Impact of Timanian thrust systems on the late Neoproterozoic–Phanerozoic tectonic evolution of the Barents Sea and Svalbard

The Svalbard Archipelago consists of three basement terranes that record a complex Neoproterozoic–Phanerozoic tectonic history, including four contractional events (Grenvillian, Caledonian, Ellesmerian, and Eurekan) and two episodes of collapse- to rift-related extension (Devonian–Carboniferous and late Cenozoic). Previous studies suggest that these three terranes likely accreted during the early to mid-Paleozoic Caledonian and Ellesmerian orogenies. Yet recent geochronological analyses show that the northwestern and southwestern terranes of Svalbard both record an episode of amphibolite (–eclogite) facies metamorphism in the latest Neoproterozoic, which may relate to the 650–550 Ma Timanian Orogeny identified in northwestern Russia, northern Norway, and the Russian Barents Sea. However, discrete Timanian structures have yet to be identified in Svalbard and the Norwegian Barents Sea. Through analysis of seismic reflection, as well as regional gravimetric and magnetic data, this study demonstrates the presence of continuous thrust systems that are several kilometers thick, NNE-dipping, deeply buried, and extend thousands of kilometers from northwestern Russia to northeastern Norway, the northern Norwegian Barents Sea, and the Svalbard Archipelago. The consistency in orientation and geometry, as well as apparent linkage between these thrust systems and those recognized as part of the Timanian Orogeny in northwestern Russia and Novaya Zemlya, suggests that the mapped structures are likely Timanian. If correct, these findings would imply that Svalbard's three basement terranes and the Barents Sea were accreted onto northern Norway during the Timanian Orogeny and should hence be attached to Baltica and northwestern Russia in future Neoproterozoic–early Paleozoic plate tectonics reconstructions. In the Phanerozoic, the study suggests that the interpreted Timanian thrust systems represent major preexisting zones of weakness that were reactivated, folded, and overprinted by (i.e., controlled the formation of new) brittle faults during later tectonic events. These faults are still active at present and can be linked to folding and offset of the seafloor.

Soft-Output Detector Using Multi-Layer Perceptron for Bit-Patterned Media Recording

As conventional data storage systems are faced with critical problems such as the superparamagnetic limit, bit-patterned media recording (BPMR) has received significant attention as a promising next-generation magnetic data storage system. However, the reduced spacing between islands at increased areal density causes severe intersymbol and intertrack interference, which degrade BPMR system performance. In this study, we introduce a soft-output detector using multi-layer perceptron to predict reliable information. A received signal is equalized and detected by the MLP detector. The MLP detector provides a well-estimated value by using the binary-cross entropy function as a loss function and the identity function as an activation function for the output layer of the MLP detector. This study investigates the received probability distributions out of the detectors and compares the performance of various versions against a conventional detector. Compared with the conventional detection, the proposed MLP detectors provide a small variance and better BER performance than the conventional detection. Simulations of MLP designs show an advantage over conventional detection. Moreover, the proposed MLP detectors with the demodulator exhibit better BER performance than the conventional detector with the demodulator.

Application of magnetic method to characterize Abaya campus building site, Southern Ethiopia

A geophysical survey involving magnetic method is conducted using ENVI-MAG proton precision magnetometer. The study is carried out with the aim of identifying the possible geological structures which may responsible for the failure of engineering structures. Three traverses having east –west orientation with a ten meters profile spacing and a readings station spacing and one traverse across the three traverses and randomly collected magnetic data were used. At each station three readings were taken and averaged out in order to increase the accuracy of data and diurnal and geomagnetic corrections were made. With the corrected data different anomalous maps were produced like total magnetic field anomaly map, residual magnetic anomaly map and analytical signal map using Oasis montaji6.4 software for further interpretation. The result of this research has shown that the area is affected by different geological structures which may be the cause for the crack and the failure of the building in the area.

3D Convolution Conjugate Gradient Inversion of Potential Fields in Acoculco Geothermal Prospect, Mexico

Potential field data have long been used in geophysical exploration for archeological, mineral, and reservoir targets. For all these targets, the increased search of highly detailed three-dimensional subsurface volumes has also promoted the recollection of high-density contrast data sets. While there are several approaches to handle these large-scale inverse problems, most of them rely on either the extensive use of high-performance computing architectures or data-model compression strategies that may sacrifice some level of model resolution. We posit that the superposition and convolutional properties of the potential fields can be easily used to compress the information needed for data inversion and also to reduce significantly redundant mathematical computations. For this, we developed a convolution-based conjugate gradient 3D inversion algorithm for the most common types of potential field data. We demonstrate the performance of the algorithm using a resolution test and a synthetic experiment. We then apply our algorithm to gravity and magnetic data for a geothermal prospect in the Acoculco caldera in Mexico. The resulting three-dimensional model meaningfully determined the distribution of the existent volcanic infill in the caldera as well as the interrelation of various intrusions in the basement of the area. We propose that these intrusive bodies play an important role either as a low-permeability host of the heated fluid or as the heat source for the potential development of an enhanced geothermal system.

