Active fiber-optic distributed temperature sensing to assess the geothermal potential and groundwater flow over the traditional territory of the Lù'àn Män Ku Dän, Yukon
Bibliographic record
Abstract
The traditional territory of the Lù'àn Män Ku Dän (Kluane Lake People) is found along the Saint Elias Mountains in Yukon. It hosts the Burwash Landing community, home of the Kluane First Nation, which is one of eleven self-governing First Nations operating in tripartite with Yukon Government and Canada. Burwash Landing is primarily dependent on diesel for space heating and power generation. Cutting-edge technologies were deployed in the scope of geothermal resource assessment to evaluate the thermal state and properties of the subsurface. Active distributed temperature sensing was conducted with a composite heating and fiber-optic cable installed in the water column of two existing wells with the objective of quantifying the geothermal potential and groundwater flow along available wellbores. Heat injection tests were made in the 220 and 385 m deep wells located on the south and north side of the Denali fault, near a probable releasing bend that is favorable to permeability. Melting glacier water infiltrates in mountains and groundwater flows toward Kluane Lake, which is hypothesized to be a major groundwater discharge zone. The shallower well is at an altitude of 925 masl and intercepted 40 m of quaternary deposits before hitting fractured bedrock while the deeper well is at the valley bottom near the lake (altitude of 795 masl) and entirely drilled in quaternary deposits. Passive temperature monitoring was initially made and revealed a geothermal gradient of 34 ⁰C km-1 and 47 ⁰C km-1 in the shallow south side and deep north side wells. Heat was injected during active tests for 2 and 3 days and thermal recovery was monitored for 6 and 8 days, respectively. Temperature was measured every 25 cm at 4-minute intervals. The infinite line source equation and the superposition principle were used to analyze data and calculate a thermal conductivity profile. Nearly continuous ground thermal properties and temperature profiles were combined to assess the Earth natural heat flux, considering paleoclimate and topographic corrections. Analysis indicated a heat flux above 90 mW m‑2, thought to be favorable for geothermal resource development. Peclet number analysis was undertaken to infer horizontal groundwater flow in permeable horizons. Results are being used to develop a regional groundwater flow and heat transfer model to evaluate temperature at kilometer depth and assess the communities’ geothermal potential. This presentation will illustrate how active temperature sensing can be deployed to reduce geothermal exploration risks, acknowledging Kluane First Nation that allowed us to better understand groundwater flow in this magnificent territory.
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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".