Guangdong Key Laboratory of Geological Processes and Mineral Resource Exploration

Guangzhou, China

Guangdong Key Laboratory of Geological Processes and Mineral Resource Exploration

Guangzhou, China
SEARCH FILTERS
Time filter
Source Type

Zhang J.,Beijing Normal University | Liu S.,Beijing Normal University | Li J.,Sun Yat Sen University | Li J.,Guangdong Key Laboratory of Geological Processes and Mineral Resource Exploration | And 3 more authors.
Arabian Journal of Geosciences | Year: 2017

Taking K-successions of the H-Zone of the Pearl River Mouth Basin as a testing example, we used two kinds of approaches to implement the microfacies identification. One is a direct identification, the other is an indirect approach in which we conducted the lithofacies classification first and then identified the microfacies based on previously estimated lithofacies. Both approaches were trained and checked by interpretations of experienced geologists from real subsurface core data. Multinomial logistic regression (MLR) and artificial neural network (ANN) were used in these two approaches as classification algorithms. Cross-validations were implemented. The source data set was randomly divided into training subset and testing subset. Four models, namely, MLR_direct, ANN_direct, MLR_indirect, and ANN_indirect, were trained with the training subset. The result of the testing set shows that the direct approaches (MLR_direct and ANN_direct) perform relatively poor with a total accuracy around 75%. While the indirect approaches (MLR_indirect and ANN_indirect) perform much better with a total accuracy of around 89 and 82%, respectively. This indirect method is simple and reproducible, and it could lead to a robust way of analyzing sedimentary microfacies of horizontal wells with little core data or even are almost never cored while core data are available for nearby vertical wells. © 2017, Saudi Society for Geosciences.


Zhang Y.,Sun Yat Sen University | Zhang Y.,China National Offshore Oil Corporation | Zhang Y.,Guangdong Key Laboratory of Geological Processes and Mineral Resource Exploration | Zhou Y.-Z.,Sun Yat Sen University | And 19 more authors.
Journal of Central South University | Year: 2013

Distinguishing geochemical anomalies from background is a basic task in exploratory geochemistry. The derivation of geochemical anomalies from stream sediment geochemical data and the decomposition of these anomalies into their component patterns were described. A set of stream sediment geochemical data was obtained for 1 880 km2 of the Pangxidong area, which is in the southern part of the recently recognized Qinzhou-Hangzhou joint tectonic belt. This belt crosses southern China and tends to the northwest (NE) direction. The total number of collected samples was 7 236, and the concentrations of Ag, Au, Cu, As, Pb and Zn were measured for each sample. The spatial combination distribution law of geochemical elements and principal component analysis (PCA) were used to construct combination models for the identification of combinations of geochemical anomalies. Spectrum-area (S-A) fractal modeling was used to strengthen weak anomalies and separate them from the background. Composite anomaly modeling was combined with fractal filtering techniques to process and analyze the geochemical data. The raster maps of Au, Ag, Cu, As, Pb and Zn were obtained by the multifractal inverse distance weighted (MIDW) method. PCA was used to combine the Au, Ag, Cu, As, Pb, and Zn concentration values. The S-A fractal method was used to decompose the first component pattern achieved by the PCA. The results show that combination anomalies from a combination of variables coincide with the known mineralization of the study area. Although the combination anomalies cannot reflect local anomalies closely enough, high-anomaly areas indicate good sites for further exploration for unknown deposits. On this basis, anomaly and background separation from combination anomalies using fractal filtering techniques can provide guidance for later work. © 2013 Central South University Press and Springer-Verlag Berlin Heidelberg.


Zhang Y.,Sun Yat Sen University | Zhang Y.,Guangdong Key Laboratory of Geological Processes and Mineral Resource Exploration | Zhang Y.,China National Offshore Oil Corporation | Zhou Y.-Z.,Sun Yat Sen University | Zhou Y.-Z.,Guangdong Key Laboratory of Geological Processes and Mineral Resource Exploration
Zhongnan Daxue Xuebao (Ziran Kexue Ban)/Journal of Central South University (Science and Technology) | Year: 2012

Taking Pangxidong silver gold mine prediction as an example, the application of singularity theory in mineral deposits prediction was studied. Based on the fact that the geochemical is abnormal and the threshold selection is difficult, singularity analysis method was used to map geochemical singular value. In order to understand the variation of shallow and deep mineralization types in Pangxidong area, S-A generalized self-similar method was used to decompose complex anomalies, and combines with the spatial principal component analysis method to delineate complex anomalies of trace elements such as Ag, Au, Cu, Pb and Zn. Tte results show that the singularity analysis method not only emphasizes the data on the statistical characteristics, but also pays attention to the feature in the spatial domain, identifies and delineates anomalies from a variety perspective of geochemical data sets. The anomaly extracted by S-A method agrees with the known ore deposits which are mainly in Tangpeng area. There are a few known ore deposits in Shijiao area where the anomalies are weak. The anomaly of the area by S-A method shows that there may be concealed deposits, which can be investigated by further work.


