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Record W2596051173 · doi:10.3997/2214-4609.201601094

Three-dimensional Marine CSEM Forward Modelling in the Flemish Pass Basin Using Realistic Unstructured Meshes

2016· article· en· W2596051173 on OpenAlexaffabout
Michael W. Dunham, Seyedmasoud Ansari, Colin G. Farquharson

Bibliographic record

Venue78th EAGE Conference and Exhibition 2016 · 2016
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological Modeling and Analysis
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsFlemishContext (archaeology)Submarine pipelineSensitivity (control systems)GeologyStructural basinPolygon meshConvergence (economics)Scale (ratio)Computer sciencePaleontologyGeotechnical engineeringEngineeringGeographyCartography

Abstract

fetched live from OpenAlex

Summary Recent seismic data acquired in the Flemish Pass Basin offshore Newfoundland and Labrador shows AVO anomalies in three Tithonian age sands up-dip from where a well was drilled, Mizzen L-11, which indicates a potential for hydrocarbons. As an alternative to fluid substitution, this study considers marine CSEM forward modelling to assess the reservoir potential and de-risk the prospect. In the context of this study, it is important to know if a sensitivity to these Tithonian sands even exists, so a 1D forward modelling analysis for sensitivity was performed. The sensitivities derived from 1D modelling are overestimated due to the 1D assumption, but nonetheless give an indication of the preferred frequencies to use for 3D modelling. The 3D models were built by incrementally adding surfaces to gradually increase complexity resulting in three distinct models. In summary, the constructed models were able to reflect the necessary scale and complexity of the Flemish Pass Basin, and the marine CSEM results generated from these three models were of good quality and convergence. The results and models shown here are preliminary, but they serve as important stepping stones to incorporating reservoir information in upcoming future work.

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 categoriesInsufficient payload (model declined to judge)
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 score0.710
Threshold uncertainty score0.999

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.044
GPT teacher head0.228
Teacher spread0.184 · 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.

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

Citations0
Published2016
Admission routes2
Has abstractyes

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