Dimensionless Analysis and Scale-Up of Experiments with Heavy Oil
Bibliographic record
Abstract
Abstract This study investigates the scaling criteria used to evaluate immiscible water and chemical floods, and miscible solvent injection and VAPEX processes by deriving dimensionless groups. We present findings from various flooding experiments and evaluate the interplay between viscous and capillary forces as functions of oil viscosity, injection velocity, and porous media characteristics. Updated dimensionless times, capillary numbers, and diffusion numbers were derived from the results of different core floods, which accurately predict recovery performance for different solvent and chemical types, injection rates, and rock properties. The capillary number (Nca) and dimensionless time (tD) are the most commonly used dimensionless numbers to characterize oil recovery performance in porous media. Nca balances forces at a given moment, and tD captures the displacement process over time. However, none of these individual numbers accurately correlate with the recovery factor. To address this, we incorporated viscosity ratios, oil density, reservoir thickness, porosity, and permeability, and adjusted the exponent for each term in new dimensionless numbers. We propose combined dimensionless scales to predict oil production in immiscible and miscible floods. The effect of each dimensionless group in our proposed numbers on oil recovery was examined through sensitivity analysis. The proposed updated dimensionless numbers successfully predicted oil recovery for water flooding, chemical flooding, and solvent injection in heavy oil systems. It was found that while traditional dimensionless numbers failed to accurately correlate with the recovery factor, our modified dimensionless numbers improved oil recovery prediction across varying viscosity ratios, solvent types, injection velocities, and core porosities and permeabilities. Incorporating oil density and reservoir height into Nenniger's dissolution term enabled the development of a new capillary number, Nca*, which improved the prediction of oil recovery during solvent injection processes. Our results showed increased recovery efficiency with higher Nca* values, as viscous forces overcame capillary forces. Dimensionless parameters provide accurate scaling from laboratory to field conditions. While extensive dimensionless analysis has been conducted on waterflooding, little work has focused on developing scaling laws for solvent flooding in heavy oil reservoirs. Our study demonstrated that the incorporation of viscosity ratio and dissolution term improved the accuracy of the existing dimensionless numbers in predicting oil production during immiscible and miscible flooding.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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 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".