Skip to main content

Research Repository

Advanced Search

Crustal constraint through complete model space screening for diverse geophysical datasets facilitated by emulation

Roberts, A.W.; Hobbs, R.W.; Goldstein, M.; Moorkamp, M.; Jegen, M.; Heincke, B.

Crustal constraint through complete model space screening for diverse geophysical datasets facilitated by emulation Thumbnail


Authors

A.W. Roberts

R.W. Hobbs

M. Goldstein

M. Moorkamp

M. Jegen

B. Heincke



Abstract

Deep crustal constraint is often carried out using deterministic inverse methods, sometimes using seismic refraction, gravity and electromagnetic datasets in a complementary or “joint” scheme. With increasingly powerful parallel computer systems it is now possible to apply joint inversion schemes to derive an optimum model from diverse input data. These methods are highly effective where the uncertainty in the system is small. However, given the complex nature of these schemes it is often difficult to discern the uniqueness of the output model given the noise in the data, and the application of necessary regularization and weighting in the inversion process means that the extent of user prejudice pertaining to the final result may be unclear. We can rigorously address the subject of uncertainty using standard statistical tools but these methods also become less feasible if the prior model space is large or the forward simulations are computationally expensive. We present a simple Monte Carlo scheme to screen model space in a fully joint fashion, in which we replace the forward simulation with a fast and uncertainty-calibrated mathematical function, or emulator. This emulator is used as a proxy to run the very large number of models necessary to fully explore the plausible model space. We develop the method using a simple synthetic dataset then demonstrate its use on a joint data set comprising first-arrival seismic refraction, MT and scalar gravity data over a diapiric salt body. This study demonstrates both the value of a forward Monte Carlo approach (as distinct from a search-based or conventional inverse approach) in incorporating all kinds of uncertainty in the modelling process, exploring the entire model space, and shows the potential value of applying emulator technology throughout geophysics. Though the target here is relatively shallow, the methodology can be readily extended to address the whole crust.

Citation

Roberts, A., Hobbs, R., Goldstein, M., Moorkamp, M., Jegen, M., & Heincke, B. (2012). Crustal constraint through complete model space screening for diverse geophysical datasets facilitated by emulation. Tectonophysics, 572-573, 47-63. https://doi.org/10.1016/j.tecto.2012.03.006

Journal Article Type Article
Acceptance Date Mar 2, 2012
Publication Date Oct 1, 2012
Deposit Date May 10, 2011
Publicly Available Date Feb 23, 2016
Journal Tectonophysics
Print ISSN 0040-1951
Publisher Elsevier
Peer Reviewed Peer Reviewed
Volume 572-573
Pages 47-63
DOI https://doi.org/10.1016/j.tecto.2012.03.006
Keywords Bayesian, Statistical methods, Emulation, Joint inversion, Salt diapir, Crustal imaging.

Files




You might also like



Downloadable Citations