|dc.description.abstract||This thesis has evaluated a wide range of techniques to militate one of the big challenges of petroleum industry, water production. The techniques discussed waterflooding management, all aim to reduce excessive water production. The injection and production history at a well and field level are most common available data in any oil field, especially when nowadays we can have these data in real time with the implementation of the digital oil field and the intelligent well completion. This research aims to understand the strength and weaknesses of the existing techniques and “repackage” them to provide an optimum combination for more effective waterflood management by analysing injection and production data history.
The first part of this research reviewed, tested and compared the analytical techniques that have been previously used for analysing the injection and production. The methods studied fell in to two distinct classes: those that monitor the waterflood performance secondly, methods for determining the inter-well connectivity.
The second part of this thesis showed that an improved workflow used the captured information from the phase one methods could be combined to give more effective waterflood management via combination of reservoir voidage management (RVM), water allocation management (WAM) and production allocation management (PAM).
Finally, a semi-analytical method was introduced in this thesis for performing RVM. Two approaches were defined for WAM and new techniques developed for PAM, all of which employed only the production and injection history. The results from these techniques were compared with the more advanced reservoir simulation methodologies such as gradient free optimisation. This comparison showed the reliability of the proposed techniques.||en_US