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İki Boyutlu Radyo-Manyetotelürik Verilerin Doğrusal Olmayan Yüzdelik Süzgeç ile Parçacık Sürüsü Optimizasyonu Kullanılarak Modellenmesi

Year 2021, Volume: 42 Issue: 3, 301 - 311, 23.12.2021
https://doi.org/10.17824/yerbilimleri.815473

Abstract

Jeofizik verilerin modellenmesi amacıyla kullanılan geleneksel ters çözüm yöntemlerinde, yuvarlatıcılı ve keskin sınırlı modelleme için genelde türev tabanlı durağanlaştırıcılar kullanılır. Bu yöntemler genelde verilerin model parametrelerine göre kısmi türevlerinden oluşan Jacobian matrisinin hesabına gereksinim duyar.
Buna karşın, Jacobian dizeyi çoğu Global Optimizasyon yöntemi için gereksizdir ve en uygun model “deneme yanılma” ile belirlenir. Bu çalışmada, görüntü işleme uygulamalarında sıklıkla kullanılan, doğrusal olmayan bir görüntü işleme süzgeci olan yüzdelik süzgeç kullanılarak görece verimli bir Global Optimizasyon yaklaşımı geliştirilmiştir.
Yöntemin başarısı, evrimsel Global Optimizasyon yöntemi olan Parçacık Sürüsü Optimizasyonu kullanılarak gösterilmiştir ve Radyo-Manyetotelürik verilerin 2 Boyutlu modellenmesi için uygulanmıştır. Geliştirilen işleçte, yüzdelik süzgecin model parametrelerindeki yüksek frekanslı değişimleri atarken yapı sınırlarını koruduğu gözlenmiştir. Ayrıca, yuvarlatıcı Gauss süzgeciyle kıyaslandığında daha az yineleme gerektirdiği belirlenmiştir. İşlecin başarısı hem yapay hem de arazi veri kümeleri üzerinde gösterilmiş ve sonuçları kıyaslanmıştır.

Thanks

Düz ve yuvarlatıcılı ters çözüm Manyetotelürik algoritmalarının geliştirilmesinde katkısı bulunan Prof.Dr. Emin Candansayar’a, Dr. İsmail Demirci’ye, Dr. Özcan Özyıldırım’a, Dr. Erhan Erdoğan’a, Dr. Cem Demirel’e teşekkür ederim. RMT arazi verisini sağlayan Prof.Dr. Emin Candansayar ve Prof.Dr. Bülent Tezkan’a teşekkür ederim.

