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Record W2111744515 · doi:10.1190/1.3309641

The wedge model revisited: A physical modeling experiment

2010· article· en· W2111744515 on OpenAlexafffund
Joanna K. Cooper, Don C. Lawton, Gary F. Margravé

Bibliographic record

VenueGeophysics · 2010
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicSeismic Imaging and Inversion Techniques
Canadian institutionsBP (Canada)
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsWedge (geometry)AmplitudeOffset (computer science)GeologyGeometryAcousticsSeismologyMechanicsPhysicsOpticsMathematicsComputer science

Abstract

fetched live from OpenAlex

Abstract To assess seismic amplitude effects commonly associated with the classic wedge model in geophysics, we built a scaled physical model of a simple high-velocity wedge immersed in water. In addition to demonstrating the well-known tuning effect related to thin beds, a 2D marine zero-offset seismic survey over the physical model shows a surprising number of high-amplitude dipping events corresponding to elastic multimodes, multiples, and mixed-mode reflections having nonreciprocal raypaths. These events cause additional complexities in the amplitudes of the top-wedge and base-wedge reflections that are not observed in simple acoustic seismic responses of the wedge model. Finite-difference, acoustic, exploding-reflector numerical model data, calculated using the same wedge geometry and velocity model, assisted in the identification of these events. It was found that the amplitudes of mixed-mode multiples in data recorded over high-velocity rocks with a wedge-like geometry might be significant. We also discovered that there is a maximum number of zero-offset pure-mode multiples within the wedge for a given wedge taper angle. Conventional P-wave migration of the physical model data confirmed that the multimode reflections degrade the quality of the migrated image.

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 score0.915
Threshold uncertainty score0.344

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 head0.015
GPT teacher head0.234
Teacher spread0.220 · 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

Citations20
Published2010
Admission routes2
Has abstractyes

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