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Record W2075806518 · doi:10.1190/1.2369894

Velocity measurements of conglomerates and pressure sensitivity analysis of AVA response

2006· article· en· W2075806518 on OpenAlexaff
Tiewei He, Douglas R. Schmitt

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicSeismic Imaging and Inversion Techniques
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsGeologySensitivity (control systems)Pore water pressureSaturation (graph theory)PorosityMineralogySeismologyGeophysicsGeotechnical engineeringMathematicsEngineering

Abstract

fetched live from OpenAlex

During hydrocarbon depletion and enhanced oil recovery, the pore pressure and the fluid saturation levels in the reservoir will change. These changes can be reflected from the time‐lapse seismic data. In order to better understand the AVO changes and time shift of the time‐lapse data, P‐ and S‐wave velocities were measured on a series of low porosity conglomerates under different confining and pore pressures and under both dry and water saturated conditions using standard pulse transmission methods. To better understand the time‐lapse seismic data, we also performed the pressure sensitivity analysis of the P‐P and P‐SV reflectivity on a simple two layer interface using complete Zoeppritz's equations based on the laboratory velocity measurement. The result suggests that both of the P‐P and P‐SV reflections are very sensitive to the effective pressure at low effective pressure.

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)0.001
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 score0.146
Threshold uncertainty score0.979

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.221
Teacher spread0.203 · 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

Citations20
Published2006
Admission routes1
Has abstractyes

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