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Record W2801960062 · doi:10.2118/190086-ms

Single Phase Microemulsions Applied to Oil Sands

2018· article· en· W2801960062 on OpenAlexaboutno aff
Pushpesh Sharma, Konstantinos Kostarelos, Xiaolu Xiong

Bibliographic record

VenueSPE Western Regional Meeting · 2018
Typearticle
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsAsphaltPulmonary surfactantOil sandsPetroleum engineeringMicroemulsionPhase (matter)DiluentWork (physics)Oil in placeFlow (mathematics)Materials scienceEnvironmental sciencePetroleumChemical engineeringChemistryGeologyMechanicsComposite materialEngineeringMechanical engineering

Abstract

fetched live from OpenAlex

Abstract Extra–heavy oil sands deposits represent a significant part of the oil resources available all around the world. Current recovery techniques such as open pit mining, SAG-D, etc., are not very efficient and have been debated for their possible adverse effect on environment. We propose a method of oil recovery that has the potential of being a "game changer" for such resources: using cyclic injection of surfactant solutions forming single–phase microemulsion (m.e.) without mobilizing the oil. This type of m.e. has several advantages: it is less viscous than the extra heavy oil/bitumen; when the surfactant is injected, the m.e. can finger through the tar to a production well, where it will contain a high mass of heavy oil and can be transported without addition of diluent. This approach would use two parallel horizontal wells as an injector/producer pair so that injected surfactant solution would create viscous fingers/flow paths through the oil sands. The m.e. formed during the process would be produced in the second well. After transportation, the surfactant will need to be recovered from the m.e. and recycled for re-injection. Phase behavior experiments such as surfactant screening, salinity scans and aqueous stability were conducted focusing on forming single phase m.e. Previous work aimed at single phase m.e. used coal tar as a model oil for phase behavior studies and flow experiments that yielded promising results. As a result of the previous work, new phase behavior studies were conducted using bitumen extracted from oil sands obtained from Alberta, Canada that are presented in this paper. Three flow experiments were conducted using a surfactant formulation selected based on the results of the phase behavior experiments to recover bitumen from the oil sands. For bitumen, single phase m.e. was achieved with a mixture of internal olefin sulfonate and alcoxy sulfate (1:1) surfactants with alkali (sodium carbonate), with bitumen solubilization of the order of 300,000 ppm. The three flow experiments were conducted to explore two different flow schemes, to compare a synthetic oil sand (bitumen from oil sands mixed with OK-75 sand) with an actual oil sand, and to investigate the effects of two experimental setups. The recoveries from these flow experiments were lower than expected, only achieving a bitumen solubilization of the order of 10,000 ppm. The analyses of the results and possible reasons for lower recovery are discussed in the paper. Surfactant solubilization method using single phase m.e., could provide an environment-friendly alternative to current recovery methods. It would also eliminate the need of adding solvents for transportation. While improved surfactant formulations could yield better recovery, the economic feasibility of the process will depend upon the final step—recovery of the surfactant from the produced m.e. Work is currently being conducted on several potential surfactant recovery processes.

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 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 score0.170
Threshold uncertainty score0.860

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.023
GPT teacher head0.273
Teacher spread0.250 · 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.

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

Citations2
Published2018
Admission routes1
Has abstractyes

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