Air Injection and Waterflood Performance Comparison of Two Adjacent Units in Buffalo Field: Economic Analysis
Bibliographic record
Abstract
Abstract Buffalo Field covers a large area on the southwestern flank of the Williston Basin, in the northwest corner of South Dakota. In 1987, 8,000 acres of the field were divided into two units to initiate improved oil recovery operations with two different methods: air injection and waterflooding. After collecting 18 years of production history a comparison has been made between the two projects to determine the relative success of both units. In a previous paper (SPE 99454) the technical comparison of the projects was discussed and the superiority of the air injection project was demonstrated. This second paper addresses the economic analysis of both projects in terms of economic parameters such as net present value, payout time, incremental profit and rate of return. A sensitivity analysis on some of the key drivers of the project economics namely oil price, operating cost and capital investment was also performed. In spite of being technically less successful, the West Buffalo "B" Red River Unit (WBBRRU) under waterflooding has shown greater economic benefit over its "twin" West Buffalo Red River Unit (WBRRU) under air injection. This results primarily from the low oil prices (less than $20/bbl) experienced during most of the life of the projects. This case study shows that for an air injection project to be successful not only technically but also economically, a sufficiently high oil price (greater than $25/bbl) is needed due mainly to the high operating costs and capital investment. Air injection can be an economically attractive IOR process in large prospects, particularly in deep, high pressure, low permeability reservoirs where water injectivity is limited and other recovery processes become uneconomic.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".