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Record W2556888708 · doi:10.2523/iptc-18876-ms

Use of Nickel Nanoparticles for Promoting Aquathermolysis Reaction During Cyclic Steam Stimulation

2016· article· en· W2556888708 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueInternational Petroleum Technology Conference · 2016
Typearticle
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSteam injectionNickelAsphalteneNanoparticleChemical engineeringPenetration (warfare)Materials scienceEnhanced oil recoveryEmulsionPulp and paper industryChemistryPetroleum engineeringMetallurgyNanotechnologyGeology

Abstract

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Abstract Late cycles of cyclic steam stimulation (CSS) are characterized with a decreasing heavy-oil recovery and an increasing water cut. Nickel nanoparticles can be used to promote aquathermolysis reactions between water and heavy oil in steam injection processes, thereby increasing the recovery factor. In this paper, detailed investigations were performed to determine the optimum operational parameters and answers to the following questions: (1) What is the optimum concentration of nickel nanoparticles for promoting aquathermolysis under high steam temperature?; (2) Can we improve oil recovery at lower steam temperatures with the presence of nickel nanoparticles?; (3) What effect does the penetration depth of nickel nanoparticles have on the final oil recovery? CSS experiments were conducted between temperatures 150°C and 220°C. Steam generated under these temperatures was injected into sand packs saturated with Mexican heavy oil. Powder-form nickel nanoparticle was introduced into this process to boost the oil production. In an attempt to obtain the optimum concentration, different concentrations were tested. Next, oil sands without any nanoparticle additives were first added into the cylinder. Then, only one third of the sand pack was mixed with nickel nanoparticle near the injection port. Experiments were executed to study the effects of temperature, nickel concentrations, and nanoparticle penetration depth on the ultimate oil recovery and produced oil-water ratios after each cycle. Produced oil quality and emulsion formation were evaluated with gas-chromatography (GC) analysis, viscosity measurements, saturates-asphaltenes-resins-aromatics (SARA) test, and microscopic analysis of the effluents. Experimental results show that the best concentration of nickel nanoparticles, which gives the highest ultimate oil recovery factor, is 0.20 wt% of initial oil in place (IOIP) under 220°C, while the nickel concentration of 0.05 wt% provides the highest recovery factors at the early stages. A lower temperature of 150°C provides a much lower recovery factor than 220°C, which is mainly due to a lower level of aquathermolysis reactions at 150°C. By analyzing the compositions of produced oil and gas samples with GC and SARA, we confirm that (1) the major reaction mechanism during the aquathermolysis reaction is the breakage of C-S bond, (2) the nickel nanoparticles can act as catalyst for the aquathermolysis reaction, and (3) the catalytic effect becomes less remarkable from cycle to cycle. One run of experiment to test the effect of particle penetration depth revealed that nickel nanoparticle distributed near the injection port greatly contributed to the ultimate recovery factor.

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)0.000
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 score0.037
Threshold uncertainty score0.482

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 head0.019
GPT teacher head0.249
Teacher spread0.230 · 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