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Computing first-arrival seismic traveltimes on unstructured 3-D tetrahedral grids using the Fast Marching Method

2010· article· en· W2157130303 on OpenAlexaffabout
Peter G. Lelièvre, Colin G. Farquharson, Charles A. Hurich

Bibliographic record

VenueGeophysical Journal International · 2010
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicSeismic Imaging and Inversion Techniques
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsFast marching methodTetrahedronMarching cubesUnstructured gridComputer scienceAlgorithmComputational scienceGeologyGridGeometryMathematicsVisualizationData mining

Abstract

fetched live from OpenAlex

The Fast Marching Method is an efficient numerical algorithm for propagating interfaces such as first-arrival seismic wave fronts travelling through a velocity distribution. Fast Marching solutions have been developed for use on rectilinear grids in 2-D and 3-D. We are interested in unstructured grids as they provide some computational advantages when dealing with complicated shapes that are difficult to represent with rectilinear grids. Fast Marching solutions have also been developed for unstructured 2-D triangular grids but this has yet to be extended to unstructured 3-D tetrahedral grids. In this paper, we extend the Fast Marching Method to unstructured 3-D tetrahedral grids using a derivation that follows the 2-D case. The resulting equations are discussed in intuitive terms and an error analysis is performed. Our method is applied to a simple synthetic example and to a more complicated model based on the Voisey's Bay massive sulphide deposit in Labrador, 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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.930
Threshold uncertainty score0.835

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.012
GPT teacher head0.270
Teacher spread0.258 · 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 teacher head, 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

Citations59
Published2010
Admission routes2
Has abstractyes

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