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Record W1987403651 · doi:10.2118/167193-ms

Optimizing Cyclic CO2 Injection for Low- permeability Oil Reservoirs through Experimental Study

2013· article· en· W1987403651 on OpenAlexaff
Zengxiang Wang, Jinhua Ma, Ruimin Gao, Fanhua Zeng, Chunxia Huang, Paitoon Tontiwachwuthikul, Zhiwu Liang

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsUniversity of Regina
Fundersnot available
KeywordsPetroleum engineeringResidual oilPermeability (electromagnetism)PetroleumWater injection (oil production)PorosityEnhanced oil recoveryOil in placeEnvironmental scienceOil fieldRelative permeabilityOil productionPetroleum reservoirGeologyGeotechnical engineeringChemistry

Abstract

fetched live from OpenAlex

Abstract Cyclic CO2 huff ’n’ puff process in diverse reservoir conditions, such as immiscible, near-miscible, and miscible, has been tested in the laboratory and applied in the fields as a viable secondary or tertiary means to recover the residual oil in water flooded reservoirs or pressure depleted reservoirs. Recently, petroleum operators have shown increasingly interest in taking CO2 huff ’n’ puff process as a preferred option to extract light oil in low-pressure and low-permeability reservoirs. In this paper, experimental results from a series of coreflood tests are presented and operation strategies for cyclic CO2 injection are optimized to maximize the light oil recovery factor in a low- permeability reservoir with low original reservoir pressure and while, minimize CO2 utilization. 6 cyclic coreflood tests, 20 cycles in total, are conducted in a 973 mm-long composite core with an average porosity of 9.6% and an average permeability of 2.3mD. The reservoir pressure is 12.9MPa, far below the measured MMP value of 23MPa, which indicates that the reservoir has no sufficient energy support to do primary production. The impacts of primary operational parameters, such as slug size, injection pressure, chasing gas (N2) and CO2 injection rate on the performance have been investigated. It is concluded that, on the basis of experimental data, 0.1PV seems to be an optimal slug size for the first cycle, with a cycle recovery factor as high as 14.52% when reservoir pressure depleted to 8MPa. The recovery factor is suggested to be sensitive to the maximum pressure and the maximum pressure should be built up to as high as formation permits. In the following cycles, injecting N2 as chasing gas after CO2 injection seems to improve the cycle performance significantly and concurrently reduce the CO2 utilization. The optimal operation should have three cycles and the ultimate recovery factor for these three cycles could reach above 30%. The findings of this paper extend the understanding of cyclic CO2 operation and may be employed as technique reference for cyclic CO2 process operations in low-pressure and low-permeability closed boundary 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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.133
Threshold uncertainty score0.732

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 communication0.0000.001
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 head0.019
GPT teacher head0.279
Teacher spread0.260 · 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 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

Citations29
Published2013
Admission routes1
Has abstractyes

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