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Record W2857247081 · doi:10.3997/2214-4609.201800771

Reservoir Characterization of a Shale-Gas Play in the Duvernay Formation using Seismic, Microseismic, and Well Log Data

2018· article· en· W2857247081 on OpenAlex
Germán Rodríguez‐Pradilla, David W. Eaton

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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueProceedings · 2018
Typearticle
Languageen
FieldEngineering
TopicHydraulic Fracturing and Reservoir Analysis
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMicroseismHydraulic fracturingGeologyOil shalePetroleum engineeringUnconventional oilDrillingShale gasReservoir modelingDirectional drillingSource rockFossil fuelPetroleum reservoirSeismologyPetrologyStructural basinGeomorphologyPaleontologyEngineering

Abstract

fetched live from OpenAlex

Summary The Duvernay Formation, located in central Alberta, Canada, is mainly an organic-rich shale highly attractive as a source rock for conventional oil and gas reservoirs, and more recently also very attractive for exploitation as unconventional shale plays. The development of these types of plays requires the implementation of unconventional techniques as horizontal drilling and hydraulic fracturing to increase the permeability of the reservoir. To assess the performance of a hydraulic fracturing stimulation, microseismic monitoring can be implemented to track the fractures propagation and estimate the effective stimulated reservoir volume. The obtained results of the near-surface microseismic monitoring in a shale-gas play in the Duvernay formation, together with the available 3D seismic and well log data, are assessed to extract key characteristics of the reservoir and to forecast the hydrocarbon productivity after the hydraulic fracturing stimulation.

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)0.000
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 score0.926
Threshold uncertainty score0.357

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 studies0.0000.000
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 head0.021
GPT teacher head0.240
Teacher spread0.218 · 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