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Wide-azimuth amplitude-variation-with-offset analysis of anisotropic fractured reservoirs

2014· book-chapter· en· W4247354619 on OpenAlexaff
Andreas Rüger, David R. Gray

Bibliographic record

VenueSociety of Exploration Geophysicists eBooks · 2014
Typebook-chapter
Languageen
FieldEarth and Planetary Sciences
TopicSeismic Imaging and Inversion Techniques
Canadian institutionsNexen (Canada)
Fundersnot available
KeywordsAmplitude versus offsetAzimuthGeologyAmplitudeAnisotropySeismologyOffset (computer science)Reflection (computer programming)GeodesyMineralogyOpticsPhysics

Abstract

fetched live from OpenAlex

Abstract Amplitudes of reflected seismic waves carry high-resolution information about the subsurface velocity and density structure. Observing changes of reflection amplitude variation with off-set (AVO) has been a valuable direct hydrocar-bon-indicator technology for many years. More recently, with the increased availability of wide-azimuth seismic data sets, azimuthal amplitude-variation with-offset analysis (AVO with azimuth, or AVAZ) is evolving into a robust technique to characterize fractured reservoirs. The main physical reason for the method’s success is the high sensitivity of the azimuthally changing reflection coefficient to pertinent anisotropy parameters. Combining these anisotropy parameters with those obtained from other seismic signatures and interpreting them in the context of effective-media theory can provide an improved understanding of fracture systems.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.020
GPT teacher head0.218
Teacher spread0.198 · 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 designNot applicable
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

Citations25
Published2014
Admission routes1
Has abstractyes

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