ESP Operation, Optimization, and Performance Review: ConocoPhillips China Inc. Bohai Bay Project
Bibliographic record
Abstract
SPE Gulf Coast Section Electric Submersible Pump Workshop, The Woodlands, Texas, 25–27 April, 2007 Abstract ConocoPhillips China Inc. (COPC) operates the Penglai 19–3 oil field, located offshore in Bohai Bay, the People's Republic of China. COPC holds a production sharing agreement with China National Offshore Oil Corporation(CNOOC). The Penglai 19–3 field is the second largest oil field in China with 3.8 billion bbl of oil in place, discovered in May 1999 and put on productionin December 2002. Electrical submersible pumps (ESPs) were selected as the most economic artificial lift method to develop the field, based on the reliability, flexibility and robustness to produce wells with high flow rates and lift heavyoil in an offshore environment. The first ESP installations were challenged with high free gas and excessives and production, resulting in operational issues and a number of failures. Even in this hostile environment, production peaked at 37,800 BOPD during November 2003, before declining as a consequence of reservoir pressure depletion. Moreover, the lower reservoir pressure increased the free gas, thereby reducing pump performance, excessive sand production lead to plugging of the pumping system and sand fill across the reservoir reduced productivity. Various enhancements to the completion and ESP system were made during subsequent well interventions improving ESP performance, maximizing and maintaining production from the field. Furthermore, performing continuous ESP data trend analysis and performance modeling enabled the artificial lift system to be analyzed and diagnosed to maintain optimum well performance. Collaboration between Operator and Service Provider through performance review meetings and changes to operational practices were also implemented. This paper reviews the operation, optimization, and performance of the ESP systems and the challenges faced during the first 3 years of production. Covering initial installations, subsequent well interventions, operation philosophy, optimization methodology, case studies demonstrating value of gas separation and handling devices, completion improvements, ESP configuration enhancements, run life assessment and equipment dismantle findings.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".