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Record W4223944146 · doi:10.2118/209433-ms

Evaluation of Environmentally Friendly Green Solvents for the Recovery of Heavy Oils

2022· article· en· W4223944146 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueSPE Improved Oil Recovery Conference · 2022
Typearticle
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsChemistryLimoneneEnvironmentally friendlySolventXyleneEnvironmental chemistryTolueneWaste managementEnvironmental scienceOrganic chemistryChromatographyEssential oil

Abstract

fetched live from OpenAlex

Abstract Solvent injection recovery processes were introduced as a more energy-efficient and environmentally friendly alternative to Steam injection processes. However, BTX chemicals (Benzene, Toluene, and Xylene), commonly used for crude oil recovery due to their strong solvency and low asphaltene precipitation, are acutely toxic and harmful to the environment. These chemicals are easily soluble in water causing groundwater contamination. This paper evaluates the recovery efficiency of two green solvents, Limonene, and beta-pinene, on two samples of Californian heavy oil (C1 has an 874.8 cP viscosity and C2 has 178500 cP viscosity). On both C1 and C2, 5 core flood experiments were conducted, in total 10 experiments were run. CO2, limonene, and Beta-pinene were tested as solvents on both oils. Limonene and beta-pinene were both chosen due to their ready availability in the State of California. Both these solvents are plant-derived, non-toxic, and biodegradable. They also have much higher flash points than BTX solvents allowing for safer handling. They have been either injected as sole solvents or co-injected with CO2 during the experiments. Limonene and beta-pinene were injected at 2 mL/min while CO2 was injected at 2000 ml/min with a back pressure of 45-55 psi. Core packs were prepared by filling the pore space of Ottawa sand with 60% PV oil samples and 40% PV water by volume. Produced oil and water samples were collected every 20 min during the experiments. Thermogravimetric analyses (TGA/DSC) were conducted on these samples to identify oil, water, and solvent percentages. Because CO2 is insoluble in these types of high viscosity crude oils, CO2 flooding resulted in immiscibility with almost no oil production. Since both limonene and beta-pinene are aromatic solvents, by sole limonene or beta-pinene injection miscible flooding was achieved. Limonene achieved 35 and 23 vol. % oil recovery from a total of 60% oil for C1 and C2 respectively while Pinene achieved 31 and 27 vol. %. Co-injections of green solvents with CO2 are expected to yield higher recovery due to the presence of two active drive mechanisms namely miscible and immiscible. Co-injection of limonene and CO2 provided the greatest recovery with 45 vol. %, however, recovery efficiencies of pinene and CO2 had comparable recoveries with that of pinene possibly due to phase trapping. Produced samples analysis showed that oil percentages in produced samples were higher for Limonene than Pinene. Our results indicated that limonene and beta-pinene are very promising solvents for heavy oil recovery. Because these solvents are citrus-based, they are both easy to handle and non-toxic. Hence, we believe that our study can be a breakthrough for many heavy oil and bitumen reservoirs all around the world.

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.637
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 science0.0010.000
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 head0.024
GPT teacher head0.253
Teacher spread0.229 · 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