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Record W4242388343 · doi:10.2523/129594-ms

CO2 Based VAPEX for Heavy Oil Recovery in Naturally Fractured Carbonate Reservoirs

2010· article· en· W4242388343 on OpenAlexaffabout
Ali Gül, Japan Trivedi

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicReservoir Engineering and Simulation Methods
Canadian institutionsUniversity of Alberta
FundersNational Foundation for Cancer Research
KeywordsCitationEnhanced oil recoveryPetroleum engineeringCarbonateFossil fuelEnvironmental scienceEngineeringWaste managementComputer scienceLibrary scienceMaterials science

Abstract

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CO2 Based VAPEX for Heavy Oil Recovery in Naturally Fractured Carbonate Reservoirs Ali Gul; Ali Gul University of Alberta Search for other works by this author on: This Site Google Scholar Japan J Trivedi Japan J Trivedi University of Alberta Search for other works by this author on: This Site Google Scholar Paper presented at the SPE EOR Conference at Oil & Gas West Asia, Muscat, Oman, April 2010. Paper Number: SPE-129594-MS https://doi.org/10.2118/129594-MS Published: April 11 2010 Cite View This Citation Add to Citation Manager Share Icon Share Twitter LinkedIn Get Permissions Search Site Citation Gul, Ali , and Japan J Trivedi. "CO2 Based VAPEX for Heavy Oil Recovery in Naturally Fractured Carbonate Reservoirs." Paper presented at the SPE EOR Conference at Oil & Gas West Asia, Muscat, Oman, April 2010. doi: https://doi.org/10.2118/129594-MS Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex Search Dropdown Menu nav search search input Search input auto suggest search filter All ContentAll ProceedingsSociety of Petroleum Engineers (SPE)SPE EOR Conference at Oil and Gas West Asia Search Advanced Search Abstract With the increasing demand for energy production and environmental concerns, the focus has been shifting towards new green recovery techniques for heavy oil complex reservoirs such as naturally fractured carbonate reservoirs (NFCRs). After the success of VAPEX as an alternate to SAGD for heavy oil recovery, it has been studied for fractured reservoirs in recent years. Moreover, CO2 has been a successful EOR agent in fractured light-medium oil reservoirs and thus can be used as a higher soluble, low cost, and environment friendly alternate to solvent. Our aim is to show that CO2 with VAPEX could be a feasible choice for NFCRs. This work is focused on investigating the applicability and optimization of CO2 based solvent extraction process for heavy oil recovery and greenhouse gas sequestration from NFCRs.A series of numerical experiments were performed to study the role of a) solvent type, b) operating condition, c) oil and gas diffusion, and d) extraction process; in various single/multiple fracture configurations while injecting CO2 - solvent in different ratios. The optimal injection rate and CO2 - solvent concentration ratio were obtained considering maximum oil recovery and CO2 storage. A parametric study was also performed to analyze the influence of various operational and reservoir parameters such as fracture properties, fracture configurations, oil viscosity, solvent type, and injection/production constrains. The results suggested that CO2 or conventional VAPEX alone may not be able to achieve higher recovery in high pressure NFCRs, but CO2 based VAPEX can provide efficient technique to recover heavy oil with emphasis on sequestration. Keywords: carrier gas, injection rate, modeling & simulation, effective molecular diffusion coefficient, permeability, vapex process, enhanced recovery, fractured reservoir, recovery, diffusion coefficient Subjects: Improved and Enhanced Recovery, Unconventional and Complex Reservoirs, Naturally-fractured reservoirs, Carbonate reservoirs Copyright 2010, Society of Petroleum Engineers You can access this article if you purchase or spend a download.

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 score0.083
Threshold uncertainty score0.708

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 head0.011
GPT teacher head0.259
Teacher spread0.248 · 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".

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Citations2
Published2010
Admission routes2
Has abstractyes

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