Turquoise hydrogen to reduce emissions of the north American oil upstream sector
Bibliographic record
Abstract
In Canadian remote oil sites, natural gas extracted with the bitumen is flared or vented, impacting on the environment. Providing a pipeline network to recover the gas is unaffordable in most cases. Here we propose the economic framework of an innovative process to recover the gas, based on pyrolysis at T = 1223 K and P = 0.1 MPa, performed in situ. Part of produced hydrogen combusts to sustain the process, while solid carbon is sold. We conceptualised and simulated in Aspen Plus two process alternatives. In configuration 1, the remaining part of hydrogen is sent to a gas turbine, where it burns to produce electricity. In configuration 2, the unburnt hydrogen is purified and sold. Both configurations reduce CO 2 emissions by more than 92 % compared to flaring. Both configurations produce a profit over 10 years, being their IRR above 20 % and payback time below 3.5 y. • Flaring and venting natural gas contribute to 1.7 % of Canada’s global emissions. • Methane pyrolysis is a promising technology to abate oil sector’s emissions. • We present techno-economics and sensitivity analysis of two process alternatives. • Turquoise H 2 sustains energetically the process that produces carbon, to be sold. • Emissions compared to the flaring scenario are reduced by over 90 %.
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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 | 0.000 | 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 | 0.001 | 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 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".