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Record W2040143860 · doi:10.2118/75714-ms

3D Analysis and Prediction of Microseismicity in Fracturing by Coupled Geomechanical Modeling

2002· article· en· W2040143860 on OpenAlexaff
A. Settari, R. B. Sullivan, D. A. Walters, Paul A. Wawrzynek

Bibliographic record

VenueSPE Gas Technology Symposium · 2002
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicSeismic Imaging and Inversion Techniques
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMicroseismGeologyPoromechanicsFracture (geology)SeismologyUnconventional oilGeophysicsGeotechnical engineeringOil shalePorous mediumPorosity

Abstract

fetched live from OpenAlex

Abstract Microseismic monitoring is widely used for mapping fractures but the fracture dimensions are only inferred from it. This paper presents a 3-D analysis to relate the seismic events and fracture geometry. The method is based on continuum geomechanical modeling and shows that the poroelastic as well as thermal stresses are the key to explaining the characteristic pattern of events recorded in the Cotton Valley waterfracs. The method provides a tool for relating the geometry of the fracture to the microseismic image. The analysis shows that events can occur ahead of fluid and also suggests possibility of recorded events far from the fracture.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.954
Threshold uncertainty score0.534

Codex and Gemma teacher scores by category

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 head0.008
GPT teacher head0.187
Teacher spread0.179 · 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 designSimulation or modeling
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
Published2002
Admission routes1
Has abstractyes

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