References

  • Akça, I., Başokur, A.T., 2010. Extraction of structure-based geoelectric models by hybrid genetic algorithms. Geophysics 75 (1), F15–F22.
  • Akça, İ., Günther, T., Müller-Petke, M., Basokur, A.T., Yaramanci, U., 2014. Joint parameter estimation from magnetic resonance and vertical electric soundings using a multiobjective genetic algorithm. Geophys. Prospect. 62 (2), 364–376.
  • Attwa, M., Akca, I., Basokur, A. T., & Günther, T., 2014. Structure-based geoelectrical models derived from genetic algorithms: a case study for hydrogeological investigations along Elbe River coastal area, Germany. Journal of Applied Geophysics, 103, 57-70.
  • Candansayar, M.E., Tezkan, B., 2008. Two-dimensional joint inversion of radiomagnetotelluric and direct current resistivity data. Geophys. Prospect. 56 (5), 737–749.
  • Clerc, M., Kennedy, J., 2002. The particle swarm–explosion, stability, and convergence in a multidimensional complex space. IEEE Trans. Evol. Comput. 6 (1), 58–73.
  • deGroot-Hedlin, C., Constable, S., 1990. Occam inversion to generate smooth, 2-dimensional models from magnetotelluric data. Geophysics 55 (12), 1613–1624.
  • de Groot-Hedlin, C., & Constable, S., 2004. Inversion of magnetotelluric data for 2D structure with sharp resistivity contrasts. Geophysics, 69(1), 78-86.
  • Karcıoğlu, G., Gürer, A., 2019. Implementation and model uniqueness of Particle Swarm Optimization method with a 2D smooth modeling approach for Radio-Magnetotelluric data. Journal of Applied Geophysics, 169, 37-48.
  • Kelbert, A., Meqbel, N., Egbert, G. D., & Tandon, K., 2014. ModEM: A modular system for inversion of electromagnetic geophysical data. Computers & Geosciences, 66, 40-53.
  • Kennedy, J., 2003. Bare bones particle swarm. Proc. IEEE SIS, Apr. 2003, pp. 80–87.
  • Li, X., Yao, X., 2011. Cooperatively Coevolving Particle Swarms for large Scale Optimization. IEEE Trans. Evol. Comput. 16 (2), 210–224.
  • Mehanee, S., Zhdanov, M., 2002. Two‐dimensional magnetotelluric inversion of blocky geoelectrical structures. Journal of Geophysical Research: Solid Earth, 107(B4), EPM-2.
  • Montes de Oca, M.A., Van den Enden, K., Stützle, T., 2008. Incremental particle swarmguided local search for continuous optimization. In: Blesa, M.J., vd. (Eds.), LNCS 5296. Proceedings of the InternationalWorkshop on HybridMetaheuristics. Springer, Berlin, Germany, pp. 72–86.
  • Montesinos, F.G., Arnoso, J., Vieira, R., 2005. Using a genetic algorithm for 3-D inversion of gravity data in Fuerteventura (Canary Islands). Int. J. Earth Sci. 94 (2), 301–316.
  • Moorkamp,M., Jones, A.G., Eaton, D.W., 2007. Joint inversion of teleseismic receiver functions and magnetotelluric data using a genetic algorithm: are seismic velocities and electrical conductivities compatible? Geophys. Res. Lett. 34, L16311.
  • Moorkamp,M., Jones, A.G., Fishwick, S., 2010. Joint inversion of receiver functions, surface wave dispersion and magnetotelluric data. J. Geophys. Res. 115 (2010), B04318.
  • Özyıldırım, Ö., Candansayar, M. E., Demirci, İ., & Tezkan, B., 2017. Two-dimensional inversion of magnetotelluric/radiomagnetotelluric data by using unstructured mesh. Geophysics, 82(4), E197-E210.
  • Pallero, J.L.G., Fernández-Martínez, J.L., Bonvalot, S., Fudym, O., 2017. 3D gravity inversion and uncertainty assessment of basement relief via Particle Swarm Optimization. J. Appl. Geophys. 139, 338–350.
  • Pekşen, E., Yas, T., Kayman, A. Y., & Özkan, C., 2011. Application of particle swarm optimization on self-potential data. Journal of Applied Geophysics, 75(2), 305-318.
  • Pekşen, E., Yas, T., & Kıyak, A., 2014. 1-D DC resistivity modeling and interpretation in anisotropic media using particle swarm optimization. Pure and Applied Geophysics, 171(9), 2371-2389.
  • Portniaguine, O., & Zhdanov, M. S., 1999. Focusing geophysical inversion images. Geophysics, 64(3), 874-887.
  • Sasaki, Y., 1989. Two-dimensional joint inversion of magnetotelluric and dipole-dipole resistivity data. Geophysics 54, 254–262.
  • Sen, M. K., Stoffa, P. L., 2013. Global optimization methods in geophysical inversion. Cambridge University Press.
  • Streich, R., 2003. Geophysical Prospecting of Suspected Holocene Fault Activity in the Lower Rhine Embayment. Ph.D. thesis. Potsdam University.
Year 2021, Volume: 42 Issue: 3, 301 - 311, 23.12.2021
https://doi.org/10.17824/yerbilimleri.815473

