Buffalo Field High-Pressure-Air-Injection Projects: Technical Performance and Operational Challenges
Bibliographic record
Abstract
Summary The Buffalo field air-injection units, located in northwest South Dakota, are the oldest high-pressure-air-injection (HPAI) projects currently in operation. Air injection began in January 1979, and as of December 2007, approximately 240 Bscf of air has been injected into the field. A total of 17.2 million bbl of incremental oil has been produced by the HPAI process, which is equivalent to 9.4% of the original oil in place (OOIP). The cumulative air/oil ratio (AOR) after 29 years of air injection is approximately 14 Mscf of air/bbl of incremental oil. This paper summarizes the performance of the projects and the overall experience gained by the operators after nearly 30 years of air injection. It covers almost every aspect of the entire operation since its inception; it discusses general management practices, technical and operational challenges encountered, injection and production facilities, and drilling and well-completion practices. It also includes estimates of incremental oil recovery caused by air injection and discusses how the air use has changed over time To date, the three HPAI projects in the Buffalo field continue to be a commercial success. In the last 3 years, horizontal laterals have been drilled out of more than 40 old vertical wells to enhance production, to take advantage of accumulated reservoir energy, and to improve sweep efficiency. Drilling injection wells out of old vertical wells was not possible because the openhole laterals cross a porosity zone that would have taken away some of the injection into nonproductive reservoir.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".