Optimal design for real-time quantitative monitoring of sand in gas flowline using computational intelligence assisted design framework
- Submitting institution
-
Glasgow Caledonian University
- Unit of assessment
- 12 - Engineering
- Output identifier
- 33060454
- Type
- D - Journal article
- DOI
-
10.1016/j.petrol.2019.03.024
- Title of journal
- Journal of Petroleum Science and Engineering
- Article number
- -
- First page
- 1059
- Volume
- 177
- Issue
- -
- ISSN
- 0920-4105
- Open access status
- Compliant
- Month of publication
- March
- Year of publication
- 2019
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
2
- Research group(s)
-
-
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This paper presents a novel application of a computational intelligence [grey wolf optimisation of an ANN] to the challenging problem of sand monitoring in flowlines in the oil and gas sector. This work has generated interest following a presentation at the Sand Management Network in Aberdeen and has led to the development of a joint research funding proposal with TechnipFMC. This work is an application and expansion of an established theory to a new field with the potential for impact on safety and maintenance strategies. Published in a Q1 journal in the field of petroleum engineering.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
