Temperature-Dependent Irreducible Water Trapping in Heavy-Oil Reservoirs
Bibliographic record
Abstract
Summary Temperature-dependent irreducible water saturation has great implications for heavy-oil production. Especially in processes using thermal methods, the irreducible water saturation varies significantly when temperature rises from the initial reservoir condition to the temperature of injected hot fluids. In this work, the irreducible water saturation retained in a heavy-oil/oil-sands reservoir has been theoretically analyzed as a function of temperature in the view of thermodynamics. This analysis involves oil/water interactions, thermodynamic stability, pendular rings between particles, and a dense random-packing theory. The temperature-dependent irreducible water saturation in two heavy-oil reservoir samples (Coalinga and Huntington Beach) and two oil-sands reservoir samples (Cat Canyon and Peace River) have been analyzed using an oil/water/silica system. The computed results have been compared with published experimental data. The good agreements of the comparison demonstrate the feasibility of the proposed analysis to describe the irreducible water saturation in a heavy-oil/oil-sands reservoir up to 300°C. Through these analyses, the theoretical understandings of temperature-dependent irreducible water in a heavy-oil/oil-sands reservoir have been provided. As temperature increases, the mutual water/oil solubilities are increased by enhanced molecular interactions, as well as the surface energy at an oil/water connecting interface. As a result, the oil/water interfacial tension (IFT) decreases, which diminishes the contact angle and enlarges a water-filled pendular ring between particles at elevated temperatures. Thus, the irreducible water saturation is increased by the enlarged pendular rings in a dense packing porous medium. In addition, this study demonstrates the possibilities to alter the irreducible water saturation appropriately in a heavy-oil/oil-sands reservoir to enhance oil recovery, decrease water cut, save costs of surface oil/water separation, and reduce heat consumption.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 teacher head, 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".