REFR-REFL_SeisTOMO A nonlinear method is used to compute first seismic arrivals and reflection travel times for velocity models with complex reflector geometry. The method uses a combination of refraction and reflection travel-times for simultaneous determination of velocity and interface depth of the model. The elastic waves assumed to be transmitted or reflected at interfaces at which the raypaths satisfy Snell’s law. The travel times of critically refracted waves and derivative matrix are computed by applying a revised ray bending method, supplemented by an approximate computation of the first Fresnel zone at each point of the ray. Travel-times and raypaths of reflected waves are computed by applying a fast finite-difference scheme based on a solution to the eikonal equation and following the travel-time gradient backward from the receiver to the source, respectively. A damped least squares inversion scheme is used to reconstruct the velocity model above the reflector and the geometry of the interface by minimizing the difference between observed and calculated (direct, refracted and reflected) travel-times. In order to reduce inversion artifacts both damping and smoothing regularization factors are applied. The applicability of the proposed method is tested using synthetic data. This simultaneous inversion scheme is appropriate for static seismic corrections, as well as determination of lateral velocity variations and reflector’s geometry. 

This algorithm presented in detail at the followings publications,

  • Soupios P., Papazachos C. and Tsokas G., 1999, Simultaneous Determination of velocity and Interface depth in reflection tomography, In Second Balkan Geophysical Congress and Exhibition.
  • Soupios, P. M., Papazachos, C. B., Juhlin, C. and Tsokas, G. N., 2001, Nonlinear Three-Dimensional Traveltime Inversion of Crosshole Data with an Application in the Area of Middle Urals, Geophysics, 66, 627-636.
  • Soupios, P.M., Papazachos, C.B., Vallianatos, F., Papakostas, T., 2003, Numerical Treatment and Inspection of Inverse Problems, WSEAS Transactions, Issue 3, Vol. 2, pp. 547-552, ISSN 1109-2734.
  • Soupios P, Papazachos C, Tsokas G, Vafidis A, 2005, Non-Linear Inversion of Seismic Data for the Determination of Reflector Geometry and Velocity Structure, Journal of Balkan Geophysical Society, Σεπτέμβριος 2005.
  • Soupios, P.M., Tamas Toth, 2005, A Shallow Marine Seismic Reflection Survey in Lake Balaton, Journal of Balkan Geophysical Society, Vol. 8, No. 1, February, 2005, pp. 20-27.
HybridGenetic_SeisTOMO The application of hybrid genetic algorithms in seismic tomography is examined and the efficiency of least-squares and genetic methods as representative of the local and global optimization, respectively, is presented and evaluated. The robustness of both optimization methods has been tested and compared for the same source-receiver geometry and characteristics of the model structure (anomalies, etc.). In order to solve the forward modeling and estimate the traveltimes, revisited ray bending method was used supplemented by an approximate computation of the first Fresnel volume. The root mean square (RMS) error as the misfit function was used and calculated for the entire random velocity model for each generation. After the end of each generation and based on the misfit of the individuals (velocity models), the selection, crossover and mutation (typical process steps of genetic algorithms) operators take place continuing the evolution theory and coding the new generation. To optimize the computation time, since the whole procedure, the MATLAB Distributed Computing Engine (MDCE) was used in a multicore engine. During the tests, the initially fast convergence of the algorithm (typically first 5 generations) is followed by progressively slower improvements of the reconstructed velocity models. Therefore, to improve the final tomographic models, a hybrid genetic algorithm (GA) approach was adopted by combining the GAs with a local optimization method after several generations, on the basis of the convergence of the resulting models. This approach is shown to be efficient, as it directs the solution search towards a model region close to the global minimum.

This algorithm presented in detail at the followings publications,

  • Soupios P., Akca I., Mpogiatzis P., Basokur A. and Papazachos C., 2010, Application of Genetic Algorithms in Seismic Tomography, EGU meeting, 2-7 May, Vienna (EGU2010-1555.pdf)
  • Soupios P, Akca I, Mpogiatzis P, Basokur A, Papazachos C., Applications of Hybrid Genetic Algorithms in Seismic Tomography, Journal of Applied Geophysics, Volume 75, Issue 3, November 2011, Pages 479-489

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