Sand Control Through Frac Pack: Learnings from Over 400 Wells in the Penglai Oilfield, Bohai Bay, China
Bibliographic record
Abstract
Abstract After many years of field trials, cased hole frac pack has become the primary sand control and production enhancement method in developing the unconsolidated formations in the Penglai oilfield, Bohai Bay, China. The thick productive formations have low net-to-gross ratios, and the sandstone pays are separated by weak mudstones. This paper presents field cases of successful frac pack design and operations in the Penglai Oilfield. This study reviews the sand control methods adopted in the Penglai oilfield and presents the major challenges in their field trials. The first cased-hole frac pack pilot was executed in 2008, followed by a four-well extended trial in 2009. After the field proof-of-concept, the large-scale adoption of frac pack began in 2011. Since then, continuous efforts have been made to optimize the key design parameters in successful frac packs, including perforation design, fracturing fluid, gravel placement, job size, downhole tools, etc. Well inflow modeling, laboratory evaluation and field trials have been performed and integrated in these optimization studies. The study showcases over 400 frac-packed wells and more than 1500 stages, demonstrating the effectiveness of frac pack as an efficient sand control method when appropriately designed. This paper thoroughly examines the reservoir characteristics and key completion parameters during the frac pack, encompassing well architecture, net perforation thickness, perforation flow area, fracturing fluid, proppant, and various frac pack pumping parameters. Additionally, the paper summarizes key challenges, best practices, and valuable insights derived from extensive well data analysis. Results from this study emphasize the importance of maintaining the key design variables and call for the continuous optimization for the frac pack completion technology in waterflooded formations. The paper also presents an integrated frac pack design approach that combines frac simulation, lab testing, and perforation optimization. This design approach has been successfully implemented in a large-scale well campaign in the Penglai oilfield. These findings contribute to the knowledge base of sand control and production enhancement in unconsolidated formations and provide key insights for improving the frac pack technology.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".