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Record W2009134301 · doi:10.1016/j.egypro.2014.11.368

Quantifying Thermally Driven Fracture Geometry During CO2 Storage

2014· article· en· W2009134301 on OpenAlexaff
Jacob Taylor, Steven L. Bryant

Bibliographic record

VenueEnergy Procedia · 2014
Typearticle
Languageen
FieldEngineering
TopicHydraulic Fracturing and Reservoir Analysis
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsThermoelastic dampingFracture (geology)Stress (linguistics)Hydraulic fracturingMechanicsGeotechnical engineeringGeologyPore water pressurePermeability (electromagnetism)Materials scienceThermalThermodynamicsChemistry

Abstract

fetched live from OpenAlex

The desired lifetime for CO2 injection for sequestration is several decades at a high injection rate (up to 10 bbl/min or 2,400 tons/day per injector). Government regulations and geomechanical design constraints may impose a limit on the injection rate such that, for example, the bottomhole pressure remains less than 90% of the hydraulic fracture pressure. Despite injecting below the critical fracture pressure, fractures can nevertheless initiate and propagate due to a thermoelastic stress reduction caused by cool CO2 encountering hot reservoir rock. Here we develop a numerical model to calculate whether mechanical and thermal equilibrium between the injected CO2 and the reservoir evolves, such that fracture growth ceases. When such a condition exists, the model predicts the corresponding fracture geometry and time to reach that state. The critical pressure for fracture propagation depends on the thermoelastic stress, a function of rock properties and the temperature difference between the injected fluid and the reservoir (ΔT). Fractures will propagate as long as the thermoelastic stress and the fluid pressure at the fracture tip exceed a threshold; we calculate the extent of a fracture such that the tip pressure falls below the thermoelastically modified fracture propagation pressure. Fracture growth is strongly dependent upon the formation permeability, the level of injection pressure above fracture propagation pressure, and ΔT.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.362
Threshold uncertainty score0.834

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 communication0.0000.000
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 head0.006
GPT teacher head0.198
Teacher spread0.192 · 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

Citations10
Published2014
Admission routes1
Has abstractyes

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