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9th International Conference on Environmental and Engineering Geophysics, ICEEG 2020

作者： Zhang, Hongyu Xia, Jianghai Pang, Jingyin Cheng, Feng Xing, Huaixue Key Laboratory of Geoscience Big Data and Deep Resource of Zhejiang Province School of Earth Sciences Zhejiang University Hangzhou China Dept. of Earth Environmental And Planetary Sciences Rice University Houston United States Nanjing Center of Geological Survey China Geological Survey Nanjing China

Passive surface-wave methods are widely used in urban areas because of their economic efficiency. It usually needs long-time observation to provide phase velocity information at frequencies ranging from several Hz to several tens of Hz. A complex urbanized environment, however, leads to a reduction in acquisition time. Consequently, it's necessary to extract surface waves with ultrashort traffic noise for engineering applications. Although noise segments are limited in the circumstance of ultrashort acquisition, we still need data selection to avoid stacking neutralization of data with a different signal-to-noise ratio (SNR). Then we compare linear stacking, phase-weighted stacking (PWS), and time-frequency phase-weighted stacking (tf-PWS) through processing one-minute noise records after selection. We can obtain clear and continuous dispersion energy with these three methods. Our results indicate that PWS or tf-PWS has better performance than linear stacking by comparing dispersion energy images, and PWS improves SNR most, strongly contrasting before and after selection. © Published under licence by IOP Publishing Ltd.

关键词： Signal to noise ratio

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Radiative Effects on Kinetic and Potential Energy Budgets Associated with Rapid Intensification of Typhoon Mujigae in 2015

SSRN

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SSRN 2024年

作者： Zhang, Chi Li, Xiaofan Liu, Rui Key Laboratory of Geoscience Big Data and Deep Resource of Zhejiang Province School of Earth Sciences Zhejiang University Hangzhou310058 China

This study investigated radiative effects on kinetic and potential energy budgets associated with rapid intensification of Typhoon Mujigae in 2015 by conducting sensitivity experiments with Weather Research and Forecasting (WRF) model simulation. We found that the inclusion of radiative effects mainly increases the symmetric rotational kinetic energy ([[EQUATION]]), while the radiative effects are from infrared longwave radiative effects. The comparison in symmetric potential energy ([[EQUATION]]) and [[EQUATION]] budget between the sensitivity experiments excluding the radiative effects and solar shortwave radiative effects only reveals that the inclusion of infrared longwave radiative effects destabilizes the moist atmosphere and increases the conversion from [[EQUATION]] to symmetric divergent kinetic energy ([[EQUATION]]), which reduces [[EQUATION]] and enhances [[EQUATION]] through the strengthened conversion from [[EQUATION]] to [[EQUATION]]. © 2024, The Authors. All rights reserved.

关键词： Potential energy

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Fe-Mn interdiffusion in aluminosilicate garnets

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geoscience Frontiers 2024年第1期15卷 118-125页

作者： Yanjun Yin Baohua Zhang Xinzhuan Guo Key Laboratory of High-temperature and High-pressure Study of the Earth’s Interior Institute of GeochemistryChinese Academy of SciencesGuiyang 550081GuizhouChina University of Chinese Academy of Sciences Beijing 100049China Key Laboratory of Big Data in Geosciences and Deep Earth Resources of Zhejiang Province School of Earth SciencesZhejiang UniversityHangzhou 310058China

Precise determination of cation diffusivity in garnet can provide critical information for quantitatively understanding the timescales and thermodynamics of various geological processes,but very few studies have been performed for Fe-Mn *** this study,Fe-Mn interdiffusion rates in natural single crystals of Mn-bearing garnet with 750 ppm H2O are determined at 6 GPa and 1273-1573 K in a Kawai-type multi-anvil *** profiles were acquired by electron microprobe and fitted using Boltzmann-Matano *** experimental results show that the Fe-Mn interdiffusion coefficient(DFe-Mn)slightly decreases with increasing *** experimentally determined DFe-Mn in Mn-bearing garnet can be fitted by the Arrhenius equation:DFe-Mn(m2/s)=D0XFenexp(-E*/RT),where E*=(1-XFe)E*Mn+XFeE*Fe,D0=8.06-6.04+9.87×10-9 m2/s,E*Mn=248±27 KJ/mol,E*Fe=226±59 KJ/mol,n=-1.36±*** comparing the present results with previous experimental data suggest that water can greatly enhance the DFe-Mn in *** results indicate that the time required for homogenization of the compositional zoning of a garnet is much shorter than previously thought.

