Chemical Tracing Diagnostic Application for Monitoring Flow Contribution in Unstimulated Open Hole Multi-Lateral Wells Utilizing An Engineered Solid Carrier
Bibliographic record
Abstract
Abstract The oil and gas industry approaches field development in many ways. One approach is to drill and produce unstimulated open-hole horizontal multilateral (also referred to as multileg) wells. The Clearwater formation, among others in the Western Canadian Sedimentary Basin (WCSB) is an excellent example of this strategy. A method to positively determine flow contribution from each leg has been historically lacking. An innovative approach, using existing tracer technology is now available to provide these insights. As drilling is completed for each lateral leg, a unique oil soluble tracer, chemically bonded to a resin (sand-like) solid carrier is displaced out the drilling string while pulling out of hole. This tracer is normally spotted in the toe region to provide toe flow monitoring; Occasionally, a second unique tracer is spotted halfway through the same leg for mid leg flow monitoring. Volumetric calculations estimate required volumes for displacement. This process is repeated with unique tracers for each displacement. Hydrocarbon samples collected at surface upon initial production are analyzed for the presence of these tracers to assess contribution from each traced section. Over the last three (3) years, oil tracers have been utilized in approximately two hundred (200) multilateral wells to monitor hydrocarbon contribution of each drilled/traced leg. On average these wells have six (6) legs but can range from two (2) to more than ten (>10). Approximately one thousand two hundred (1,200) individual lateral legs have been traced and monitored. Oil sample analyses results have provided indication of which legs contribute initial flow, or present partial or total leg integrity concerns. While sampling schedules are typically designed for three (3) months of monitoring, oil soluble tracers are detectable in produced hydrocarbon for periods ranging from weeks to months, depending mainly on production rates. Tracer concentrations provide a relative productivity assessment of each leg over time. Overall, the deployment of oil tracers with a solid carrying mechanism in unstimulated open hole multilateral wells has provided operators with an efficient strategy to verify hydrocarbon contribution from each individual leg. Future work to increase value of this diagnostic application aims to integrate tracer characteristic performance of each multilateral well with its production, drilling, and subsurface datasets, to identify patterns and correlations between datasets to assist operators in their development plans. Additionally, future work aims to extend the tracer detection window to allow for monitoring multilateral wells that present elevated borehole collapse risk beyond the initial months of flow.
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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 | 0.000 |
| 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) | 0.001 | 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".