Dividing Oil Fields into Regions with Similar Characteristic Behavior Using Neural Network and Fuzzy Logic Approaches
byMasoud Nikravesh, A. R. Kovscek, Tadeusz W. Patzek
Nikravesh, Masoud, A. R. Kovscek, and T. W. Patzek. "Dividing oil fields into regions with similar characteristic behavior using neural network and fuzzy logic approaches." In Fuzzy Information Processing Society, 1996. NAFIPS., 1996 Biennial Conference of the North American, pp. 164-169. IEEE, 1996.
Here we present the next generation of “intelligent” oil Field surveillance and prediction software based on neural networks and fuzzy logic. We treat the entire oil Field as a coupled, highly nonlinear system of water injectors and oil/water/gas producers. The oil field is divided into regions with similar characteristic behavior using neural network and fuzzy logic. Wells in each region are then modeled with specialized neural networks trained to recognize their particular behavior. The model helps to improve waterflood management, avoid reservoir damage, and increase oil recovery per unit volume of injected water. Finally, the model visualizes the global trajectory of an entire field project and allow engineers to recognize patterns of incipient reservoir damage and poor performance.