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Record W4233408975 · doi:10.2118/05-09-tn

Solvent Co-Injection in SAGD: Prediction of Some Operational Issues

2005· article· en· W4233408975 on OpenAlexfundaboutno aff
H.F. Thimm

Bibliographic record

VenueJournal of Canadian Petroleum Technology · 2005
Typearticle
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsnot available
FundersMonash UniversityRoyal Australian Chemical InstituteRoyal Society of ChemistryRoyal SocietyChemical Institute of CanadaInnovative Research Group Project of the National Natural Science Foundation of China
KeywordsDissolutionSolventChemistryCarbon dioxideSteam injectionOil sandsPetroleum engineeringEnhanced oil recoveryHydrocarbonFossil fuelViscosityHydrogenWork (physics)Water injection (oil production)Chemical engineeringThermodynamicsOrganic chemistryMaterials scienceGeology

Abstract

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Abstract In recent years, substantial progress has been made in the theoretical treatment of hydrocarbon dissolution in water, near the critical point of water (374 °C). At these temperatures, water becomes a solvent for gases including the lower hydrocarbons, and possibly, the higher hydrocarbons. The SAGD process is currently the only viable method for in situ recovery of Canada's Athabasca oil sands deposit, a deposit of high viscosity oil in unconsolidated sand. Recent studies have sought to understand modifications at lower steam pressures and gas injection. Most recently, the idea of solvent co-injection has been under discussion. In the present paper, the predictive capabilities that have been developed for gas production in the SAGD process are studied in conjunction with the chemical kinetics and mechanisms of solvolytic reactions. The reactions that produce hydrogen sulphide and carbon dioxide, generally referred to by the name "aquathermolysis, are thought to be solvolytic reactions by their nature. The results of this work suggest strongly that the production of the acid gases, hydrogen sulphide, and carbon dioxide will be suppressed in SAGD operations if a solvent is co-injected. The work has implications for the need for sulphur recovery plants in SAGD projects that are considered for solvent co-injection. Recently published thermodynamic data have made possible the prediction of individual solvent component production or retention in the steam zone. Introduction In 2001, Thimm(1) proposed that gas production in SAGD proceeds via a dissolution mechanism. Gases are dissolved in the produced liquids, and break out of solution in the wellbore and facilities. There has been no case reported so far where it is necessary to assume free gas production in SAGD in order to account for observed gas production or composition. The rationale is as follows. The distribution coefficient (K-value) of a solute gas in equilibrium with a solvent is given by: Equation (Available In Full Paper) In this form, the unit of the Henry's Law coefficient is that of pressure, as is evident from inspection. For the purpose of this work, all Henry's Law constants are given in units of MPa. The equation shows that the K-values are related to the Henry's Law constant. Determination of Henry's Law Constants Henry's Law coefficients for gases in water normally follow a power law known as the Valentiner Equation: Equation (Available In Full Paper) However, at elevated temperatures, this equation begins to fail at about 175 °C, and could only be used for the lowest steam pressure situations. Above this temperature, deviations become progressively larger, because an asymptotic behaviour of the Henry's Law constant near the critical point of water makes an increasingly important contribution. Above 175 °C, the specific volume of water begins to fall significantly from the normal 55.56 mole/L, and Harvey and Levelt Sengers(2) have shown a linear relationship between: Equation (Available In Full Paper) in the range 175 °C and the critical point of water at 374 °C. For small, non-polar molecules and noble gases, Harvey and Levelt Sengers(2) have shown that the use of the equation: Over the last 25 years there have been a number of reports in the literature of planned or executed field tests of the electric heating process, mostly based on the ohmic dissipation of electric energy in the formation. Electrothermic Co., for example, stimulated four wells of the Little Tom field in South Texas

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)0.002
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 score0.014
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.221
Teacher spread0.215 · 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
Published2005
Admission routes2
Has abstractyes

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