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Record W2790149439 · doi:10.2118/189765-ms

Phase Behaviour and Viscosity of Bitumen-CO2/Light Hydrocarbon Mixtures at Elevated Temperatures: A Cold Lake Case Study

2018· article· en· W2790149439 on OpenAlexafffund
Sara Eghbali, Hassan Dehghanpour, Jarrett Dragani, Xin Zhang

Bibliographic record

VenueSPE Canada Heavy Oil Technical Conference · 2018
Typearticle
Languageen
FieldChemistry
TopicPetroleum Processing and Analysis
Canadian institutionsCenovus Energy (Canada)University of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaCenovus Energy
KeywordsAsphaltSolubilityAsphalteneViscosityViscometerSolventChemistryHydrocarbonLight crude oilOil sandsThermodynamicsSteam-assisted gravity drainagePhase (matter)Analytical Chemistry (journal)Materials scienceChromatographyOrganic chemistryComposite material

Abstract

fetched live from OpenAlex

Abstract Co-injection of CO2 or light hydrocarbons with steam in the SAGD process may improve SAGD efficiency and lead to lower greenhouse gas emissions through reduced Steam Oil Ratios (SORs). Various additives are postulated to have differing effects on bitumen recovery, depending on the nature of the reservoir, the operating conditions, and the API gravity of the oil. A PVT study was conducted to investigate the phase behaviour of CO2-, C3-, and C4-bitumen systems at varying concentrations, representing the edge of a SAP steam chamber with the expected temperature range of 70°C to 160°C. A produced and dewatered bitumen sample was collected from the Cenovus Osprey Pilot in the Cold Lake oil sands region and characterized. Constant Composition Expansion (CCE) experiments were conducted on solvent-bitumen systems in the temperature range of 70°C to 160°C. Filtration tests were also conducted at high temperature and reservoir pressure to investigate the effect of solvent type and concentration on asphaltene precipitation. A Peng-Robinson Equation of State (PR-EOS) model was calibrated to measured data for CO2-, C3-, and C4-bitumen systems. Viscosity of the bitumen saturated with CO2, C3, and C4 was measured with an electromagnetic-based viscometer elevated temperatures. Phase equilibrium calculations were performed using the calibrated EOS to predict the solubility of the solvents in bitumen. A correlation was fitted to the measured viscosity data to predict the liquid phase viscosity as a function of solvent solubility and temperature for each solvent. From the CCE tests, two equilibrium phases (i.e., liquid and vapour) were observed for the C3- and CO2-bitumen systems. Three equilibrium phases were observed for the C4-bitumen system at high C4 concentrations. These three phases include a bitumen-rich heavy oil phase, a solvent-rich lighter oil phase, and a vapour phase. Due to the extracting/condensing mechanism and asphaltene precipitation, the bitumen-rich phase formed in C3-bitumen system was lighter than the one in C4-bitumen system. Filtration tests showed more asphaltene precipitation by C3 and C4 dissolution than CO2. Moreover, C3 has more potential for asphaltene precipitation than C4. Viscosity measurements showed that dissolution of C3 and C4 in bitumen resulted in greater viscosity reduction than CO2 dissolution. This difference was more pronounced at lower temperatures. The highest C4 solubility in bitumen and C4 potential for forming a C4-rich liquid phase showed stronger condensing and extracting effect of C4 than C3 and CO2 in solvent-bitumen interactions. Moreover, C4 lead to more bitumen swelling than C3 and CO2. EOS predictions and viscosity measurements indicated that increasing the solvent concentration in a solvent-bitumen system beyond a defined Threshold Solvent Concentration (TSC) has an insignificant effect on solvent solubility and bitumen viscosity reduction.

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 categoriesMeta-epidemiology (narrow)
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 score0.718
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.013
GPT teacher head0.266
Teacher spread0.252 · 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.

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

Citations12
Published2018
Admission routes2
Has abstractyes

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