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Record W2315202083 · doi:10.22059/ijmge.2012.51322

Coupling Geomechanics and Transport in Naturally Fractured Reservoirs

2012· article· en· W2315202083 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueRWTH Publications (RWTH Aachen) · 2012
Typearticle
Languageen
FieldEngineering
TopicHydraulic Fracturing and Reservoir Analysis
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsThermoelastic dampingPorosityPore water pressureAdvectionGeomechanicsGeologyAnisotropyStress (linguistics)Steam injectionOverpressurePoromechanicsGeotechnical engineeringThermalMechanicsPorous mediumPetroleum engineeringThermodynamics

Abstract

fetched live from OpenAlex

Large amounts of hydrocarbon reserves are trapped in naturally fractured reservoirs which arechallenging in terms of accurate recovery prediction because of their joint fabric complexity andlithological heterogeneity. Canada, for example, has over 400 billion barrels of crude oil in fracturedcarbonates in Alberta, most of this being bitumen of viscosity greater than 106 cP in the GrosmontFormation, which has an average porosity of about 13-15%. Thermal methods are the most commonexploitation approaches in such viscous oil reservoirs which, in the case of steam injection, are associatedwith up to 275-300°C temperature changes, leading to considerable thermoelastic expansion. Thistemperature change, combined with pore pressure changes from injection and production processes, leadsto massive effective stress variations in the reservoir and surrounding rocks. The thermally-induced(thermoelastic) stress changes can easily be an order of magnitude greater than the pore pressure effectsbecause of the high intrinsic stiffness of the low porosity limestone and bounding strata. Study of thesestress-pressure-temperature effects requires a thermo-hydro-mechanical (THM) coupling approach whichconsiders the simultaneous variation of effective stress, pore pressure, and temperature and theirinteractions. For example, thermal expansion can lead to significant joint dilation, increasing themacroscopic, joint-dominated transmissivity by an order of magnitude in front of and normal to thethermal front, while reducing it in the direction tangential to the heating front. This leads to stronginduced anisotropy of transport processes, which in turn affects the spatial distribution of the heatingarising from advective heat transfer.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.236
Threshold uncertainty score0.866

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.011
GPT teacher head0.227
Teacher spread0.216 · 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