Continual long-term monitoring of methane in wells above the Utica Shale using total dissolved gas pressure probes
Bibliographic record
Abstract
Abstract Monitoring of dissolved methane concentrations in groundwater is required to identify impacts from oil and gas development and to understand temporal variability under background conditions. Currently, long-term (i.e., multiyear) monitoring is performed via periodic groundwater sampling; hence, the data are temporally limited and can suffer from degassing losses in-well and at surface for groundwater with high dissolved gas concentrations. The application of total dissolved gas pressure ( P TDG ) probes for long-term monitoring of methane-rich groundwater was investigated for >2 years in three monitoring wells in a low-permeability bedrock aquifer above the Utica Shale, Canada. The advantage of these probes is that they allow for continual in situ monitoring. A hydraulic packer was installed in each well, below which P TDG and water pressure were measured every 15 or 30 min. The major dissolved gas species composition, required to calculate methane concentrations from P TDG , was determined from groundwater samples collected approximately bimonthly. Methane was the dominant gas in each well (~80–97%), with relatively consistent composition over time, indicating P TDG provided a reasonable proxy for methane concentrations. All three wells had high P TDG (reaching 53.0 m H 2 O), with P TDG -derived methane concentrations (34–156 mg/L) much higher (3–12 times) and relatively more stable than determined by conventional groundwater analysis. P TDG monitoring also revealed substantial short-term changes during pumping and between sampling events (up to 4 m H 2 O), possibly associated with background variability. Limitations and technical remedies are discussed. This study demonstrates that P TDG probes can be a valuable tool for monitoring methane-rich groundwater.
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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 | 0.001 | 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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".