Cargo scheduling decision support for offshore oil and gas production: a case study
Woodside Energy Ltd (Woodside), Australia’s largest independent oil and gas company, operates multiple oil and gas facilities off the coast of Western Australia. These facilities require regular cargo shipments from supply vessels based in Karratha, Western Australia. In this paper, we describe a de...
| Main Authors: | , , , |
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| Format: | Journal Article |
| Published: |
Springer New York LLC
2017
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| Online Access: | http://hdl.handle.net/20.500.11937/52760 |
| _version_ | 1848759004073820160 |
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| author | Mardaneh, Elham Lin, Qun Loxton, Ryan Wilson, N. |
| author_facet | Mardaneh, Elham Lin, Qun Loxton, Ryan Wilson, N. |
| author_sort | Mardaneh, Elham |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | Woodside Energy Ltd (Woodside), Australia’s largest independent oil and gas company, operates multiple oil and gas facilities off the coast of Western Australia. These facilities require regular cargo shipments from supply vessels based in Karratha, Western Australia. In this paper, we describe a decision support model for scheduling the cargo shipments to minimize travel cost and trip duration, subject to various operational restrictions including vessel capacities, cargo demands at the facilities, time windows at the facilities, and base opening times. The model is a type of non-standard vehicle routing problem involving multiple supply vessels—a primary supply vessel that visits every facility during a round trip taking at most 1 week, and other supply vessels that are used on an ad hoc basis when the primary vessel cannot meet all cargo demands. We validate the model via test simulations using real data provided by Woodside. |
| first_indexed | 2025-11-14T09:52:59Z |
| format | Journal Article |
| id | curtin-20.500.11937-52760 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T09:52:59Z |
| publishDate | 2017 |
| publisher | Springer New York LLC |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-527602019-02-19T05:36:18Z Cargo scheduling decision support for offshore oil and gas production: a case study Mardaneh, Elham Lin, Qun Loxton, Ryan Wilson, N. Woodside Energy Ltd (Woodside), Australia’s largest independent oil and gas company, operates multiple oil and gas facilities off the coast of Western Australia. These facilities require regular cargo shipments from supply vessels based in Karratha, Western Australia. In this paper, we describe a decision support model for scheduling the cargo shipments to minimize travel cost and trip duration, subject to various operational restrictions including vessel capacities, cargo demands at the facilities, time windows at the facilities, and base opening times. The model is a type of non-standard vehicle routing problem involving multiple supply vessels—a primary supply vessel that visits every facility during a round trip taking at most 1 week, and other supply vessels that are used on an ad hoc basis when the primary vessel cannot meet all cargo demands. We validate the model via test simulations using real data provided by Woodside. 2017 Journal Article http://hdl.handle.net/20.500.11937/52760 10.1007/s11081-017-9348-3 Springer New York LLC fulltext |
| spellingShingle | Mardaneh, Elham Lin, Qun Loxton, Ryan Wilson, N. Cargo scheduling decision support for offshore oil and gas production: a case study |
| title | Cargo scheduling decision support for offshore oil and gas production: a case study |
| title_full | Cargo scheduling decision support for offshore oil and gas production: a case study |
| title_fullStr | Cargo scheduling decision support for offshore oil and gas production: a case study |
| title_full_unstemmed | Cargo scheduling decision support for offshore oil and gas production: a case study |
| title_short | Cargo scheduling decision support for offshore oil and gas production: a case study |
| title_sort | cargo scheduling decision support for offshore oil and gas production: a case study |
| url | http://hdl.handle.net/20.500.11937/52760 |