CASE STUDY E: Predicting recovery factor for all the oil fields in the North Sea

THE PROBLEM
The recovery efficiency of a field is usually determined by reservoir simulation modelling, but can also be estimated through the use of analogues where time and cost is an issue such as in exploration or data room exercises. The client wanted to build an effective analogue database for the UK North Sea to allow recovery efficiency to be easily predicted for any type of field.

THE TASK
We were commissioned to build an analogue database of recovery efficiency across the UK North Sea and develop a correlation between field recovery factor and field complexity.

OUR SOLUTION

	We collated a large volume of field information and built a database for 130 active offshore oil fields covering 35 reservoir and development characteristics.
	Next, we ranked these characteristics based on correlation coefficients and developed a Complexity Index based on the five most significant characteristics.
	A correlation was then developed between this Complexity Index and ultimate Recovery Factor.

THE RESULTS

	The client now has a comprehensive analogue database of every field in the UK North Sea and is able to predict an average recovery factor for any field of any complexity.
	We also compared actual recovery factors achieved against those predicted. This allowed us to rank and compare fields by type, area and also by the type of operator managing them, providing an indispensable indicator for the client.

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