TECHNICAL AND OPERATING SUPPORT FOR PILOT DEMONSTRATION OF MORPHYSORB ACID GAS REMOVAL PROCESS
Bibliographic record
Abstract
GTI and Krupp Uhde have been jointly developing advanced technology for removing high concentrations of acid gas from high-pressure natural gas for over a decade. This technology, the Morphysorb{reg_sign} process, based on N-formyl and N-acetyl morpholine mixtures, has now been tested in a large-scale facility and this paper presents preliminary results from acceptance testing at that facility. Earlier publications have discussed the bench-scale and pilot plant work that led up to this important milestone. The site was Duke Energy's new Kwoen sour gas upgrader near Chetwynd B.C., Canada. This facility has a nameplate capacity of 300 MMscfd of sour natural gas. The objective of the Morphysorb process at this site was to remove 33 MMscfd of acid gas (H{sub 2}S and CO{sub 2}) for reinjection downhole. This represents about half the acid gas present in the feed to the plant. In so doing, proportionately more of the plant ''sales'' gas, which is sent for final processing at the nearby Pine River plant, can be sent down the line without coming up against the sulfur removal capacity limits of Pine River plant, than could with other solvents that were evaluated. Other benefits include less loss of methane downhole with the rejected acid gas and lower circulation and recycle compression horsepower than with competitive solvents. On the downside, the process is expected to have higher solvent vaporization losses than competitive solvents, but this is a comparatively minor drawback when weighed against the value of the benefits. These benefits (and drawbacks) were developed into quantitative ''acceptance'' criteria, which will determine if the solvent will continue to be used at the site and for award of monetary bonuses to the process developer (GTI).
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.
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 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.018 | 0.003 |
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".