Analysis of Magnitude for Earthquake
Detection using Primary waves and
VARDHAMAN COLLEGE OF ENGINEERING
Shamshabad – 501 218, Hyderabad.
Shankar Murthy P
Earthquake is the natural disaster which occurs due to
release of sudden energy.
It occurs due to imbalance in stress field and strength field.
Certain waves are released during earthquake, called
Seismic waves, which are recorded over seismogram to
calculate its intensity on Richter magnitude scale.
Many methods like Precursor techniques, Animal behavior
have been propose to detect/predict the earthquake.
A new technique based on seismic waves is proposed to
determine earthquake magnitude and few seismic
It is also called as “Blue planet”, as it supports life
It has four spheres namely Biosphere, Lithosphere,
Formation of earth
Many theories have been proposed to support this
formation like Steady state theory, Cyclic Universe theory
among all these, Big Bang theory is the Universal accepted
Earth got cooled down due to continuous loss of heat
energy which resulted in formation of several layers.
Tectonic plates are puzzle like structures which
floats above the liquid rocky materials in the outer
The shaking of these tectonic plates results in
shaking of earth surface, known as earthquake.
There are eight major and many minor tectonic
Convergent, Divergent and Transform are the
types of tectonic movements.
Year Disaster Location
1931 Flood China
1887 Flood China
1556 Earthquake China
1970 Cyclone Bangladesh
2010 Earthquake Haiti
1926 Earthquake Antioch
1976 Earthquake China
2004 Tsunami Indian Ocean
1920 Earthquake Haiyuan
1975 Dam Failure China
Earthquake is the sudden release of energy, which
results due to imbalance between strength field of
tectonic plates and stress field of heat energy released
from molten liquid in outer core.
The location within the earth where the rock breaks is
called Origin and the location on earth surface straight
above the focus is called as Epicenter.
The waves originate from focus are Primary waves
(P-waves) and Secondary waves (S-waves).
Love waves, Stonely waves, Rayleigh waves
originate from Epicenter.
The speed of P-waves is 4800 meters/sec and
speed of S-waves is 3400 meters/sec.
Many different techniques have been proposed to
detect the earthquake.
1. Animal Behavior
3. Co-seismic signal extractions
4. Early Earthquake Warning systems (EEWS)
These experimentation determined the occurrence
of earthquake and alerts by issuing the alarm.
• Chinese conducted an experiment over animals like
snakes and rats.
• The unanimous behavior of those animals acts as an alert
message before striking of earthquake.
• Japanese made an experiment over aquatic animals, as
they have high perception of sensing the changes in
• Since, the shaking of ground disturbs the earth’s electro-
magnetic field which is immediately sensed by aquatic
animals and behaves unanimously.
Precursor techniques are based on pattern evaluation
which are formulated by the Radon emissions of elements
like thoron, radon, uranium etc.
The pattern includes the relationship between
intensity/velocities of the gases emitted and (2 x half life
period of the element).
Extraction of co-seismic signals
Co-seismic signals are extracted from the underground
Using HHT transform technique the frequency and energy
of co-seismic signals are extracted using IMF (Intrinsic
Mode Function) and EMD (Energy Mode Decomposition)
A new modern technical approach is proposed to
detect the earthquake using seismic waves.
Analysis on seismic wave produces seismic
parameters like energy, frequency, surface
magnitude, wavelength and rupture area.
More detail experimentation is shown in the
following flow chart diagram.
Stage 1 : Seismic wave acquisition
Seismic waves are combination of P and S-waves which
are recorded by a seismogram.
The seismic waves can be in two forms
1. Image format
2. Signal format
Seismic signal is chosen, instead of seismic image, for
the experimentation as it is more clear in representation
and free from external noises.
All the seismic signals are bought from
1. SSA (Seismological Society of America)
2. JMA (Japan Metrological Agency)
3. USGS (United State Geological Survey)
4. SCEC (Southern California Earthquake data Centre)
Stage 2: De-noising
Seismic signal may contain certain noisy data which are to
Hence, these seismic signals are subjected to a technique
called De-noising using Haar wavelet.
The following figure shows the levels in decompositions in
de-noising process and the de-noised signal.
Stage 3: FFT Spectrum
The de-noised signal is further processed to extract certain
parameters which include
1. Histograms - frequency distribution graph.
2. Cumulative Histogram - cumulative frequency distribution
3. Autocorrelation – computes periodicity in seismic signal.
4. FFT Spectrum – represents graphical relation between
energy and frequency of seismic signal.
Stage 4: Feature extraction from the graph
Parameters like energy and frequency of seismic signal
can be extracted from FFT Spectrum.
The maximum energy level value is computed along with
its frequency value from the following graph.
Stage 5: Other seismic parameters
Other seismic parameters include, wavelength computed using
represents speed of seismic wave
Surface magnitude is computed using
E represents energy of seismic wave
Ms represents surface magnitude
Rupture area is computed using
Ms represents surface magnitude
A represents rupture area
10log |1.5 11.8|sE M
10log |1.02 4.01|sA M
Based on the experimentation, the minimum surface
magnitude fixed value is 4.
If the Ms 4 earthquake, else Ms No earthquake.
In order to predict the earthquake the seismic signals are to
be extracted prior to the occurrence of earthquake, this can
be done using GPR (Ground Penetrating Radar).
Those extracted signals are analyzed as above stated
procedure to obtain parameters.
Since we can get Magnitude value we can predict the
severity of earthquake in advance.
The proposed methodology detects the earthquake
with five seismic parameters.
Simple and modern technical approach.
Magnitude based detection/prediction.
Same approach can be used to predict the earthquake
by extracting changes in seismic signals from
Different wavelets can be used instead of haar wavelet to
Certain seismic parameters like seismic moment, volcanic
eruption rates can be considered to improve efficiency.