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Record W1999460485 · doi:10.5539/eer.v3n2p73

A Techno-Economic Analysis of Coupling Enhanced Hydrocarbon Recovery and CO2 Storage in Gas Condensate Reservoirs

2013· article· en· W1999460485 on OpenAlexvenueno aff
Jo Ann Tan, Guy Allinson, Yildiray Cinar

Bibliographic record

VenueEnergy and Environment Research · 2013
Typearticle
Languageen
FieldEngineering
TopicReservoir Engineering and Simulation Methods
Canadian institutionsnot available
FundersAustralian Government
KeywordsEnvironmental sciencePetroleum engineeringFossil fuelCoupling (piping)Production (economics)Production rateHydrocarbonWaste managementChemistryGeologyMaterials scienceProcess engineeringEngineering

Abstract

fetched live from OpenAlex

Coupling enhanced gas (EGR) and condensate (ECR) recoveries with CO2 storage could potentially maintain fossil fuel supply and reduce CO2 emissions to the atmosphere. This paper evaluates the techno-economic potential of simultaneous EGR, ECR and CO2 storage in gas condensate reservoirs. We demonstrate that, for a closed gas condensate reservoir, injecting CO2 later in production life is more profitable than early injection. This is because it delays CO2 breakthrough at the production wells while enhancing gas and condensate production. In contrast, for a bottom-water drive gas condensate reservoir, we find that early CO2 injection minimises water influx from the underlying aquifer. This maximises incremental gas and condensate production and CO2 storage in the reservoir.

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)0.001
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 score0.017
Threshold uncertainty score0.472

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.018
GPT teacher head0.260
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

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

Citations1
Published2013
Admission routes1
Has abstractyes

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