Simultaneous Operations in Multi-Well Pad: a Cost Effective way of Drilling Multi Wells Pad and Deliver 8 Fracs a Day
Bibliographic record
Abstract
Abstract Unconventional gas or tight shale-oil plays require a high density of wells and multistage hydraulic fracturing to economically develop. This leads to the use of high density well pads to reduce land costs, associated environmental impact and well delivery efficiency through batch drilling. A pad in Shell's North American assets of Groundbirch and Fox Creek (Canada), Appalachia, Permian and Eagleford (USA) can comprise of two opposing rows of 13 - 20 horizontal wells spaced three to six meters apart. Considering it takes an average of 14 days to drill a 5,000m well and a subsequent nine days to complete the multistage hydraulic fracturing sequence, a typical 26 well pad in the Grounbirch asset would take approximately two years from spud to first gas. Simultaneous Operations (SIMOPS) is defined as when two or more mutually exclusive activities take place within 50m of a wellbore, or each other. The activities are classified as critical and have to be carefully planned to ensure the safety of all personnel involved and comply with regulatory spacing stipulations. This paper aims to illustrate how Shell Canada implemented SIMOPS; further highlighting how rig operations were successfully co-ordinated during a restrictive weather period (melting snow and associated road bans) and how simultaneous completion operations were utilized to achieve eight hydraulic fracturing jobs, or ‘fracs’, a day, averaging 6.2 fracs/day over 13 wells.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".