Analysis of Near-Miscible CO2-WAG Displacements: The Distinction between Compositional and Interfacial Tension Effects
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Bibliographic record
Abstract
Abstract CO2 Water-Alternating-Gas injection (CO2 WAG), which involves complex phase and flow behaviour, is still a challenging task to simulate and predict accurately. In this paper, we focus specifically on the regime of viscous fingering flow in CO2 WAG in heterogeneous systems because of its importance. We investigated two key physical processes that occur during near-Miscible WAG (nMWAG) processes, namely oil stripping (Mechanism 1, M1) and low-interfacial-tension (IFT) film flow effects (Mechanism 2, M2). The low IFT effects in M2 manifest themselves in an increased mobility of oil phase due to film flow process (discussed below). The importance of properly simulating the interaction of viscous, compositional (M1), and low-interfacial-tension effects (M2) is clearly demonstrated in this study. Our specific aim is to improve the modelling of CO2 displacement in the transition from immiscible to miscible flows in CO2 WAG processes. We simulated both immiscible and near-miscible CO2 WAG and also continuous CO2 displacements with unfavourable mobility ratios for 1D and 2D systems. 2D heterogeneous permeability fields were generated with certain Dykstra-Parsons coefficients and dimensionless correlation ranges. IFT (σgo) was calculated by the simulator as part of the compositional simulation using the McLeod-Sugden equation. The consequent IFT effects on relative permeability was imposed using two commonly used models, i.e. Coats (1980) and Betté et al. methods (1991), which have been implemented in many commercial software packages, such as CMG/GEM and E300. Thus, we identify two clear mechanisms of oil recovery that may occur in near-miscible CO2 (or other gas) injection which we denote as, M1 for oil stripping or compositional effects, and M2 for low-IFT effects which are described by an enhanced hydrocarbon relative permeability. We tested various combinations of oil-stripping effects (M1) and IFT effects (M2) to evaluate the potential impact of each mechanism on the flow behaviour such as the local displacement efficiency, the tracking of tracer flow and the ultimate oil recovery. Oil bypassed by viscous fingering/local heterogeneity, can be efficiently recovered by WAG in the cases where both M1 and M2 are taken into account (as opposed to either mechanism being considered alone). Through tracer analysis, we found that a major recovery mechanism in near-miscible displacement was viscous crossflow between non-preferential (bypassed) flow-paths and preferential flow-paths (i.e. fingers). Indeed this is the key to the recovery of the bypassed oil, which can be strongly amplified/enhanced by the combined mechanisms of M1 and M2 in the case of WAG, but not under continuous CO2 injection alone. This is because during continuous CO2 injection, gas fingers are dominant in the preferential flow paths, and therefore significantly suppress oil flow from the non-preferential (bypassed) paths into the preferential routes. In contrast, the relatively stable displacing front of WAG is able to make full use of M2, leading to viscous crossflow of bypassed oil into the main preferential flow paths (fingers) and be efficiently produced through M1 by subsequent injections. Eventually, these overall combined mechanisms greatly improve the displacement performance in the case of near-miscible WAG. Due to the significance of IFT effects (M2), we comment on the discrepancy between two of the IFT-dependent relative permeability models (Bette and Coats) and its impact on the simulation of the flow behaviour.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it