Re: EQ Prediction to be proved impossible?
Posted by Pavel Kalenda on March 29, 2001 at 09:39:13:

Hi Roger,

my oppinion is, that the prediction is possible (see 6450)and maybe the prediction will be in operation sooner than 1020. I tested this year the LURR theory in Western Bohemia swarm region and at the coal mines. The result is perfect: Tidal forces have big influenece to tge triggerin proces of EQs. I include the abstract of this paper that will be published this year on Czech-Polish conferrence:


Kalenda P., Skalský L.
Abstract

The LURR theory (Load - unload response ratio) (Yin et al. 1995) was verified in the Ostrava-Karviná Coal Basin (OKCB) mines. The theory is based on the influence of tidal forces on the rock mass. The massive in normal conditions does not show the difference between the seismic activity in the load and unload phase of the tidal variations. In the breaking stress conditions the seismic activity rises much more during the load phase of the tidal variations, which leads to the rise of the LURR coefficient value before the main event (Yin et al. 1995).
The LURR theory was tested at the areas of coal blocks with a high seismic activity and well-localised foci of seismic events. It was found that the tidal forces had influence on the seismic activity, but the phase shift varied from coal face to coal face. The phase shift varied in the area of one coal face depending on the height of the seismogenic layer above the mined-out coal seam.
Finally it was found that LURR coefficient could not be used in induced seismology in the same manner as in global - not induced - seismology because seismic activity depended mainly on the time and intensity of coal excavation, which implied that the LURR coefficient varied according to the shift between excavation and tidal waves cyclus. In the conditions of induced seismicity b coefficient of energy-frequency distribution can be used instead LURR coefficient. The disadvantage of b coefficient is its variance according to the strenght and strain and a high number of events, necessary for its evaluation.