Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.721866
Title: Maximising oil production through data modelling, simulation and optimisation
Author: Peñuelas, Jose Antonio
Awarding Body: University of Sheffield
Current Institution: University of Sheffield
Date of Award: 2017
Availability of Full Text:
Access from EThOS:
Access from Institution:
Abstract:
The research work presented on this thesis provides an alternative tool for characterising oil fields under fluid injection by analysing historical production/injection rates. In particular polynomial and radial basis Non Linear Autoregressive with Exogenous Input Model (NARX) models were developed; these models were capable of capturing the dynamics of an operating field in the North Sea. A Greedy Randomised Adaptive Search Procedure (GRASP) heuristic optimisation method was applied for estimating a future injection strategy. This approach is combined with a risk analysis methodology, a popular approach in financial mathematics. As a result, it is possible to estimate how likely it is to reach a production goal. According to the simulations, it is possible to increase oil production by 10% in one year by implementing a smart injection strategy with low statistical uncertainty. Resulting from this research project, a computational tool was developed. It is now possible to estimate NARX models from any field under fluid injection as well as finding the best future injection scenario.
Supervisor: Hua-Liang, Wei Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.721866  DOI: Not available
Share: