Comprehensive Review of Fracture Control for Conformance Improvement in the Kuparuk River Unit - Alaska
Bibliographic record
Abstract
Abstract This paper is a field case review of the process and methodologies used to identify, characterize, design, and execute a solution for a waterflood conformance problem in the Kuparuk River Unit in late 2013. In addition, post treatment analysis in a complex WAG flood will be discussed. The Kuparuk River Field is a highly fractured and faulted, multi-layer sandstone reservoir located on the North Slope of Alaska. Large scale water injection in the field was initiated in 1981 and overall the field responded favorably to waterflood operations. In 1996, Kuparuk implemented a miscible WAG flood in many areas of the field. However, natural fault and fracture connectivity has resulted in some significant conformance issues between high angle wells in the periphery. Methodologies employed to identify and characterize one specific conformance issue will be outlined. Details of diagnostic efforts, and how they were used to identify, characterize and mitigate an injector/producer interaction through a void space conduit will be discussed. The solution selected to resolve this conformance issue involved pumping a large crosslinked hydrolyzed polyacrylamide (HPAM) gel system. The solution used a tapered concentration design with one of the highest molecular weight HPAM polymers available. Before execution of this solution, extensive history matching and modeling of the solution design and benefits were used to justify this effort. These modeling efforts and their projections will be reviewed. This solution was pumped into the offending injector in late 2013, and offset producers were carefully monitored for gel breakthrough. The polymer treatment design parameters, including rates and pressure limits were used to generate an effective solution. A discussion of this active design approach, a complete review of the well problem dynamics, treatment operations, products used, and potential complications associated with these products will be discussed. Post solution execution performance analysis was difficult due to the active nature of this MWAG flood. A variety of plotting and analysis techniques were used to identify and quantify the results. A discussion of these results will be provided. Finally, a summary of lessons learned, and a limited discussion of future plans will be presented.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".