Improving the Resolution of 3-D Resistivity Surveys Along the Perimeter of a Confined Area Using Optimized Arrays

Three-dimensional (3-D) resistivity surveys usually use a rectangular grid of electrodes to accurately resolve the subsurface structures in areas with very complex geology. However, in some survey areas such as heavily urbanized areas, it is not possible to use a normal grid of electrodes due to physical obstructions such as constructions, buildings, or other types of obstacle. The only practical arrangement is to use electrodes confined to the perimeter of the survey area. Many approaches have been proposed to investigate subsurface features for confined areas, such as the “Baker” and “L and Corner” arrays. These techniques normally use heuristic rules and are designed for perimeters with sharp corners such as rectangles, but might not be applicable for perimeters with smooth shapes such as a circle. New techniques that automatically select arrays that maximize the model resolution can be adapted to select optimum arrays for perimeters of any shape. We study the effectiveness of two sets of optimized perimeter arrays generated based on a modified “Compare R” (CR) method. The performance of these optimized perimeter arrays is compared with the standard “L and Corner” arrays. This is demonstrated by using two synthetic examples and one field survey dataset. In the synthetic models, the results show that, when using both the optimized and standard arrays, the vertical resolution is poorer than the horizontal resolution. However, the optimized perimeter arrays produce better resolution and structure detectability than “L and Corner” arrays. In addition, there is a slight improvement with the noise-weighted optimized dataset, which shows slightly higher resistivity contrasts and the lowest data misfits.