Optimization of Well Completion Strategy for Double Displacement Process (DDP) and Water Alternating Gas (WAG) Injection in a Dipping Stratified Reservoir
Bibliographic record
Abstract
Abstract This study assesses how zone-by-zone completion strategy which including top-down & bottom-up mechanisms affect the performance of the double displacement process (DDP) and water alternating gas (WAG) up-dip and down-dip. It further seeks to develop an optimal zone-by-zone completion strategy to overcome the gas override problem and increase oil recovery in a dipping stratified reservoir. The impact of connection transmissibility on completion strategies in a dipping stratified reservoir is also investigated. The research was conducted on a stratified block model reservoir with dimension 4000 m × 1000 m × 80 m and is divided into four main reservoir zones in Z direction. Zones are separated from each other by a thin shale bed with thickness of 0.2 m. The communication between reservoir zones and shale beds have level of 0, 0.1, 0.01 relating to completely sealing shale, leaky shale and completely open shale. Well completion strategies simulated included all zones injecting and producing, top-down and bottom-up. The simulation begins with waterflooding to obtain 95% water cut, then the performance of DDP, WAG up-dip, and WAG down-dip with the various completion strategies were simulated. The results prove that zone-by-zone completion strategy is a successful way to overcome gas override and improve vertical conformance with WAG injection in a stratified reservoir to maximize oil recovery from the offshore field in East Canada. With zone-by-zone completion strategy, the recovery factor of WAG up-dip increased 0.8% more than the all-zone injecting and producing scheme. The results also identified bottom-up was effective completion strategy for WAG up-dip in stratified reservoirs without zonal communication and top-down was a successful completion strategy for communicating stratified reservoirs with 0.01 level of connection transmissibility with WAG up-dip and without zonal communication with WAG down-dip. DDP and WAG are considered as potentially effective enhanced oil recovery methods for offshore reservoir. However, most of studies be conducted on laboratory and reservoir simulation scale, and focus on operation parameters such as WAG ratio, WAG cycle, slug size. Our understanding is that this is the first study on the effect of top-down and bottom-up completion strategies to the performance of DDP and WAG in pilot stage on a dipping stratified reservoir block model.
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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 | 0.000 |
| 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 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".