Forties Infill Drilling Eight Years on; Continued Success Through the Application of Thorough Development Geoscience Driven by 4D Seismic
Bibliographic record
Abstract
Abstract In the eight years since Apache purchased the Forties Field from BP over 100 infield targets have been drilled with an overall success rate of 74%. As a result of this infill drilling campaign the field production rate has been held at a plateau rate of 60,000 bopd despite an average rate of 41,000 bopd in 2003, the year of purchase from BP. Indeed the success of this campaign has resulted in a shortage of sidetrack donor wells so there has been a return to surface drilling on all five platforms. Furthermore, to enable the full exploitation of the forward target portfolio Apache is installing a new 18 slot platform, the Forties Alpha Satellite Platform (FASP) in 2012. Key to Apache's success on Forties has been a constant drive to push the boundaries of 4D seismic interpretation and lithology prediction from seismic and the ability to integrate this information with local production and well data. In this paper case histories are presented to illustrate our approach to target generation and the evolution of target generation over time is evaluated. The above methodology has led to many convincing successes over the years. The acquisition of a new 4D seismic volume in 2010 has resulted in a significant boost to our drilling results, allowing us to have our most productive drilling 6 months to date, including one well with an initial production rate of 12,000 bopd, the highest initial rate recorded in the field since 1992.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".