MétaCan
Menu
Back to cohort
Record W1979977390 · doi:10.1021/ie050572y

Effect of Operational Parameters on Carbon Dioxide Storage Capacity in a Heterogeneous Oil Reservoir:  A Case Study

2005· article· en· W1979977390 on OpenAlexaffabout
K. Asghari, Adal Al-Dliwe, Nader Mahinpey

Bibliographic record

VenueIndustrial & Engineering Chemistry Research · 2005
Typearticle
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsUniversity of Regina
Fundersnot available
KeywordsEnvironmental scienceCarbon dioxidePetroleum engineeringEnhanced oil recoveryInjectorCarbonateCarbon capture and storage (timeline)Fossil fuelReservoir engineeringGeologyWaste managementPetroleumMaterials scienceChemistryEngineeringClimate changeOceanography

Abstract

fetched live from OpenAlex

Underground storage of carbon dioxide (CO 2 ) is attracting considerable interest worldwide as a means of avoiding continued release of CO 2 from anthropogenic sources. Here, a heterogeneous oil reservoir in Alberta, Canada, was chosen for evaluating the potential use of this site for storage of a mixture of 90% CO 2 + 10% H 2 S produced from a nearby gas plant. This reservoir produces 34° API light oil from a pinnacle reef, which is a carbonate reservoir with a depth of 4800 ft (1441 m). A fully compositional, three-dimensional (3-D) reservoir simulation model, CMG-GEM, was used to simulate various operational conditions, study the reservoir and fluid characteristics, and investigate the amount of CO 2 stored and oil recovered. The results of this study show that a combination of two vertical injectors and one horizontal producer optimizes the incremental oil recovered and amount of CO 2 stored. The procedure developed in this study, and the findings of this study, can be used as guidelines for designing and implementing any future CO 2 injection and storage project in similar oil reservoirs.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.541
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.070
GPT teacher head0.322
Teacher spread0.252 · 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.

Study designBench or experimental
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

Citations30
Published2005
Admission routes2
Has abstractyes

Explore more

Same venueIndustrial & Engineering Chemistry ResearchSame topicEnhanced Oil Recovery TechniquesFrench-language works237,207