Three-Dimensional Numerical Modeling of Eustatic Control On Continental-Margin Sand Distribution

Harris, Ashley D.; Covault, Jacob A.; Madof, Andrew S.; Sun, Tao; Sylvester, Zoltán; Granjeon, Didier

doi:10.2110/jsr.2016.85

Cited by 42 publications

(54 citation statements)

References 52 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Determining realistic diffusion coefficients from ancient or even modern sediment transport system remains difficult. Continental and marine diffusion coefficients used here (Table 2) are within the range of values in other applications of diffusion based modelling (Csato, Catuneanu, & Granjeon, 2014;Gvirtzman, Csato, & Granjeon, 2014;Harris et al, 2016;Kenyon & Turcotte, 1985). Perhaps more importantly, the modelled results suggest the selected diffusion coefficients are reasonable because resulting stratal geometries form over a realistic time span, and topset gradient of modelled deltaic clinoform ranges from 0.003-0.06°, close to both present-day and ancient examples (Patruno, Hampson, & Jackson, 2015).…”

Section: Sediment Transport Diffusion Coefficientsupporting

confidence: 68%

Can sediment supply variations create sequences? Insights from stratigraphic forward modelling

et al. 2018

Self Cite

View full text Add to dashboard Cite

Classic sequence stratigraphy suggests depositional sequences can form due to changes in accommodation and due to changes in sediment supply. Accommodation‐dominated sequences are problematic to define rigorously, but are commonly interpreted from outcrop and subsurface data. In contrast, supply‐dominated sequences are much less commonly identified. We employ numerical stratigraphic forward modelling to compare stratal geometries forced by cyclic changes in relative sea level with stratal geometries forced by sediment discharge and water discharge changes. Our quantitative results suggest that both relative sea‐level oscillations and variations in sediment/water discharge ratio are able to form sequence‐bounding unconformities independently, confirming previous qualitative sequences definitions. In some of the experiments, the two types of sequence share several characteristics, such as an absence of coastal‐plain topset deposits and stratal offlap, something typically interpreted as the result of falling relative sea level. However, the stratal geometries differ when variations in amplitude and frequency of relative sea‐level change, sediment/water discharge ratio, transport diffusion coefficient and initial bathymetry are applied. We propose that the supply‐dominated sequences could be recognised in outcrop or in the subsurface if the observations of stratal offlap and the absence of coastal‐plain topset can be made without any strong evidence of relative sea‐level fall (e.g. descending shoreline trajectory). These quantitative results suggest that both supply‐dominated and accommodation‐dominated sequences are likely to occur in the ancient record, as a consequence of multiple, possibly complex, controls.

show abstract

Section: Sediment Transport Diffusion Coefficientsupporting

confidence: 68%

Can sediment supply variations create sequences? Insights from stratigraphic forward modelling

et al. 2018

Self Cite

View full text Add to dashboard Cite

show abstract

“…DionisosFlow software is a 4-D process-based deterministic multi-lithology forward stratigraphic model that simulates basin filling (Granjeon, 1997(Granjeon, , 2014Granjeon and Joseph, 1999). A range of sedimentary processes are modeled including diffusive sediment transport, delta autoretreat, incision, largescale avulsion, and slope failure in response to tectonic, climate, and sea-level fluctuations during millennia and longer time scales (e.g., Pinheiro-Moreira, 2000; Rabineau et al, 2005;Alzaga-Ruiz et al, 2009;Gvirtzman et al, 2014;Harris et al, 2016;Hawie et al, 2017). Detailed fluid dynamics are not considered in this model; the goal is to simulate the large-scale (10 2 -10 3 m cell size) and long-term (10 3 -10 5 yr time steps) evolution of basin fill.…”

