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Simulation of the sedimentary fill of basins

2024· article· en· W4406748921 on OpenAlexaboutno aff
Christopher Kendall, Philip Moore, John Strobel, Robert Cannon, James C. Bezdek, Gautam Biswas

Bibliographic record

VenueBulletin (Kansas Geological Survey) · 2024
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological Studies and Exploration
Canadian institutionsnot available
Fundersnot available
KeywordsGeologySedimentary rockSedimentary basinSedimentary basin analysisBasin modellingEarth scienceGeomorphologyPaleontology

Abstract

fetched live from OpenAlex

There are many forward models that simulate sedimentary processes. The significance and utility of any particular model is a matter of need, computer hardware, and programming resources. Some forward-model simulations are one-dimensional; they are used to define third-order sea-level curves to infer the origin of peritidal cyclic carbonates, model the interdependence of sea level, depth-dependent carbonate accumulation, and the flexural response of the earths crust, and handle diagenesis of carbonate in relation to the eustatic record. Other simulations are two-dimensional and may handle clastics alone; they are used to create synthetic seismograms for sediment packages by modeling subsidence, sea level, sediment supply, and erosion, provide sedimentation rates for clastic fluvial systems using sediment compaction and tectonic movement, and simulate transport, deposition, erosion, and compaction of clastic sediments, emphasizing fluid velocity. Other simulations are two-dimensional carbonate shelf models that respond to sea-level changes and erosion, allowing redeposition of sediment with user-defined production functions; still others are two-dimensional mixed clastic and carbonate basin fill models. Both of these last kinds of models respond to sea-level changes and erosion, allowing redeposition of sediment with user-defined production functions. The program SEDPAK models some of the functions described and tests seismic interpretations based on sea-level curves. These curves are input parameters to the program. The program responds to tectonic movement, eustasy, and sedimentation, modeling sedimentary bypass and erosion. It reproduces clastic systems (including lacustrine, alluvial, and coastal plains, marine shelf, basin slope, and basin floor systems, and carbonate systems) and accounts for progradation, development of hardgrounds, downslope aprons, keep-up, catch-up, back-step, and drowned reef systems, and lagoonal and epeiric sea settings. SEDPAK simulates extensional vertical faulting of the basin, sediment compaction, and isostatic response to sediment loading. Sediment geometries can be viewed immediately on a graphics terminal as they are computed. Based on the observed geometric patterns, the user can repeatedly change the parameter and rerun the program until satisfied with the resultant geometry. This simulation is implemented in the C programming language (Kernighan and Ritchie, 1978), uses the X window system for graphical plotting functions (Scheifler and Gettys, 1986), and is operated on a Unix-based workstation, such as DEC 3 100, Sun, and Apollo. The simulation output is illustrated with examples from the Permian basin of West Texas and New Mexico, the Permian of the Sichuan basin, and the Upper Devonian of western Canada.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0060.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.037
GPT teacher head0.226
Teacher spread0.190 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2024
Admission routes1
Has abstractyes

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