)
ARC Australian Research Council
1/01/18 → 12/11/21
Project: Research