Section: Forward Stratigraphic Modelingmentioning

confidence: 99%

“…That said, the diffusion equation (Equation 1) does not account for stratification of flow; both the velocity and concentration maxima of turbidity currents occur near the base of the flow (Sequeiros et al, 2010;Eggenhuisen and McCaffrey, 2012). Choosing K w values for different grain sizes is a challenge because published values span orders of magnitude and they depend on many factors in addition to grain size, such as lithology, roundness, and discharge (Rivenaes, 1992;Falivene et al, 2014;Gvirtzman et al, 2014;Harris et al, 2016). Following Hawie et al (2018), we used a range of K w from 10 to 100 km 2 /kyr for coarse sand to silt/clay.…”

Section: Forward Stratigraphic Modelingmentioning

confidence: 99%

“…They used much larger K w values in order to transport sediment across a much larger area (1,200 × 1,200 km); their individual cell sizes are nearly the size of our entire model domain (Deville et al, 2015). Ideally, we would tune diffusion coefficients to produce geometries and grain-size distribution similar to deposits of a field case (Harris et al, 2016). We created a reference-case model during an initial phase of model calibration.…”

Section: Forward Stratigraphic Modelingmentioning

confidence: 99%

See 1 more Smart Citation

Grain-Size and Discharge Controls on Submarine-Fan Depositional Patterns From Forward Stratigraphic Models

2019

Self Cite

View full text Add to dashboard Cite

Submarine fans are important components of continental margins; they contain a stratigraphic record of environmental changes and host large accumulations of oil and gas. The grain size and volume of sediment supply to fans is thought to control the heterogeneity of deep-water deposits; predicting spatial variability of sandy and muddy deposits is an important applied challenge in the characterization of fans. Here, we use DionisosFlow stratigraphic-forward models to evaluate the sensitivity of submarine-fan deposition to a range of grain sizes, with corresponding diffusion coefficients ranging from 10 to 100 km 2 /kyr for coarse sand to silt/clay, and discharges. In general, finer grains are transported farther in our models because they have larger diffusion coefficients. Coarser grains typical of a sand-rich fan tend to pile up and compensationally stack at the mouth of a proximal feeder channel. Increasing sediment-gravity-flow discharge resulted in a thicker depositional system; however, relatively coarse sediment piled up at the mouth of the feeder channel, which created a slope that promoted basinward sediment transport. Our modeling results can be applied to predict the overall geometry, stacking, and grain-size distribution of submarine fans. Improved understanding of grain-size and discharge controls also informs interpretation of the stratigraphic record of submarine fans. For example, outcrop observations of heterogeneity and compensational stacking of depocenters can be related to changing boundary conditions, namely changes in the caliber and overall supply of sediment delivery to deep-water basin margins.

show abstract

“…Over the past few decades, SFM has been widely used to investigate the interplay between major sequence-controlling factors (e.g. eustasy, tectonics, flexural isostasy, sediment supply, sediment compaction, basin physiography) and their influences in the formation of stratigraphic sequences (Reynolds et al, 1991;Posamentier and Allen, 1993;Steckler et al, 1993;Carvajal and Steel, 2009;Burgess et al, 2012;Granjeon et al, 2014;Csato et al, 2014;Sylvester et al, 2015;Harris et al, 2015Harris et al, , 2016. SFM can therefore provide insights into the quantification of links between sequence formation and the changing δA/δS ratio.…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2019

View full text Add to dashboard Cite

Abstract. The sedimentary architecture at continental margins reflects the interplay between the rate of change of accommodation creation (δA) and the rate of change of sediment supply (δS). Stratigraphic interpretation increasingly focuses on understanding the link between deposition patterns and changes in δA∕δS, 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 δA) and sedimentation rate (proxy for δS) 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.

show abstract

Three-Dimensional Numerical Modeling of Eustatic Control On Continental-Margin Sand Distribution

Cited by 42 publications

References 52 publications

Can sediment supply variations create sequences? Insights from stratigraphic forward modelling

Can sediment supply variations create sequences? Insights from stratigraphic forward modelling

Grain-Size and Discharge Controls on Submarine-Fan Depositional Patterns From Forward Stratigraphic Models

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

Contact Info

Product

Resources

About