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Global Geology
2022 Vol.25 Issue.1
Published 2022-02-25
1
Three-dimensional magnetotelluric forward modeling using structural-point EFGM and FEM coupling method
CAO Jin and LIU Yunhe
In this paper, the authors propose a method of three-dimensional (3D) magnetotelluric (MT) forward modeling algorithm based on the meshfree and finite element coupling method. The model is discretized by regular nodes in the central area, and the radial point interpolation method (RPIM) based on the global weakness is utilized to construct the meshfree shape function. The Governing equations in each background gird are solved by Gaussian integration. In the extended area where the points are sparsely distributed, to avoid the instability of the meshfree method, finite element method (FEM) with regular grids is used to solve the governing equation. Finally, the meshfree and finite element governing equations are coupled by the continuity of the field at the interfaces, and the direct solution technique is used to realize the 3D MT forward modeling. Numerical experiments of several typical electrical models are used to verify the effectiveness of the method.
2022 Vol. 25 (1): 1-10 [
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11
Application of artificial bee colony algorithm in Rayleigh wave inversion
DONG Xuri and WANG Xin
In order to solve the problems of multi-parameter, multi-extreme and multi-solution in the nonlinear iterative optimization process of Rayleigh wave inversion, the artificial bee colony (ABC) algorithm is selected for global nonlinear inversion. The global nonlinear inversion method does not rely on a strict initial model and does not need to calculate the derivative of the objective function. The ABC algorithm uses the local optimization behavior of each individual artificial bee to finally highlight the global optimal value in the colony, and the convergence speed is faster. While searching for the global optimal solution, an effective local search can also be performed to ensure the reliability of the inversion results. This paper uses the ABC algorithm to perform Rayleigh wave dispersion inversion on the actual seismic data to obtain a clear undergrounding of shear wave velocity profile and accurately identify the location of the high-velocity interlayer. It is verified that the ABC algorithm used in the inversion of the Rayleigh wave dispersion curve is stable and converges quickly.
2022 Vol. 25 (1): 11-15 [
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128
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16
Extraction of altered minerals from Aster remote sensing data in Gongchangling iron deposit of Liaoning, China
LUAN Yiming, HE Jinxin, DONG Yongsheng, JIANG Tian and XIAO Zhiqiang
The precision of Aster data is higher than that of Landsat series of multispectral remote sensing data, which can more accurately reveal the distribution of altered minerals. It plays an important role in prospecting, but it is rarely used in areas with complex terrain and high vegetation coverage. Based on this purpose, this study used Aster remote sensing data, and took Gongchangling iron deposit as a case study. It combined the mineral spectrum theory and the basic geologic data of the study area, using the model of principal component analysis (PCA) and color synthesis to extract abnormal altered minerals. The results show that the distribution of identified anomalies is basically consistent with the existing geological data in this study area, which provides a reliable reference for the mineral resources ex-ploration and delineation of mining areas.
2022 Vol. 25 (1): 16-25 [
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188
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26
3D joint inversion of controlled-source audio-frequency magnetotelluric and magnetotelluric data
RONG Zhihao and LIU Yunhe
Different geophysical exploration methods have significant differences in terms of exploration depth, especially in frequency domain electromagnetic (EM) exploration. According to the definition of skin depth, this difference will increase with the effective detection frequency of the method. As a result, when performing three-dimensional inversion on single type of EM data, it is not possible to effectively distinguish the subsurface geoelectric structure at the full scale. Therefore, it is necessary to perform joint inversion on different type of EM data. In this paper we combine the magnetotelluric method (MT) with the controlled-source audio-magnetotelluric method (CSAMT) to study the frequency-domain threedimensional (3D) joint inversions, and we use the unstructured finite-element method to do the forward modeling for them, so that the numerical simulation accuracies of different electromagnetic methods can be satisfied. By combining the two sets of data, we can obtain the sensitivity of the electrical structure at different depths, and depict the full-scale subsurface geoelectric structures. In actual mineral exploration, the 3D joint inversion is more useful for identifying subsurface veins in the shallow part and blind mines in the deep part. It can delineate the morphological distribution of ore bodies more completely and provide reliable EM interpretations to guide the mining of minerals.
