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Record W2591070234 · doi:10.1088/1742-2140/aa5c0d

Improved minimum miscibility pressure correlation for CO<sub>2</sub> flooding using various oil components and their effects

2017· article· en· W2591070234 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.

fundA Canadian funder is recorded on the work.
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

VenueJournal of Geophysics and Engineering · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicCO2 Sequestration and Geologic Interactions
Canadian institutionsnot available
FundersCentral University Basic Research Fund of ChinaChina Scholarship CouncilFundamental Research Funds for the Central UniversitiesUniversity of Alberta
KeywordsMole fractionMiscibilityFraction (chemistry)Petroleum engineeringEnhanced oil recoveryCorrelationChemistryMaterials scienceMathematicsEngineeringChromatographyOrganic chemistryPolymer

Abstract

fetched live from OpenAlex

Carbon dioxide (CO2) flooding is an effective method of enhanced oil recovery (EOR) that has become one of the most important EOR processes. One of the key factors in the design of a CO2 injection project is the minimum miscibility pressure (MMP), whereas local sweeping efficiency during gas injection is dependent on the MMP. There are many empirical correlation analyses for the MMP calculation. However, these analyses focus on the molecular weight of the C5+ or C7+ fraction, and do not emphasize the effects of various components on MMP. Our study aims to develop an improved CO2–oil MMP correlation analysis that includes parameters such as reservoir temperature and various oil mole fractions. Here, correlation analysis was performed to define the influence of various components on the MMP using various data from 45 oilfields which have experimental CO2–oil MMP and oil compositions readily available. Thirty of the data sets were used to develop an improved correlation, and the other 15 data sets were used to verify the correlation. It was found that the mole fraction of C3 and C6 were the main factors that affected MMP. There was a good quadratic polynomial relationship between the mole fraction of C3 and MMP, and the relationship also existed between the mole fraction of C6 and MMP. The results do not include the molecular weight of the C5+ or C7+ fraction like other common correlations. Nine popular correlations were then used to also predict the MMP, and the comparison showed that the improved CO2–oil MMP correlation defined here was a better estimate. The correlation was then used in Dongshisi and Fuyu oilfields to assess EOR potential, the results also indicated that MMP increased over the course of the CO2 flooding process. This increase shows that it would be more difficult to achieve a mixed phase between crude oil and CO2, therefore the oil recovery would be difficult to further improve towards the end of injection.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.952
Threshold uncertainty score0.273

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 head0.011
GPT teacher head0.226
Teacher spread0.215 · 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