Bibliographic record
Abstract
Abstract ADNOC has one of the largest Sulphur Granulation and Handling systems in the region designed for 22000 MTPD with a common main receiving/export facilities at Ruwais and two granulations facilities at Habshan and Shah fields that were commissioned in 2014. The sulphur is produced as a side product from the Gas Processing in particular from the Gas Sweetening Process that removes H2S then is converted to Liquid sulphur in the Sulphur Recovery Units (SRU) and finally that liquid sulphur is processed to produce Granulated Sulphur. In general, the higher the gas sourness (High H2S content) the higher the sulphur production. Production of large amount of granulated sulphur with the existing design had its impact on generating Sulphur Dust that raises HSE and integrity concenrs. Nevertheless the large scale sulphur granulation production and the sulphur dust issues did not stop ADNOC to produce a premium level granulated sulphur quality, that mainly follows SUDIC-Sulphur Development Institute of Canada-Specifications, where this product is being exported to different international markets since the commissioning of the plants couple years ago. The credit of ADNOC success goes to overcoming different challenges faced throughout the plants life cycle starting from the project (Study and execution levels), to commissioning and starting the normal operation and maintenance level up to date. This paper will introduce number of challenges in vels, design level and the operating level that stimulate sulphur dust generation in all the sites, .for which the current available challenges with the way of mitigation will be addressed along with addressing the different options that can be considered in future project. Such possible options available for enhancements in the current Sulphur Granulation and Handling Plants are listed below:–Drop height Reduction–Train Load-out Methodology–Dust Control System – Dust Suppression – by spraying surfactant Versus Dust Prevention System – by using foaming. Moreover, there are number of future different options that can be considered in the earlier stages of the project such as the study and the design stages, like: gramatic structure!!!–The transportation methodology such us using the road tracks to transfer the liquid sulphur or transferring the granulated sulphur from the granulations plants to export location via train. why?–For Granulated Sulphur the Storage mechanism of Stacking and Reclaiming selection between Booming or Pushing Stacking is significant in supporting maintaining the quality of the granulated Sulphur. The above challenges were handled to reduce its impact on producing the Sulphur Dust that is caused by the breakage of the granulated Sulphur. And the future options proposed above are things to be studied well before concluding and finalizing the selected options or/and methodology and the sections below will highlight the above challenges and future options in much details.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".