MétaCan
Menu
Back to cohort
Record W1997371729 · doi:10.2118/164123-ms

Quantitative and Visual Characterization of Asphaltenic Components of Heavy-Oil and Bitumen Samples after Solvent Interaction at Different Temperatures and Pressures

2013· article· en· W1997371729 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

VenueSPE International Symposium on Oilfield Chemistry · 2013
Typearticle
Languageen
FieldChemistry
TopicPetroleum Processing and Analysis
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAsphalteneSolventAsphaltPrecipitationVapor pressureChemistryChemical engineeringMaterials scienceLight crude oilAnalytical Chemistry (journal)Petroleum engineeringChromatographyOrganic chemistryComposite materialGeology

Abstract

fetched live from OpenAlex

Abstract Due to inefficiency of steam injection caused by technical, economic, and operational reasons, solvent methods have received special attention in heavy oil and bitumen recovery recently. A solvent can be injected in the form of vapor extraction process at reservoir temperature. Hot solvent injection can be applied to improve the recovery rate at lower temperatures than steam injection. These solvent driven recovery processes are quite complex on account of their "asphaltene destabilization" that takes place due to changes in temperature, pressure, and solvent dissolved in oil. As a result of this destabilization, the asphaltene precipitates, flocculates, and eventually plugs the pores in the reservoir. In this research, the de-asphalting of a heavy oil sample was evaluated in a PVT cell with optical visualization. The experiments were undertaken at different temperature ranges (50°C to 80°C) and pressure (30psig to 500psig), which is the suggested range for hot solvent injection. Three light hydrocarbons (propane, n-hexane, and n-decane) were used as solvents. Applying standard SARA analysis (ASTM D2007 and ASTM D2549), the characteristics of the asphaltene precipitated at the bottom of the PVT cell, were determined quantitatively. Moreover, a methodology for "asphaltene precipitation concentration analysis" was developed in order to determine the effect the temperature, pressure, and solvent type had on asphaltene destabilization. This quantitative analysis was complemented through visual observations of asphaltene characteristics on the PVT cell as well as using optical microscopy. In addition, the refractive index measurements at the onset of precipitation were used to evaluate the changes in the oil after interacting with the solvent at different temperatures and pressures. Finally, a comparative analysis of the esults was provided. Based on the quantitative and qualitative observations, the characteristics of asphaltene were classified in terms of their shape, size, and amount for different oil/solvent types, pressure, and temperature. This study will eventually lead to the identification of the effects of asphaltene characteristics on pore plugging during heavy-oil/bitumen recovery by gravity drainage from oilsands.

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 score0.005
Threshold uncertainty score0.555

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 head0.010
GPT teacher head0.254
Teacher spread0.244 · 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