Increasing the Resolution of the Inversion by Combining Deep Resistivity with Ultra-Deep Resistivity

Abstract This paper explores the enhancement of 1D inversion resolution by integrating Deep Azimuthal Resistivity (DAR) and Ultra-Deep Azimuthal Resistivity (UDAR) data. The primary aim is to improve the resolution of resistivity models, focusing on the identification of thin layers and increased depth of detection (DOD). The enhanced resolution in 1D inversion supports more accurate geological interpretation, particularly in reservoirs with complex layering and subtle petrophysical variations. The workflow employs a hybrid inversion approach that combines DAR and UDAR measurements. This method leverages parameter domain scanning and forward modeling to refine inversion results. By increasing the depth of detection through UDAR, and using DAR to capture finer resistivity contrasts, the inversion process enhances the resolution of the model. Misfit analysis and azimuthal signal variations across frequencies help identify and address multi-dimensional influences, enabling more accurate 1D resistivity profiles. The resulting models are generated with ultra-high-definition (UHD) resolution, allowing for a more precise interpretation of subsurface features, particularly thin layers and boundary delineations. The use of enhanced resolution in 1D inversion helps address challenges in complex reservoirs with fine-scale variations, allowing for better detection of thin layers and more precise boundary delineation. The methodology offers a significant improvement in subsurface mapping and enhances the overall reliability of reservoir evaluations.