Numerical stratigraphic forward models as conceptual knowledge repositories and experimental tools: An example using a new enhanced version of CarboCAT

Masiero, Isabella; Kozlowski, Estanislao; Antonatos, Georgios; Xi, Haiwei; Burgess, Peter M.

doi:10.1016/j.cageo.2020.104453

Cited by 8 publications

(10 citation statements)

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“…R is equal to one (maximum carbonate production) in model cells with the optimum number of same‐facies neighbours ( noptimum ). R decreases linearly from one to zero where the number of same‐facies cells is equal to minS or maxS and the resulting carbonate production is zero, from Masiero et al ., (2020). (B) Rationale of topography‐controlled sediment transport, red arrow indicates flow pathway, flows will converge towards shallow water depth area following Snell’s law.…”

Section: Model Formulationmentioning

confidence: 99%

“…'CarboCAT' is a reduced-complexity numerical forward model designed to explore the evolution of carbonate platforms and the strata they produce. The model is documented in detail in Burgess (2013) and Masiero et al (2020). This current study uses a new version of CarboCAT modified to include elements from Burgess et al (2001) and Burgess & Wright (2003), to explore and understand how cross-platform sediment transport can produce self-organized autocyclic carbonate strata.…”

Section: Model Descriptionmentioning

confidence: 99%

“…The model is documented in detail in Burgess (2013) and Masiero et al . (2020). This current study uses a new version of CarboCAT modified to include elements from Burgess et al .…”

Section: Model Formulationmentioning

confidence: 99%

“…Each cell can either contain a single in situ carbonate facies or be empty, and the spatial distribution of facies and empty cells is determined by cellular automata rules, simulating facies dynamics in response to ecological stress (Burgess, 2013). Autotrophic organisms require light for photosynthesis, so modelled carbonate production rate decreases with increasing water depth as an approximation of decreasing light penetration into deep water (Bosscher & Schlager, 1992), and modified by a scaling factor R (Masiero et al ., 2020). The value of R is calculated from the cellular automaton, producing a symmetrical profile showing increased production due to resource optimization and colonization, followed by a linear decrease due to competition of space and nutrients (Fig.…”

Section: Model Formulationmentioning

confidence: 99%

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The stratigraphic significance of self‐organization: Exploring how autogenic processes can generate cyclical carbonate platform strata

Burgess

2022

Sedimentology

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Autogenic spatial self‐organization can produce coherent patterns of ordered cyclical strata through interaction of system components, independent of initial conditions and without external forcing. Previous numerical modelling work that partially explored self‐organized cyclicity in carbonate strata is expanded, refined and tested using a different numerical model formulation of an existing carbonate forward model ‘CarboCAT’. Results show that cross‐platform sediment transport creates a series of self‐organized prograding islands and shorelines that generate upward‐shallowing autocycles, defined by strong statistical evidence for ordered facies successions. A subtidal factory in front of each shoreline supplies sediment that drives shoreline progradation and these subtidal supply‐zone widths are also self‐organized to an optimal characteristic width due to island progradation, such that an accommodation creation/sediment supply ratio of around one maintains self‐organized shoreline progradation. The resulting island progradation rate determines autocycle thickness, which is very different from the accommodation control assumed in most sequence stratigraphic and cyclostratigraphic interpretations. This self‐organization process is comparable to the reaction–diffusion model first suggested by Alan Turing. The simplest possible combination of processes that leads to self‐organization are water‐depth‐dependent production, straight long‐distance cross‐platform transport and uniform subsidence. Additional more complex processes can produce self‐organization, but also more diverse island morphologies, less ordered autocyclic strata and more variable lateral facies continuity. Exploration of the model parameter space shows that self‐organization occurs for only a limited range of accommodation creation/sediment supply ratios. The modelling is calibrated and checked for realism against shoreline progradation rates measured on the Peros Banhos carbonate platform, British Indian Ocean Territory, and a Holocene Abu Dhabi shoreline, suggesting that this is a realistic and perhaps ubiquitous process in geological history. Given the fundamental nature of processes modelled here, and the match with observed processes in modern depositional systems, it seems possible that similar autogenic, self‐organizing processes have operated on many carbonate platforms and are an important component in the stratigraphic record.

