Li Wan

Wuhan Textile University

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Qingfei Wang

China University of Geosciences (Beijing)

Jun Deng

China University of Geosciences (Beijing)

Liqiang Yang

China National Petroleum Corporation (China)

Jie Zhao

China University of Geosciences (Beijing)

Guodong Ding

Beijing Forestry University

Huan Liu

Tianjin University of Technology

Qingjie Gong

China University of Geosciences (Beijing)

Yijian Zeng

University of Twente

Ran Niu

China University of Geosciences (Beijing)

Deying Wang

Research Institute of Petroleum Exploration and Development

Cooperative Institutions

China University of Geosciences (Beijing)

Beijing Forestry University

Chinese Academy of Sciences

China University of Geosciences

Ministry of Natural Resources

State Forestry and Grassland Administration

Research Institute of Petroleum Exploration and Development

China Geological Survey

Northwest A&F University

National University of Singapore

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Orebody vertical structure and implications for ore-forming processes in the Xinxu bauxite deposit, Western Guangxi, China

Ore Geology Reviews (2011)

Qingfei Wang Jun Deng Qizuan Zhang Huan Liu Xuefei Liu

Devonian

Sedimentation

10.1016/j.oregeorev.2011.02.004

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Citations (39)

Identification of Mineral Intensity along Drifts in the Dayingezhuang Deposit, Jiaodong Gold Province, China

Resource Geology (2010)

Li Wan Qingfei Wang Jun Deng Qingjie Gong Liqiang Yang

Abstract Great mineral intensity in drifts or drills is characterized by both the high proportion and spatial cluster of the high grades. Great mineral intensity indicates the high ore quality and low dilution in the exploitation. The fractal dimension, the fluctuation exponent proposed in this paper and the lacunarity are utilized to analyze the mineral intensity along drifts in the Dayingezhuang gold deposit in Jiaodong gold province, China. It is proven that the combination of the parameters can identify the mineral intensity. The fractal dimension and fluctuation exponent are negatively correlated. In the places where the fractal dimension is small and fluctuation exponent is great, the mineralization is more pronounced. While in the case that the fractal dimensions are similar, smaller fluctuation exponent means more clustered structure of high grades and greater mineral intensity. In the diagram of fractal dimension versus lacunarity, the drifts with great mineral intensity can also be identified. The methods used in this paper provide a relatively comprehensive description for local mineral intensity, providing information for both the ore‐forming process and the exploitation.

Lacunarity

Intensity

Mineral resource classification

Exponent

10.1111/j.1751-3928.2010.00117.x

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Citations (21)

Comment on hess-2022-403

Kai-Gao Ouyang Xiaowei Jiang Gang Mei Hong‐Bin Yan Ran Niu

Abstract. Rock moisture, which is considered as a hidden component of the terrestrial hydrological cycle, has received little attention. In this study, the frequency-domain reflectometry (FDR) is used to obtain fluctuating rock water content in a sandstone cave of the Yungang Grottoes, China. We identified two major cycles of rock moisture addition and depletion, one in the summer and the other in the winter. By using the LSTM (Long Short-Term Memory) network and the SHAP (SHapley Additive exPlanations) method, relative humidity, air temperature and wall temperature are found to have contributions to rock moisture in the summer. By using vapor concentration and the difference between dew point temperature and wall temperature as two input variables of the LSTM network, the predicted rock water content has a very good agreement with the measured rock water content, with the Nash–Sutcliffe efficiency coefficient (NSE) being as high as 0.978. Because the two new input variables are factors directly controlling vapor condensation, they provide informative priors to the deep learning model and improved prediction performance. After identifying the causal factors of rock water content fluctuations, we also identified the mechanism controlling the multi diurnal vapor condensation. The increased vapor concentration accompanying a precipitation event leads to transport of water vapor into rock pores, which is subsequently adsorbed onto the surface of rock pores and then condensed into liquid water. With the aid of the deep learning model, this study increases understanding of sources of water in caves, which would contribute to future strategies of alleviating weathering in caves.

Dew point

Dew

10.5194/hess-2022-403-rc1

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Citations (0)

Journal of Geochemical Exploration (2009)

Jun Deng Qingfei Wang Li Wan Liqiang Yang Qingjie Gong

Gold ore

10.1016/j.gexplo.2009.03.003

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Citations (88)

Physics-informed machine learning for understanding rock moisture dynamics in a sandstone cave

