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Record W2969731908 · doi:10.3390/ma12172656

Bitumen Recovery from Crude Bitumen Samples from Halfaya Oilfield by Single and Composite Solvents—Process, Parameters, and Mechanism

2019· article· en· W2969731908 on OpenAlexaboutno aff
Yunfeng Liu, Zhengsong Qiu, Hanyi Zhong, Zhen Nie, Jia Li, Weian Huang, Xin Zhao

Bibliographic record

VenueMaterials · 2019
Typearticle
Languageen
FieldChemistry
TopicPetroleum Processing and Analysis
Canadian institutionsnot available
FundersNational Science and Technology Major ProjectNatural Science Foundation of Shandong ProvinceNational Natural Science Foundation of China
KeywordsAsphaltComposite numberMechanism (biology)Process (computing)Petroleum engineeringMaterials scienceCrude oilComposite materialProcess engineeringGeologyEngineeringComputer science

Abstract

fetched live from OpenAlex

Since 2007, heterogeneous, high-viscosity active bituminous formations have often occurred during the drilling process in Yadavaran oilfield (Iran), Halfaya oilfield (Iraq), and tar sands (Canada). The formation of bitumen exhibits plastic and creep properties, and its adhesion is strong, so drilling accidents are easily caused, such as adhering vibrating screen, drill pipe sticking, lost circulation, and even well abandonment. These complex problems cause huge economic losses. Solvents used to dissolve bitumen are a feasible technology to remove bitumen effectively. In order to solve this problem, we used crude bitumen samples from Halfaya oilfield to study the relation between the bitumen component and different solvents. In this study, the temperature, crude bitumen sample to solvent ratio, stirring rate, stirring time, and ultrasound time on bitumen recovery by toluene were investigated by a single factor experiment. The optimum process parameter for bitumen recovery was obtained. Toluene, n-heptane, tetrahydrofuran, cyclohexane, cyclopentane, ethyl acetate, and n-pentane were chosen as the solvents for single solvent extraction and composite solvent extraction. The bitumen recovery increased significantly with the use of a composite solvent compared to a single solvent. The composite solvent ratio was 1:1. The highest bitumen recovery was 98.9 wt% by toluene/cyclohexane composite solvent. The SARA (saturates, aromatics, resins, and asphaltenes) components of the bitumen were analyzed. The toluene showed the highest asphaltene content, while the n-alkanes showed the lowest asphaltene content. The higher the asphaltene content, the higher the bitumen recovery. The composite solvent obtained the highest asphaltene content and bitumen recovery. The viscosity of bitumen extraction by different solvents was measured. The lower the bitumen viscosity, the higher the bitumen recovery. The element analysis indicated the solvent's ability to extract bitumen colloids with the C/H ratio. This study provides a reliable theoretical basis for the subsequent adoption of effective anti-bitumen polluted drilling fluid additives.

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), Insufficient payload (model declined to judge)
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 score0.007
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 communication0.0010.000
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 head0.011
GPT teacher head0.210
Teacher spread0.199 · 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

Citations17
Published2019
Admission routes1
Has abstractyes

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