关键词： Fe-Mn interdiffusion Diffusion coefficient Garnet High pressure experiment Water

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Electrical conductivity of melts: implications for conductivity anomalies in the Earth's mantle

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National Science Review 2021年第11期8卷 133-151页

作者： Bao-Hua Zhang Xuan Guo Takashi Yoshino Qun-Ke Xia Key Laboratory of Geoscience Big Data and Deep Resource of Zhejiang Province School of Earth Sciences Zhejiang University CAS Key Laboratory of Crust-Mantle Materials and Environments School of Earth and Space Sciences University of Science and Technology of China Institute for Planetary Materials Okayama University

Magmatic liquids,including silicate and carbonate melts,are principal agents of mass and heat transfer in the Earth and terrestrial planets,and they play a crucial role in various geodynamic processes and in Earth's *** conductivity data of these melts elucidate the cause of electrical anomalies in Earth's interior and shed light on the melt *** the improvement in high-pressure experimental techniques and theoretical simulations,major progress has been made on this front in the past several *** review aims to summarize recent advances in experimental and theoretical studies on the electrical conductivity of silicate and carbonate melts of different compositions and volatile contents under high temperature and *** electrical conductivity of silicate melts depends strongly on temperature,pressure,water content and the ratio of non-bridging oxygens to tetrahedral cations（NBO/T）.By contrast,the electrical conductivity of carbonate melts exhibits a weak dependence on temperature and pressure due to their fully depolymerized *** electrical conductivity of carbonate melts is higher than that of silicate melts by at least two orders of *** can increase electrical conductivity significantly and reduce the activation energy of silicate ***,this effect is weak for carbonate *** addition,the replacement of alkali-earth elements(Ca2+or Mg2+) with alkali elements causes a significant decrease in the electrical conductivity of carbonate melts.A distinct compensation trend is revealed for the electrical conductivity of silicate and carbonate melts under anhydrous and hydrous *** important applications of laboratory-based melt conductivity are introduced in order to understand the origin of high-conductivity anomalies in the Earth's *** for future studies are also provided.

关键词： electrical conductivity silicate melt carbonate melt high-conductivity anomaly Earth's mantle

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Surface Processes Driving Intracontinental Basin Subsidence in the Context of India–Eurasia Collision:Evidence from Flexural Subsidence Modeling of the Cenozoic Southern Tarim Basin along the West Kunlun Foreland,NW Tibetan Plateau

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Acta Geologica Sinica(English Edition) 2023年第6期97卷 1778-1786页

作者： HUANG Hao LIN Xiubin AN Kaixuan ZHANG Yuqing CHEN Hanlin CHENG Xiaogan LI Chunyang Key Laboratory of Geoscience Big Data and Deep Resources of Zhejiang Province School of Earth SciencesZhejiang UniversityHangzhou 310027China Research Center for Structures in Oil and Gas-Bearing Basins Ministry of EducationHangzhou 310027China Research Institute of Petroleum Exploration and Development PetroChinaBeijing 100083China Research Institute of Petroleum Exploration and Development Sinopec Southwest Oil and Gas CompanyChengdu 610041China

The India–Eurasia collision has produced a number of Cenozoic deep intracontinental basins,which bear important information for revealing the far-afield responses to the remote *** their significance,their subsiding mechanism remains the subject of debate,with end-member models attributing it to either orogenic or sedimentary *** this study,we conduct flexural subsidence modeling with a two-dimensional finite elastic plate model on the Hotan-Mazatagh section along the southern Tarim Basin,which defines a key region in the foreland of the West Kunlun Orogen,along the NW margin of the Tibetan *** modeling results indicate that the orogenic load of West Kunlun triggers the southern Tarim Basin to subside by up to less than ~6 km,with its impact weakening towards the basin interiors until ~230 km north from the Karakax *** sedimentary load,consisting of Cenozoic strata,forces the basin to subside by ~2 to~7 *** combination with the retreat of the proto-Paratethys Sea and the paleogeographic reorganization of the Tarim Basin,we propose that surface processes,in particular a shift from an exorheic to an endorheic drainage system associated with the consequent thick sedimentary load,played a decisive role in forming deep intracontinental basins in the context of the India-Eurasia collision.

