Handling Spatial Heterogeneity in Reservoir Parameters Using Proper Orthogonal Decomposition Based Ensemble Kalman Filter for Model-Based Feedback Control of Hydraulic Fracturing Conference Paper uri icon

abstract

  • © 2018 American Chemical Society. Accurate characterization of reservoir properties is of central importance to achieve a desired fracture geometry during a hydraulic fracturing process. However, the estimation of spatially varying geological properties in hydraulic fracturing is inherently ill-posed due to a limited number of measurements. In this work, parametrization is performed to reduce the dimensionality of spatially varying Young's modulus profiles via proper orthogonal decomposition (POD), and a data assimilation technique called ensemble Kalman filter (EnKF) is used to estimate the parameter values in the reduced low-dimensional subspace. Through a series of simulation results, it is demonstrated that the POD-based EnKF technique provides a process model with updated spatially varying geological parameters, which is able to make an accurate prediction of the fracture propagation dynamics in hydraulic fracturing. Next, we use the updated high-fidelity process model in a model predictive control framework to construct a closed-loop system of hydraulic fracturing to achieve uniform proppant concentration at the end of pumping.

altmetric score

  • 0.5

author list (cited authors)

  • Narasingam, A., Siddhamshetty, P., & Kwon, J.

citation count

  • 33

publication date

  • March 2018