Recent impacts of light olefin demands on refining processes
Bibliographic record
Abstract
Global demand for light olefins (ethylene and propylene) points to strong prospects for growth, stimulating investments in overall productive capacity. With propylene demand growing slightly faster than that of ethylene, rising prices and difficulties in supplies of petrochemical feedstocks such as naphtha or natural gas, steam crackers alone are not able to fill the light olefins gap nor do they allow extraordinary margins. As petrochemical market dynamics also influence refining activities, there has been significant progress in the development of technologies for petrochemical refining, leading to a larger degree of integration between the refining and petrochemical industries. This integration offers great opportunities for synergism since both industries share many common challenges, like increasing process efficiency, meeting more severe environmental requirements and optimizing the use of utilities. New specifications for fuels also contribute to this approximation since additional olefinic and aromatic hydrocarbon streams will become available in refineries. Petrochemical FCC is an example of advances in petrochemical refining. Based on a higher severity operation of the traditional FCC, it permits high ethylene and propylene yields, besides producing highly aromatic naphtha. However, to take full advantage of the opportunity to add value to non-conventional oils (which tend to increase in importance in oil markets) while to still have enough feedstock for cracking, deep conversion and treatment processes should also be present in refining schemes. Refinery off-gases correspond to another alternative feedstock for petrochemicals. Thus, a refinery (originally projected for production of fuels) has become an alternative source of petrochemicals, making possible the conception of petrochemical refineries that may be integrated or not to a petrochemical complex. This paper provides an overview of the recent impacts of light olefin demands on refining processes as well as an update of the refining-petrochemistry scenario in the world.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 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".