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Record W2596094530 · doi:10.3997/2214-4609.201600756

The Potential for Predicting Production by Characterizing Fluid Flow and Drainage Patterns Using Microseismicity

2016· article· en· W2596094530 on OpenAlexaff
T. Urbancic, Lindsay Smith-Boughner, A. M. Baig, Eric von Lunen, Jessica Budge, Jason Hendrick

Bibliographic record

Venue78th EAGE Conference and Exhibition 2016 · 2016
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicSeismic Imaging and Inversion Techniques
Canadian institutionsCanadian Apheresis Group
Fundersnot available
KeywordsGeologyHydraulic fracturingInduced seismicityFracture (geology)Flow (mathematics)GeomechanicsGeotechnical engineeringSeismologyPetroleum engineeringPetrologyMechanics

Abstract

fetched live from OpenAlex

Summary We apply a continuum approach to describe the dynamics of seismicity observed during a hydraulic fracture of a multiple horizontal well pad. By exploiting the multi-well observation geometry, we are able to resolve the seismic moment tensors of the high-quality events. Not only does this information constrain the fracture orientations, but it can be used to reconstruct the state of stress/strain in the reservoir. We use the strain to drainage of the reservoir through a strain-flow analysis. Furthermore we examine the spatial and temporal variations in the microseismicity, as well as the energy release characteristics, to image the regions of the reservoir where plastic damage is most confined around the wellbores. To validate both approaches we use PLT data.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.671
Threshold uncertainty score0.466

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 studies0.0010.000
Scholarly communication0.0000.001
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 head0.017
GPT teacher head0.216
Teacher spread0.199 · 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 designBench or experimental
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

Citations0
Published2016
Admission routes1
Has abstractyes

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