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Mejora de la interpretación de la tomografía de resistividad eléctrica con atributos de textura de la matriz de

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Este estudio mejora la interpretación de la tomografía de resistividad eléctrica (ERT) utilizando los atributos textuales de la Matriz de Coocurrencia de Nivel Gris (GLCM). GLCM mejora la delimitación de los límites de arcilla subterránea y las zonas de aguas subterráneas en entornos geológicos complejos.

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Área de la Ciencia:

  • La geofísica
  • Hidrogeología
  • Análisis de imágenes

Sus antecedentes:

  • La tomografía de resistividad eléctrica (ERT) es crucial para las imágenes subterráneas, pero la interpretación a menudo es ambigua debido a los límites lisos de la inversión.
  • Delinear los límites de arcilla es vital para la exploración de aguas subterráneas, pero los métodos tradicionales de ERT luchan con esto en entornos heterogéneos.

Objetivo del estudio:

  • Aplicar los atributos textuales de la Matriz de Coocurrencia de Nivel Gris (GLCM) para mejorar la interpretación del ERT.
  • Mejorar la precisión de la caracterización del subsuelo, especialmente para la evaluación de los recursos hídricos subterráneos.

Principales métodos:

  • Análisis de una encuesta 3D ERT de 100 × 100 m.
  • Aplicación de tres atributos textuales del GLCM: media, varianza y entropía.
  • Integración de los atributos GLCM con la inversión ERT tradicional.

Principales resultados:

  • GLCM Reducción media del suavizado de la inversión, mejora de la definición del límite de arcilla y de la morfología de la lente.
  • El GLCM Variance identificó una zona de recarga de alcance superficial previamente ambigua.
  • GLCM Entropy mejoró el contraste entre las unidades de arcilla y los depósitos de agua subterránea, ayudando a la discriminación de los acuíferos y las capas confinantes.

Conclusiones:

  • El análisis de la textura del GLCM mejora significativamente la interpretación del ERT en ambientes sedimentarios heterogéneos.
  • Este flujo de trabajo proporciona información textual adicional valiosa a partir de datos de resistividad eléctrica para una mejor caracterización del subsuelo.
  • El método muestra un gran potencial para la evaluación y gestión de los recursos hídricos subterráneos.