Abstract

References

  • Akça, I., Başokur, A.T., 2010. Extraction of structure-based geoelectric models by hybrid genetic algorithms. Geophysics 75 (1), F15–F22.
  • Akça, İ., Günther, T., Müller-Petke, M., Basokur, A.T., Yaramanci, U., 2014. Joint parameter estimation from magnetic resonance and vertical electric soundings using a multiobjective genetic algorithm. Geophys. Prospect. 62 (2), 364–376.
  • Attwa, M., Akca, I., Basokur, A. T., & Günther, T., 2014. Structure-based geoelectrical models derived from genetic algorithms: a case study for hydrogeological investigations along Elbe River coastal area, Germany. Journal of Applied Geophysics, 103, 57-70.
  • Candansayar, M.E., Tezkan, B., 2008. Two-dimensional joint inversion of radiomagnetotelluric and direct current resistivity data. Geophys. Prospect. 56 (5), 737–749.
  • Clerc, M., Kennedy, J., 2002. The particle swarm–explosion, stability, and convergence in a multidimensional complex space. IEEE Trans. Evol. Comput. 6 (1), 58–73.
  • deGroot-Hedlin, C., Constable, S., 1990. Occam inversion to generate smooth, 2-dimensional models from magnetotelluric data. Geophysics 55 (12), 1613–1624.
  • de Groot-Hedlin, C., & Constable, S., 2004. Inversion of magnetotelluric data for 2D structure with sharp resistivity contrasts. Geophysics, 69(1), 78-86.
  • Karcıoğlu, G., Gürer, A., 2019. Implementation and model uniqueness of Particle Swarm Optimization method with a 2D smooth modeling approach for Radio-Magnetotelluric data. Journal of Applied Geophysics, 169, 37-48.
  • Kelbert, A., Meqbel, N., Egbert, G. D., & Tandon, K., 2014. ModEM: A modular system for inversion of electromagnetic geophysical data. Computers & Geosciences, 66, 40-53.
  • Kennedy, J., 2003. Bare bones particle swarm. Proc. IEEE SIS, Apr. 2003, pp. 80–87.
  • Li, X., Yao, X., 2011. Cooperatively Coevolving Particle Swarms for large Scale Optimization. IEEE Trans. Evol. Comput. 16 (2), 210–224.
  • Mehanee, S., Zhdanov, M., 2002. Two‐dimensional magnetotelluric inversion of blocky geoelectrical structures. Journal of Geophysical Research: Solid Earth, 107(B4), EPM-2.
  • Montes de Oca, M.A., Van den Enden, K., Stützle, T., 2008. Incremental particle swarmguided local search for continuous optimization. In: Blesa, M.J., vd. (Eds.), LNCS 5296. Proceedings of the InternationalWorkshop on HybridMetaheuristics. Springer, Berlin, Germany, pp. 72–86.
  • Montesinos, F.G., Arnoso, J., Vieira, R., 2005. Using a genetic algorithm for 3-D inversion of gravity data in Fuerteventura (Canary Islands). Int. J. Earth Sci. 94 (2), 301–316.
  • Moorkamp,M., Jones, A.G., Eaton, D.W., 2007. Joint inversion of teleseismic receiver functions and magnetotelluric data using a genetic algorithm: are seismic velocities and electrical conductivities compatible? Geophys. Res. Lett. 34, L16311.
  • Moorkamp,M., Jones, A.G., Fishwick, S., 2010. Joint inversion of receiver functions, surface wave dispersion and magnetotelluric data. J. Geophys. Res. 115 (2010), B04318.
  • Özyıldırım, Ö., Candansayar, M. E., Demirci, İ., & Tezkan, B., 2017. Two-dimensional inversion of magnetotelluric/radiomagnetotelluric data by using unstructured mesh. Geophysics, 82(4), E197-E210.
  • Pallero, J.L.G., Fernández-Martínez, J.L., Bonvalot, S., Fudym, O., 2017. 3D gravity inversion and uncertainty assessment of basement relief via Particle Swarm Optimization. J. Appl. Geophys. 139, 338–350.
  • Pekşen, E., Yas, T., Kayman, A. Y., & Özkan, C., 2011. Application of particle swarm optimization on self-potential data. Journal of Applied Geophysics, 75(2), 305-318.
  • Pekşen, E., Yas, T., & Kıyak, A., 2014. 1-D DC resistivity modeling and interpretation in anisotropic media using particle swarm optimization. Pure and Applied Geophysics, 171(9), 2371-2389.
  • Portniaguine, O., & Zhdanov, M. S., 1999. Focusing geophysical inversion images. Geophysics, 64(3), 874-887.
  • Sasaki, Y., 1989. Two-dimensional joint inversion of magnetotelluric and dipole-dipole resistivity data. Geophysics 54, 254–262.
  • Sen, M. K., Stoffa, P. L., 2013. Global optimization methods in geophysical inversion. Cambridge University Press.
  • Streich, R., 2003. Geophysical Prospecting of Suspected Holocene Fault Activity in the Lower Rhine Embayment. Ph.D. thesis. Potsdam University.
There are 24 citations in total.

Details

Primary Language Turkish
Subjects Engineering
Journal Section Articles
Authors

Gökhan Karcıoğlu 0000-0002-5081-8113

Publication Date December 23, 2021
Submission Date October 23, 2020
Acceptance Date November 24, 2021
Published in Issue Year 2021 Volume: 42 Issue: 3

Cite

EndNote Karcıoğlu G (December 1, 2021) İki Boyutlu Radyo-Manyetotelürik Verilerin Doğrusal Olmayan Yüzdelik Süzgeç ile Parçacık Sürüsü Optimizasyonu Kullanılarak Modellenmesi. Yerbilimleri 42 3 301–311.