Zonal Isolation Technology Case History
Bibliographic record
Abstract
Abstract Mitchell Energy first unlocked the potential of unconventional shale reservoirs in the Barnett shale through numerous hydraulic fracturing experiments. Fracturing techniques have evolved and led to new shale exploration in North America. The most common completion style in the market is the plug-and-perforate method where composite plugs are spaced into a wellbore to divert the hydraulic fracturing treatment to a specific zone in the reservoir. After each wellbore is thoroughly fractured, coiled tubing or threaded pipe, in tandem with positive displacement motors, is summoned to remove the composite plugs from the wellbore to enable production. The paper describes the run history of new zonal isolation technology that provides operators with benefits that improve operational efficiency and enable earlier production. The paper will focus on two regions; the Horn River Basin in British Columbia and the Utica Shale in the Northeastern United States. The benefits from the technology include eliminating the need for composite plug removal after the conclusion of all zonal stimulations, and a larger than traditional inside diameter (ID) through which high-rate flowback and production is accommodated. An integral aspect of the technology is the use of disintegrating fracturing balls that rapidly deteriorate after stimulation. By eliminating composite plug removal, operators spend fewer days on location, reducing health, safety, and environmental risks. Because coiled tubing is no longer needed for post-fracture treatment plug drilling, operators can also complete longer lateral wellbores more quickly and economically. In general, operators realize reduced total zonal completion cost and achieve quicker production when compared to traditional plug-and-perforate (PNP) completion methods. As exploitation of unconventional reservoirs grows globally, the technology enables operators more flexibility in designing completions, particularly in remote locations.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.025 | 0.004 |
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".