ESP Design Changes for High GLR and High Sand Production; Apache Stag Project
Bibliographic record
Abstract
Abstract Initial ESP designs for the Stag oil field, located on the Australian Northwest Shelf, were based on a low GOR, high viscosity, 19 API, crude oil. However, higher than forecasted gas rates and gas-oil separation in the 3300 ft long horizontal production sections resulted in flow from the reservoir in the form of slugs of gas and oil. Then, with the onset of water production, high volumes of produced sand compounded the problems. These two main issues, plus a rapidly declining reservoir pressure, have combined to present a challenging ESP production environment. This paper reviews in detail the evolution of the completion design, focusing mainly on the ESP design, which initially ran for only 191 days, but now averages 511 days. The intent of this paper is to provide advice to be considered when designing ESP completions for new reservoirs, to provide an example of a good completion design for handling fluids with high ratios of gas and sand, and finally, to provide information on new technology developments that have evolved from these learning experiences.
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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 | 0.002 | 0.002 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".