Case History of Conformance Solutions for West Sak Wormhole/Void Space Conduit with a New Reassembling Pre-formed Particle Gel RPPG
Bibliographic record
Abstract
Abstract Waterflood conformance is a significant problem in the West Sak field of Alaska. Re-assembling Pre-Formed Particle Gels (RPPG) have been used to treat Void Space Conduits (VSC) and repair the "short-circuited" waterflood. These VSC’s are typically formed by sand producing wormholes. Several dozen VSC solutions have been implemented since 2006, including molten wax, cement blends, and pre-formed particle gels. To date, all the solutions have been faced with various limitations due to the low reservoir temperature and poor sand consolidation. A good percentage of the pre-formed particle gel (PPG) solutions have been successful in sealing off VSCs, but often show limited longevity that can range from as little as several weeks to several years. An effort was undertaken to develop a product that would provide enhanced stability in the VSC and extend solution life beyond the current range. A cost-effective conformance solution was developed with increased mechanical strength through a re-crosslinking process known as RPPG. The goal of the RPPG solution is to provide a longer-term repair to a VSC and restore the primary water flood characteristics. This paper will present the results of the seventeen RPPG solutions that have been pumped between 2017 and 2019 in the West Sak field on the North Slope of Alaska. RPPG treatments have shown a 23% improvement over traditional PPG treatments at the economic payout during the field trial. There have been some significant learnings through this time period. The focus of this paper will be to review the VSC problem understanding and the reason for the RPPG product development, detail the evolution of RPPG job design over time and provide results and operational knowledge from the field trial efforts. The latest advancements in conformance engineering will be of interest to Reservoir and Production Engineers who are focused on supporting and optimizing conventional waterflooded assets, particularly when faced with conformance issues in an unconsolidated reservoir. In addition, the field results will be useful to those seeking to implement RPPG solutions in their area of operation.
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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".