MétaCan
Menu
Back to cohort
Record W2586950020 · doi:10.2118/185003-ms

Simple Calculation of the Effect of Volatile Solvents and Dissolved Gases on the Viscosity of Heavy Oils and Bitumens

2017· article· en· W2586950020 on OpenAlexaff
N. P. Freitag, A. E. Dolter

Bibliographic record

VenueSPE Canada Heavy Oil Technical Conference · 2017
Typearticle
Languageen
FieldChemistry
TopicPetroleum Processing and Analysis
Canadian institutionsGovernment of SaskatchewanSaskatchewan Research Council (Canada)
Fundersnot available
KeywordsViscosityThermodynamicsArrhenius equationSolventChemistryRelative viscosityMole fractionTolueneExponentPower lawAnalytical Chemistry (journal)Organic chemistryActivation energyPhysical chemistryMathematics

Abstract

fetched live from OpenAlex

Abstract A new method is proposed for simple and reliable viscosity calculations for mixtures of heavy oils or bitumens with light solvents. This method has three characteristics that give it an advantage over current approaches. First, it is simple to implement. Second, it faithfully portrays the viscosity of mixtures of Newtonian fluids up to at least 190°C. Third, and most importantly, it makes use of the recent discovery that, for any given heavy oil, all light solvents can be represented at low concentrations by the same mole-fraction-weighted form of the Arrhenius equation. For high concentrations, an additional, empirical power-law term, whose exponent was determined from new viscosity data for toluene–heavy oil mixtures, was developed. The average absolute relative deviation (AARD) between 307 experimental viscosity measurements and the new equation was 20.1%. The data set included mixture viscosities from 1 to 440,000 mPa·s, at temperatures from 12 to 190°C. The largest disagreements were -63% and 101% of the measured values. It is suggested that a substantial portion of the observed disagreements arose from combined errors in the experimental measurement of viscosities, solvent compositions, and average molecular weights of the oils. It was found that the one key constant for describing concentration effects could be correlated reasonably well with the viscosity of the dead oil. When this constant was calculated from the resulting correlation, the AARD for the initial data set increased by only a modest amount to 27.7%. The disagreements were somewhat larger when the new method was used to make pure predictions of two published data sets. Accordingly, it was concluded that the new approach can be used to make reasonable predictions (possibly within a factor of 2) of solvent–oil mixture viscosities simply from accurate knowledge of the viscosities and molecular weights of the dead oil and solvent. However, substantially better predictions may be obtained for any light solvent if the above information is supplemented with even relatively inexpensive laboratory data taken with a lower-volatility solvent such as toluene.

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)0.001
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 score0.115
Threshold uncertainty score0.916

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.015
GPT teacher head0.256
Teacher spread0.241 · 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

Citations0
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueSPE Canada Heavy Oil Technical ConferenceSame topicPetroleum Processing and AnalysisFrench-language works237,207