Skip to main content

Construction of Shear Wave Models by Applying Multi-Objective Optimization to Multiple Geophysical Data Sets

  • Conference paper
  • First Online:
Analysis, Modelling, Optimization, and Numerical Techniques

Part of the book series: Springer Proceedings in Mathematics & Statistics ((PROMS,volume 121))

Abstract

For this work, our main purpose is to obtain a better understanding of the Earth’s tectonic processes in the Texas region, which requires us to analyze the Earth structure. We expand on a constrained optimization approach for a joint inversion least-squares (LSQ) algorithm to characterize a Earth’s structure of Texas with the use of multiple geophysical data sets. We employed a joint inversion scheme using multiple geophysical data sets for the sole purpose of obtaining a three-dimensional velocity structure of Texas in order to identify an ancient rift system within Texas. In particular, we use data from the USArray, which is part of the EarthScope experiment, a 15-year program to place a dense network of permanent and portable seismographs across the continental USA. Utilizing the USArray data has provided us with the ability to image the crust and upper mantle structure of Texas. We prove through numerical and experimental testing that our multiobjective optimization problem (MOP) scheme performs inversion in a more robust, and flexible matter than traditional inversion approaches.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Astiz, L., Earle, P., Shearer, P.: Global stacking of broadband seismograms. Seis. Res. Lett. 67, 8–18 (1996)

    Google Scholar 

  2. Bashir, L., Gao, S.S., Liu, K.H., Mickus, K.: Crustal structure and evolution beneath the Colorado Plateau and the southern Basin and Range Province: results from receiver function and gravity studies. Geochem. Geophys. Geosyst. 12, Q06008 (2011). doi:10.1029/2011GC003563

    Google Scholar 

  3. Bailey, I.W., Miller, M.S., Liu, K., Levander, A.. Vs and density structure beneath the Colorado Plateau constrained by gravity anomalies and joint inversions of receiver function and phase velocity data. J. Geophys. Res. 117, B02313 (2012). doi:10.1029/2011JB0085

    Google Scholar 

  4. Bodin, T., Sambridge, M., Tkalcic, H., Arroucau, P., Gallagher, K., Rawlinson, N.: Transdimensional inversion of receiver functions and surface wave dispersion. J. Geophys. Res. 117 (2012). doi:10.1029/2011JB008560

    Google Scholar 

  5. Cho, K.H., Herrmann, R.B., Ammon, C.J., Lee, K.: Imaging the upper crust of the Korean Peninsula by surface-wave tomography. Bull. Seismol. Soc. Am. 97, 198–207 (2007)

    Google Scholar 

  6. Colombo, D., De Stefano, M.: Geophysical modeling via simultaneous joint inversion of seismic, gravity, and electromagnetic data: Application to prestack depth imaging. Leading Edge 26, 326–331 (2007)

    Article  Google Scholar 

  7. Dzierma, Y., Rabbel, W., Thorwart, M.M., Flueh, E.R., Mora, M.M., Alvarado, G.E.: The steeply subducting edge of the Cocos Ridge: evidence from receiver functions beneath the northern Talamanca Range, south-central Costa Rica. Geochem. Geophys. Geosyst. 12 (2011). doi:10.1029/2010GC003477

    Google Scholar 

  8. Gurrola, H., Baker, E.G., Minster, B.J.. Simultaneous time-domain deconvolution with application to the computation of receiver functions. Geophys. J. Int. 120, 537–543 (1995)

    Article  Google Scholar 

  9. Haber, E., Oldenburg, D.: Joint inversion: A structural approach. Inverse Probl. 13, 63–77 (1997)

    Article  MATH  Google Scholar 

  10. Hansen, P.C.: Discrete inverse problems: Insight and algorithms, 225 pp. Soc. Ind. Appl. Math. Philadelphia, Pa. (2010)

