Effects of Electrode Spacing and Inversion Techniques on the Efficacy of 2D Resistivity Imaging to Delineate Subsurface Features

In this study, the effect of the choice of appropriate electrode spacing and inversion algorithms on the efficacy of 2D imaging to map subsurface features was investigated. The target being investigated was the drainage concrete pipe buried at approximately 0.3 m into the subsurface. A profile perpendicular to the strike of the pipe was established. 2D resistivity data was separately collected with the electrode spacings of 1.5 m and 0.5 m. using the Dipole-Dipole, the Wenner and the Wenner-Schlumberger array configurations. The results obtained showed that when the electrode spacing of 1.5 m was used for the investigations, none of the three array types was able to map the target with either of the two inversion techniques. The results further show that the attainment of RMS error of less about 10% which usually gives the indication of a good subsurface model is not a guarantee that subsurface features are successfully mapped. On the other hand, when the electrode spacing of 0.5 m was used for the data collection, the results obtained with the standard constrains inversion technique showed that all the three array configurations mapped the target however, only the dipole-dipole array was able to resolve the boundary between the concrete pipe and the entrapped air. With the robust constrain inversion technique; the target was also successfully mapped by all the three array types. In addition to this, the boundary between the entrapped air and the concrete pipe was resolved by all the three array types. This suggests that if there is a significant contrast in the subsurface layers’ resistivities, the robust constrain inversion algorithm technique gives better boundaries resolution irrespective of the array types used for the survey. The inversion of the 3D data gave 3D resistivity sections which were presented as horizontal depth slices. The result obtained from the inversion of the 3D data has assisted us in getting information about the dimension and orientation of the target. The study revealed that a miniature subsurface feature can only be effectively delineated if the feature is not deeply buried into the subsurface.