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Record W2900044216 · doi:10.2118/192734-ms

Miscibility Effects on Performance of Cyclic CO2 Injection in Hysteretic Tight Oil Reservoirs

2018· article· en· W2900044216 on OpenAlexaff
Yasaman Assef, Pedro Pereira Almao, Peyman Pourafshary

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsRelative permeabilityPermeability (electromagnetism)MiscibilitySaturation (graph theory)HysteresisPetroleum engineeringEnhanced oil recoveryMaterials scienceOil productionWettingMultiphase flowThermodynamicsGeologyChemistryComposite materialPorosityMathematics

Abstract

fetched live from OpenAlex

Abstract Dependency of relative permeability on saturation path during cyclic CO2 injection (CCI) in various operational constraints affects the oil recovery in different ways. A compositional reservoir sector model is built based on the available production data of hydraulically fractured horizontal well in Bakken formation. The work discusses the simulation results of the CCI and investigates the contributions of non-wetting phase's relative permeability hysteresis in oil production below and above the minimum miscibility pressure (MMP). A CMG-GEM model is built based on the Bakken geological settings, well production and live oil PVT data. Relative permeability hysteresis model is incorporated within the simulator using the Killough's method. A cyclic CO2 injection (CCI) EOR scheme is designed and implemented in the numerical model. Effects of structural trapping and hysteresis-induced CO2 /gas retardation on oil recovery are studied during CCI in which a strong flow reversals may occur. The results of simulation revealed that in non-hysteretic model, performing cyclic CO2 injection at immiscible (2000psi) and miscible (5000psi) conditions increases the recovery up to 12.8% and 22.64% respectively. Recovered oil after inclusion of relative permeability hysteresis demonstrate major corresponding effects of gas retardation, CO2 trapping and improved water permeability. The results show mole fraction of CO2 invading the reservoir remains constant at miscible condition and is not affected by hysteresis. Yet in hysteretic model, the oil recovery factor is slightly declined as the relative permeability to water is improved. The immiscible-hysteretic model incorporates high residual gas/ CO2 gas saturation at the end of each production (imbibition) cycle which increases gradually with historical gas saturation. CO2 mole fractions in both gas and oil phases are intensely decreased due to hysteresis following by decline in CO2 injectivity. Residual CO2 trapped during early cycles, limits the CO2 extent in reservoir and makes the recovery less efficient. In addition to residual saturation, oil composition varies due to different rates of vaporization and diffusion by CO2 as a result of its uneven distribution in reservoir. We accurately evaluated the efficiency of cyclic CO2 injection in to Bakken tight oil reservoir by incorporating gas-trapping mechanisms in the model. Shortcomings of uncertainties associated with the previous simplified non-hysteretic reservoir models is reduced. Various operational conditions are tested. Our results draw a distinction amongst underlying mechanisms of recovery induced by hysteresis at different miscibility conditions.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.000

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 head0.006
GPT teacher head0.224
Teacher spread0.218 · 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 source (direct Gemma or distilled Codex), 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
Published2018
Admission routes1
Has abstractyes

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