Appraisal of a new 1D weighted joint inversion of ground based and helicopter‐borne electromagnetic data

Abstract

In order to couple spatial data from frequency‐domain helicopter‐borne electromagnetics with electromagnetic measurements from ground geophysics (transient electromagnetics and radiomagnetotellurics), a common 1D weighted joint inversion algorithm for helicopter‐borne electromagnetics, transient electromagnetics and radiomagnetotellurics data has been developed. The depth of investigation of helicopter‐borne electromagnetics data is rather limited compared to time‐domain electromagnetics sounding methods on the ground. In order to improve the accuracy of model parameters of shallow depth as well as of greater depth, the helicopter‐borne electromagnetics, transient electromagnetics, and radiomagnetotellurics measurements can be combined by using a joint inversion methodology. The 1D joint inversion algorithm is tested for synthetic data of helicopter‐borne electromagnetics, transient electromagnetics and radiomagnetotellurics. The proposed concept of the joint inversion takes advantage of each method, thus providing the capability to resolve near surface (radiomagnetotellurics) and deeper electrical conductivity structures (transient electromagnetics) in combination with valuable spatial information (helicopter‐borne electromagnetics). Furthermore, the joint inversion has been applied on the field data (helicopter‐borne electromagnetics and transient electromagnetics) measured in the Cuxhaven area, Germany. In order to avoid the lessening of the resolution capacities of one data type, and thus balancing the use of inherent and ideally complementary information content, a parameter reweighting scheme that is based on the exploration depth ranges of the specific methods is proposed. A comparison of the conventional joint inversion algorithm, proposed by Jupp and Vozoff (), and of the newly developed algorithm is presented. The new algorithm employs the weighting on different model parameters differently. It is inferred from the synthetic and field data examples that the weighted joint inversion is more successful in explaining the subsurface than the classical joint inversion approach. In addition to this, the data fittings in weighted joint inversion are also improved.

Exploration of geothermal resources using comprehensive electromagnetic method

“…To process the obtained data, the GDP32II data preprocessing software is applied for data sorting and removal of dead pixels. Then, TEM-1D software (Guo et al, 2020; Sudha et al, 2014) and CSAMT-2D software (Fu et al, 2013; Hedlin et al, 1990; Kouadio et al, 2020) of Zonge Co. were used to invert the data. The two softwares use the OCCAM inversion method (Constable and Parker, 1987; Xing et al, 2021) to solve the Green function and the adjoint function in the 2D domain and the 1D domain, respectively, to obtain the Jacobian matrix required for the inversion, and then realize the spatial inversion of the electric field data.…”

Joint inversion of lake-floor electrical resistivity tomography and boat-towed radio-magnetotelluric data illustrated on synthetic data and an application from the Äspö Hard Rock Laboratory site, Sweden

“…ERT and RMT data sets usually have different data point densities and different sensitivities to model structures and are affected differently by 3-D anomalies implying the need of different weights on the ERT and RMT data sets (Kalscheuer et al 2013;Sudha et al 2014). Since the ERT data set has more data points and better data 520 S. Wang et al coverage than the RMT data set, more weight on the ERT data set only results in the joint inversion model being close to the ERT single inversion model (Fig.…”

Exploring multiple electrical layers overlying coal seams using the transient electromagnetic method

“…Auken introduced lateral constraints in 1D inversion and successfully solved the problems of poor lateral continuity of resistivity and layer thickness in the inversion profiles and improved the resolution of thin layers [ 9 ]. Sudha et al used an inversion program based on the damped least squares method and Occam algorithm to carry out a joint inversion of the loop-source TEM and long-offset TEM, which solved the problem of the interface of inversion depth layer not being smooth [ 10 ].…”