Interaction Between Hydraulic Fracture and Natural Fracture - A New Prediction Model by Adaptive Neuro-Fuzzy Inference System (ANFIS)

Abstract

Abstract Hydraulic-fracturing (HF) treatments have become an essential technology for tight gas field development. Tight gas formations often contain natural fractures (NF). In presence of NF, more complex fracture networks may form during the hydraulic treatment. The interaction between fractures may alter the way the hydraulic fracture propagates through the formation, causing a complex network of fractures, which can significantly influence the overall geometry and effectiveness of hydraulic fracture. The hydraulic fracture may cross, dilate or slip into the fracture plane upon its arrival at the natural fractures. Although there have been studies on investigation of the interaction between HF and NF, most of them cannot be applied reliably due to the inherent assumptions in the analytical formulation. In cases of laboratory studies, the limitation of the equipment could also be a factor. With this study a multi-ANFIS model is established to predict the interaction between HF and NF. The advantage of this model is that it is a data-based model. Therefore, as long as there are reliable data the model can work smoothly and easily, so that it can predict the interaction in real time. Results show that the dilation and slippage will be more likely to occur when the approach angle is very low. Whereas, in the case of higher differential horizontal stress, it is more likely that the cross interaction will happen. The significance of this work is to help to predict the interaction between HF and NF, thus optimizing the hydraulic-fracture treatment design parameters in a naturally fractured tight gas reservoir. Insightful parametric sensitivity analyses will also be presented. This model could also be used to study the potential of the deep UAE gas sands, which are naturally fractured.