Title : The effect of perforations orientation on reducing formation breakdown pressure in hydraulic fracturing operations using machine learning
Abstract:
One of the common methods for well stimulation in low-permeability reservoirs include hydraulic or acid fracturing. In these methods, fluid is injected into the well at a pressure higher than the formation's fracture pressure, causing fractures in the reservoir rock and increasing permeability. One of the most significant limitations of fracturing operations is the ability of surface and subsurface equipment to withstand high pressures. Therefore, any method that reduces the pressure required to fracture the formation is welcomed by the industry. One of the crucial parameters affecting the pressure needed to fracture the formation is the orientation of the perforations. Choosing appropriate orientations for perforations, considering the surrounding stress conditions, can reduce the required fracturing pressure by an average of 10 to 30 percent. Lowering the required pressure for fracturing means reducing operational costs. Higher required pressures demand more robust and costly equipment and also pose higher operational risks. In this research, the impact of perforation orientation on reducing the required pressure for fracturing was initially examined. Subsequently, using machine learning and neural network algorithms, the optimal perforation orientation based on the rock's mechanical properties and the applied stress conditions was calculated. The optimal perforation orientation is defined as the direction in which hydraulic fractures can initiate at the lowest possible pressure at a measured depth. The model's results were compared with a laboratory sample, and the machine learning models showed high accuracy in predicting fracturing pressure based on the perforation orientation and other related parameters. This study provides valuable insights for optimizing perforation design and improving hydraulic or acid fracturing outcomes, leading to reduced operational costs, increased hydrocarbon recovery, and improved well productivity. The findings of this study can be applied in planning and simulation processes of fracturing operations to reduce the required pressure for fracturing the formation by optimizing the perforation orientation on a field scale.
