dc.contributor.advisor | Tomasgard, Asgeir | |
dc.contributor.advisor | Fleten, Stein-Erik | |
dc.contributor.advisor | Gounaris, Chrysanthos | |
dc.contributor.author | Bakker, Steffen Jaap | |
dc.date.accessioned | 2020-10-06T07:19:03Z | |
dc.date.available | 2020-10-06T07:19:03Z | |
dc.date.issued | 2020 | |
dc.identifier.isbn | 978-82-326-4997-6 | |
dc.identifier.issn | 1503-8181 | |
dc.identifier.uri | https://hdl.handle.net/11250/2681237 | |
dc.description.abstract | This thesis applies operations research methods to planning problems related to the plugging and abandoning of offshore oil and gas wells. We consider two problem settings, for which we develop new models and solution approaches.
The first problem is on a tactical planning level and considers the optimal planning of a plugging campaign. The problem is defined as a variant of an uncapacitated vehicle routing problem with time-windows and is being treated in the first three papers in this thesis. We focus on different aspects, ranging from the application of different model formulations and solution methods, to obtaining more economically oriented insights. A main finding is that significant cost-savings can be made by using the developed methodology for planning plugging campaigns, as opposed to conventional methods. In addition, we contribute to the vehicle routing literature by developing a methodology that allows for incorporating a learning effect. That is, the time it takes to perform a particular operation reduces as similar operations have been performed before.
The second problem considers the strategic problem of developing a mature offshore oil field, and is treated in the fourth paper. We develop a multistage stochastic integer program and solve it using the stochastic dual dynamic integer programming algorithm (SDDiP). The problem can be considered to represent a portfolio of real options, incorporating both shutdown and expansion options. We show that the SDDiP algorithm is very suitable for solving complex real options problem. This enables us to perform an extensive analysis on factors affecting the abandonment decision. We show that traditional real options findings for single options might behave differently when considered in portfolios. | en_US |
dc.language.iso | eng | en_US |
dc.publisher | NTNU | en_US |
dc.relation.ispartofseries | Doctoral theses at NTNU;2020:324 | |
dc.relation.haspart | Paper 1: Bakker, Steffen J.; Aarlott, Mats Mathisen; Tomasgard, Asgeir; Midthun, Kjetil Trovik. Planning of an Offshore Well Plugging Campaign: A Vehicle Routing Approach. Lecture Notes in Computer Science (LNCS) 2017 ;Volum 10572 LNCS. s. 158-173
https://doi.org/10.1007/978-3-319-68496-3_11 | en_US |
dc.relation.haspart | Paper 2: Bakker, Steffen J.; Vrålstad, Torbjørn; Tomasgard, Asgeir. An optimization model for the planning of offshore plug and abandonment campaigns. Journal of Petroleum Science and Engineering 2019 ;Volum 180. s. 369-379
https://doi.org/10.1016/j.petrol.2019.05.042
This is an open access article under the CC BY-NC-ND license | en_US |
dc.relation.haspart | Paper 3: Bakker, Steffen J.; Wang, Akang; Gounaris, Chrysanthos. Vehicle routing with endogenous learning: Application to offshore plug and abandonment Campaign Planning.
European Journal of Operational Research 2020
https://doi.org/10.1016/j.ejor.2020.06.039 | en_US |
dc.relation.haspart | Paper 4:
Bakker, Steffen Jaap; Kleiven, Andreas; Fleten, Stein-Erik; Tomasgard, Asgeir.
Mature offshore oil field development: solving a real options problem using stochastic dual dynamic integer programming | en_US |
dc.title | Optimization models for the plugging and abandoning of offshore oil and gas fields | en_US |
dc.type | Doctoral thesis | en_US |
dc.subject.nsi | VDP::Social science: 200::Economics: 210 | en_US |