Performance evaluation and influential factor analysis for
stacking-based seismic location
Abstract
Seismic source locations provide fundamental information on earthquakes
and lay the foundation for seismic monitoring at all scales. Subsurface
engineering operations, such as hydraulic fracturing, usually generate
abundant microseismic events with low signal-to-noise ratios, thus
raising a higher demand on the reliability and computational efficiency
of seismic location methods. Stacking-based method involves
reconstructing and focusing the radiated seismic source energy with a
certain stacking operator, for example, the diffraction stacking
operator or the cross-correlation stacking operator. They are
noise-resistant, automatic, and data-driven. The source locations are
resolved as images instead of discrete dots, offering more insights into
source processes and surrounding structures. In this work, we conduct
the performance evaluation and influential factor analysis with
synthetic examples, to further improve the understanding of the method.
Three categories of factors are investigated, including the velocity
model, array geometry, and waveform complexity. Each of the three
factors consists of several detailed factors, such as different array
types and noise levels. Multiple parameters are considered for the
performance evaluation, including location error/bias, imaging
resolution, signal alignment with time shifts, and the computational
cost. The proposed scheme is also applied to field microseismic datasets
to demonstrate its feasibility. This study will be conducive to the
design and evaluation of surface monitoring projects.