Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract The Horseshoe Canyon coal formation in Alberta, Canada is an anomaly for coals. It is dry, for the most part producing no formation water. Therefore, no dewatering is required. In fact, it is severely damaged by water influx. Normal permeability injection tests and conventional hydraulic fracturing techniques, even foams, have been unsuccessful in this environment. The best part of this reservoir has an areal extent in excess of 12,000 square miles containing 1-2 BCF per square mile of recoverable gas. Commercial development of this resource is a very appealing prospect. Numbers of coal seams vary from 5 to 30 per well, spread out over 600 – 1,300 ft. Individual seam thicknesses vary from 1 to 13 ft. Most seams are discontinuous over a large area. The better part of the formation has permeability in the range of 1 – 100 md. This makes it difficult to avoid damaging the formation during drilling and cementing operations, hence some type of stimulation is required. Nitrogen hydraulic fracturing is the only stimulation process that has had any success in this formation to date. The treatments involve pumping nitrogen at high rates, without proppant, through coiled tubing (CT) and a selective cup-type packer (SCP), isolating each coal seam while treating it. Bottomhole treating gradients vary greatly with an average of approximately 2.2 psi/ft. Whether these nitrogen treatments are in fact fracturing the formation or just having the damage flushed out has been a matter for speculation. Over 1,600 wells have been treated in this way and more continue to be added on an everyday basis. This paper describes the formation characteristics and geology of the Horseshoe Canyon coal and presents case histories of hydraulic fracturing treatments performed including production results.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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) | 0.000 | 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 it