关键词： flexural subsidence modeling India-Eurasia collision West Kunlun Tarim Basin Northwest Tibetan Plateau

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EG17: Accurate linear-array dispersion imaging of passive surface waves in urban environments 7

EG17: Accurate linear-array dispersion imaging of passive su...

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7th International Conference on Engineering Geophysics, ICEG 2023

作者： Liu, Ya Cheng, Feng Mi, Binbin Pang, Jingyin Ning, Ling Zhang, Hao Xi, Chaoqiang Chen, Xinhua Guan, Bo You, Baiyang Hong, Yu Ma, Yulong Zhou, Jie Xia, Jianghai Key Laboratory of Geoscience Big Data and Deep Resource of Zhejiang Province School of Earth Sciences Zhejiang University Hangzhou China State Key Laboratory of Mining Response and Disaster Prevention and Control in Deep Coal Mines School of Earth and Environment Anhui University of Science and Technology Huainan China GBA Branch of Aerospace Information Research Institute Chinese Academy of Sciences Guangzhou510700 China

Passive surface-wave methods are gaining more and more attention in near-surface geophysical and geotechnical applications. The key to the success of surface-wave methods is accurate dispersion imaging. In urban environments, a linear receiver array is commonly used for dispersion analysis for its high efficiency and low cost. Non-ideal distribution of noise sources can lead to inaccurate imaging results. For obtaining accurate phase-velocity estimation with a linear array, we propose a new workflow for dispersion imaging. Two schemes are used for handling nonuniform source distributions. With three-component data, the source azimuth can be determined and utilized for apparent velocity correction during dispersion imaging. Without three-component data, the strength of the stationary-phase-zone sources is estimated by single-component data and used for the stacking of crosscorrelations. Two synthetic examples demonstrate that the proposed workflow is effective for accurate linear-array dispersion imaging when noise sources are nonuniformly distributed. Our workflow would be an alternative to the applications of passive surface-wave methods in urban areas, especially for nonuniform source distribution. © 2024 7th International Conference on Engineering Geophysics, ICEG 2023. All rights reserved.

关键词： Surface waves

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High pressure geochemistry:Preface

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geoscience Frontiers 2021年第2期12卷 893-895页

作者： Jianguo Du Baohua Zhang Bo Zou Bin Chen Geeth Manthilake United Laboratory of High-Pressure Physics and Earthquake Science Key Laboratory of Earthquake PredictionInstitute of Earthquake ForecastingCEABeijing 100036China Key Laboratory of Geoscience Big Data and Deep Resource of Zhejiang Province School of Earth SciencesZhejiang UniversityHangzhou 310027China State Key Laboratory of Superhard Materials Jilin UniversityChangchun 130012China Hawaii Institute of Geophysics and Planetology School of Ocean and Earth Science and TechnologyUniversity of Hawaii at ManoaHonoluluHI 96822USA Laboratoire Magmas et Volcans CNRS IRDOPGCUniversitéClermont Auvergne63000 Clermont-FerrandFrance

The origin and history of the Earth are manifested as the evolutionary processes of chemistry and physics of its interiors,which can be recognized by deciphering the geochemical signals recorded in minerals and *** interiors of the Earth and other rocky planets are under both extreme pressure and temperature,i.e.,approximately 360 gigapascals(GPa)and as high as 7000 K at the center of the Earth.

关键词： Earth geochemistry minerals

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Seasonal Forecast of Winter Precipitation Over China Using Machine Learning Models

SSRN

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SSRN 2023年

作者： Jia, XiaoJing Qian, QiFeng Zhejiang Institute of Meteorological Science Zhejiang Hangzhou China Key Laboratory of Geoscience Big Data and Deep Resource of Zhejiang Province School of Earth Sciences Zhejiang University Zhejiang Hangzhou China

