First Field Application in Canada of Carbon Dioxide Separation for Hydraulic Fracture Flow Back Operations
Bibliographic record
Abstract
Abstract Carbon dioxide has a long history of successful usage in hydraulic fracturing fluids, dating as far back as 1962. The Canadian Deep Basin area is known to contain many water desiccated natural gas reservoirs which are very amenable to carbon dioxide based stimulation. Another major advantage of carbon dioxide use is to displace fresh water, reducing environmental impacts. However, in recent years, some operators have moved away from carbon dioxide, due to difficulties related to the contaminated gas stream during fracture flow back operations. An extended period of flaring may be required to reduce the carbon dioxide content to acceptable levels in the sales pipeline. This may contribute to longer periods of flaring, noise and light pollution, increased green house gas emissions, as well as lost revenue to the operator, as otherwise saleable natural gas and gas liquids are being flared. This paper will outline the development of portable trailer mounted membrane separation equipment for well site separation of carbon dioxide from natural gas. The equipment used and how the process works will be discussed. Included is documented information from what is believed to be the first successful deployment of this equipment in Canada, on a well site near Grande Prairie, AB. Process information on flow rates, pressures, carbon dioxide inlet and sales content, etc. will be included. The development of this equipment has many benefits, including reduced flaring, increased sales volumes for the operator, increased royalties for governments, etc. Operators may now take advantage of the reservoir enhancing benefits of carbon dioxide, without any of the negative flow back issues. In conclusion, we will discuss future research and developments that will reduce or eliminate carbon dioxide venting at the well site.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".