Assessing groundwater vulnerability to shale gas activities in the Sussex area, southern New Brunswick
Bibliographic record
Abstract
A project studying potential hydrocarbon migration through natural pathways or fracking-induced fractures from deep (~2 km) Carboniferous shale or tight sand units to shallow aquifers was initiated in 2015 in the Sussex area, southern New Brunswick. The study area includes the McCully gas field that has been in production since 2001 and the Elgin field that is investigated for its condensate potential. Because the intermediate zone located between shallow aquifers and units targeted for hydrocarbon production is poorly characterized, this project relies on the integration of data from different earth science disciplines, including geology, geophysics, geomechanics, hydrogeology and water and rock geochemistry. Fieldwork in 2016-2017 comprised the drilling of observation wells, borehole geophysics, hydraulic tests and groundwater and rock sampling. Initial groundwater chemistry shows that only a few wells contain methane (< 5 mg/L) with either a thermogenic (McCully gas field) or a microbial (Elgin area) signature. One well in the McCully gas field showed some ethane in groundwater, as well as small amounts of gaseous methane in core samples, while drill cuttings revealed the presence of long-chain hydrocarbons. Rock-Eval analyses of shallow cores showed very low S1, S2 and TOC values, except for that specific well. 3-D seismic data have been reprocessed and the resulting geological interpretation revealed that faults are mostly confined within the Horton Group, where the two units targeted by the industry are located. In addition, the geomechanical study concluded that the intermediate zone provides an effective barrier to induced fractures, based on well logs. The development of numerical groundwater flow models (from 1D to 3D) is ongoing. This study will provide a scientific basis to support informed decisions by provincial authorities on future hydrocarbon development.
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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 | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".