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Simulator Reservoir Neural Network


Sirenn, plug-in for Petrel*, is a very powerful and flexible tool to build proxy models of reservoir simulators. The proxy models are developed using artificial neural networks, a technique that has been expanding rapidly in petroleum engineering applications, as in other fields requiring huge computer power like aerospace (flight simulation). Sirenn can be used for many applications: the Well Placement Optimization, Field Development Scheduling, History Matching with Multiple Models, Global Optimization of Oil Production Systems, Screening and Designing Improved Oil Recovery Methods.

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Sirenn allows bypassing time consuming reservoir simulations, while maintaining a good approximation of results. This can be very useful, particularly for inverse problems, sensitivity analysis and uncertainty analysis which, all of them, requires huge amounts of reservoir simulations. With Sirenn, you will be able to handle cases that could not be handled using directly reservoir simulators. Neuro-Simulation techniques are the best suited approach as they are very well adapted to represent nonlinear phenomena.

Sirenn is a very powerful and flexible tool to build proxy models of reservoir simulators; very useful for History Matching studies. The proxy models are developed using artificial neural networks. This tool identifies the best neural network for your problem with the option "Optimal neural network". This tool allows you to save computation time while keeping high accuracy of your results.  

Sirenn aims to improve History Matching workflows using a proxy model based on neural network to avoid time consuming reservoir simulation. For example, Sirenn allows to history match all production data (Pressure, water-cut …) or maximize the production (wells placement, production rates …)  

Sirenn shows its superiority over other proxies. With three new cases, which were not used to learning, the water cut predictions provides by Sirenn are extremely close to those provides by Eclipse*.  

* Trademark of Schlumberger

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