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Record W4411333698 · doi:10.1016/j.csite.2025.106506

Temporal and spatial temperature distributions and heavy oil production performances in hot-water flooding processes at different water temperatures and injection rates

2025· article· en· W4411333698 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

VenueCase Studies in Thermal Engineering · 2025
Typearticle
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsUniversity of Regina
FundersNatural Sciences and Engineering Research Council of CanadaPetroleum Technology Research Centre
KeywordsWater floodingEnvironmental scienceFlooding (psychology)Materials scienceOil productionProduction (economics)Petroleum engineeringSoil scienceGeology

Abstract

fetched live from OpenAlex

The petroleum industry becomes more and more interested in applying some low-heat thermal-based enhanced oil recovery (EOR) processes to recover heavy oils due to their much-reduced energy consumptions, greenhouse-gas emissions and project costs in comparison to other thermal-based EOR processes, such as steam flooding (SF) and steam assisted gravity drainage (SAGD). In this paper, the heavy oil production performance of hot-water flooding (HWF) as a typical low-heat thermal-based EOR process for reducing the viscosity of heavy oil and improving its mobility was experimentally studied by using a 1-D cylindrical sandpacked physical model with the porosity and permeability of 35.0 % and 4.50 mD, respectively. A total of eight coreflooding tests with different injected water temperatures from 20 °C to 90 °C and injection rates from 0.5 cc/min to 5.0 cc/min were conducted to compare seven HWF tests and one conventional waterflooding (WF) test. In particular, the transient temperature vs. time data were measured at five different locations in the physical model during each HWF/WF test by using a high-precision thermocouple probe with five sensors. The measured in-situ temperature vs. hot-water (HW) injection time/volume data in the HWF tests at a low HW injection rate exhibited three distinct periods. Period I had a progressive increase in the temperature, which was followed by Period II with a decrease in the temperature and Period III at a stable temperature. The transition from Period I to Period II indicated possible HW breakthrough (BT). In contrast, the measured in-situ temperature was always increased with the HW injection volume in the HWF tests at the medium to high HW injection rates. It was found that the heavy oil recovery factor was always increased as the ambient temperature and HW temperature were increased. However, the HW injection rate needs to be optimized due to its dual opposite effects on the heavy oil production performance of HWF. Overall, HWF is found to be an effective low-heat thermal-based EOR process in the heavy oil reservoirs, in comparison with the traditional WF.

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 score0.125
Threshold uncertainty score0.690

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 head0.007
GPT teacher head0.236
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