  In this work we propose a novel algorithm for multiple-event localization for
Hydraulic Fracture Monitoring (HFM) through the exploitation of the sparsity of
the observed seismic signal when represented in a basis consisting of space
time propagators. We provide explicit construction of these propagators using a
forward model for wave propagation which depends non-linearly on the problem
parameters - the unknown source location and mechanism of fracture, time and
extent of event, and the locations of the receivers. Under fairly general
assumptions and an appropriate discretization of these parameters we first
build an over-complete dictionary of generalized Radon propagators and assume
that the data is well represented as a linear superposition of these
propagators. Exploiting this structure we propose sparsity penalized algorithms
and workflow for super-resolution extraction of time overlapping multiple
seismic events from single well data.
