The minimum fluid flow velocity to ensure particle transport is an essential design and operation consideration for pipelines of oil and gas production. This flow velocity is difficult to estimate due to complex nature of the physical processes. It has been shown that the model predictions may vary several orders of magnitude for the same inputs. This paper introduces a systematic approach to reduce this discrepancy using data clustering, model selection, and cluster identification techniques. The case study results show that the H-spread of the error percentages between the predictions and experimental velocities are reduced from 71.6 % to 34.4 %.
Data Clustering for Uncertainty Reduction – A Case Study of Solids Transport in Oil/Gas Pipelines
2014
6 Seiten, 6 Quellen
Aufsatz (Konferenz)
Englisch
Hydraulic transportation of solids in vertical pipelines
TIBKAT | 1981
|Hydraulic transportation of solids in horizontal pipelines
TIBKAT | 1959
|Britannia Export Pipelines: A Case Study
British Library Conference Proceedings | 1998
|Testing explores SET for transport pipelines
Tema Archiv | 2007
|Transport av flytgödsel i rörledning = (Transport of slurry in pipelines)
Katalog Agrar | 1992
|