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Record W1983945725 · doi:10.3997/2214-4609.20147801

Methods of Multicomponent Seismic Data Interpretation

2008· article· en· W1983945725 on OpenAlexaboutno aff
Robert R. Stewart

Bibliographic record

Venue70th EAGE Conference and Exhibition incorporating SPE EUROPEC 2008 · 2008
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicSeismic Imaging and Inversion Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsGeologySeismogramLithologySeismologySeismic to simulationInversion (geology)IsochronSynthetic seismogramStructural basinSeismometerSeismic inversionCarbonateOil shalePetrologyMineralogyGeomorphologyGeochemistryPaleontology

Abstract

fetched live from OpenAlex

Analysing both the compressional (PP) and converted (PS) wavefields from a multicomponent seismic survey can provide more information about subsurface structures, lithologies and their fluid saturants. This paper discusses the techniques of jointly interpreting P-wave data in association with converted-wave seismic data. The methods include log analysis, generation of synthetic seismograms, VSP correlation, along with registering, picking, and calculating ratios of the PP and PS sections. Two cases of oilfields in clastic (sand-shale) environments are discussed - the Cambay Basin, India and the Williston Basin (Ross Lake), Saskatchewan. In addition, a carbonate case is considered from the Cantarell oilfield in Mexico. Vp/Vs values from traveltime thickness (isochron) ratios and amplitude inversion are especially useful for characterizing lithologies.

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)0.004
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.007
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.010
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0060.005
Science and technology studies0.0010.001
Scholarly communication0.0040.002
Open science0.0020.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0070.003

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 head0.078
GPT teacher head0.293
Teacher spread0.215 · 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 designTheoretical or conceptual
Domainnot available
GenreMethods

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

Citations3
Published2008
Admission routes1
Has abstractyes

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Same venue70th EAGE Conference and Exhibition incorporating SPE EUROPEC 2008Same topicSeismic Imaging and Inversion TechniquesFrench-language works237,207