Processing and Interpretation of UAV Magnetic Data: A Workflow Based on Improved Variational Mode Decomposition and Levenberg-Marquardt Algorithm

Unmanned aerial vehicles (UAVs) have become a research hotspot in the field of magnetic exploration because of their unique advantages, e.g., low cost, high safety, and easy to operate. However, the lack of effective data processing and interpretation method limits their further deployment. In view of this situation, a complete workflow of UAV magnetic data processing and interpretation is proposed in this paper, which can be divided into two steps: (1) the improved variational mode decomposition (VMD) is applied to the original data to improve its signal-to-noise ratio as much as possible, and the decomposition modes number K is determined adaptively according to the mode characteristics; (2) the parameters of target position and magnetic moment are obtained by Euler deconvolution first, and then used as the prior information of the Levenberg–Marquardt (LM) algorithm to further improve its accuracy. Experiments are carried out to verify the effectiveness of the proposed method. Results show that the proposed method can significantly improve the quality of the original data; by combining the Euler deconvolution and LM algorithm, the horizontal positioning error can be reduced from 15.31 cm to 4.05 cm, and the depth estimation error can be reduced from 16.2 cm to 5.4 cm. Moreover, the proposed method can be used not only for the detection and location of near-surface targets, but also for the follow-up work, such as the clearance of targets (e.g., the unexploded ordnance).

Analisis Kinerja Protokol MQTT dan HTTP Pada Akuisisi Data Magnet Berbasis Internet of Things

One of the determinants of the quality of magnetic data is continuous data, so we need a data transmission system that can continuously transmit observational data. In this research, a magnetometer communication system design was carried out with the concept of the Internet of Things (IoT) using the MQTT and HTTP protocol, where measurement data in the form of the x-axis, y-axis, z-axis, horizontal components, and total magnetic field components are displayed on the dashboard in real time and continuously. Testing the performance of sending data is done using the Wireshark, it is known that the MQTT protocol has a better delivery quality compared to the HTPP protocol with an average delay value of 0.0120 seconds, an average value of packet length of 54 bytes and a packet loss value of 0.11%, while the HTTP protocol has an average delay value of 0.0257 seconds, an average packet length value of 268.1 bytes and a packet loss value of 0.5%.

New Perspective in Regional and Residual Separation of Gravity and Magnetic Data Processing

Separation between Regional and Residual anomaly in Gravity and Magnetic data processing is very important to get the best result in geological interpretation. Several method were used to solve this problem like upward continuation and polynomial fitting. With the same principle, 2D FFT is applied by make an interactive tools based on Matlab Language Programming, named “Oasis Ala-Ala”. It adopt the algorithm from software Oasis. It started with make visualization map or the original data, then the map divide into some grids. Each of grid contain gravity or magnetic data. Then it transformed from special to wavenumber domain. After that, it convolve with our own filter matrix. And the last step is inverse it to get the regional and residual anomaly map. However, Matlab is powerful in facilitate this process in the GUI Toolbox. One important thing is the size of gravity and magnetic data. It will improve to Filter matrix size before do inverse process.

Leveling airborne geophysical data using a unidirectional variational model

Airborne geophysical data leveling is an indispensable step to the conventional data processing. Traditional data leveling methods mainly explore the leveling error properties in the time and frequency domain. A new technique is proposed to level airborne geophysical data in view of the image space properties of leveling error, including directional distribution property and amplitude variety property. This work applied unidirectional variational model on entire survey data based on the gradient difference between the leveling errors in flight line direction and the tie-line direction. Then spatially adaptive multi-scale model is introduced to iteratively decompose the leveling errors which effectively avoid the difficulty on the parameter selection. Considering the anomaly data with large amplitude may hide the real data level, a leveling preprocessing method is given to construct a smooth field based on the gradient data. The leveling method can automatically extract the leveling errors of the entire survey area simultaneously without the participation of staff members or tie-line control. We have applied the method to the airborne electromagnetic, magnetic data, and apparent conductivity data collected by Ontario Geological Survey to confirm its validity and robustness by comparing the results with the published data.