The application of PSO to joint inversion of microtremor Rayleigh waves dispersion curves and refraction traveltimes

Poormirzaee, R.. Hamidzadeh Moghadam, R. and Zarean, A.. 2015. The application of PSO to joint inversion of microtremor Rayleigh waves dispersion curves and refraction traveltimes. Journal of Seismic Exploration, 24: 305-325. The accurate estimation of shear wave velocity (Vs) by Rayleigh wave dispersion analyses is very important for geotechnical and earthquake engineering studies, but dispersion curve inversion is challenging for most inversion methods due to its high nonlinearity and mix-determined trait. In order to overcome these problems, the current study proposes a joint inversion scheme based on a particle swarm optimization (PSO) algorithm. Seismic data considered for designing the objects were the Rayleigh wave dispersion curve and seismic refraction traveltime. For joint inversion, the objective functions were combined into a single function. The proposed algorithm was tested on two synthetic datasets and also on an experimental dataset. Synthetic models demonstrated that the joint inversion of Rayleigh wave and traveltime returned a more accurate estimation of Vs compared with single inversion Rayleigh wave dispersion curves. To verify the applicability of the proposed method, it was applied at a sample site in Tabriz city. northwestern Iran. For a real dataset. the refraction microtremor (ReMi) was used as a passive method for obtaining Rayleigh wave dispersion curves. Using PSO joint inversion, a three-layer subsurface mode] was delineated: the first layer’s velocity was 316 m/s and its thickness was 5.5 m, the second layer’s velocity was 280 m/s and its thickness was 2.8 m, and the last layer’s velocity was 512 m/s. The results of synthetic datasets and the field dataset showed that the proposed joint inversion technique significantly reduces the uncertainties of inverted models and improves the revelation of boundaries.
- Carlisle, A. and Dozier, G.. 2001. An off-the-shelf PSO. Proc. of the 2001 Workshop On particle
- Swarm Optimization, Indianapolis: 1-6.
- Cha, Y.H., Kang, J.S. and Jo. C.H, 2006. Application of linear-array microtremor surveys for rock
- mass classification in urban tunnel design. Explor. Geophys., 37: 108-113.
- Clerc, M., 1999. The swarm and the queen: towards a deterministic and adaptive particle swarm
- optimization. In: Angeline, P.J., Michalewicz, Z., Schoenauer, M., Yao, X. and Zalzala,
- A. (Eds.), Proc. of the Congress of Evolutionary Computation. IEEE Press: 1951-1957.
- Clerc, M.A. and Kennedy, J., 2002. The particle swarm-explosion, stability, and convergence in
- a multidimensional complex space. IEEE Transact. Evolution. Computat., 6: 58-73.
- Coccia, $., Del Gaudio, V., Venisti, N. and Wasowski, N., 2010. Application of Refraction
- Microtremor (ReMi) technique for determination of 1-D shear wave velocity in a landslide
- area. J. Appl. Geophys., 71: 71-89.
- Coello, C.A., Pulido, G.T. and Lechuga, M.A., 2004. Handling multiple objectives with particle
- swarm optimization. IEEE Transact. Evolution. Computat., 8(3): 23-38.
- Dal Moro, G., 2008. Vs and V, vertical profiling via joint inversion of Rayleigh waves and
- refraction traveltimes by means of bi-objective evolutionary algorithm. J. Appl. Geophys.,
- 66: 15-24.
- Deb, K., Agrawal, S., Pratab, A. and Meyarivan, T., 2000. A fast elitist nondominated sorting
- genetic algorithm for multi-objective optimization: NSGA-II. In: Proc. Parallel Problem
- Solving From Nature VI Conf.: 849-858.
- Evers, G.1., 2009. An Automatic Regrouping Mechanism to Deal with Stagnation in Particle Swarm
- Optimization. M.Sc. thesis, Univ. of Texas-Pan American.
- Fernandez Martinez, J.L., Garcia Gonzalo, E., Fernandez Alvarez, J.P., Kuzma, H.A and
- Menéndez Pérez, C.O., 2010a. PSO: a powerful algorithm to solve geophysical inverse
- problems: application to a 1D-DC resistivity case. J. Appl. Geophys., 71: 13-25.
- Fernandez Martinez, J.L., Garcia Gonzalo, E., Fernandez Muiiz, Z., Mariethoz, G. and Mukerji.
- T., 2010b. Posterior sampling using particle swarm optimizers and model reduction
- techniques. Internat. J. Appl. Evolution. Computat., 1(3): 27-48.
- Foti, S., Sambuelli, L., Socco, V.L. and Strobbia, C., 2003. Experiments of joint acquisition of
- seismic refraction and surface wave data. Near Surf. Geophys., 3: 119-129.
- Garcia, Ch., Kang, F.J. and Tae-Seob, K., 2014. Lateral heterogeneities and microtremors:
- Limitations of HVSR and SPAC based studies for site response. Engineer. Geol.,
- doi: 10.1016/j.
- Gardner, G.F., Gardner, L-W. and Gregory, A.R., 1974. Formation velocity and density the
- diagnostic basic for stratigraphic trap. Geophysics, 39: 770-780.
