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Record W4235430375 · doi:10.2118/140662-pa

Investigation of Cyclic Solvent Injection Process for Heavy Oil Recovery

2010· article· en· W4235430375 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of Canadian Petroleum Technology · 2010
Typearticle
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsAlberta Innovates
FundersAlberta Innovates - Technology Futures
KeywordsSolventDissolutionPetroleum engineeringOil in placeProcess (computing)Materials scienceWater injection (oil production)Oil productionEnvironmental sciencePulp and paper industryChemical engineeringChemistryPetroleumGeologyOrganic chemistryComputer scienceEngineering

Abstract

fetched live from OpenAlex

Summary This paper summarizes numerical and experimental simulation results of a cyclic solvent injection process study, which was part of a continuing investigation into the use of solvents as a follow-up process in Cold Lake and Lloydminster reservoirs that have been pressure-depleted by cold heavy oil production with sand (CHOPS). Typically only 5% - 10% of the original oil in place (OOIP) is recovered during cold production; therefore, an effective follow-up process is required. The cyclic solvent injection (CSI) experiment consisted of primary production followed by six solvent (28% C3H8 - 72% CO2) injection cycles. Oil recovery after primary production and six solvent cycles was 50%, which indicates the potential viability of the CSI process. Concurrently with the laboratory physical simulation, a numerical simulation model was developed to represent the physical behaviour of the experimental results. A history match of the primary production portion of the experiment was obtained using an Alberta Innovates - Technology Futures (AITF) foamy oil model. This resulted in the characterization (fluid saturations and pressures) of the oil sandpack at the start of the solvent injection process. The history match of the subsequent six solvent injection cycles was used to validate the numerical model of the CSI process developed at AITF. This model includes nonequilibrium rate equations that simulated the delay in solvent reaching its equilibrium concentration as it dissolves or exsolves in the oil in response to changes in the pressure and/or gas-phase composition. Dissolution of CH4, C3H8 and CO2 in oil and CO2 in water were considered, as was exsolution of CH4, C3H8 and CO2 from oil and CO2 from water. Reduced gas-phase permeabilities resulting from gas exsolution were also included. The history match simulations indicated that: The important mechanisms were represented in the simulations. Significant oil swelling by solvent dissolution occurs during solvent injection periods. This can reduce solvent injectivity and penetration into a heavy oil reservoir during solvent injection periods. Low oil and gas-phase relative permeabilities are required during production periods to match the experimental oil and gas production during solvent cycles. A parametric simulation study showed that the quantity of gas injected in an injection period was relatively insensitive to the oil-phase diffusion coefficients, but was sensitive to solvent solubility in oil, dissolution rates, gas-phase diffusion coefficients, molar densities in the oil phase, gas-phase relative permeability and capillary pressure. It was shown that oil production is highly dependent on how quickly solvent can dissolve in the oil during injection and exsolve from the oil during production.

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.

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 score0.100
Threshold uncertainty score0.958

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.009
GPT teacher head0.222
Teacher spread0.213 · 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