Review of the effect of temperature on oil-water relative permeability in porous rocks of oil reservoirs
Bibliographic record
Abstract
Thermal methods of heavy oil recovery involve multiphase flow at high temperatures. Numerical simulation studies of such processes require accounting for changes in the multi-phase flow behavior of the rock-fluid system with increasing temperature. Although the effect of temperature on two-phase relative permeability has been studied for more than five decades, it remains an unresolved issue. Experimental results that frequently contradict each other are still being reported and the issue remains a matter of debate. The purpose of this review is to critically examine the reported results and explore the possible reasons for contradictory results. We have examined the reported results of more frequently cited papers from past five decades and attempted to rationalize the disagreements in findings. There appear to be three main reasons for the lack of consensus in experimentally observed results. The measurements of relative permeability at high temperature are complex and the reported results often include experimental artifacts. Secondly, meaningful relative permeability measurements require that capillary forces control the fluid distribution within the pore space, but this condition is difficult to ensure in viscous oil systems. The third reason is that the impact of temperature is not same in all rock-fluid systems, it depends on how the wettability, interfacial tension and the pore geometry changes with temperature. It becomes apparent that it is not advisable to generalize the effect of temperature on relative permeability from previous studies without having a good understanding of how the underlying parameters that can influence the relative permeability are changing with temperature. The relative permeability of a specific petroleum reservoir may (or may not) vary with temperature.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".