This study employs two machine learning (ML) models, namely the light gradient boosting machine (LightGBM) and the extreme gradient boosting (XGBoost) model, to perform seasonal forecasts for winter precipitation over China. The seasonal forecast results derived from a dynamic model are used for the purpose of comparison. The predictors employed in the two ML models consist of climate variables from the preceding autumn. The ML models are trained using data from 1979 to 2010 without an additional predictor selection process. Consequently, the ML models autonomously extract useful information and then apply it to perform seasonal forecasts of winter precipitation for 2011-2020. Results indicate that the two ML models exhibit reasonable forecast skills and demonstrate superior performance over various regions when compared to the dynamic model. Additionally, the ensemble forecasts of the two ML models and the dynamic model exhibit higher skill in southern China compared to the dynamic model forecast alone. Further investigation reveals that the forecast skill of the ML models can be attributed to their skillful forecast accurate predictions of the first empirical orthogonal function mode (EOF1) of the winter precipitation. In addition, the split time count method and the Shapley additive explanation (SHAP) values analysis are performed to further understand and explain the ML model forecast results. Results show that the sea surface temperature (SST), especially the SST over the western Pacific plays an important role in the ML model seasonal forecasts of winter precipitation over China, consistent with previous studies. The outcomes of this investigation provide valuable insights that can enhance the practical implementation and understanding of ML models in the field of seasonal forecasting. © 2023, The Authors. All rights reserved.

关键词： Machine learning

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Seismic Traveltime Tomography with Label-free Learning

arXiv

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arXiv 2024年

作者： Wang, Feng Yang, Bo Wang, Renfang Qiu, Hong College of Big Data and Software Engineering Zhejiang Wanli University Ningbo315100 China Key Laboratory of Geoscience Big Data and Deep Resource of Zhejiang Province School of Earth Sciences Zhejiang University Hangzhou310027 China

deep learning techniques have been used to build velocity models (VMs) for seismic traveltime tomography and have shown encouraging performance in recent years. However, they need to generate labeled samples (i.e., pairs of input and label) to train the deep neural network (NN) with end-to-end learning, and the real labels for field data inversion are usually missing or very expensive. Some traditional tomographic methods can be implemented quickly, but their effectiveness is often limited by prior assumptions. To avoid generating and/or collecting labeled samples, we propose a novel method by integrating deep learning and dictionary learning to enhance the VMs with low resolution by using the traditional tomography-least square method (LSQR). We first design a type of shallow and simple NN to reduce computational cost followed by proposing a two-step strategy to enhance the VMs with low resolution: (1) Warming up. An initial dictionary is trained from the estimation by LSQR through dictionary learning method;(2) Dictionary optimization. The initial dictionary obtained in the warming-up step will be optimized by the NN, and then it will be used to reconstruct high-resolution VMs with the reference slowness and the estimation by LSQR. Furthermore, we design a loss function to minimize traveltime misfit to ensure that NN training is label-free, and the optimized dictionary can be obtained after each epoch of NN training. We demonstrate the effectiveness of the proposed method through the numerical tests on both synthetic and field data. Copyright © 2024, The Authors. All rights reserved.

关键词： Tomography

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Low-Dose CT Reconstruction Using dataset-Free Learning

SSRN

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SSRN 2024年

作者： Wang, Feng Wang, Renfang Yang, Bo Qiu, Hong College of Big Data and Software Engineering Zhejiang Wanli University Zhejiang Ningbo315100 China Key Laboratory of Geoscience Big Data and Deep Resource of Zhejiang Province School of Earth Sciences Zhejiang University Zhejiang Hangzhou310027 China

Low-Dose computer tomography (LDCT) is an ideal alternative to reduce radiation risk in clinical applications. Although supervised-deep-learning-based reconstruction methods have demonstrated superior performance compared to conventional model-driven reconstruction algorithms, they require collecting massive pairs of low-dose and norm-dose CT images for neural network training, which limits their practical application in LDCT imaging. In this paper, we propose an unsupervised and training data-free learning reconstruction method for LDCT imaging that avoids the requirement for training data. The proposed method is a post-processing technique that aims to enhance the initial low-quality reconstruction results, and it reconstructs the high-quality images by neural work training that minimizes the l-norm distance between the CT measurements and their corresponding simulated sinogram data, as well as the total variation (TV) value of the reconstructed image. Moreover, the proposed method does not require to set the weights for both the data fidelity term and the plenty term. Experimental results on the AAPM challenge data and LoDoPab-CT data demonstrate that the proposed method is able to effectively suppress the noise and preserve the tiny structures. And these results also shows the proposed method's low computational cost and rapid convergence. The source code is available at https://***/linfengyu77/IRLDCT. © 2024, The Authors. All rights reserved.

关键词： deep learning

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