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Maximising Oil Production Through Data Modelling, Simulation and Optimisation.

Peñuelas, Jose Antonio (2017) Maximising Oil Production Through Data Modelling, Simulation and Optimisation. PhD thesis, University of Sheffield.

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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.

Item Type: Thesis (PhD)
Academic Units: The University of Sheffield > Faculty of Engineering (Sheffield) > Automatic Control and Systems Engineering (Sheffield)
Identification Number/EthosID: uk.bl.ethos.721866
Depositing User: Jose Antonio Peñuelas
Date Deposited: 31 Aug 2017 14:16
Last Modified: 12 Oct 2018 09:43
URI: http://etheses.whiterose.ac.uk/id/eprint/17960

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