An Interdisciplinary Economic Appraisal of Plug-And-Perf Versus Single-Point Entry Completions Systems Using Simulation
Bibliographic record
Abstract
Abstract Selecting which formation access and interstage isolation approach is economically superior is difficult to assess due to the complex interactions of these systems’ impact on drilling and completions cycle time and cost and well performance. An integrated view is necessary to assess the economics of single-point entry sleeve completions systems and plug-and-perf systems. The difficulty is exacerbated by the uncertainty of the percentage of effective plug-and-perf clusters. This paper documents the use of commercial simulation software to precisely estimate the daily cashflows for the life of a well pad (from rig move to decommissioning) using designs based on each system. The plug-and-perf cluster efficiency percentage is swept, and the percentage at which its economics breakeven with the single-point entry scenario is calculated. This is performed for multiple subsurface areas whose well performance vary differently from one another as effective cluster spacing changes. Using NPV/section, it was discovered plug-and-perf scenarios needed a cluster efficiency between 38-52% to breakeven with the corresponding single-point entry scenario. However, these results are highly dependent on an operator's contractual frameworks, well performance, and well production constraints.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".