Inversion seismic refraction data using particle swarm optimization: a case study of Tabriz, Iran
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ORIGINAL PAPER
Inversion seismic refraction data using particle swarm optimization: a case study of Tabriz, Iran Rashed Poormirzaee & Rasoul Hamidzadeh Moghadam & Ahmad Zarean
Received: 23 March 2014 / Accepted: 30 September 2014 # Saudi Society for Geosciences 2014
Abstract Seismic refraction method is a powerful geophysical tool that is used in the fields of engineering geology, geotechnical engineering, and exploration geophysics. In order to achieve reliable results, processing of seismic refraction data in particular inversion stage should be done accurately. Recently, particle swarm optimization (PSO) algorithm, as a swarm intelligence technique, is used in many fields of studies. The PSO is a stochastic, population-based algorithm modeled on swarm intelligence. The use of PSO in geophysical inverse problems is a relatively recent development and offers many advantages in dealing with the nonlinearity inherent in such applications. The current study intends to move one step ahead in application of PSO in inversion and discuss applying PSO to invert seismic refraction data. A new framework for inversion seismic refraction data will also be proposed. For efficiency evaluation of developed method, different synthetic models were inverted and then a statistically analyzed PSO parameters function was presented. Finally, PSO inversion method was investigated in a case study at the part of Tabriz city in NW-Iran to delineate subsurface features. The findings show that the study area is composed of two main layers: first layer velocity is 550 m/s and its thickness is 5.5 m, and second layer velocity is 1350 m/s. The results emphasize the reliability of the PSO inversion method in seismic refraction data interpretation with an acceptable misfit and convergence speed.
R. Poormirzaee (*) : R. H. Moghadam Sahand University of Technology, Tabriz, Iran e-mail: [email protected] A. Zarean Department of Civil Engineering, College of Engineering, Shabestar Branch, Islamic Azad University, Shabestar, Iran e-mail: [email protected]
Keywords Seismic refraction data . PSO . Inversion . P-wave velocity
Introduction Many geophysical optimization problems are nonlinear and result in irregular objective functions. Consequently, local optimization methods, like matrix inversion, steepest descent, and conjugate gradients, are prone to trapping in local minima, and their success depends heavily on the choice of a starting model (Boschetti et al. 1995). Particle swarm optimization (PSO) is a novel and powerful technique in geophysical data interpretation and has the potential to avoid the aforementioned limitation. In geophysical surveys, several significant PSO applications have recently been emerged. The PSO on a multilayered 1D vertical electric sounding (VES), induced polarization (IP), and magnetotelluric (MT) methods, both synthetic and field data, has successfully been carried out by Shaw and Srivastava (2007). Naudet et al. (2008) studied water table estimation using the PSO on self-potential (SP) data. In a
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