Effect of Saline Soil Cracks on Satellite Spectral Inversion Electrical Conductivity

The dehydration cracking of saline soil is a kind of common natural phenomenon, and the cracks of saline soil will affect the satellite spectrum, and then affect the accuracy of satellite spectral inversion of electrical conductivity (EC). This study introduces the concept of crack rate (CR) to describe the crack information of saline soil, and quantifies the influence of saline soil crack on the EC of satellite spectral inversion. In 2014 and 2020, the satellite-ground synchronous observation experiments of soda-type inland saline soil and coastal chlorinated-type saline soil were carried out, and the CR of surface cracked saline soil was extracted by an image processing algorithm. For the saline soil spectrum data, the correlation analysis method is used to establish the best band combination that characterizes the relationship between the different saline soil spectrum data and salinity, and the EC inversion model is established using the BP neural network method. The results show that: after the CR is introduced, the determination coefficient (R2) for the EC of soda-type saline soil satellite spectral inversion increased from 0.59 to 0.67, with an increase of 14.42%, and the mean square error (MSE) reduced from 0.20 to 0.16, with a decrease of 19.49%. The R2 for the EC of coastal chlorinated-type saline soil satellite spectral inversion increased from 0.64 to 0.75, an increase of 17.73%, and the MSE decreased from 0.16 to 0.12, a decrease of 25.15%. The study proved the influence of the cracks in the saline soil on the satellite spectrum and provided a new way to improve the accuracy of the satellite spectrum inversion of the EC of the cracked saline soil.

3-D time-domain spectral inversion of resistivity and full-decay induced polarization data—full solution of Poisson's equation and modelling of the current waveform

SUMMARY We present a new algorithm for 3-D forward modelling and spectral inversion of resistivity and time-domain full-decay induced polarization (IP) data. To our knowledge, all algorithms available for handling 3-D spectral inversion of full-decay IP data use a time-domain approximation to Poisson's equation in the forward response. To avoid this approximation, we compute the response in the frequency domain solving the full version of Poisson's equation for a range of frequencies (10–8–104 Hz) and then transform the response into the time domain, where we account for the transmitted current waveform. Solving Poisson's equation in 3-D is computationally expensive and in order to balance accuracy, time, and memory usage we introduce the following: (1) We use two separate meshes for the forward response and the model update, respectively. The forward mesh is an unstructured tetrahedral mesh allowing for local refinements whereas the model (inversion) mesh is a node-based structured mesh, where roughness constraints are easily implemented. By decoupling the two meshes, they can be tuned for optimizing the forward accuracy and the inversion resolution, independently. (2) A singularity removal method known from resistivity modelling has been adapted to the complex IP case and is applied to minimize the numerical errors caused by the fast changing potential close to the source electrodes. The method includes splitting the potential field into a primary part (response of a homogenous background) and a secondary part (from the anomalies). Two different forward meshes are then used to compute the forward response: a dense mesh for the primary potential field (only computed once for each frequency) and a coarser mesh for the secondary potential field (computed in each iteration step of the inversion). With this method, the singularity is minimized and the memory usages is decreased significantly at the same time. (3) Finally, we are sparsing (downsampling) the Jacobian matrix based on a threshold value of the normalized sensitivity. The Jacobian computation is performed by time-transforming the frequency-domain Jacobian obtained through the adjoint method. The Jacobian downsampling is carried out before the time-transform in the frequency domain, thus avoiding the time-transformation of the Jacobian elements with negligible sensitivity. We invert resistivity data and all IP time-gates simultaneously and use the Gauss–Newton model update to minimize the L2 misfit function. We invert the resistivity data and all IP time-gates simultaneously and use the Gauss–Newton model update to minimize the L2 misfit function. We demonstrate the performance of our inversion approach with a synthetic data example with 3-D anomalies and a field example, where lithology logs verify the results. The data sets contain 1256 quadrupole measurements with 33 IP time-gates each. The inversions results show good data fits and model retrieval. The inversion takes approximately one hour per iteration using four CPUs. With this speed and accuracy, we believe this modelling and inversion approach will be a strong tool for 3-D spectral inversion of resistivity and full-decay IP field data for both surface and borehole applications.

Inference of chromospheric plasma parameters on the Sun

The solar chromosphere can be observed well through strong absorption lines. We infer the physical parameters of chromospheric plasmas from these lines using a multilayer spectral inversion. This is a new technique of spectral inversion. We assume that the atmosphere consists of a finite number of layers. In each layer the absorption profile is constant and the source function varies with optical depth with a constant gradient. Specifically, we consider a three-layer model of radiative transfer where the lowest layer is identified with the photosphere and the two upper layers are identified with the chromosphere. The absorption profile in the photosphere is described by a Voigt function, and the profile in the chromosphere by a Gaussian function. This three-layer model is fully specified by 13 parameters. Four parameters can be fixed to prescribed values, and one parameter can be determined from the analysis of a satellite photospheric line. The remaining 8 parameters are determined from a constrained least-squares fitting. We applied the multilayer spectral inversion to the spectral data of the Hα and the Ca II 854.21 nm lines taken in a quiet region by the Fast Imaging Solar Spectrograph (FISS) of the Goode Solar Telescope (GST). We find that our model successfully fits most of the observed profiles and produces regular maps of the model parameters. The combination of the inferred Doppler widths of the two lines yields reasonable estimates of temperature and nonthermal speed in the chromosphere. We conclude that our multilayer inversion is useful to infer chromospheric plasma parameters on the Sun.

SPECTRAL INVERSION IS A PROMISING TOOL TO ACCELERATE THE PROJECT

This article reveals the possibilities of applying the results of spectral inversion on the example of a field in Eastern Siberia and shows the advantages of this approach over standard methods.