Description: The Okavango Delta of northern Botswana is one of the world's largest inland deltas or megafans. To obtain information on the character of sediments and basement depths, audiomagnetotelluric (AMT), controlled-source audiomagnetotelluric (CSAMT) and central-loop transient electromagnetic (TEM) data were collected on the largest island within the delta. The data were inverted individually and jointly for 1-D models of electric resistivity. Distortion effects in the AMT and CSAMT data were accounted for by including galvanic distortion tensors as free parameters in the inversions. By employing Marquardt–Levenberg inversion, we found that a 3-layer model comprising a resistive layer overlying sequentially a conductive layer and a deeper resistive layer was sufficient to explain all of the electromagnetic data. However, the top of the basal resistive layer from electromagnetic-only inversions was much shallower than the well-determined basement depth observed in high-quality seismic reflection images and seismic refraction velocity tomograms. To resolve this discrepancy, we jointly inverted the electromagnetic data for 4-layer models by including seismic depths to an interface between sedimentary units and to basement as explicit a priori constraints. We have also estimated the interconnected porosities, clay contents and pore-fluid resistivities of the sedimentary units from their electrical resistivities and seismic P -wave velocities using appropriate petrophysical models. In the interpretation of our preferred model, a shallow ~40 m thick freshwater sandy aquifer with 85–100 m resistivity, 10–32 per cent interconnected porosity and 〈13 per cent clay content overlies a 105–115 m thick conductive sequence of clay and intercalated salt-water-saturated sands with 15–20 m total resistivity, 1–27 per cent interconnected porosity and 15–60 per cent clay content. A third ~60 m thick sandy layer with 40–50 m resistivity, 10–33 per cent interconnected porosity and 〈15 per cent clay content is underlain by the basement with 3200–4000 m total resistivity. According to an interpretation of helicopter TEM data that cover the entire Okavango Delta and borehole logs, the second and third layers may represent lacustrine sediments from Paleo Lake Makgadikgadi and a moderately resistive freshwater aquifer comprising sediments of the recently proposed Paleo Okavango Megafan, respectively.

Description: The Okavango Delta of northern Botswana is one of the world's largest inland deltas or megafans. To obtain information on the character of sediments and basement depths, audiomagnetotelluric (AMT), controlled-source audiomagnetotelluric (CSAMT) and central-loop transient electromagnetic (TEM) data were collected on the largest island within the delta. The data were inverted individually and jointly for 1-D models of electric resistivity. Distortion effects in the AMT and CSAMT data were accounted for by including galvanic distortion tensors as free parameters in the inversions. By employing Marquardt–Levenberg inversion, we found that a 3-layer model comprising a resistive layer overlying sequentially a conductive layer and a deeper resistive layer was sufficient to explain all of the electromagnetic data. However, the top of the basal resistive layer from electromagnetic-only inversions was much shallower than the well-determined basement depth observed in high-quality seismic reflection images and seismic refraction velocity tomograms. To resolve this discrepancy, we jointly inverted the electromagnetic data for 4-layer models by including seismic depths to an interface between sedimentary units and to basement as explicit a priori constraints. We have also estimated the interconnected porosities, clay contents and pore-fluid resistivities of the sedimentary units from their electrical resistivities and seismic P -wave velocities using appropriate petrophysical models. In the interpretation of our preferred model, a shallow ~40 m thick freshwater sandy aquifer with 85–100 m resistivity, 10–32 per cent interconnected porosity and 〈13 per cent clay content overlies a 105–115 m thick conductive sequence of clay and intercalated salt-water-saturated sands with 15–20 m total resistivity, 1–27 per cent interconnected porosity and 15–60 per cent clay content. A third ~60 m thick sandy layer with 40–50 m resistivity, 10–33 per cent interconnected porosity and 〈15 per cent clay content is underlain by the basement with 3200–4000 m total resistivity. According to an interpretation of helicopter TEM data that cover the entire Okavango Delta and borehole logs, the second and third layers may represent lacustrine sediments from Paleo Lake Makgadikgadi and a moderately resistive freshwater aquifer comprising sediments of the recently proposed Paleo Okavango Megafan, respectively.

Description: Joint inversion of different geophysical data sets is becoming a more popular and powerful tool, and it has been performed on data sensitive both to the same physical parameter and to different physical parameters. Joint inversion is undertaken to reduce acceptable model space and to increase sensitivity to model parameters that one method alone is unable to resolve adequately. We examine and implement a novel hybrid joint inversion approach. In our inversion scheme a model—the reference model—is fixed, and the information shared with the subsurface structure obtained from another method will be maximized; in our case conductivity structures from magnetotelluric (MT) inversion. During inversion, the joint probability distribution of the MT and the specified reference model is estimated and its entropy minimized in order to guide the inversion result towards a solution that is statistically compatible with the reference model. The powerful feature of this technique is that no explicit relationships between estimated model parameters and reference model ones are presumed: if a link exists in data then it is highlighted in the estimation of the joint probability distribution, if no link is required, then none is enforced. Tests performed verify the robustness of this method and the advantages of it in a 1-D anisotropic scenario are demonstrated. A case study was performed with data from Central Germany, effectively fitting an MT data set from a single station within as minimal an amount of anisotropy as required.