A numerical comparison of enhancing horizontal resolution (EHR) technique utilizing 2D resistivity imaging

Abstract

The effectiveness of inversion apparent resistivity data to determine accurately the true resistivity distribution over 2D structures has been investigated using a common inversion scheme based on smoothness-constrained nonlinear least-squares optimization with enhancing horizontal resolution (EHR) technique by numerical simulation. The theoretical model generates in RES2DMOD software at specific distance and depth using Wenner, Wenner–Schlumberger, and pole–dipole arrays were inverted. The inversion model was compared with the original 2D model in RES2DINV software. The study model includes horizontal layering, vertical resolution, and horizontal two layers with different resistivity. Also, the response to variations in data density of these arrays was investigated. The study shows the best array suitable to be used in the survey was chosen for real data acquisition at the actual site. Subsequently, the results from borehole were used to verify the results of 2D resistivity imaging method with and without EHR technique. Saturated zone (0–40 Ω-m) was found scattered at the depth of 10–20 m. The borehole is located at 63 m at 2D resistivity imaging survey which shows at depth 10–20 m is sandy silt. Highly weathered sandstone was found at 6 m depth with resistivity value of 800 Ω-m and SPT N value of 20. The bedrock was found at 27 m depth with resistivity value of 3,000 Ω-m and SPT N value of 50. The application of 2D resistivity imaging with EHR technique indicate the ability of the proposed approach in terms of density, depth, and resistivity value of anomalous and layer in a computationally and numerically efficient manner and to exhibit good performance in the data inversion.