Wettability, Trapping and Fracture-Matrix Interaction during WAG Injection in Fractured Carbonate Reservoirs
Bibliographic record
Abstract
Abstract Relative permeabilities show significant dependence on the saturation path during enhanced oil recovery. This dependence (or hysteresis) is particularly important for water-alternating-gas (WAG) injection, a successful EOR method for clastic and carbonate reservoirs. WAG is characterized by an alternating sequence of drainage and imbibition cycles. Hysteresis is hence common and results in trapping of the non-wetting phase, which impacts incremental recovery. The competition of trapping and geological heterogeneity during WAG, particularly in carbonate reservoirs, is not yet fully understood. In this study, we therefore use a high-resolution simulation model of a Jurassic Carbonate ramp, which is an analogue for the highly prolific reservoirs of the Arab D formation in Qatar, to investigate the impact of non-wetting phase trapping during miscible and immiscible WAG in heterogeneous carbonate formations. We then compare the impact of trapping on recovery to the impact of heterogeneity in wettability and reservoir structure. We test end-member wettability scenarios and multiple rock types. We also compute effective fracture permeabilities using discrete fracture networks (DFN), ranging from sparsely distributed background fractures to fracture networks where intensity varies with proximity to faults. The results enable us to analyse and compare WAG efficiency in carbonate reservoirs by ranking the impact of physical displacement processes (imbibition, drainage, trapping, miscibility) versus heterogeneity (wettability, faults, fractures, layering) that are typical for carbonate reservoirs. We show that while miscible WAG injection gives better displacement results than immiscible WAG injection or water flooding for this reservoir, recovery efficiency is limited by structurally induced bypassing and flow channelling. This bypassing is magnified if fractures are considered, leading to an earlier breakthrough of injected fluids and ultimate recoveries that are at least 8% lower compared to matrix-only models. We also demonstrate the impact of different hysteresis models and show that when irreversibility of the drainage and imbibition scanning curves during WAG is accounted for, trapping is enhanced and at least a 5% increase in recovery is observed. This modelling approach, therefore, enables us to increase the reliability of WAG simulations by accounting for trapping and its interaction with wettability, miscibility, and geological heterogeneity in fractured carbonate reservoirs.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".