http://localhost:8081/jspui/handle/123456789/6 Thu, 03 Jul 2025 14:09:16 GMT 2025-07-03T14:09:16Z http://localhost:8081/jspui/handle/123456789/17557 Title: WIENER ESTIMATION OF GREEN'S FUNCTION Authors: Vermun, Pratik Abstract: The seismic response of a layered model earth is a convolution of the source time function with impulse response or Green's function of the earth model. This function is the response of the model when an impulse of unit amplitude (defined by a delta function) is sent through the model. To determine the Green's function from recorded seismic data in the presence of noise is an important problem when an estimate of the source time function is available. This is also called signature deconvolution. Among the various techniques that may be used for this purpose, use of Wiener's theory is expected to give acceptable results. The deconvolution first involves estimating the noise in the recorded pulse, removing the same from the data and then applying Wieiiers technique for estimating the Green's function. In this thesis the basic concepts of deconvolution and inverse filtering have been explained. A mathematical approach to wiener filter is also discussed and then its implementation to estimate Green's Cunction. The above method has been demonstrated on a marine seismic data and the findings have been discussed. A numerical experiment has been designed wherein, a synthetic seismogram has been created and noise has been added. An effort has been made to design a filter to minimize the noise for precise deconvolution Fri, 01 May 2015 00:00:00 GMT http://localhost:8081/jspui/handle/123456789/17557 2015-05-01T00:00:00Z http://localhost:8081/jspui/handle/123456789/17551 Title: DEVELOPMENT OF REGRESSION MODEL BASED ON STRONG MOTION DATA Authors: Deepthi, Surepalli Abstract: One of the crucial requirements for the estimation of the seismic hazard of an area is the attenuation relation and these relations are derived generally from the regression analysis. The coefficients of regression relation are derived from regional strong motion data. Selection of regression model stands as the primary step in regression I analysis and the selection of the model is done on the basis of how the peak ground acceleration depends on the hypocentral distance and the magnitude. Checking for many such functional dependencies are done and the regression model that gives minimum error and the best correlation is selected as the final regression model. The area of study forms the Garhwal and Kumaon regions of the Uttarakhand Himalayas within latitude 29°-33°N and longitude 78°-81°E, which are considered as important regions seismotectonically. Bulk of the earthquakes originate generally at depths approximating 10-15 km. Strong motion data is collected for these regions and formulated in the regression model by keeping the value of IV' as R+x where x varies from 10 to 14 corresponding to the depths. On successful execution of the program in FORTRAN, we get the regression coefficients for various models and the model R+14 gave the best correlation and minimum error. Hence, this is the new regression model which is selected and an attenuation relation is formulated for both Kumaon and Garhwal l-Iimalayan regions. Fri, 01 May 2015 00:00:00 GMT http://localhost:8081/jspui/handle/123456789/17551 2015-05-01T00:00:00Z http://localhost:8081/jspui/handle/123456789/17550 Title: STRESS REGIME AND MICROGRAVITY RELATED TO MAJOR EARTHQUAKES Authors: Reddy, Sunkesula Chandrakanth Abstract: Generally, GPS and InSAR data are used in monitoring surface deformation that results from an earthquake. This surface deformation is a small manifestation of overall changes that take place within the subsurface. Present study is aimed at tensorial analysis of co-seismic stress changes associated with an earthquake. Three significant earthquakes, namely Sumatra earthquake 2004. Japan earthquake 2011 and recent Nepal earthquake 2015 were considered for this study. Variations in six independent components of symmetric stress tensor (ar , a22. a33. U12, a13 and (T23) in a half-space have been generated and analysed for the above mentioned earthquakes rupture models, and an attempt is made to correlate aftershock distribution with the modelled stress changes. Results in this regard showed similarity between aftershock pattern and a22 component of modelled stress change, which showed maximum variation compared to other components. Stress changes in a material cause deformation and theoretically this deformation in turn leads to gravity variation. By considering the global coverage by satellite missions like GRACE and GOCE, they may provide invaluable additional data which can constrain the seismic stress change models. An attempt is also made to correlate modelled co-seismic stress changes with satellite gravity signals for Sumatra earthquake 2004 and Japan earthquake 2011. Achieved results in this regard also indicated most similarity with a22 component of modelled stress change. Fri, 01 May 2015 00:00:00 GMT http://localhost:8081/jspui/handle/123456789/17550 2015-05-01T00:00:00Z http://localhost:8081/jspui/handle/123456789/17548 Title: ESTIMATION OF QUALITY FACTOR OF CODA WAVES FOR THE DELHI REGION Authors: Kejriwal, Siddharth Abstract: Seismograms of 19 earthquakes which have occurred in and around Delhi region during 2007 to 2014 and recorded at different stations have been analyzed to study the seismic coda wave attenuation characteristics in this region. In the present study, local earthquake events with depths less than 75 km and magnitude range between 3.3 and 5.1 is used to study coda Q, i.e. Q, using the single isotropic backscaltering model proposed by Aki. Q values are estimated at 6 central frequencies 1, 2, 4, 8, 12 and 16 Hz using several starting lapse-times of 40. 50 60 and 70 sec., and coda window-lengths of 25, 30, 35 and 40 sec. In the considered frequency range, Q lit the frequency dependent power-law Q. = QOP. The frequency dependent power law for 40 sec lapse time with 25 sec coda window length is QC = 86.83 f° and for 70 sec lapse time with 40 sec coda window length is Qe = 168.44 f°96. The Q (Qc at 1 Hz) estimates vary from about 87 for a 40 sec lapse time and 25 sec window length, to about 168 for a 70 sec lapse time and 40 sec window length combination. The exponent of the frequency dependence law n ranges from 0.96 to 1 .05, which correlates well with the values obtained in other seismically and tectonically active and heterogeneous regions of the world. It is observed for the study region that Q values increases both with respect to lapse time and frequency or attenuation decreases as quality factor is inversely proportional to attenuation. The low Q values or high attenuation at lower frequencies and high Q values or low attenuation at higher frequency may indicate that the heterogeneity decreases with increasing depth, in the study region. Fri, 01 May 2015 00:00:00 GMT http://localhost:8081/jspui/handle/123456789/17548 2015-05-01T00:00:00Z