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Record W2105140348 · doi:10.1190/1.3353730

Beyond the dots in the box: Microseismicity-constrained fracture models for reservoir simulation

2010· article· en· W2105140348 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueThe Leading Edge · 2010
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicSeismic Imaging and Inversion Techniques
Canadian institutionsMicrosemi (Canada)
Fundersnot available
KeywordsMicroseismGeologyInversion (geology)SeismologyHydraulic fracturingShale gasFracture (geology)Shear (geology)Slip (aerodynamics)PetrologyOil shalePetroleum engineeringGeotechnical engineeringTectonicsEngineeringPaleontology

Abstract

fetched live from OpenAlex

Monitoring induced microseismic events usually results in locations for these events and a geometrical interpretation of these “dots in the box.” In this study, we show how additional information obtained from observed microseismic events, namely the source mechanisms, were used to generate a discrete fracture network. Using the wide aperture of a surface star-like array allows inversion for both shear- and nonshear-source mechanisms. Both volumetric and shear-only source mechanism inversion was done on microseismic events from the treatment of a shale gas reservoir in the continental United States. During the same hydraulic fracture stimulation treatment, both dip-slip and reverse faulting sources were active in this reservoir. The source mechanisms revealed fracture orientations more accurately than could be inferred from microseismic event locations alone. The activity of different mechanisms is interpreted as indicating reactivation of existing fractures in the rock, as well as suggesting generation of new fractures.

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.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.415
Threshold uncertainty score0.341

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 science0.0010.000
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 head0.025
GPT teacher head0.267
Teacher spread0.242 · 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