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Section: Model Formulationmentioning

confidence: 99%

Section: Model Descriptionmentioning

confidence: 99%

“…The model is documented in detail in Burgess (2013) and Masiero et al . (2020). This current study uses a new version of CarboCAT modified to include elements from Burgess et al .…”

Section: Model Formulationmentioning

confidence: 99%

Section: Model Formulationmentioning

confidence: 99%

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The stratigraphic significance of self‐organization: Exploring how autogenic processes can generate cyclical carbonate platform strata

Burgess

2022

Sedimentology

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“…In sedimentary systems facies architectures and stratal geometries are both the result of an interaction between changes in accommodation, and the relative rates of sediment production to sediment transport (Bosence & Waltham, 1990; Helland‐Hansen & Gjelberg, 1994; Meijer, 2002; Burgess & Steel, 2008; Williams et al ., 2011; Prince & Burgess, 2013; Burgess & Prince, 2015). In carbonate platform systems, carbonate grain associations, and the associated carbonate producing factories (Table 1), have been thought to control stratal architecture and platform geometry (Wilson, 1975; Read, 1985; Wright & Faulkner, 1990; Bosence & Waltham, 1990; Burchette & Wright, 1992; Bosence et al ., 1994; Aurell et al ., 1998; Bowman & Vail, 1999; Pomar, 2001; Schlager, 2005; Pomar & Kendall, 2008; Warrlich et al ., 2008; Williams et al ., 2011; Pomar et al ., 2012; Masiero et al ., 2020; Reijmer, 2021). This is because carbonate factories influence the rate of sediment production, the depth distribution of sediment production (production profiles) (e.g.…”

Section: Introductionmentioning

confidence: 99%

How do carbonate factories influence carbonate platform morphology? Exploring production−transport interactions with numerical forward modelling

2021

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Understanding how carbonate factories influence platform evolution is either based on qualitative conceptual models or quantitative numerical stratigraphic forward models. This study establishes new production depth profiles for four Cenozoic carbonate factories and uses two-dimensional stratigraphic forward models to explore how interactions between sediment production and transport within carbonate systems influence carbonate platform development. Newly established production/depth profiles are used to model photozoan and heterozoan carbonate grain associations, and the associated carbonate producing factories, and results are compared with wellstudied outcrop successions. Sediment production from photozoan and heterozoan grain associations is also equalized, so that the total sediment production is the same but the depth/production profiles retain their distinctly different form. Thus, the effect of the different production profiles can be assessed. Ramps form when sediment diffusional transport rates are high relative to production rates and flat-top steep-margin platforms form when sediment diffusional transport rates are low relative to production rates, whether they are photozoan or heterozoan grain associations. The control exerted by sediment production and transport is expressed as a sediment transport-production ratio where transport ratio is a diffusional sediment transport in two-dimensions and production ratio is the total sediment production rate which is the product of a production profile that varies in depth and laterally. The transport-production ratio is a key control on the evolution and geometry of carbonate platforms. This is the case with different production profiles (both euphotic and oligophotic) and in mixed grain-size and mixed transport-rate systems. Carbonate producing factories significantly influence the rate of sediment production, the depth distribution of sediment production (production profiles), as well as the type of grain sizes produced (influencing resistance to erosion). Thus, different types of carbonate grain associations, and the associated carbonate producing factories, can produce the critical differences between carbonate platform geometries.

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A parameter optimizer based on genetic algorithm for the simulation of carbonate facies

Garcia

Lôndero

2021

Intelligent Systems with Applications

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Numerical stratigraphic forward models as conceptual knowledge repositories and experimental tools: An example using a new enhanced version of CarboCAT

Cited by 8 publications

References 46 publications

The stratigraphic significance of self‐organization: Exploring how autogenic processes can generate cyclical carbonate platform strata

The stratigraphic significance of self‐organization: Exploring how autogenic processes can generate cyclical carbonate platform strata

How do carbonate factories influence carbonate platform morphology? Exploring production−transport interactions with numerical forward modelling

A parameter optimizer based on genetic algorithm for the simulation of carbonate facies

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