Location-based parameterization of controlled-source electromagnetic data inversion for the monitoring of hydraulic fracturing with magnetically enhanced proppants

Abstract

The injection of fluids with electromagnetic (EM) contrast is regarded as a promising tool for EM monitoring. We have developed a novel model-based inversion method, designated as a particle mapping (PM) method, as a fit-for-purpose inversion tool for EM monitoring. The PM method optimizes the location of particles while constraining a priori information on the net physical property-volume products in the inversion domain. In addition, as a regularization method for location-based inversion, a fuzzy clustering method is adopted to integrate the PM method with the geometries of an a priori anomalous distribution. The EM monitoring of hydraulic fracturing is considered as a primary application of the PM method. In particular, numerical experiments focus on the injection of magnetically enhanced proppants and the use of the fracture model as a cluster geometry. Numerical experiments also include situational assumptions of incorrect a priori injected amounts of fluids and the distribution of anomalous regions to fully investigate the practicality of the method. The results indicate not only how clear and intrinsically interpretable the imaging results can be obtained with the PM method but also how known or assumed information on injected fluids and the fracture model can be integrated with the EM inversion.