TY - GEN
T1 - An approach to reduce the amount of ili data in fatigue analysis of pits in pipelines
AU - Larrosa, Nicolas O.
AU - Lopez-Crespo, Pablo
AU - Ainsworth, Robert A.
N1 - Publisher Copyright:
Copyright © 2017 ASME.
PY - 2017
Y1 - 2017
N2 - This paper presents a screening methodology that is used to reduce the amount of data requiring detailed analysis from that obtained during in-line inspection (ILI). The methodology uses ILI outputs (dimensions of flaws, orientation and distance from starting point) to generate a visualisation of the pits within the pipeline, a ranking of pits in terms of sphericity (roundness) and depth, to evaluate pit density and generate the models for finite element analysis. The rendering tool allows a clearer view of defects within the pipelines and provides a simplified way to focus on critical pits. For a particular case of in-field data provided by BP, the number of pits in a 12-inch riser of 11 km length was reduced from 1750 obtained to 43, 15 or 4 requiring analysis, depending on the level of conservatism introduced by the analyst. The tool will allow Oil and Gas owners and operators to reduce the immense amount of data obtained during pigging to a much less time-consuming set for flaw assessment.
AB - This paper presents a screening methodology that is used to reduce the amount of data requiring detailed analysis from that obtained during in-line inspection (ILI). The methodology uses ILI outputs (dimensions of flaws, orientation and distance from starting point) to generate a visualisation of the pits within the pipeline, a ranking of pits in terms of sphericity (roundness) and depth, to evaluate pit density and generate the models for finite element analysis. The rendering tool allows a clearer view of defects within the pipelines and provides a simplified way to focus on critical pits. For a particular case of in-field data provided by BP, the number of pits in a 12-inch riser of 11 km length was reduced from 1750 obtained to 43, 15 or 4 requiring analysis, depending on the level of conservatism introduced by the analyst. The tool will allow Oil and Gas owners and operators to reduce the immense amount of data obtained during pigging to a much less time-consuming set for flaw assessment.
UR - https://www.scopus.com/pages/publications/85031917005
U2 - 10.1115/OMAE201762594
DO - 10.1115/OMAE201762594
M3 - Conference contribution
AN - SCOPUS:85031917005
T3 - Proceedings of the International Conference on Offshore Mechanics and Arctic Engineering - OMAE
BT - Structures, Safety and Reliability
PB - American Society of Mechanical Engineers (ASME)
T2 - ASME 2017 36th International Conference on Ocean, Offshore and Arctic Engineering, OMAE 2017
Y2 - 25 June 2017 through 30 June 2017
ER -