Images reconstruction for well to well tomography with Levenberg Marquardt method

The Cross-Borehole-Seismic Tomography is a seismic method most used for the determination of subsurface structure of the land. This method involves placing in a borehole the seismic wave generating sources, and in another borehole the receiver as waves detector. The tomographic image reconstructed f...

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Detalles Bibliográficos
Autores: Chambi Chambi, Juan, Carita Montero, Raul, Berrocal Tito, Mariella
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2013
País:Perú
Institución:Universidad Nacional Mayor de San Marcos
Repositorio:Revistas - Universidad Nacional Mayor de San Marcos
Idioma:español
OAI Identifier:oai:revistasinvestigacion.unmsm.edu.pe:article/8680
Acceso en línea:https://revistasinvestigacion.unmsm.edu.pe/index.php/fisica/article/view/8680
Access Level:acceso abierto
Palabra clave:Inverse problem
Cross-Borehole-Seismic Tomography
Levenberg Marquardt method.
Problema inverso
tomografía pozo a pozo
método Levenberg Marquardt.
Descripción
Sumario:The Cross-Borehole-Seismic Tomography is a seismic method most used for the determination of subsurface structure of the land. This method involves placing in a borehole the seismic wave generating sources, and in another borehole the receiver as waves detector. The tomographic image reconstructed from Cross-Borehole-Seismic Tomography is obtained by considering a parameter called slowness which is reverse speed with which the seismic waves travel, slowness S varies depending on the geological structure. We consider direct waves traveling from one borehole to another and we obtain an approximation of the following linear system as MS = T , where M is a matrix and is related to the discretization domain, S is the vector formed by the slowness of each discretized domain element and T is the arrival time of the first wave coming from source to detector. For the evaluation of the algorithms we design underground structures, which get the data from the detectors. To obtain more realistic data, we added random noise to 3.0%. With these data we proceed to rebuild the soil properties.