- Golpasand, M.B., Nikudel, M.R. and Uromeihy, A., 2013. Predicting the occurrence of mixed face
- conditions in tunnel route of Line 2 Tabriz metro, Tabriz, Iran. In; Wu, F. and Qi, S.,
- (Eds. ), Global View of Engineering Geology and the Environment. Taylor & Francis Group,
- London.
- Hering, A.. Misiek, R., Gyulai, A., Ormos. T., Dobroka, M. and Dresen, L.. 1995. A joint
- inversion algorithm to process geoelectric and sutface wave seismic data, Part 1: basic ideas.
- Geophys. Prosp., 43: 135-156.
- Journal_SEISMIC_No24-4:JOURNAL SEISMIC 11-06 24/086 14:23 Page325
- INVERSION OF RAYLEIGH WAVES 325
- Herrmann, R.B., 1987. Computer Programs in Seismology, User’s Manual II. St. Louis University,
- St. Louis, MS.
- Kearey, P., Brooks, M. and Hill, I.. 2002. An Introduction to Geophysical Exploration. Blackwell
- Publications, Oxford.
- Kennedy, J. and Eberhart, R.C., 1995. Particle swarm optimization. Proc. IEEE Internat. Conf.
- Neural Netw., Perth, Piscataway, Australia: 1942-1948.
- Louie, J.N., 2001. Faster, better: shear wave velocity to 100 meters depth from refraction
- microtremor arrays. Bull. Seismol. Soc. Am., 91: 347-364.
- Mahajan, A.K., Mundepi, A.K., Chauhan, N., Jasrotia, A.S., Rai, N. and Gachhayat, T.K., 2012.
- Active seismic and passive microtremor HVSR for assessing site effects in Jammu city, NW
- Himalaya, India, A case study. J. Appl. Geophys., 77: 51-62.
- Panzera. F. and Lombardo, G., 2013. Seismic property characterization of lithotypes cropping out
- in the Siracusa urban area, Italy. Engin. Geol., 153: 12-24.
- Peksen, E., Yas, T.A., Kayman, Y. and fzkan, C., 2011. Application of particle swarm
- optimization on self-potential data. J. Appl. Geophys., 75: 305-318.
- Poormirzaee, R. and Hamidzadeh, R.M., 2014. Determination of S-wave structure via refraction
- microtremor technique in urban area: a case study. J. Tethys, 2: 347-356.
- Poormirzaee, R., Hamidzadeh, R.M. and Zarean, A., 2014a. Inversion seismic refraction data using
- particle swarm optimization: a case study of Tabriz, Iran. Arab. J. Geosci., in press.
- DOI: 10. 1007/s12517-014-1662-x.
- Poormirzaee, R., Hamidzadeh, R.M. and Zarean, A., 2014b. PSO: a powerful and fast intelligence
- optimization method in processing of passive geophysical data. Proc. Internat. Conf. Swarm
- Intellig. Based Optimiz., Mulhouse, France: 12-19.
- Rucker, M.L., 2003. Applying the refraction microtremor (ReMi) shear wave technique to
- geotechnical characterization. Proc. 3rd Internat. Conf. Applic. Geophys. Methodol., 8-12.
- Schutte, J.F. and Groenwold, A.A., 2005. A study of global optimization using particle swarms.
- J. Global Optimiz., 31: 93-108.
- Scott, J.B., Clark, M., Rennie, T., Pancha, A., Park, H. and Louie, J.N., 2004. A shallow
- shear-wave velocity transect across the Reno, Nevada, area basin. Bull. Seismol. Soc. Am.,
- 94; 2222-2228.
- Seislmager/SW Manual, 2009. Windows Software for Analysis of Surface Waves. Version 3.0.
- http://www. geometrics.com.
- Shi, Y. and Eberhart, R.C., 1998. A modified particle swarm optimizer. Proc. [EEE Internat. Conf.
- Evolution. Computat., Piscataway, NJ: 69-73.
- Srinivas, N. and Deb, K., 1994. Multiobjective optimization using nondominated sorting in genetic
- algorithms. Evol. Comput., 2: 221-248.
- Stephenson, W.J., Louie, J.N., Pullammanappallil, $., Williams, R.A. and Odum, J.K., 2005. Blind
- shear-wave velocity comparison of ReMi and MASW results with boreholes to 200 m in
- Santa Clara Valley. Implications for earthquake ground-motion assessment. Bull. Seismol. Soc. Am.
- 95: 2506-2516.
- Trelea, I.C., 2003. The particle swarm optimization algorithm: Convergence analysis and parameter
- selection. Informat. Process. Lett., 85: 317-325.
- Xia, J., Miller, R.D. and Park, C.B., 1999. Estimation of near-surface shear-wave velocity by
- inversion of Rayleigh waves. Geophysics, 64: 691-700.
- Yang, X.S., 2010. Engineering Optimization, Introduction with Metaheuristic Applications. John
- Wiley & Sons, New York: 19-22.
- Zarean, A., Mirzaei, N. and Mirzaei, M., 2015. Applying MPSO for building shear wave velocity
- models from microtremor Rayleigh-wave dispersion curves. J. Seismic Explor., 24: 51-82.