عنوان مقاله [English]
It is very important to study and simulate S-wave structure for near surface (alluvium parts, in particular) owing to its direct relationship to urban facilities in geotechnical and earthquake engineering studies. So, in seismic microzonation, the first step is to study and identify S-wave pattern in alluvium in order to categorize different parts of cites according to S-wave velocity. Current techniques of estimating shallow shear velocities for assessment of earthquake site response are too costly for use at most construction sites. They require large sources to be effective in noisy urban settings, or specialized independent recorders laid out in an extensive array. Recently, refraction microtremor (ReMi) data have been frequently used for estimating of dispersion curves and simulating velocity of S-waves, because ReMi method is fast and cheap. However, inversion is the main problem in processing ReMi data for estimating velocity of S-waves. With the development of computer science, emergence of single-and multi-objective optimization techniques and inspiration of science from nature, an opportunity has been provided for decrease in non-uniqueness of inversion and finding the best possible solution. In this study, the joint inversion of microtremor and seismic refraction data was proposed using multi-objective Genetic Algorithm optimization and Pareto front concept for estimating S-wave velocity. After programming the multi-objective Genetic algorithm in Matlab, its efficiency was investigated by synthetic models and real datasets. Real datasets were obtained from 1 stations in south part of Tabriz (near Elgoli Road) that contain Miocene –Pliocene and pyroclastic bedrocks. For actual dataset we used Refraction microtremor (ReMi) as a passive method for achieve Rayleigh wave and seismic refraction data as an active method for getting travel time. For ReMi and seismic refraction data acquisition, the same layout can easily provide both P-wave travel times and surface wave dispersion curves if the sampling parameters are properly designed to satisfy the requirements of the two techniques. In current study ReMi and seismic refraction method was performed with using an OYO 24-channal seismograph and 4.5Hz and 28Hz geophones with a receiver spacing of 5m. for ReMi, Unfiltered 17 second records were collected at study site. Also in this study, resistivity data, as auxiliary information, are used. Resistivity method can provide information about bed rock and water table in study area. For this goal, resistivity measurements were carried out by using high-resolution RESECS resistivity meter system. In this study Wenner array, with 32 electrodes (2m unit electrode spacing), for measurements of 1-D resistivity imaging profile is used. For evaluation of proposed joint inversion algorithm, the results were compared with single inversion of ReMi data by Particle Swarm Optimization (PSO) algorithm. with Using joint inversion algorithm, a three layer subsurface model was found, which the first layer velocity is 321m/s and its thickness is 5.8m, second layer velocity is 365m/s and its thickness is 4.6m and last layer velocity is 547m/s.. The results of inversion in both synthetic and real dataset proved the reliability of proposed method, as a powerful technique for joint inversion, in comparison to current methods. . Also by Pareto concept the quality of inversion procedure can be easily detected. Because symmetry of Pareto front is strongly depends to accuracy of estimations. By using joint inversion algorithm we can achieve to a more correct Vs structure and decrease the non-uniqueness of Rayleigh wave inversion.