TITLE:
The Theoretical and Practical Foundations of Strong Earthquake Predictability
AUTHORS:
Oleg Elshin, Andrew A. Tronin
KEYWORDS:
Global Earthquake Prediction, Earthquakes, Geophysics, Big Data, Remote Sensing, Seismic Analysis, Terra Seismic, Future Technologies
JOURNAL NAME:
Open Journal of Earthquake Research,
Vol.10 No.2,
April
19,
2021
ABSTRACT: Earthquakes and the tsunamis they produce are
the world’s most devastating natural disasters, affecting more than 100
countries. Not surprisingly, the problem of earthquake prediction has occupied
scientists’ minds for more than two thousand years. This paper provides
theoretical and practical arguments regarding the possibility of predicting
strong and major earthquakes worldwide. Many strong and major earthquakes can
be predicted at least two to five months in advance, based on identifying
stressed areas that begin to behave abnormally before strong events, with the
size of these areas corresponding to
Dobrovolsky’s formula. We make predictions by combining knowledge from
many different disciplines: physics, geophysics, seismology, geology, and earth
science, among others. An integrated approach is used to identify anomalies and
make predictions, including satellite remote sensing techniques and data from
ground-based instruments. Terabytes of information are currently processed
every day with many different multi-parametric prediction systems applied
thereto. Alerts are issued if anomalies are confirmed by a few different
systems. It has been found that geophysical patterns of earthquake preparation
and stress accumulation are similar for all key seismic regions. The same
earthquake prediction methodologies and systems have been successfully applied
in global practice since 2013, with the technology successfully used to
retrospectively test against more than 700 strong and major earthquakes since
1970. In other words, the earthquake prediction problem has largely been
solved. Throughout 2017-2021, results were presented to more than 160
professors from 63 countries.