Mechanism of microearthquakes from acoustic emission in a laboratory:
How to evaluate efficiently a large amount of data
Abstract
The laboratory approach brings a significant simplification compared to
the actual conditions in situ. Laboratory experiments represent the only
chance to control the physical conditions under which the investigated
physical phenomena occur. Acoustic emission (AE) is the process
accompanying the brittle fracturing of solid body and simultaneously an
indispensable tool for its study. Laboratory experiments under
controlled loading conditions make it possible to differentiate the
effect of important factors like material structure, stress field, crack
occurrence, etc. on fracture initiation and development, and allow
simulate the nature in situ. Microearthquakes detected during AE can be
analyzed by methods developed in earthquake seismology. We apply the
shear-tensile crack (STC) to describe the source mechanism of the AE
events with the aim to detect the mode of rock fracturing, in particular
to distinguish between a shear slip and tensile crack, the latter both
in the phase of its opening and closing. The benefit of discerning
between shear and tensile fracturing is an insight into changes of the
permeability of the rock massif both in space and time. By contrast to
natural seismology, tens of thousands AE events occur in laboratory
during the experiment. Expecting to process large volumes of data, an
urgent demand was to make the non-linear STC search together with the
estimate of the errors involved as fast as possible. To assess the
reliability of the STC solution, the confidence regions of source model
parameters are constructed. The misfit function is converted into the
probability density function which is integrated over a trial volume of
low misfit until requested probability content is achieved. For
individual microearthquakes, we display confidence regions both for the
mechanism orientation and its decomposition. Aiming to process a large
bulk of AE data, a method of assessing of these zones needs to be
proposed, which describes them by estimates of their extreme size. This
allows us select for subsequent interpretation from all solutions only
those that are stable and reliable. We have applied this approach to the
experimental data obtained from a couple of uniaxial loading tests
performed on a Westerly Granite and Liberec Granite specimen using a 14
channel AE monitoring system.