Modeling Two-Phase Flow in Tight Core Plugs with an Application for Relative Permeability Measurement
Bibliographic record
Abstract
Summary The two-phase flow of immiscible fluids in porous media has been studied for a long time in different disciplines of engineering. Relative permeability (kr) is one of the constitutional relationships in the general equation governing immiscible displacement that needs to be determined. Due to the complexity and nonlinear nature of governing equations of the problem, there is no unique model for relative permeability. The modified Brooks and Corey (MBC) model is the most common model for kr prediction. Here, a practical technique is presented to measure kr for low-permeability tight rocks. We use this experimental data to tune the empirical constants of the MBC model. The proposed method is based on a simple mathematical technique that uses assumptions of frontal advance theory to model the pressure drop along the core plug during two-phase immiscible displacement at constant injection flow rate. We make simplifying assumptions about the highest point on the observed pressure profile and use those assumptions to determine relative permeability of a tight rock sample. In the end, the amount of work for an immiscible displacement is calculated as the area under the pressure-profile curve. The effect of initial water saturation (Swi) and interfacial tension (IFT) is studied on the work required for an immiscible displacement. Using this concept, it is concluded that adding chemical additives such as surfactants to fracturing fluids can help the reservoir oil to remove the water blockage out of the rock matrix more easily while maintaining the flow rate at an economic level.
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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 | 0.000 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".