Soft Computing on Reservoir Characterization & Production Forecasting

The book "Soft Computing on Reservoir Characterization & Production Forecasting" offers a comprehensive analysis of the application of soft computing techniques in reservoir characterization and production forecasting. It highlights the crucial role that production forecasts and reservoir modeling play in the optimal development and management of oil reservoirs. The authors, Chithra Chakra N C and Madan M. Gupta, present innovative approaches based on artificial neural networks (ANN) and genetic algorithms (GA). These methods enable efficient and rapid numerical modeling, which is essential for creating historical reservoir models and reliable production forecasts. The book describes the implementation of a higher-order neural network (HONN) with various synaptic operations for predicting oil production and the application of an adaptive genetic algorithm (AGA) for the automatic adjustment of reservoir models. The results demonstrate that these soft computing methods provide a fast convergence rate and reduced computational efforts.