When collecting data using ERT2D (2D electrical resistivity tomography) and TDIPT2D (2D time domain-induced polarization), different phenomena can occur, which can cause natural or anthropogenic noise, contaminating the data and making its processing, analysis, and interpretation difficult. Different techniques have been developed to eliminate or reduce these effects on the data, such as noise filtering or the development of new techniques to improve data collection in the field. In the present work, an iterative, weighted, least-squares filter was employed after voltage normalization using current and geometrical factor correction on data collected in rough topographic terrains. The selected filter basis function should be able to represent the natural behavior of the function to be filtered. Stationary or variable voltages in electrical prospecting decay with the inverse of the distance, which can be represented by an expansion in Legendre polynomials. On the other hand, uneven spacing of the electrodes leads to using the incorrect geometric factor, resulting in an error in the calculation of the electrical anomaly. The efficiency of the proposed technique was analyzed and tested with field examples using different filters and by comparing applying and not applying the proposed correction factor. The results indicated low RMS and L2-Norm errors, and better definition of the inverted resistivity image was obtained. For the TDIP data, a better correspondence between the inverted images of resistivity and chargeability was obtained.

Se desarrolló un curso en línea de modelado e inversión de datos geoeléctricos empleando software libre o comercial demostrativo, con el propósito de eficientar, enriquecer y complementar el desarrollo académico y la experiencia educativa del alumnado en la asignatura de Prospección Eléctrica (PE) del 8° semestre de la carrera de Ingeniería Geofísica de la Facultad de Ingeniería (FI) de la Universidad Nacional Autónoma de México (UNAM). Otro propósito que se persigue con este desarrollo es mejorar la oferta educativa en línea que ofrece la UNAM en materia de Ciencias de la Tierra. Este curso fue implementado por primera vez de febrero a mayo de 2022 de forma híbrida (presencial y a distancia). En comparación con cursos previos, en éste los estudiantes necesitaron menos tiempo para conocer y utilizar software de interpretación de datos geoeléctricos en corriente continua (o DC por sus siglas en inglés). Adicionalmente, mediante videos demostrativos se mejoró la comprensión del proceso de adquisición de datos reales en prácticas de campo, y finalmente, se generó un espacio virtual como apoyo a la comunidad en el proceso de enseñanza-aprendizaje, durante y después de la pandemia.

When collecting data from ERT2D (electrical resistivity tomography) and TDIPT2D (time domain IP tomography), different phenomena occur, whether natural or anthropogenic noise, which contaminate the data, and it can make their processing, analysis and interpretation difficult. Different techniques have been developed to eliminate or reduce these effects on the data, such as noise filtering or the development of new techniques for better data collection in the field. In the present work an iterative weighted least squares filter is employed after voltage normalization by current and a geometrical factor correction applied on strong topographic terrains. The selection of the filter basis function is recommended to be able to represent the natural behavior of the function to be filtered. Stationary or variable voltages in electrical prospecting decay with the inverse of the distance, which can be represented by an expansion in Legendre polynomials. On the other hand, uneven spacing of the electrodes leads to not using the correct geometric factor which results in an error in the calculation of the electrical anomaly. The efficiency of the proposed technique is analyzed and tested with field examples using different filters and applying the proposed correction factor or without using it. The results indicate a low RMS and L2-Norm error, whereby a better definition of the inverted resistivity image is obtained. For the TDIP case a better correspondence between the inverted images of resistivity and chargeability can be reached.