Quantitative stratigraphic analysis in a source-to-sink numerical framework

<p>The sedimentary architecture at continental margins reflects the interplay between the rate of change of accommodation creation (<span class="inline-formula"><i>δ</i><i>A</i></span>) and the rate of change of sediment supply (<span class=&quo...

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Main Authors: X. Ding, T. Salles, N. Flament, P. Rey
Format: Article
Language:English
Published: Copernicus Publications 2019-06-01
Series:Geoscientific Model Development
Online Access:https://www.geosci-model-dev.net/12/2571/2019/gmd-12-2571-2019.pdf
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spelling doaj-7d1a985f1d334a52a5b3e0a8f230bf3f2020-11-24T20:58:22ZengCopernicus PublicationsGeoscientific Model Development1991-959X1991-96032019-06-01122571258510.5194/gmd-12-2571-2019Quantitative stratigraphic analysis in a source-to-sink numerical frameworkX. Ding0T. Salles1N. Flament2P. Rey3Basin GENESIS Hub, EarthByte Group, School of Geosciences, The University of Sydney, Sydney, NSW 2006, AustraliaBasin GENESIS Hub, EarthByte Group, School of Geosciences, The University of Sydney, Sydney, NSW 2006, AustraliaSchool of Earth and Environmental Science, University of Wollongong, Wollongong, NSW 2522, AustraliaBasin GENESIS Hub, EarthByte Group, School of Geosciences, The University of Sydney, Sydney, NSW 2006, Australia<p>The sedimentary architecture at continental margins reflects the interplay between the rate of change of accommodation creation (<span class="inline-formula"><i>δ</i><i>A</i></span>) and the rate of change of sediment supply (<span class="inline-formula"><i>δ</i><i>S</i></span>). Stratigraphic interpretation increasingly focuses on understanding the link between deposition patterns and changes in <span class="inline-formula"><i>δ</i><i>A</i>∕<i>δ</i><i>S</i></span>, with an attempt to reconstruct the contributing factors. Here, we use the landscape modelling code pyBadlands to (1) investigate the development of stratigraphic sequences in a source-to-sink context; (2) assess the respective performance of two well-established stratigraphic interpretation techniques: the trajectory analysis method and the accommodation succession method; and (3) propose quantitative stratigraphic interpretations based on those two techniques. In contrast to most stratigraphic forward models (SFMs), pyBadlands provides self-consistent sediment supply to basin margins as it simulates erosion, sediment transport and deposition in a source-to-sink context. We present a generic case of landscape evolution that takes into account periodic sea level variations and passive margin thermal subsidence over 30 million years, under uniform rainfall. A set of post-processing tools are provided to analyse the predicted stratigraphic architecture. We first reconstruct the temporal evolution of the depositional cycles and identify key stratigraphic surfaces based on observations of stratal geometries and facies relationships, which we use for comparison to stratigraphic interpretations. We then apply both the trajectory analysis and the accommodation succession methods to manually map key stratigraphic surfaces and define sequence units on the final model output. Finally, we calculate shoreline and shelf-edge trajectories, the temporal evolution of changes in relative sea level (proxy for <span class="inline-formula"><i>δ</i><i>A</i></span>) and sedimentation rate (proxy for <span class="inline-formula"><i>δ</i><i>S</i></span>) at the shoreline, and automatically produce stratigraphic interpretations. Our results suggest that the analysis of the presented model is more robust with the accommodation succession method than with the trajectory analysis method. Stratigraphic analysis based on manually extracted shoreline and shelf-edge trajectory requires calibrations of time-dependent processes such as thermal subsidence or additional constraints from stratal terminations to obtain reliable interpretations. The 3-D stratigraphic analysis of the presented model reveals small lateral variations of sequence formations. Our work provides an efficient and flexible quantitative sequence stratigraphic framework to evaluate the main drivers (climate, sea level and tectonics) controlling sedimentary architectures and investigate their respective roles in sedimentary basin development.</p>https://www.geosci-model-dev.net/12/2571/2019/gmd-12-2571-2019.pdf
collection DOAJ
language English
format Article
sources DOAJ
author X. Ding
T. Salles
N. Flament
P. Rey
spellingShingle X. Ding
T. Salles
N. Flament
P. Rey
Quantitative stratigraphic analysis in a source-to-sink numerical framework
Geoscientific Model Development
author_facet X. Ding
T. Salles
N. Flament
P. Rey
author_sort X. Ding
title Quantitative stratigraphic analysis in a source-to-sink numerical framework
title_short Quantitative stratigraphic analysis in a source-to-sink numerical framework
title_full Quantitative stratigraphic analysis in a source-to-sink numerical framework
title_fullStr Quantitative stratigraphic analysis in a source-to-sink numerical framework
title_full_unstemmed Quantitative stratigraphic analysis in a source-to-sink numerical framework
title_sort quantitative stratigraphic analysis in a source-to-sink numerical framework
publisher Copernicus Publications
series Geoscientific Model Development
issn 1991-959X
1991-9603
publishDate 2019-06-01
description <p>The sedimentary architecture at continental margins reflects the interplay between the rate of change of accommodation creation (<span class="inline-formula"><i>δ</i><i>A</i></span>) and the rate of change of sediment supply (<span class="inline-formula"><i>δ</i><i>S</i></span>). Stratigraphic interpretation increasingly focuses on understanding the link between deposition patterns and changes in <span class="inline-formula"><i>δ</i><i>A</i>∕<i>δ</i><i>S</i></span>, with an attempt to reconstruct the contributing factors. Here, we use the landscape modelling code pyBadlands to (1) investigate the development of stratigraphic sequences in a source-to-sink context; (2) assess the respective performance of two well-established stratigraphic interpretation techniques: the trajectory analysis method and the accommodation succession method; and (3) propose quantitative stratigraphic interpretations based on those two techniques. In contrast to most stratigraphic forward models (SFMs), pyBadlands provides self-consistent sediment supply to basin margins as it simulates erosion, sediment transport and deposition in a source-to-sink context. We present a generic case of landscape evolution that takes into account periodic sea level variations and passive margin thermal subsidence over 30 million years, under uniform rainfall. A set of post-processing tools are provided to analyse the predicted stratigraphic architecture. We first reconstruct the temporal evolution of the depositional cycles and identify key stratigraphic surfaces based on observations of stratal geometries and facies relationships, which we use for comparison to stratigraphic interpretations. We then apply both the trajectory analysis and the accommodation succession methods to manually map key stratigraphic surfaces and define sequence units on the final model output. Finally, we calculate shoreline and shelf-edge trajectories, the temporal evolution of changes in relative sea level (proxy for <span class="inline-formula"><i>δ</i><i>A</i></span>) and sedimentation rate (proxy for <span class="inline-formula"><i>δ</i><i>S</i></span>) at the shoreline, and automatically produce stratigraphic interpretations. Our results suggest that the analysis of the presented model is more robust with the accommodation succession method than with the trajectory analysis method. Stratigraphic analysis based on manually extracted shoreline and shelf-edge trajectory requires calibrations of time-dependent processes such as thermal subsidence or additional constraints from stratal terminations to obtain reliable interpretations. The 3-D stratigraphic analysis of the presented model reveals small lateral variations of sequence formations. Our work provides an efficient and flexible quantitative sequence stratigraphic framework to evaluate the main drivers (climate, sea level and tectonics) controlling sedimentary architectures and investigate their respective roles in sedimentary basin development.</p>
url https://www.geosci-model-dev.net/12/2571/2019/gmd-12-2571-2019.pdf
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