
AIMS Geosciences, 2016, 2(1): 6387. doi: 10.3934/geosci.2016.1.63
Research article Special Issues
Export file:
Format
 RIS(for EndNote,Reference Manager,ProCite)
 BibTex
 Text
Content
 Citation Only
 Citation and Abstract
A MultiObjective Optimization Framework for Joint Inversion
1 Department of Geological Sciences, University of Texas at El Paso (UTEP), 500 W. University Avenue, El Paso, TX 79968, USA
2 Department of Computer Science, University of Texas at El Paso (UTEP), 500 W. University Avenue, El Paso, TX 79968, USA
Received: , Accepted: , Published:
Special Issues: Inversion methods and strategies to integrate multidisciplinary geophysical data
To make the joint inversion process more robust, it is therefore desirable to repeatedly solve the joint inversion problem with different possible combinations of variances. From the mathematical viewpoint, such solutions form a Pareto front of the corresponding multiobjective optimization problem.
References
1. Bashir, L., S.S. Gao, K.H. Liu, and K. Mickus (2011). 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, doi:10.1029/2011GC003563.
2. Bailey, I.W., M.S. Miller, K. Liu, and A. Levander (2012). 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, doi:10.1029/2011JB0085.
3. Cho, K. H., R. B. Herrmann, C. J. Ammon, and K. Lee (2007). Imaging the upper crust of the Korean Peninsula by surfacewave tomography. Bulletin of the Seismological Society of America, 97, pp 198–207.
4. Colombo, D., and M. De Stefano (2007). Geophysical modeling via simultaneous joint inversion of seismic, gravity, and electromagnetic data: Application to prestack depth imaging. The Leading Edge, 26, pp 326–331.
5. Dzierma, Y., W. Rabbel, M.M. Thorwart, E.R. Flueh, M.M. Mora, and G.E. Alvarado (2011). The steeply subducting edge of the Cocos Ridge: evidence from receiver functions beneath the northern Talamanca Range, southcentral Costa Rica. Geochem. Geophys. Geosyst. 12: doi:10.1029/2010GC003477.
6. Gurrola, H., E. G. Baker, and B.J. Minster (1995). Simultaneous timedomain deconvolution with application to the computation of receiver functions. Geophys. J. Int., 120, pp. 537–543.
7. Jin, G., and J. B. Gaherty (2014), Surface Wave Measurement Based on Crosscorrelation, Geophys. J. Int, submitted.
8. Haber, E., and D. Oldenburg (1997). Joint inversion: a structural approach. Inverse Problems, 13, pp. 63–77.
9. Hansen, P.C. (2010). Discrete Inverse Problems: Insight and Algorithms, 225pp., Soc. for Ind. and Appl. Math., Philadelphia, Pa.
10. Hansen, S.M., K.G. Dueker, J.C. Stachnik, R.C. Aster, and K.E. Karlstrom (2013). 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, doi:10.1002/ggge.20143.
11. Julia, J., C. J. Ammon, R. Hermann, and M. Correig (2000). Joint inversion of receiver function and surface wave dispersion observations. Geophys. J. Int., 142, pp. 99–112.
12. Kozlovskaya, E. (2000). An algorithm of geophysical data inversion based on nonprobabilistic presentation of aprior information and definition of paretooptimality. Inverse Problems, 16, pp. 839–861.
13. Langston, C. A. (1981). Evidence for the subducting lithosphere under southern Vancouver Island and western Oregon from teleseismic P wave conversions. J. Geophys. Res., 86, pp. 3857–3866.
14. Laske, G., G. Masters and C. Reif (2000). Crust 2.0. The Current Limits of Resolution for Surface Wave Tomography in North America. EOS Trans AGU, 81, F897, http://igpppublic.ucsd.edu/gabi/ftp/crust2/
15. Lees, J.M. and J. C. Vandecar (1991). Seismic tomography constrained by bouguer gravity anomalies: Applications in western Washington. PAGEOPH, 135, pp 31–52.
16. Ligorria, J. P., and C. J. Ammon (1999), Iterative deconvolution and receiverfunction estimation, Bull. Seismol. Soc. Am., 89(5), pp 1395–1400.
17. Maceira, M., and C.J. Ammon (2009). Joint inversion of surface wave velocity and gravity observations and its application to central Asian basins svelocity structure. J. Geophys Res., 114,
B02314, doi:10.1029/2007JB0005157.
18. Nocedal, J. and S.J. Wright (2006). Numerical Optimization. 2nd edn. Springer, New York, NY.
19. Obrebski, M., S. Kiselev, L. Vinnik, and J. P. Montagner (2010). Anisotropic stratification beneath Africa from joint inversion of SKS and P receiver functions. J. Geophys. Res., 115, B09313, doi:10.1029/2009JB006923.
20. Owens, T. J., H. P. Crotwell, C. Groves, and P. OliverPaul (2004). SOD: Standing Order for Data. Seismol. Res. Lett., 75, 515–520.
21. Sambridge, M. (1999a). Geophysical inversion with a neighborhood algorithm I: searching a parameter space. Geophys. J. Int., 138, pp. 479–494.
22. Sambridge, M. (1999b). Geophysical inversion with a neighborhood algorithm II: appraising the ensemble. Geophys. J. Int., 138, pp. 727–746.
23. Shearer, P.M. (2009). Introduction to Seismology, Second Edition, Cambridge University Press, Cambridge.
24. Shen W., M. H. Ritzwoller, and V. SchultePelkum (2013). A 3D 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, doi:10.1029/2012JB009602.
25. Sosa, A., A.A. Velasco, L. Velasquez, M. Argaez, and R. Romero. (2013). Constrained Optimization framework for joint inversion of geophysical data sets. Geophys. J. Int., 195, pp 197–211.
26. Stein, S., and M. Wysession (2003). An Introduction to Seismology Earthquakes and Earth Structure, Blackwell, Maiden, Mass.
27. Thompson, L., A. A. Velasco, V. Kreinovich, R. Romero, and A. Sosa, 2016, 3D Shear Wave Based Models of the Texas Region Using 1D Constrained MultiObjective Optimization, Journal of Geophysical Research, (submitted for publication).
28. Tikhonov, A. N., and V.Y. Arsenin (1977). Solution of IllPosed Problems. VH Winston & Sons, Washington, D.C.
29. Vogel, C. R. (2002). Computational Methods for Inverse Problems. SIAM FR23, Philadelphia.
30. Vozoff, K. and D. L. B. Jupp (1975). Joint inversion of geophysical data. Geophys. J. Roy Astr. Soc., 42, pp. 977–991.
31. Wilson, D. (2003). Imagining crust and upper mantle seismic structure in the southwestern United States using teleseismic receiver functions. Leading Edge 22, pp. 232–237.
32. Wilson, D., and R. Aster (2005). Seismic imaging of the crust and upper mantle using Regularized joint receiver functions, frequencywave number filtering, and Multimode Kirchhoff migration. J. Geophys. Res., B05305, doi:10.1029/2004JB003430.
33. Wilson, D., R. Aster, J. Ni, S. Grand, M. West, W. Gao, W.S. Baldridge, and S. Semken (2005). 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, doi:10.1029/2004JB003492.
Copyright Info: © 2016, Lennox Thompson, et al., licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution Licese (http://creativecommons.org/licenses/by/4.0)