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Record W4379523638 · doi:10.2118/213157-ms

Estimating Relative Permeabilities Through Experimental and Numerical Approaches for a Steam-Flue Gas Hybrid Process

2023· article· en· W4379523638 on OpenAlexaff
R. Pérez, Hugo García, J. Modaresghazani, S. A. Mehta, R.G. Moore, M.G. Ursenbach, D. Gutiérrez, Belenitza Sequera-Dalton, Hernan Rodríguez, Eduardo Manrique

Bibliographic record

VenueSPE Latin American and Caribbean Petroleum Engineering Conference · 2023
Typearticle
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsAlberta EnergyUniversity of Calgary
Fundersnot available
KeywordsFlue gasRelative permeabilityPetroleum engineeringPermeability (electromagnetism)Steam injectionEnvironmental scienceResidual oilReservoir simulationMechanicsMaterials scienceChemistryGeologyWaste managementGeotechnical engineeringEngineeringPorosity

Abstract

fetched live from OpenAlex

Abstract A relative permeability study was undertaken to evaluate the impact on fluid movement and fluid saturations during a steam-flue gas hybrid process to improve oil recovery and energy efficiency. Two-phase water/oil and gas/liquid relative permeability curves were obtained for modeling the recovery of a Colombian heavy oil reservoir with steam-flue gas hybrid processes at the laboratory and eventually field scale. Apparatus setup, experimental and numerical modeling procedures and results are presented. A customized experimental setup was designed and successfully operated to conduct coreflood tests at reservoir pressure and temperatures up to 280°C. Relative permeabilities were determined using the unsteady state method, where fluids are injected in a specified sequence. Two series of isothermal core-flooding experiments were conducted with the injection of oil, water, steam, and in one sequence, flue gas at different temperatures. One series was performed while increasing temperatures from 40°C to 260°C and another while increasing to 270°C and then decreasing to 40°C. The experiments were history matched to derive water/oil and gas/liquid relative permeability curves. Experimental results, including core temperatures, injection and production pressures and fluids, along with estimated residual core saturations from material balances after each core flood, are presented. The core flood experiments were numerically modeled while honoring core properties, fluid injection volume history, production pressures, and core temperatures. Parameters from relative permeability correlations were obtained after successfully history matching the cumulative production of oil, water, and gas (where applicable) of each core flood sequence and temperature. A single set of relative permeability curves for each system, water/oil, steam/liquid, and flue gas/liquid, could adequately model most of the core flooding experiments performed at different temperatures, especially those conducted while the core temperature was increased. Although hysteresis due to saturation history was not observed, temperature history exhibited a hysteretic effect. Higher residual oil saturations to waterfloods at 240°C and 40°C were obtained in tests performed under decreasing temperatures from 270°C compared to the ones obtained while increasing temperatures from 40°C. The two series of coreflood experiments yielded similar residual oil saturations to steamflood. Water/oil and steam/liquid relative permeability curves were consistent for those tests performed while increasing temperature. This study presents a representative methodology to obtain water/oil relative permeability curves for heavy oil and, more importantly, for steam/liquid and flue gas/liquid systems. These curves are key for the reliable modeling of heavy oil recovery with hybrid steam-flue gas processes, which in turn, allow for energy efficiency estimations and identification of opportunities to reduce the carbon footprint of thermal methods that rely on steam, via partial sequestration of flue gas into the porous media.

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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
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)0.0010.000

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 head0.021
GPT teacher head0.247
Teacher spread0.226 · 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 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

Citations4
Published2023
Admission routes1
Has abstractyes

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