## Optimization of offshore natural gas field development

##### Master thesis

##### Permanent lenke

http://hdl.handle.net/11250/266079##### Utgivelsesdato

2011##### Metadata

Vis full innførsel##### Samlinger

##### Sammendrag

In this thesis the target is to find the optimal development solution of an offshore natural gas field. Natural gas is increasing in importance as an energy source. Whilst most of the large oil fields have been developed, there are still several major natural gas deposits that may be developed. In addition, there are also smaller offshore natural gas fields that may be put into production. Finding an optimal development solution for these resources will increase the availability of natural gas.The objective of the mathematical model presented in this thesis is to maximize the total net present value of an offshore natural gas field development. The model does this by finding the optimal combination of investment decisions of the necessary natural gas field infrastructure. Infrastructure included in the model includes the number of wells to be drilled, flowlines, production facilities, energy infrastructure on site and transport infrastructure to the customers. The model also decides whether gas sales agreements should be made with selected customers and the natural gas production in all time periods.This offshore natural gas field development problem is formulated as a mixed integer linear programming problem. Piecewise linearization is used to increase the accuracy of the reservoir model and to find the energy demand for a given natural gas flow rate and pressure difference. The linearization makes the model easier to solve than if it was formulated as a non-linear program.Branch and bound was chosen as the solution method for the implementation of the model. The model has been implemented in the Mosel programming language, using Xpress-MP as the solver.Results from testing of the model on three different test cases indicate promising potential for the utilisation of the model. Optimal solutions were found in less than six minutes for all of the test cases, and close to optimal solutions were found quickly in the global search.