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Record W2795001256 · doi:10.1007/s12182-018-0220-7

Enhancing recovery and sensitivity studies in an unconventional tight gas condensate reservoir

2018· article· en· W2795001256 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.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenuePetroleum Science · 2018
Typearticle
Languageen
FieldEngineering
TopicHydraulic Fracturing and Reservoir Analysis
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of CanadaMitacsUniversity of Calgary
KeywordsPetroleum engineeringTight gasHydraulic fracturingWell stimulationProduction (economics)Environmental scienceSecondary air injectionEnvironmental engineeringChemistryWaste managementGeologyEngineeringReservoir engineeringPetroleum

Abstract

fetched live from OpenAlex

The recovery factor from tight gas reservoirs is typically less than 15%, even with multistage hydraulic fracturing stimulation. Such low recovery is exacerbated in tight gas condensate reservoirs, where the depletion of gas leaves the valuable condensate behind. In this paper, three enhanced gas recovery (EGR) methods including produced gas injection, CO 2 injection and water injection are investigated to increase the well productivity for a tight gas condensate reservoir in the Montney Formation, Canada. The production performance of the three EGR methods is compared and their economic feasibility is evaluated. Sensitivity analysis of the key factors such as primary production duration, bottom-hole pressures, and fracture conductivity is conducted and their effects on the well production performance are analyzed. Results show that, compared with the simple depletion method, both the cumulative gas and condensate production increase with fluids injected. Produced gas injection leads to both a higher gas and condensate production compared with those of the CO 2 injection, while waterflooding suffers from injection difficulty and the corresponding low sweep efficiency. Meanwhile, the injection cost is lower for the produced gas injection due to the on-site available gas source and minimal transport costs, gaining more economic benefits than the other EGR methods.

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 score0.301
Threshold uncertainty score0.399

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 studies0.0000.001
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 head0.023
GPT teacher head0.289
Teacher spread0.265 · 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