Analysis of Nitrogen Stimulation Technique in Shallow CBM Formations
Bibliographic record
Abstract
Abstract Nitrogen (N2) stimulation has become the preferred technique for stimulation of coal seams in the Horseshoe Canyon play in Alberta. It consists of stimulating each seam by pumping at very high rates for short time (2-4 mins). Because the coal is producible at shallow depths, ERCB has been developing and updating regulatory guidelines that aim to protect the freshwater supply. This study was undertaken to improve the understanding of the process and provide recommendations on the regulatory guidelines for shallow depth (less than 200 m). The study was provided with extensive data from the industry (over 20,000 fractures in over 2000 wells) and has carried out several types of analyses in order to estimate fracture orientation and dimensions, and their dependence on N2 injection rate, duration and reservoir parameters. This included statistical analysis of large amounts of surface pressure data, pressure transient analysis of downhole pressure data, analysis of fracture mapping data, and conceptual simulations of the injection process using coupled reservoir and geomechanical models. Coupled geomechanical modeling provided realistic physical model of the process (in contrast to conventional models). Stress dependence of coal permeability and permeability anisotropy were shown to be the controlling mechanisms. This model was then used to investigate height growth mechanisms. After considering the results of the analysis, its limitations, uncertainties in geological description of the coal and shale sequences, available case histories, and other factors, recommendations were made for modifications of the ERCB Shallow fracturing Directive 27.
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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 | 0.001 | 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".