Enhanced Multi-Zone Single Trip Sand-Control System Successfully Treats Six Zones in Offshore Indonesia
Bibliographic record
Abstract
Although multiple-zone, downhole sand-control tool systems have been in use since the early 1990s, these systems had been designed for jobs requiring low-pump-rates with low-pressure differentials. Multiple-zone systems capable of high fracturing pump rates and the associated differentials only recently have been introduced to the oilfield. Although these jobs are becoming more common, most of the completions have been limited to four or five discretely treated zones. This paper presents a case history from Indonesia in which a high pump rate, high differential pressure-rated single-trip multiple zone-sand control tool system was capable of treating six discrete zones in an offshore deployment. The challenges for this completion were numerous. Manufacturing lead time was very short, and the system would have to be adapted to the unique requirements of the completion design and the use of new components. Since the proppant and pump rating limit testing for these systems had been based on five zones, complicated calculations and extrapolations had to be used to ensure that the crossover tool would survive the erosive effects of treating six zones. To provide assurance of the service tool's elastomeric seal integrity, a testing program was executed between treatments to provide tracking and verification of conditions. Procedures and equipment would be in place to replace the service tools, if any leaks were evident. Since system installation experience was limited in this area, gathering sufficient knowledge and experience for system deployment had to be addressed quickly. This would require sharing of lessons learned, use of experienced personnel from previous installations, and conducting of detailed training discussions between subject matter experts and service personnel. Deployment challenges and solutions, successes experienced at the well site, and the actual performance of the operations will be detailed in the paper.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".