MétaCan
Menu
Back to cohort
Record W2944330201 · doi:10.1190/geo2018-0762.1

Case study: Phase-component amplitude variation with angle

2019· article· en· W2944330201 on OpenAlexaboutno aff
Elita De Abreu, John P. Castagna, Gabriel Gil

Bibliographic record

VenueGeophysics · 2019
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicSeismic Imaging and Inversion Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsAmplitudePhase (matter)Component (thermodynamics)Electrical impedanceGeologyOffset (computer science)Phase angle (astronomy)SeismologyOpticsGeometryPhysicsMathematicsComputer scienceThermodynamics

Abstract

fetched live from OpenAlex

ABSTRACT In detectable and isolated thin layers below seismic resolution, phase decomposition can theoretically be used to discriminate relatively high-impedance thin-layer responses from low-impedance reservoir responses. Phase decomposition can be used to isolate seismic amplitudes with a particular phase response or to decompose the seismic trace into symmetrical and antisymmetrical phase components. These components sum to form the original trace. Assuming zero-phase seismic data and normal American polarity, seismically thin layers that are high impedance relative to overlying and underlying half-spaces are seen on the +90° phase component, whereas a relatively low-impedance thin layer will appear on the −90° phase component. When such phase decomposition is applied to prestack attributes on a 2D line across a thin, 8 m thick, gas-saturated reservoir in the Western Canadian Sedimentary Basin of Alberta, Canada, amplitude-variation-with-angle is magnified on the −90° phase component. The −90° far-offset component allows the lateral extent of the reservoir to be better delineated. This amplification is also seen on the −90° phase component of the gradient attribute. These results are corroborated by seismic modeling that indicates the same phase-component relationships for near- and far-angle stacks as are observed on the real data. Fluid substitution and seismic modeling indicate that, relative to full-phase data, the mixed-phase response observed in this study exhibits variations in fluid effects that are magnified and better observed at far angles on the −90° phase component.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.368
Threshold uncertainty score0.992

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 head0.014
GPT teacher head0.227
Teacher spread0.213 · 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 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

Citations9
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueGeophysicsSame topicSeismic Imaging and Inversion TechniquesFrench-language works237,207