Tang W.-K.,Sun Yat Sen University | Tao Z.,Sun Yat Sen University | Gao Q.-Z.,Sun Yat Sen University | Gao Q.-Z.,Guangdong Key Laboratory of Geological Processes and Mineral Resource Exploration | And 6 more authors.
Huanjing Kexue/Environmental Science | Year: 2014

Within the drainage basin, information about natural processes and human activities can be recorded in the chemical composition of riverine water. The analysis of the Guijiang River, the first level tributary of the Xijiang River, demonstrated that the chemical composition of water in the Guijiang River was mainly influenced by the chemical weathering of carbonate rocks within the drainage basin, in which CO2 was the main erosion medium, and that the weathering of carbonate rock by H2SO4 had a remarkable impact on the water chemical composition in the Guijiang River. Precipitation, human activities, the weathering of carbonate rocks and silicate rocks accounted for 2.7%, 6.3%, 72.8% and 18.2% of the total dissolved load, respectively. The stable isotopic compositions of dissolved inorganic carbon (δ13CDIC) indicated that DIC in the Guijiang River had been assimilated by the phytoplankton in photosynthesis. The primary production of phytoplankton contributed to 22.3%-30.9% of particulate organic carbon (POC) in the Guijiang River, which implies that phytoplankton can transform DIC into POC by photosynthesis, and parts of POC will sink into the bottom of the river in transit, which leads into the formation of burial organic carbon.


Xie C.,Sun Yat Sen University | Gao Q.,Sun Yat Sen University | Gao Q.,Guangdong Key Laboratory of Geological Processes and Mineral Resource Exploration | Tao Z.,Sun Yat Sen University | And 2 more authors.
Huanjing Kexue Xuebao/Acta Scientiae Circumstantiae | Year: 2013

Chemical runoff of Dongjiang River was investigated, and the mass balance approach and deduction methods were used to estimate the uptake of atmospheric CO2 through rock chemical weathering. We conclude that the concentration of total dissolved solids in the Dongjiang River (59.88 mg·L-1) is far lower than the averages of rivers worldwide (100 mg·L-1) and the chemical composition of the river is dominated with Ca2+, Na+ and HCO3 -, followed by dissolved Si. The dilution effect of the surface runoff on riverine total dissolved solids is not obvious due to human activities. Chemical runoff of the Dongjiang River is mainly derived from the chemical weathering of silicate mineral (72.46%-81.54%), followed by sea salt (17.65%-26.05%), while the contribution from the chemical weathering of carbonate minerals (0.81%-3.87%) is insignificant. Atmospheric CO2 is the main aggressive medium in the rocks chemical weathering within the basin. The CO2 consumption flux (3.02×105-3.08×105 mol·km-2·a-1) of chemical weathering processes in the Dongjiang River Basin is higher than that of the global average, which constitutes an important component of CO2 consumption in the global rocks chemical weathering.


Du X.-D.,Sun Yat Sen University | Du X.-D.,Guangdong Key Laboratory of Geological Processes and Mineral Resource Exploration | Zou H.-P.,Sun Yat Sen University | Zou H.-P.,Guangdong Key Laboratory of Geological Processes and Mineral Resource Exploration | And 5 more authors.
Geology in China | Year: 2013

The Daoyaoshan-Damingshan area is located in the southwestern section of the Qinzhou-Hangzhou juncture between the Yangtze Block and the Cathayian Block. The study of the early Paleaozoic sedimentary environment and tectonic setting of this area is a key to understanding the geotectonic problems in South China. Major and trace elements of 27 pieces of samples from Cambrian sandstones and mudstones in this area were analyzed and discussed. The samples generally have high ratios of Al2O3/TiO2 (in the range of 11.95∼36.26,20.81 on average) and lower ratios of Rb/Cs (in the range of 13.02∼68.27, 32.21 on average) and Cr/Zr(ranging 0.14∼ 1.15, averagely 0.59). Geochemical characteristics, such as the plots of Ni-TiO 2,Th/Sc-La/Sc and La/Th-Hf, indicate that the Cambrian sediments in the Daoyaoshan-Damingshan area were mainly sourced from the upper crustal felsic quartz rocks, with the addition of a small amount of igneous sources and ancient recirculation sediments. The distribution of trace and rare-earth elements and the data of La-Th-Sc,K2O/Na2O-SiO 2, δ Ce, δEu,Tb/Yb,La/Sc,La/Th,Th/U as well as the comparison with different tectonic settings show that the study area belonged to a passive continent-marginal setting. In addition, such evidence as the marks of shallow-sea deposits, the data of sedimentary palaeogeography, regional geology and geochemistry suggests that during the Early Paleozoic there existed no geochemical evidence for the so called "ancient ocean in South China".


He F.-P.,Sun Yat Sen University | Wang Z.,Sun Yat Sen University | Wang Z.,Guangdong Key Laboratory of Geological Processes and Mineral Resource Exploration | Fang C.,Hubei Geological Survey | And 2 more authors.
Journal of Geochemical Exploration | Year: 2014

The Gejiu mineral district, which is a world-class tin production region, is currently facing a shortage of resources; therefore, mineral exploration in the deeper and peripheral spaces has become a high priority in this old mine. Douyan district, located in the south of the Gejiu western district, is becoming the focus of mineral exploration for its favorable metallogenic geological conditions. In this study, factor analysis (FA) and a spectrum-area (S-A) fractal model, aided with geostatistics are applied to study the integrated primary geochemical anomalies associated with Sn polymetallic mineralization. The results indicate that (1) both the F3 and F5 include the information associated with Sn mineralization. F5-consisting of Sn and Sr, indicates that part of the ore-forming materials come from carbonate rocks. F3-consisting of Sn and Mo, shows magmatic activities, which would provide the ore-forming thermal conditions. (2) Sn prospects have been explored in Shuitang Mountain to the SE of study area, and the identified anomalies are related to volcanic rocks and alteration zones. (3) The key controlling factors of geochemical anomalies are the SW-trending fault (Douyan-Shuitang fault), stratus and granitoid batholiths based on geological information. © 2014 Elsevier B.V.

Loading Guangdong Key Laboratory of Geological Processes and Mineral Resource Exploration collaborators
Loading Guangdong Key Laboratory of Geological Processes and Mineral Resource Exploration collaborators