Peer-Reviewed Journal Details
Mandatory Fields
Tunwal, M;Mulchrone, KF;Meere, PA
2020
July
Geosciences
Constraining Basin Parameters Using a Known Subsidence History
Validated
WOS: 2 ()
Optional Fields
CONTINENTAL-MARGIN CAMPOS BASIN EVOLUTION TECTONICS MATURATION EXTENSION EROSION GULF
10
Temperature history is one of the most important factors driving subsidence and the overall tectono-stratigraphic evolution of a sedimentary basin. The McKenzie model has been widely applied for subsidence modelling and stretching factor estimation for sedimentary basins formed in an extensional tectonic environment. Subsidence modelling requires values of physical parameters (e.g., crustal thickness, lithospheric thickness, stretching factor) that may not always be available. With a given subsidence history of a basin estimated using a stratigraphic backstripping method, these parameters can be estimated by quantitatively comparing the known subsidence curve with modelled subsidence curves. In this contribution, a method to compare known and modelled subsidence curves is presented, aiming to constrain valid combinations of the stretching factor, crustal thickness, and lithospheric thickness of a basin. Furthermore, a numerical model is presented that takes into account the effect of sedimentary cover on thermal history and subsidence modelling of a basin. The parameter fitting method presented here is first applied to synthetically generated subsidence curves. Next, a case study using a known subsidence curve from the Campos Basin, offshore Brazil, is considered. The range of stretching factors estimated for the Campos basin from this study is in accordance with previous work, with an additional estimate of corresponding lithospheric thickness. This study provides insight into the dependence of thermal history and subsidence modelling methods on assumptions regarding model input parameters. This methodology also allows for the estimation of valid combinations of physical lithospheric parameters, where the subsidence history is known.
BASEL
2076-3263
10.3390/geosciences10070263
Grant Details