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Water Flood Management and Optimization (*)

D. Echeverra Ciaurri and M. Thiele

With 70% of oil production coming from fields that are 30 years or older, the optimal

management of reservoir floods, and of water floods in particular, is a specially important topic.Despite many advances in reservoir simulation and management, reservoir engineers still

struggle in setting optimal injection/production target rates for such fields.

Figure 1. Typical streamlines view of a field.

Streamline-based flow simulation (see Figure 1) is generally associated with fast simulations.Therefore, they are a good proxy (surrogate) to use in any workflow that requires many

simulations. An overlooked factor of streamline-based simulation is the novel data that is

generated. Examples of this are the identification of injector-producer pairs and thequantification of the reservoir volumes associated with these pairs. Armed with this information

it is possible to promote the more efficient injector/producer pairs and demote the less efficient

ones in a manner computationally very efficient. This can lead to a more successful fieldmanagement strategy.

In this project, we propose to verify how well the streamline-based heuristic flood managementapproach presented in Thiele and Batycky (2006) compares to a solution obtained using a more

rigorously framed optimization scheme. The project will be helpful in shedding light on:

the quality of the flood management solution given by the streamline-based method; a

direct comparison of approaches should in turn reveal a number of hybrid efficient

methodologies for the management of water floods (for example, a good initial guess for

a gradient-based optimization algorithm might be quickly obtained by streamlines);

delineate situations where streamlines can/cannot be used for flood managementoptimization;

investigate if streamline specific information can be directly incorporated in the morerigorous flood optimization and management problem formulation, in the hope of

improving convergence and solution accuracy.

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Figure 2. Real reservoir under study(nine producers / eight injectors).

Initially, the same problem presented in Thiele and Batycky (2006) will be used. This is a small

but real reservoir with nine producers and eight injectors (see Figure 2) with a grid of size

80x81x20 (129,600 grid points). The goal is to improve (optimize) sweep over a period of fiveyears by setting target rates every three months on both producers and injectors (this yields atotal of 340 optimization variables). Additionally, the problem can be constrained to total

available injection rate, for example. After this first test, the reservoir considered can be larger

and more realistic.

The project aims at a formal study of a streamline-based optimization methodology and

assessment of its use in water flood management scenarios, with several applications of thismethodology in cases of practical interest.

References

Thiele, M.R., and Batycky, R.P., Using Streamline-Derived Injection Efficiencies for Improved

WaterFlood Management, SPE Reservoir Evaluation & Engineering (SPEREE), Vol 9, No 2,

187-196, April 2006 (SPE84080-PA).