Pattern Generation of Strain Rate Simulation for Cross-Well Hydraulic Fracture Monitoring in Unconventional Reservoirs

Abstract

In multistage hydraulic fracturing treatments, the combination of extreme large-scale pumping (high rate and volume) and the high heterogeneity of the formation (because of large contact area) normally results in complex fracture growth that cannot be simply modeled with conventional fracture models. Lack of understanding of the fracturing mechanism makes it difficult to design and optimize hydraulic fracturing treatments. Many monitoring, testing and diagnosis technologies have been applied in the field to describe hydraulic fracture development. Strain rate measured by distributed acoustic sensors (DAS) is one of the tools for fracture monitoring in complex completion scenarios. DAS measures far-field strain rate that can be of assistance for fracture characterization, cross-well fracture interference identification, and well stimulation efficiency evaluation. Many field cases have shown DAS responses on observation wells or surrounding producers when a well in the vicinity is fractured. Modeling and interpreting DAS strain rate responses can help quantitatively map fracture propagation. In this dissertation, a methodology is developed to generate the simulated strain-rate patterns based on existing fractures. The patterns are then used to build a database for interpretation purpose. Instead of using a complex fracture model to forward simulate fracture propagation, this work starts from a simple fracture propagation model to provide hypothetical fracture geometries in a relatively reasonable and acceptable range for both single fracture case and multiple fracture case. Displacement discontinuity method (DDM) is formulated to simulate rock deformation and fiber-optic measurement. At each time step, fracture propagation is first allowed, then stress, displacement and strain field are characterized as the fracture approaches to the observation well. Afterward, the strain rate is calculated as fracture growth to generate patterns of fracture approaching. Extended simulation is conducted to build the database for fracture propagation behavior. These patterns can be used to recognize fracture development. Examples of strain rate responses in the pattern database for both single fracture and multiple fracture scenarios are presented in this dissertation to show the potential of using DAS measurements to diagnose multistage hydraulic fracturing treatments.