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Record W2091012408 · doi:10.1190/1.1468595

A multioffset vertical seismic profiling experiment for anisotropy analysis and depth imaging

2002· article· en· W2091012408 on OpenAlexafffundabout
M. Grech, Don C. Lawton, Samuel H. Gray

Bibliographic record

VenueGeophysics · 2002
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicSeismic Imaging and Inversion Techniques
Canadian institutionsUniversity of Calgary
FundersCore Research for Evolutional Science and TechnologyNatural Sciences and Engineering Research Council of CanadaUniversity of Calgary
KeywordsAnisotropyGeologyIsotropyVertical seismic profileTransverse isotropySeismologySeismic anisotropyPrestackInversion (geology)MineralogyGeophysicsOpticsPhysics

Abstract

fetched live from OpenAlex

Abstract A multioffset vertical seismic profile (VSP) was carried out in the Rocky Mountain foothills of southern Alberta, Canada. The purpose of this experiment was to investigate whether the dipping shale strata exhibit P-wave velocity anisotropy and, if so, to calculate the Thomsen anisotropy parameters for use in anisotropic depth migration. Traveltime inversion of first-arrival data from the multioffset VSP revealed that the dipping Mesozoic clastics in the area exhibit seismic velocity anisotropy of about 10%. The anisotropy parameters derived from this experiment were then used in anisotropic prestack depth migration of data from a surface seismic line close to the VSP well. Comparison of the anisotropic migration with the corresponding isotropic prestack depth migration showed that the target was imaged incorrectly in the isotropic case; a lateral shift of 180 m in the updip direction of the overlying beds was observed. The image obtained with an anisotropic velocity model was also better focused than that obtained assuming isotropic velocities.

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 score0.972
Threshold uncertainty score0.382

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)0.0000.000

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 head0.017
GPT teacher head0.232
Teacher spread0.214 · 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

Citations8
Published2002
Admission routes3
Has abstractyes

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