Design and Execution of a State-of-the-Art Water Shutoff Treatment in a Powder River Basin Tensleep Producer
Bibliographic record
Abstract
Abstract This paper summarizes the literature research on water shutoff treatment technologies, distills the critical elements for designing a treatment in a naturally fractured Tensleep producer, presents the treatment design process, and shares the field operations experiences and treatment results. The subject well is located in the Teapot Dome Field in the Naval Petroleum Reserve No. 3, Natrona County, Wyoming. The project was funded by the U.S. Department of Energy and the Rocky Mountain Oilfield Testing Center. The literature and interview research illuminated the aspects of the treatment that are scientifically sound, as well as the areas that are in need of additional research. The most important factor in treating wells for excessive water production is the characterization of the water production mechanism. This paper outlines some simple graphical techniques used to identify water flowing through a natural fracture system from an underlying aquifer. Selection of treatment technology, treatment volume, concentration schedule, and quality control issues are discussed. Critical logistics and operational matters are also covered. An unusual approach to the treatment was taken by stimulating the well with a propellant stimulation treatment prior to the water shut-off treatment. This technique is designed to improve the communication with the natural fractures in the near-wellbore area, and allow the treatment to be pumped at lower pressures with less polymer dehydration problems and more effective treatment placement. It is hoped that the improved placement will extend the life of the treatment. The job procedure, cost estimate, schedule, and project economics are presented, and compared to the actual job execution. The treatment had some unexpected pressure behavior during the placement. Ideas are proposed to explain the behavior, and suggestions are made to gather additional data during future treatments to verify the theories and better understand treatment design. The treatment was performed on October 13, 2000 and three months of production data are used to judge its success. Pre-treatment production rate was 14.1 barrels of oil per day (BOPD) (2.24 m3/d) and 7,817 barrels of water per day (BWPD) (1243 m3/d). Post treatment rates after two weeks were 18 BOPD (2.9 m3/d) and 1,880 BWPD (299 m3/d). After three months, production seems to be stabilizing around 12 BOPD (1.9 m3/d) and 3,150 BWPD (496 m3/d). Problems were experienced with ESP pump sizing following the treatment.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 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".