Online Production Optimisation on Ekofisk
Bibliographic record
Abstract
Abstract As part of the long tradition of innovative production growth and enhancement projects in the Greater Ekofisk Area, in 2004 ConocoPhillips Norway AS (COPNo) implemented the Onshore Operations Centre (OOC). The OOC facilitates improved collaborative working processes that optimise production and streamline operations through more proactive use of both field equipment and software tools. This paper describes the specification, development and implementation of the online production optimisation software used in this project. This software was provided and developed by EPS Ltd, a Weatherford company, in collaboration with COPNo. Specification of the system started in 2005, based on years of prior experience with network production modelling tools in the Ekofisk area, to simulate and optimise production from the reservoir to the export meter. The system is designed to fully utilise the OOC's continuous measurement and recording systems, throughout the entire production and process network. This production optimisation system aims to complement the existing informational displays and charts by the calibration and optimisation of complete network models several times a day. The optimisation results and comparison with real-time data and operating objectives are made available to users through a web interface so that they can be used by the operator and partner company staff at any location. Models of the wells and production/process network have been developed, following extensive discussions with all relevant disciplines, to ensure that these models can resolve the regular questions faced by the Greater Ekofisk operations teams. In addition to the daily simulation and optimisation scenarios run by the full, online system, the constituent parts of the full model can be also run offline to help evaluate exceptional production issues. The operator is experiencing benefits in two main categories firstly by identification of production problems with wells or plant that prevent the system from achieving target production and secondly by having continuously updated production scenarios available on which planning decisions can be based. These results will be discussed, with many examples.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 0.003 |
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".