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Record W2067679998 · doi:10.1190/1.1776731

Instantaneous phase and the detection of lateral wavelet stability

2004· article· en· W2067679998 on OpenAlexaff
Mike Perz, Mauricio D. Sacchi, Ann O'Byrne

Bibliographic record

VenueThe Leading Edge · 2004
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicSeismic Imaging and Inversion Techniques
Canadian institutionsEncana (Canada)University of AlbertaCisco Systems (Canada)
Fundersnot available
KeywordsWaveletSeismic vibratorWaveformGeologyInstantaneous phaseAmplitudeEnvelope (radar)Phase (matter)HingeComputer scienceStability (learning theory)AlgorithmSeismologyAcousticsArtificial intelligenceStructural engineeringEngineeringPhysicsOpticsTelecommunicationsRadar

Abstract

fetched live from OpenAlex

When it comes to the evaluation of stratigraphic plays, the issue of lateral wavelet stability ranks as an important concern. Interpreters accustomed to working complex structural plays may be inclined to relegate this type of concern to “background noise” status, but the reality is that when decisions to drill hinge on extremely subtle changes in waveform character (“when this front-loaded trough begins to show signs of splitting into a doublet, we've got porosity,” etc.), one cannot afford to be confusing geology with lateral changes in the embedded wavelet. In this short article we describe, and provide a mathematical justification for, a very simple technique which can help detect lateral changes in wavelet phase. The method entails first identifying a regionally stable and geologically “isolated” seismic event, then computing the instantaneous phase at the peak of the instantaneous amplitude (i.e., envelope) of the associated seismic waveform. Under certain restrictive conditions described below, the instantaneous phase evaluated at the peak of the instantaneous amplitude can be a good estimate of the wavelet phase.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.961
Threshold uncertainty score0.325

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 head0.018
GPT teacher head0.230
Teacher spread0.212 · 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 designOther design
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

Citations7
Published2004
Admission routes1
Has abstractyes

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