    Google Scholar 

  11. Hansen, S.M., Dueker, K.G., Stachnik, J.C., Aster, R.C., Karlstrom, K.E.: A rootless rockies - Support and lithospheric structure of the Colorado Rocky Mountains inferred from CREST and TA seismic data. Geochem. Geophys. Geosyst. 14, 2670–2695 (2013). doi:10.1002/ggge.20143

    Article  Google Scholar 

  12. Hackney, R.I., Featherstone, W.E.: Geodetic versus geophysical perspectives of the gravity anomaly. Geophys. J. Int. 154(1), 35–43 (2003)

    Article  Google Scholar 

  13. Heiskanen, W.A., Moritz, H.: Physical geodesy. W. H. Freeman and Company, San Francisco (1967)

    Google Scholar 

  14. Julia, J., Ammon, C.J., Hermann, R., Correig, M.: Joint inversion of receiver function and surface wave dispersion observations. Geophys. J. Int. 142, 99–112 (2000)

    Article  Google Scholar 

  15. Kozlovskaya, E.: An algorithm of geophysical data inversion based on non-probabilistic presentation of a-prior information and definition of pareto-optimality. Inverse Probl. 16, 839–861 (2000)

    Article  MATH  MathSciNet  Google Scholar 

  16. Langston, C.A.: Evidence for the subducting lithosphere under southern Vancouver Island and western Oregon from teleseismic P wave conversions. J. Geophys. Res. 86, 3857–3866 (1981)

    Article  Google Scholar 

  17. Laske, G., Masters, G., Reif, C.: Crust 2.0. the current limits of resolution for surface wave tomography in North America. EOS Trans. AGU 81 F897 (2000). http://igpppublic.ucsd.edu/gabi/ftp/crust2/

    Article  Google Scholar 

  18. Lees, J.M., Vandecar, J.C.: Seismic tomography constrained by bouguer gravity anomalies: Applications in western Washington. PAGEOPH. 135, 31–52 (1991)

    Article  Google Scholar 

  19. Lin, F.C., Schmandt, B., Tsai, V.C.: Joint inversion of Rayleigh wave phase velocity and ellipticity using USArray: Constraining velocity and density structure in the upper crust. Geophys. Res. Lett. 39, L12303 (2012). doi:10.1029/2012GL052196

    Article  Google Scholar 

  20. Lodge, A., Helffrich, G.: Grid search inversion of teleseismic receiver functions. Geophys. J. Int. 178, 513–523 (2009)

    Article  Google Scholar 

  21. Maceira, M., Ammon, C.J.: Joint inversion of surface wave velocity and gravity observations and its application to central Asian basins s-velocity structure. J. Geophys. Res. 114, B02314 (2009). doi:10.1029/2007JB0005157.

    Article  Google Scholar 

  22. Moorkamp, M., Jones, A.G., Fishwick, S.: Joint inversion of receiver functions, surface wave dispersion, and magnetotelluric data. J. Geophys. Res. 115, B04318 (2010). doi:10.1029/2009JB0006369

    Article  Google Scholar 

  23. Moorkamp, M., Heincke, B., Jegen, M., Roberts, A.W., Hobbs, R.W.: A framework for 3–D joint inversion of MT, gravity and seismic refraction data. Geophys. J. Int. 184, 477–493 (2011)

    Article  Google Scholar 

  24. Nocedal, J., Wright, S.: Numerical optimization. 2nd edn. Springer, New York (2006)

    Google Scholar 

  25. Obrebski, M., Kiselev, S., Vinnik, L., Montagner, J.P.: Anisotropic stratification beneath Africa from joint inversion of SKS and P receiver functions. J. Geophys. Res. 115, B09313 (2010). doi:10.1029/2009JB006923

    Google Scholar 

  26. Owens, T.J., Crotwell, H.P., Groves, C., Oliver-Paul, P.: SOD: Standing order for data. Seismol. Res. Lett. 75, 515–520 (2004)

