شماره ركورد كنفرانس :
4518
عنوان مقاله :
Simulation of Microbial Enhanced Oil Recovery by Using of Neural Networks
Author/Authors :
Mohammad Torkaman Department of Chemical and Petroleum Engineering- Sharif University of Technology, Tehran , Saeid Morshed Department of Chemical and Petroleum Engineering- Sharif University of Technology, Tehran , Mohsen Masihi Department of Chemical and Petroleum Engineering- Sharif University of Technology, Tehran , Mohammad Hosein Ghazanfari Department of Chemical and Petroleum Engineering- Sharif University of Technology, Tehran , Mohammad Hosein Sedaghat Department of Chemical and Petroleum Engineering- Sharif University of Technology, Tehran
كليدواژه :
Neural network , Enhanced oil recovery , Microbial method , Simulation , Perceptron
عنوان كنفرانس :
The 7th International Chemical Engineering Congress & Exhibition (IChEC 2011
چكيده لاتين :
In this article, we are going to simulate the reservoir by using two layer perceptron. Indeed a model was developed to simulate the increase in oil recovery caused by bacteria injection into an oil model was affected by reservoir temperature and amount of water injected into the reservoir for enhancing oil recovery. Comparing experimental and simulation results and also the erratic trend of data show that the neural networks have modeled this system properly. Considering the effects of non-linear factors and their erratic and unknown impacts on recovered oil, the perceptron neural network can develop a proper model for oil recovery factor in various conditions. The neural networks have not been applied in modeling of microbial enhanced oil recovery since now. Finally, we are going to design a controller for the neural network. This controller is designed for the case where output of the network is oil recovery factor. For this purpose, the network is designed as a one layer network in which just one output matches each time. In this case, a one layer network will have acceptable results.