Kai-Gao Ouyang Xiao‐Wei Jiang Gang Mei Hong‐Bin Yan Ran Niu

Abstract. Rock moisture, which is considered as a hidden component of the terrestrial hydrological cycle, has received little attention. In this study, the frequency-domain reflectometry (FDR) is used to obtain fluctuating rock water content in a sandstone cave of the Yungang Grottoes, China. We identified two major cycles of rock moisture addition and depletion, one in the summer and the other in the winter. By using the LSTM (Long Short-Term Memory) network and the SHAP (SHapley Additive exPlanations) method, relative humidity, air temperature and wall temperature are found to have contributions to rock moisture in the summer. By using vapor concentration and the difference between dew point temperature and wall temperature as two input variables of the LSTM network, the predicted rock water content has a very good agreement with the measured rock water content, with the Nash–Sutcliffe efficiency coefficient (NSE) being as high as 0.978. Because the two new input variables are factors directly controlling vapor condensation, they provide informative priors to the deep learning model and improved prediction performance. After identifying the causal factors of rock water content fluctuations, we also identified the mechanism controlling the multi diurnal vapor condensation. The increased vapor concentration accompanying a precipitation event leads to transport of water vapor into rock pores, which is subsequently adsorbed onto the surface of rock pores and then condensed into liquid water. With the aid of the deep learning model, this study increases understanding of sources of water in caves, which would contribute to future strategies of alleviating weathering in caves.

Dew point

Dew

10.5194/hess-2022-403

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Citations (0)

Diurnal variation in sap flow velocity & leaf water potential and relationships with plant-air temperature differences (Tp-Ta) in Artemisia ordosica .

Yu Ming-Han Guodong Ding Gao Guang-Lei Sun Bao-ping Yuanyuan Zhao

Diurnal temperature variation

Artemisia

Variation (astronomy)

10.1371/journal.pone.0135452.g007

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Number-average size model for geological systems and its application in economic geology

Nonlinear processes in geophysics (2011)

Q. F. Wang Li Wan Y. Zhang Jie Zhao H. Liu

Abstract. Various natural objects follow a number-size relationship in the fractal domain. In such relationship, the accumulative number of the objects beyond a given size shows a power-law relationship with the size. Yet in most cases, we also need to know the relationship between the accumulative number of the objects and their average size. A generalized number-size model and a number-average size model are constructed in this paper. In the number-average size model, the accumulative number shows a power-law relationship with the average size when the given size is much less than the maximum size of the objects. When the fractal dimension Ds of the number-size model is smaller than 1, the fractal dimension Ds of the number-average size model is almost equal to 1; and when Ds > 1, the Dm is approximately equal to Ds. In mineral deposits, according to the number-average size model, the ore tonnage may show a fractal relationship with the grade, as the cutoff changes for a single ore deposit. This is demonstrated by a study of the relationship between tonnage and grade in the Reshuitang epithermal hot-spring gold deposit, China.

Tonnage

Cut-off

10.5194/npg-18-447-2011

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Citations (10)

Characterization of multi-type mineralizations in the Wandongshan gold poly-metallic deposit, Yunnan (China), by fractal analysis

Journal of Geochemical Exploration (2012)

Huan Liu Qingfei Wang Gongjian Li Li Wan

Trace element

10.1016/j.gexplo.2012.05.009

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Citations (12)

Fractal models for estimating local reserves with different mineralization qualities and spatial variations

Journal of Geochemical Exploration (2011)

Qingfei Wang Jun Deng Huan Liu Yanru Wang Xiang Sun

10.1016/j.gexplo.2011.02.008

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Citations (61)

Fractal analysis of the ore-forming process in a skarn deposit: a case study in the Shizishan area, China

Geological Society London Special Publications (2011)

Qingfei Wang Jun Deng Huan Liu Li Wan Zhijun Zhang

Abstract This paper presents a tool for analysing the element distribution and mineralization intensity. The Hurst exponents and a - f ( a ) multifractal spectrum are utilized to analyse the irregular element distribution in Shizishan skarn orefield, China. The Hurst exponents reveal the Cu, Ag, Au and Zn distributions in the skarn-dominated drill cores are persistent and those in marble-dominated drill core are nearly random; the persistence indicates the mineralized segments are repeatedly developed, with accordance to multi-layer structure of the ore-controlling bedding faults and orebodies. The small a min (minimum multifractal singularity) of the Cu, Ag and Au in M 1 reflect bare mineralization. The a min also displays that the mineralization intensities are varied for distinct elements and for different locations, yet the similarity of the distinct ore-forming processes is manifested by constant a min / f ( a min ) ratio. The constant ratio indicates the wider mineralization range denotes a more compact concentration distribution. The compact distributions represent the wide Cu, Ag and Au mineralization in skarns, and the loose distributions reflect the bare Cu, Ag and Au mineralization in marbles. Moreover a min shows a positive correlation with Hurst exponents in the Shizishan skarn orefield. Using fractal analysis the author's show that although the mineralization intensities for different elements and different locations along the Shizishan skarn orefield is not consistent, similar mineralization processes can be correlated to similar fractal exponents.

Ore genesis

10.1144/sp350.6

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Citations (14)