Transdimensional inverse thermal history modeling for quantitative thermochronology - Archive ouverte HAL Access content directly
Journal Articles Journal of Geophysical Research Year : 2012

Transdimensional inverse thermal history modeling for quantitative thermochronology

(1)
1
Kerry Gallagher

Abstract

A new approach for inverse thermal history modeling is presented. The method uses Bayesian transdimensional Markov Chain Monte Carlo and allows us to specify a wide range of possible thermal history models to be considered as general prior information on time, temperature (and temperature offset for multiple samples in a vertical profile). We can also incorporate more focused geological constraints in terms of more specific priors. The Bayesian approach naturally prefers simpler thermal history models (which provide an adequate fit to the observations), and so reduces the problems associated with over interpretation of inferred thermal histories. The output of the method is a collection or ensemble of thermal histories, which quantifies the range of accepted models in terms a (posterior) probability distribution. Individual models, such as the best data fitting (maximum likelihood) model or the expected model (effectively the weighted mean from the posterior distribution) can be examined. Different data types (e.g., fission track, U-Th/He, 40Ar/39Ar) can be combined, requiring just a data-specific predictive forward model and data fit (likelihood) function. To demonstrate the main features and implementation of the approach, examples are presented using both synthetic and real data.
Fichier principal
Vignette du fichier
PL02908.pdf (1.04 Mo) Télécharger le fichier
Origin : Publisher files allowed on an open archive
Loading...

Dates and versions

insu-00676497 , version 1 (05-09-2012)

Identifiers

Cite

Kerry Gallagher. Transdimensional inverse thermal history modeling for quantitative thermochronology. Journal of Geophysical Research, 2012, 117, pp.B02408. ⟨10.1029/2011JB008825⟩. ⟨insu-00676497⟩
122 View
576 Download

Altmetric

Share

Gmail Facebook Twitter LinkedIn More