    Google Scholar 

  27. Sambridge, M.: Geophysical inversion with a neighborhood algorithm I: Searching a parameter space. Geophys. J. Int. 138, 479–494 (1999)

    Article  Google Scholar 

  28. Sambridge, M.: Geophysical inversion with a neighborhood algorithm II: Appraising the ensemble. Geophys. J. Int. 138, 727–746 (1999)

    Article  Google Scholar 

  29. Shearer, P.M.: Introduction to Seismology, 2nd edn. Cambridge University Press, Cambridge (2009)

    Book  Google Scholar 

  30. Shen, W., Ritzwoller, M.H., Schulte-Pelkum, V.: A 3-D model of the crust and uppermost mantle beneath the Central and Western US by joint inversion of receiver functions and surface wave dispersion. J. Geophys. Res. Solid Earth 118 (2013). doi:10.1029/2012JB009602

    Google Scholar 

  31. Sosa, A., Velasco, A.A., Velasquez, L., Argaez, M., Romero, R.: Constrained Optimization framework for joint inversion of geophysical data sets. Geophys. J. Int. 195, 197–211 (2013)

    Google Scholar 

  32. Stein, S., Wysession, M.: An introduction to seismology, earthquakes, and earth structure. Blackwell, Maiden (2003)

    Google Scholar 

  33. Tikhonov, A.N., Arsenin, V.Y.: Solutions if Ill-posed Problems. Winston and Sons, Washington (1977)

    Google Scholar 

  34. Vogel, C.R.: Computational methods for inverse problems. SIAM FR23, Philadelphia, (2002)

    Google Scholar 

  35. Vozoff, K., Jupp, D.L.B.: Joint inversion of geophysical data. Geophys. J. R. Astr. Soc. 42, 977–991 (1975)

    Article  Google Scholar 

  36. Wilson, D.: Imagining crust and upper mantle seismic structure in the southwestern United States using teleseismic receiver functions. Leading Edge 22, 232–237 (2003)

    Article  Google Scholar 

  37. Wilson, D., Aster, R.: Seismic imaging of the crust and upper mantle using Regularized joint receiver functions, frequency-wave number filtering, and Multimode Kirchhoff migration. J. Geophys. Res. B05305 (2005). doi:10.1029/2004JB003430

    Google Scholar 

  38. Wilson, D., Aster, R., Ni, J., Grand, S., West, M., Gao, W., Baldridge, W.S., Semken, S.: Imaging the structure of the crust and upper mantle beneath the Great Plains, Rio Grande Rift, and Colorado Plateau using receiver functions. J. Geophys. Res. 110, B05306 (2005). doi:10.1029/2004JB003492

    Google Scholar 

  39. Zhu, L., Kanamori, H.: Moho depth variation in southern California from teleseismic receiver functions. J. Geophys. Res. 105, 2969–2980 (2000)

    Article  Google Scholar 

Download references

Acknowledgment

We would like to take the time to thank the computational science, mathematical science, and computer science departments from University of Texas at El Paso (UTEP). We would also like to thank Ezer Patlan, Dr. Anibal Sosa, Dr. Rodrigo Romero, Dr. Monica Maceira, and Azucena Zamora for all of their contributions to this work. This work was sponsored by the NSF CREST under Grant Cybershare HRD-0734825.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Lennox Thompson .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer International Publishing Switzerland

About this paper

Cite this paper

Thompson, L., Velasco, A., Kreinovich, V. (2015). Construction of Shear Wave Models by Applying Multi-Objective Optimization to Multiple Geophysical Data Sets. In: Tost, G., Vasilieva, O. (eds) Analysis, Modelling, Optimization, and Numerical Techniques. Springer Proceedings in Mathematics & Statistics, vol 121. Springer, Cham. https://doi.org/10.1007/978-3-319-12583-1_22

Download citation

Publish with us

Policies and ethics