Prediction of pitch using neural network with unified particle swarm optimization

Particle swarm optimization (PSO) is a powerful optimization technique that has been applied to solve a number of complex optimization problems. The precipitation and deposition of crude oil polar fractions such as pitch in petroleum reservoirs reduce considerably the rock permeability and the oil recovery. In the present paper, the model based on a feed-forward artificial neural network (ANN) to predict pitch precipitation of the reservoir is pro-posed. After that ANN model was optimized by unified particle swarm optimization (UPSO). UPSO is used to decide the initial weights of the neural network. The UPSO-ANN model is applied to the experimental data reported in the literature. The performance of the UPSO-ANN model is compared with scaling model. The results demonstrate the effectiveness of the UPSO-ANN model.