The Role of Model Dimensionality in Linear Inverse Scattering from Dielectric Objects

This paper deals with 3D and 2D linear inverse scattering approaches based on the Born approximation, and investigates how the model dimensionality influences the imaging performance. The analysis involves dielectric objects hosted in a homogenous and isotropic medium and a multimonostatic/multifrequency measurement configuration. A theoretical study of the spatial resolution is carried out by exploiting the singular value decomposition of 3D and 2D scattering operators. Reconstruction results obtained from synthetic data generated by using a 3D full-wave electromagnetic simulator are reported to support the conclusions drawn from the analysis of resolution limits. The presented analysis corroborates that 3D and 2D inversion approaches have almost identical imaging performance, unless data are severely corrupted by the noise.

Resistivity Method for Characterising Subsurface Layers of Coastal Areas In South Sulawesi, Indonesia

The data presented in this paper are related to the characterization of a subsurface layer of coastal area in South Sulawesi. This research will fill the gap in the resistivity method study which is this method not yet use in the coastlines area, especially area influenced by seawater and coastal condition impact like South Sulawesi. The method used in this study is the method of resistivity Wenner configuration by taking the data 1-2 lines each region with lengths 45 m, 75 m, 105 m, and 120 m respectively. Data processing using non-linear least square optimization with that of the 2D inversion software Res2Dinv. The results show that the area is underlain by two layers of lithologic sections. In some sections interpreted by sandy layer, clay, sandstone, alluvium, sandy in seawater and metal minerals. From the analysis of the layers, all regions show the resistivity minimum is 0.00849 Ωm and 8.04 Ωm maximum resistivity. The result of this research can give n insight to study the large coastal area subsurface.

2D inversion of electrical resistivity investigation of contaminant plume around a dumpsite near Onitsha expressway in southeastern Nigeria

The study tries to utilize vertical electrical sounding (VES) and 2D resistivity tomography to evaluate the region of influence of the leachate plume on the groundwater around a dumpsite at Onitsha expressway, southeastern Nigeria. The borehole log data were acquired and their respective geoposition logged with Garmin GPS device. In addition, four 1D (VES) soundings and 2D electrical profile data were acquired in the field utilizing the Schlumberger and Wenner profiles respectively. Petrozenith PZ-03 Resistivity meter was used to acquire the electrical data, while RES2DINV and WinResist software were used to interpret the 2D and 1D data respectively. The resulting geoelectic layers were correlated with the borehole logs and were interpreted according to their resistivity distribution. Results of the 2D inversion at profiles 1 and 3 showed low resistivity zones indicating influence from the leachate plume. Profiles 2 and 4 gave low resistivity zone within 14.6 and 44.3 Ωm from surface to between 0.375 and 3.60 m depths indicating influence from leachate plume. Likewise, profiles 1 and 3, which penetrated groundwater, also showed very low resistivity with resistivity ranging from 3.12 to 8.7 Ωm, from surface to few meters depths. This indicates that it has been polluted by the leachate. In contrast, Profiles 2 and 4, from the 2D inversion, has no leachate influence on the groundwater. The VES result showed that the depth to the water table at location 1, 2, 3 and 4 are 21.7 m, 17.9 m, 15.9 m and 12.2 m respectively, with the leachate plume flowing in the southeast direction in line with the groundwater flow direction.

LWD DATA INVERSION FOR STRUCTURE WITH ANGULAR UNCONFORMITY

Non-structural traps and reservoir flanks are characterized by angular unconformities. Angular unconformity between dipping formation and sub-horizontal oil-water contact is common in the North Sea fields. This paper presents an approach to real-time inversion of LWD resistivity data for the scenario with angular unconformity. The approach utilizes artificial neural networks (ANNs) for calculating the tool responses in parametric surface-based 2D resistivity models. We propose a parametric model with two non-parallel boundaries suitable for scenarios with angular unconformity and pinch-out. Training of ANNs for this parametric model is performed using a database containing samples with the model parameters and corresponding tool responses. ANNs are the kernel of 2D inversion based on the Levenberg-Marquardt optimization method. To demonstrate applicability of our approach and compare with the results of 1D inversion, we analyze Extra Deep Azimuthal Resistivity tool responses in a 2D synthetic model. It is shown that 1D inversion determines either the position of the oil-water contact or dipping layers structure. At the same time, 2D inversion makes it possible to correctly reconstruct the positions of non-parallel boundaries. Performance of 2D inversion based on ANNs is suitable for real-time applications.