A Bayesian Framework for Subsidence Modeling in Sedimentary Basins: A Case Study of the Tonian Akademikerbreen Group of Svalbard, Norway
Document Type
Article
Publication Date
10-15-2023
Abstract
Quantitative subsidence analysis techniques have been widely utilized in ancient extensional basins to evaluate age relationships and unravel regional sedimentation patterns; however, uncertainties associated with various model inputs, such as lithological parameters, water depth, and relative or direct age uncertainties are often neglected. Here, we modify existing decompaction, backstripping and age-depth modeling procedures for post-rift thermally subsided basins through the introduction and propagation of uncertainties using both Monte Carlo and Markov chain Monte Carlo methods in a new program called SubsidenceChron.jl. As a case study for its potential utility in ancient extensional basins, we applied this technique to a globally relevant fossiliferous early Neoproterozoic (Tonian) sedimentary succession in northeastern Svalbard, Norway. Using two new geochronological constraints (Re-Os age from the Akademikerbreen Group and detrital zircon U-Pb maximum depositional age from the Veteranen Group) along with a published Re-Os age from the Polarisbreen Group and previously established age constraints for the onset of the Sturtian snowball Earth glaciation, our model generates a posterior stretching factor (β) of 1.29+0.08/−0.06 and a posterior thermal subsidence initiation time (t0) of 840.40+18.64/−23.61 Ma. These results, along with the calculated age estimations for different stratigraphically important horizons throughout this succession, generally agree with those suggested by previous studies based on global chemostratigraphic correlations. The fewer assumptions made in our case study, as well as the incorporation and propagation of uncertainties on model inputs in SubsidenceChron.jl more broadly, contribute to important and quantifiable uncertainties in our age-depth model results. We suggest this approach will be relevant to future subsidence and age-depth models for Precambrian and Phanerozoic extensional sedimentary basins, in addition to providing a simple test of age models built solely on chemostratigraphic correlations.
Publication Information
Zhang, Tianran; Brenhin Keller, C.; Hoggard, Mark J.; Rooney, Alan D.; Halverson, Galen P.; Bergmann, Kristin D.; Crowley, James L.; and Strauss, Justin V. (2023). "A Bayesian Framework for Subsidence Modeling in Sedimentary Basins: A Case Study of the Tonian Akademikerbreen Group of Svalbard, Norway". Earth and Planetary Science Letters, 620, 118317. https://doi.org/10.1016/j.epsl.2023.118317