Reducing Uncertainties of Fracture Characterization on Production Performance by Incorporating Microseismic and Core Analysis Data

Abstract

Abstract Hydraulic fracture treatments may induce complex network geometries that are challenging to incorporate in numerical flow simulators. To capture this complexity, we propose a workflow that integrates a semi-stochastic Discrete Fracture Network (DFN) generator constrained by Microseismic events, core data and an efficient Perpendicular Bisector (PEBI) grid generator for the explicit discretization of the network. We applied this workflow to evaluate the effect of DFN related uncertainties on production performance. We developed a DFN model that constrains the location of natural fractures by microseismic events and samples fracture characteristics from core-data-based Probability Density Functions (PDFs). The model also interconnects natural and hydraulic fractures through a geomechanics-based algorithm. For an efficient fracture discretization, we developed a PEBI meshing technique capable to conform to low-angle intersections of extensively clustered network, incorporating optimization algorithms that reduce highly skewed cells, and ensure good mesh quality. Finally, to evaluate the impact of DFN related uncertainties on production, we implemented an efficient Monte Carlo (MC) methodology that minimizes flow simulations. We implemented the workflow in a stage of a hydraulic fracture treatment to evaluate the impact of two type of DFN related uncertainties on production: those coming from the randomness of DFN modeling and those coming from the lack of accurate knowledge of PDF parameters. We show that the proposed DFN modeling approach can be applied to calculate the "Fluid-Producing DFN (FP-DFN)," which is the network area connected to the well and able to produce, to minimize flow simulations for the MC runs. After performing efficient-based MC simulations with our DFN model, we were able to generate the FP-DFN Cumulative Density Function (CDF) incorporating the aforementioned uncertainties. From this CDF, different percentiles were selected with the respective DFN realizations for fluid simulations. We show that the developed PEBI meshing algorithm is capable to grid efficiently these complex DFN geometries with good mesh quality. Finally, 20-year production simulations suggest that a difference of several MSTB between the lowest and highest percentiles may exist revealing the effect of the DFN related uncertainties on production. Our integrated workflow provides a methodology to efficiently model and mesh explicitly complex DFN systems for numerical fluid simulations, incorporating microseismic and core data. Furthermore, this methodology, together with the implementation of an efficient MC technique, allows a quantitative evaluation of the impact on production forecast of DFN related uncertainties.