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Record W2330749854 · doi:10.1190/segam2014-0222.1

Near surface velocities at Ekofisk from Scholte and refracted wave analysis

2014· article· en· W2330749854 on OpenAlexaff
Roman Kazinnik, Baishali Roy, Ali Tura, L. Vedvik, O. Knoth

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicSeismic Imaging and Inversion Techniques
Canadian institutionsConocoPhillips (Canada)
FundersConocoPhillips
KeywordsGeologySurface waveSurface (topology)SeismologyAcousticsGeophysicsOpticsGeometryPhysics

Abstract

fetched live from OpenAlex

Summary Life of Field Seismic (LoFS) permanent seabed seismic system has been installed and operating at the Ekofisk field since 2008. High quality active source seismic and passive seismic data have been recorded in the field and effectively used for management of the reservoir and overburden. In this paper we demonstrate how horizontally propagating surface waves from active source seismic data allow us to estimate near surface seismic velocities and associated anisotropy. We also show how the observed time dependent velocity changes are empirically associated with strain and stress changes from production induced subsidence. We base our analysis on Scholte waves, which are dispersive surface waves that propagate horizontally under the seabed, and critically refracted compressional (CRC) waves, which are P-waves that propagate horizontally along the seabed starting with the critical offset. The results indicate that the average seismic velocity is related to the expected principal stress magnitude, and seismic anisotropy is related to stress change preferential directions

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.031
Threshold uncertainty score0.061

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.002

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 head0.011
GPT teacher head0.190
Teacher spread0.179 · 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 designObservational
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

Citations10
Published2014
Admission routes1
Has abstractyes

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