{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,28]],"date-time":"2026-02-28T06:13:31Z","timestamp":1772259211918,"version":"3.50.1"},"reference-count":73,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2021]]},"DOI":"10.1109\/access.2021.3117891","type":"journal-article","created":{"date-parts":[[2021,10,5]],"date-time":"2021-10-05T04:25:24Z","timestamp":1633407924000},"page":"137063-137082","source":"Crossref","is-referenced-by-count":16,"title":["A Data-Driven Decision Support Tool for Offshore Oil and Gas Decommissioning"],"prefix":"10.1109","volume":"9","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3020-4971","authenticated-orcid":false,"given":"Pattaramon","family":"Vuttipittayamongkol","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Aaron","family":"Tung","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8342-9026","authenticated-orcid":false,"given":"Eyad","family":"Elyan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref73","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2007.03.021"},{"key":"ref72","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.2998723"},{"key":"ref71","article-title":"Towards machine learning-driven practices for oil and gas decommissioning—Introduction of a new offshore pipeline dataset","author":"vuttipittayamongkol","year":"2021","journal-title":"Proc 9th Int Conf Comput Commun Manage"},{"key":"ref70","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2020.106631"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.3001149"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1016\/S0167-9473(99)00095-X"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.2990152"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.2523\/IPTC-19693-MS"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.30632\/PJV59N6-2018a1"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1016\/j.petrol.2019.106681"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.4324\/9781351281881-10"},{"key":"ref36","first-page":"8887","article-title":"Application of machine learning technique to predict crude distillation column inlet temperature\/furnace coil outlet temperature in order to maximize distillate yield and to minimize fuel firing in furnaces","volume":"975","author":"kundu","year":"2021","journal-title":"Int J Comput Appl"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.18637\/jss.v028.i05"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1016\/j.petrol.2020.107818"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.2118\/202477-PA"},{"key":"ref62","doi-asserted-by":"publisher","DOI":"10.1016\/j.petrol.2019.106682"},{"key":"ref61","doi-asserted-by":"publisher","DOI":"10.1016\/j.scitotenv.2018.12.193"},{"key":"ref63","doi-asserted-by":"publisher","DOI":"10.1007\/s13202-019-0657-2"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2019.2947701"},{"key":"ref64","doi-asserted-by":"publisher","DOI":"10.1071\/AJ20026"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1023\/A:1010920819831"},{"key":"ref65","doi-asserted-by":"publisher","DOI":"10.4043\/30824-MS"},{"key":"ref66","article-title":"An exploration of stakeholder impacts on the decommissioning of offshore oil and gas facilities–the design, development, and analysis of stakeholder oriented critical paths for United Kingdom and Australia","author":"tung","year":"2021"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/TIT.1968.1054155"},{"key":"ref67","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2017.06.061"},{"key":"ref68","doi-asserted-by":"publisher","DOI":"10.1142\/S0129065720500434"},{"key":"ref69","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2019.08.062"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.19139\/soic-2310-5070-651"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ejpe.2019.06.006"},{"key":"ref20","first-page":"1","article-title":"Prediction of industrial debutanizer column compositions using data-driven ANFIS and ANN-based approaches","volume":"2021","author":"fatima","year":"2021","journal-title":"Neural Comput Appl"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.2118\/199203-MS"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2012.02.104"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1016\/j.petrol.2019.01.113"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1115\/OMAE2019-96363"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1007\/11538059_91"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1190\/tle35100906.1"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1016\/j.psep.2020.09.038"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2013.10.039"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.3997\/2214-4609.201900988"},{"key":"ref58","doi-asserted-by":"crossref","first-page":"1","DOI":"10.3389\/fmars.2021.642539","article-title":"Trash or treasure? Considerations for future ecological research to inform oil and gas decommissioning","volume":"8","author":"schl\u00e4ppy","year":"2021","journal-title":"Frontiers in Marine Science"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1016\/j.ejrs.2017.02.003"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2018.09.082"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1016\/j.petrol.2019.02.045"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1016\/j.measurement.2018.05.069"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1109\/DRBSD-549595.2019.00012"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2016.02.026"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1002\/cpe.5655"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1016\/j.ocecoaman.2018.10.024"},{"key":"ref40","article-title":"A review of multi-attributes decision-making models for offshore oil and gas facilities decommissioning","author":"li","year":"2021","journal-title":"Journal of Ocean Engineering and Science"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1007\/s10489-011-0287-y"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1016\/j.marpolbul.2018.07.077"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2017.11.077"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1016\/j.oceaneng.2016.12.030"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1613\/jair.953"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1071\/AJ20024"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-24334-4_8"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1016\/j.energy.2020.119708"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2021.3082557"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.3390\/e19060247"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.3390\/pr9071194"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1016\/j.egyai.2020.100031"},{"key":"ref8","first-page":"36","article-title":"SMOGN: A pre-processing approach for imbalanced regression","author":"branco","year":"2017","journal-title":"Proc 1st Int Workshop Learn Imbalanced Domains Theory Appl"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1002\/cpe.6031"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.3390\/s20236793"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2018.11.100"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2020.113236"},{"key":"ref45","doi-asserted-by":"crossref","DOI":"10.1038\/s41598-020-76432-4","article-title":"Prognostic value of texture analysis from cardiac magnetic resonance imaging in patients with Takotsubo syndrome: A machine learning based proof-of-principle approach","volume":"10","author":"mannil","year":"2020","journal-title":"Sci Rep"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1201\/9781420035933"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1093\/reep\/rey018"},{"key":"ref42","author":"mackenzie","year":"2021","journal-title":"Global Decommissioning Anxiety Rises"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1016\/j.petrol.2020.107013"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1016\/j.jngse.2020.103512"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1016\/j.petrol.2019.106486"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6287639\/9312710\/09558855.pdf?arnumber=9558855","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,12,17]],"date-time":"2021-12-17T19:55:51Z","timestamp":1639770951000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9558855\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"references-count":73,"URL":"https:\/\/doi.org\/10.1109\/access.2021.3117891","relation":{},"ISSN":["2169-3536"],"issn-type":[{"value":"2169-3536","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021]]}}}