2022 Vol. 25 (1): 26-33 [
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34
Research on influencing factors of coupling in SIMO antenna
SHEN Jian
In the process of radar data acquisition, limited amount of information can be provided to postprocessing interpretation by the data acquisition method of single-input and single-output, however, the location and physical parameter information of geological body can be obtained more accurately by using Multi-Input Multi-Output (MIMO) antenna with multiple transmitters and multiple receivers. Especially when collecting borehole radar data and the aperture is very narrow, but the antenna is required to be able to ensure better results in a larger frequency band, therefore, the size of the antenna will be greatly challenged. Meanwhile, the close arrangement of multiple transmitting and receiving antennas will inevitably affect the signal radiation. Based on the borehole radar, this paper simulates and optimizes the Single-Input Multi-Output antenna (SIMO antenna) , the size of which meets the aperture requirements, using HFSS antenna simulation software, and explores the factors affecting the antenna return loss and isolation. Among them, the radius of the dipole has little effect on the return loss and isolation, whereas increasing the number of receiving antennas or increasing the transceiver distance will significantly affect the antenna coupling, with a significant reduction in the amplitude of isolation.
2022 Vol. 25 (1): 34-40 [
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41
Aeromagnetic compensation method based on ridge regression algorithm
SU Zhenning, JIAO Jian, ZHOU Shuai, YU Ping and ZHAO Xiao
With the development of UAV technology, UAV aerial magnetic survey plays an important role in the airborne geophysical prospecting. In the aeromagnetic survey, the magnetic field interferences generated by the magnetic components on the aircraft greatly affect the accuracy of the survey results. Therefore, it is necessary to use aeromagnetic compensation technology to eliminate the interfering magnetic field. So far, the aeromagnetic compensation methods used are mainly linear regression compensation methods based on the T-L equation. The least square is one of the most commonly used methods to solve multiple linear regressions. However, considering that the correlation between data may lead to instability of the algorithm, we use the ridge regression algorithm to solve the multicollinearity problem in the T-L equation. Subsequently this method is applied to the aeromagnetic survey data, and the standard deviation is selected as the index to evaluate the compensation effect to verify the effectiveness of the method.
2022 Vol. 25 (1): 41-48 [
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49
Literature analysis of Dendrolimus disasters based on remote sensing monitoring
WANG Mingchang, ZHOU Yuyang, LI Mingjie, JI Xue and LIU Ziwei
bstract: Due to global climate change, Dendrolimus pests and diseases seriously threaten the protection of forestry plants and the safety of crops all over the world. This paper aims to discuss the research results and frontier progress of Dendrolimus disasters based on remote sensing monitoring, trying to find the occurrence characteristics of pests. In this paper, bibliometric methods and CiteSpace knowledge graphs were used to analyze the publication trend, highly cited documents, key research institutions, and high-frequency keywords of the extracted documents in the Web of Science (WOS) database. The following conclusions are drawn: (1) The amount of research in WOS is on the rise, but it has declined in recent years. The countries with strong influence in national cooperation are mainly the United States and China. (2) The United States Department of Agriculture-Agricultural Research Service (USDA ARS) and the Chinese Academy of Sciences have published a lot. This paper reviewed the research progress of high-frequency institutions. (3) The key research topics focus on remote sensing, agriculture, and environmental sciences. Besides, the research hotspots include remote sensing monitoring, climate change, spectral reflectance, vegetation index, and precision agriculture. Finally, we put forward the current challenges and development trends of remote sensing pest monitoring. This paper can provide a reference for the research on remote sensing monitoring of Dendrolimus disasters in the future.
2022 Vol. 25 (1): 49-59 [
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60
Object-oriented crop classification based on UAV remote sensing imagery
ZHANG Lan and ZHANG Yanhong
UAV remote sensing images have the advantages of high spatial resolution, fast speed, strong realtime performance, and convenient operation, etc., and have become a recently developed, vital means of acquiring surface information. It is an important research task for precision agriculture to make full use of the spectrum, texture, color and other characteristic information of crops, especially the spatial arrangement and structure information of features, to explore effective methods for the classification of multiple varieties of crops. In order to explore the applicability of the object-oriented method to achieve accurate classification of UAV high-resolution images, the paper used the object-oriented classification method in ENVI to classify the UAV high-resolution remote sensing image obtained from the orderly structured 28 species of crops in the test field, which mainly includes image segmentation and object classification. The results showed that the plots obtained after classification were continuous and complete, basically in line with the actual situation, and the overall accuracy of crop classification was 91.73%, with Kappa coefficient of 0.87. Compared with the crop planting area based on remote sensing interpretation and field survey, the area error of 17 species of crops in this study was controlled within 15%, which provides a basis for object-oriented crop classification of UAV remote sensing images.
2022 Vol. 25 (1): 60-68 [
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