Characterization of Production Commingled From Deep Basin Plays, Wild River Region of Western Alberta
Bibliographic record
Abstract
Abstract Previous study of unconventional tight gas plays in the Deep Basin area of the Western Canadian Sedimentary Basin identified a rapidly increasing volume of production and EUR developed in wells where production is commingled from multiple reservoirs in stacked plays. Historically, most Deep Basin wells were drilled for a primary target play – a single play strategy – and completed producing from a single play. However from 2007 to 2008, over 40% of the EUR connected in all Deep Basin plays was from multiplay producers. Extensive commingling to maximize the recovery per well and reductions in segregation and testing costs should improve well economics and increase total recovery. However, commingling multiple plays often obscures information important for resource characterization by play, such as: EUR per zone, individual zone productivity, producing success by play and well spacing by play. Commingling is especially common in the Wild River region of the Deep Basin area, where up to eight potential plays may be stacked for completion. This paper will discuss the characteristics and distribution of commingled wells in the Wild River region. What is the impact of these multi-play wells in terms of activity, EUR connected and supply compared to single play wells? Where are the commingled play wells located? Which plays are targeted in terms of zones penetrated? Which plays are completed most frequently in these commingled wells? Is recovery per well improving with experience? Does recovery improve as more plays are completed? What is the overall success rate in this area? What is the density per section of Deep Basin producing wells? How do strategies and results vary by operator? Based on the results observed in the Wild River region, the implications for resource estimates and development in other areas of the Deep Basin will be discussed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".