Challenges from Well Shut-in Amid the Oil Downturn: Long Term Impacts on Near Wellbore Skin Buildup and Sand Control
Bibliographic record
Abstract
Abstract In wake of the biggest oil crash in history triggered by the COVID-19 pandemic; Western Canada in- situ production is under tremendous price pressure. Therefore, the operators may consider shut in the wells. Current investigation offers an insight into the effect of near-wellbore skin buildup because of such shut-in. A series of simulation studies was performed to quantitatively address the impact of well shut-in on the long-term performance of well, in particular on key performance indicators of the well including cumulative steam to oil ratio and cumulative oil production. The long-term shut-in contributes to three main modes of plugging: (1) near-wellbore pore plugging by clays and fines, (2) scaling, and (3) chemical consolidation induced by corrosion. A series of carefully designed simulations was also utilized to understand the potential of skin buildup in the near-wellbore region and within different sand control devices. The simulation results showed a higher sensitivity of well performance to shut-in for the wells in the initial stage of SAGD production. If the well is shut in during the first years, the total reduction in cumulative oil production is much higher compared to a well which is shut-in during late SAGD production life. As the induced skin due to shut-in increases, the ultimate cumulative oil production drops whose magnitude depends on well completion designs. The highest effect on the cumulative oil production is in the case of completion designs with flow control devices (liner deployed and tubing deployed completions). Therefore, wellbore hydraulics and completion design play key roles in the maintenance of uniform inflow profile, and the skin buildup due to shut-in poses a high risk of inflow problem and increases the risk of hot-spot development and steam breakthrough. This investigation offers a new understanding concerning the effect of shut-in and wellbore skin buildup on SAGD operation. It helps production and completion engineers to better understand and select candidate wells for shut-in and subsequently to minimize the skin buildup in wells.
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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 | 0.001 |
| 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".