TY - JOUR
T1 - Inverse trishear modeling of bedding dip data using Markov chain Monte Carlo methods
AU - Oakley, David O.S.
AU - Fisher, Donald M.
N1 - Funding Information:
This research was supported by funding from Geological Society of America Graduate Research grants , American Association of Petroleum Geologists Grants-in-Aid , Sigma Xi Grants-in-Aid of Research (Grant ID #s G20120315159423 and G20130315164439 ), a Shell Geosciences Energy Research Facilitation Award , and the Penn State Deike grant and Scholten-Williams-Wright Scholarship in Field Geology . We thank Christopher Connors for his helpful review of the manuscript and the editor Joao Hippertt for additional comments. Move software, which was used in the research, was generously provided by Midland Valley under their Academic Software Initiative.
Publisher Copyright:
© 2015 Elsevier Ltd.
PY - 2015/11/1
Y1 - 2015/11/1
N2 - We present a method for fitting trishear models to surface profile data, by restoring bedding dip data and inverting for model parameters using a Markov chain Monte Carlo method. Trishear is a widely-used kinematic model for fault-propagation folds. It lacks an analytic solution, but a variety of data inversion techniques can be used to fit trishear models to data. Where the geometry of an entire folded bed is known, models can be tested by restoring the bed to its pre-folding orientation. When data include bedding attitudes, however, previous approaches have relied on computationally-intensive forward modeling. This paper presents an equation for the rate of change of dip in the trishear zone, which can be used to restore dips directly to their pre-folding values. The resulting error can be used to calculate a probability for each model, which allows solution by Markov chain Monte Carlo methods and inversion of datasets that combine dips and contact locations. These methods are tested using synthetic and real datasets. Results are used to approximate multimodal probability density functions and to estimate uncertainty in model parameters. The relative value of dips and contacts in constraining parameters and the effects of uncertainty in the data are investigated.
AB - We present a method for fitting trishear models to surface profile data, by restoring bedding dip data and inverting for model parameters using a Markov chain Monte Carlo method. Trishear is a widely-used kinematic model for fault-propagation folds. It lacks an analytic solution, but a variety of data inversion techniques can be used to fit trishear models to data. Where the geometry of an entire folded bed is known, models can be tested by restoring the bed to its pre-folding orientation. When data include bedding attitudes, however, previous approaches have relied on computationally-intensive forward modeling. This paper presents an equation for the rate of change of dip in the trishear zone, which can be used to restore dips directly to their pre-folding values. The resulting error can be used to calculate a probability for each model, which allows solution by Markov chain Monte Carlo methods and inversion of datasets that combine dips and contact locations. These methods are tested using synthetic and real datasets. Results are used to approximate multimodal probability density functions and to estimate uncertainty in model parameters. The relative value of dips and contacts in constraining parameters and the effects of uncertainty in the data are investigated.
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U2 - 10.1016/j.jsg.2015.09.005
DO - 10.1016/j.jsg.2015.09.005
M3 - Article
AN - SCOPUS:84943566198
SN - 0191-8141
VL - 80
SP - 157
EP - 172
JO - Journal of Structural Geology
JF - Journal of Structural Geology
ER -