Journal of China University of Geosciences最新文献

The Pulang porphyry copper deposit, located in the southern segment of the Yidun-Zhongdian island arc ore-forming belt of the Tethys-Himalaya ore-forming domain, is a recently discovered large copper deposit. Compared with the composition of granodiorite in China, the porphyry rocks in this area are enriched in W, Mo, Cu, Au, As, Sb, F, V, and Na₂O (K₁≥1.2). Compared with the composition of fresh porphyry rocks in this district, the mineralized rocks are enriched in Cu, Au, Ag, Mo, Pb, Zn, W, As, Sb, and K₂O (K₂≥1.2). Some elements show clear anomalies, such as Zn, Ag, Cu, Au, W, and Mo, and can be regarded as pathfinders for prospecting new ore bodies in depth. It has been inferred from factor analysis that the Pulang porphyry copper deposit may have undergone the multiple stages of alteration and mineralization: (a) Cu-Au mineralization; (b) W-Mo mineralization; and (c) silicification and potassic metasomatism in the whole ore-forming process. A detailed zonation sequence of indicator elements is obtained using the variability index of indicator elements as follows: Zn→Ag→Cu→Au→W→Mo. According to this zonation, an index such as (Ag×Zn)_D/(Mo×W)_D can be constructed and regarded as a significant criterion for predicting the Cu potential at a particular depth.

Monte-Carlo method is used for estimating coalbed methane (CBM) resources in key coal mining areas of China. Monte-Carlo method is shown to be superior to the traditional volumetric method with constant parameters in the calculation of CBM resources. The focus of the article is to introduce the main algorithm and the realization of functions estimated by Monte-Carlo method, including selection of parameters, determination of distribution function, generation of pseudo-random numbers, and evaluation of the parameters corresponding to pseudo-random numbers. A specified software on the basis of Monte-Carlo method is developed using Visual C++ for the assessment of the CBM resources. A case study shows that calculation results using Monte-Carlo method have smaller error range in comparison with those using volumetric method.

A series of geochemical anomalies of Pt and Pd were found in 1 358 recombined samples from a geochemical stream sediment survey in eastern Yunnan Province, China. Chemical optical emission spectroscopy, X-ray fluorescence analysis, and inductively coupled plasmas atomic emission spectrometry analyses of 22 elements and chemical compositions of 21 samples from coal-bearing strata from the Late Paleozoic, Mesozoic, and Cenozoic show Pt and Pd concentrated to some extent in coal rocks, with Pd/Pt<1. As, Pt, B, Au, Pd, V, Sb, U, Pb, and W are enriched in the Lower Carboniferous coal-bearing strata of the Wanshoushan Formation; B, Mo, As, Pt, U, W, Pb, Pd, and V are enriched in the Lower Permian coal-bearing strata of the Liangshan Formation; Pt, Cu, Mo, Pd, As, V, and Ag are enriched in the Upper Permian coal-bearing strata of the Xuanwei Formation; As, B, Pb, Pt, Pd, U, W, Sb, Mo, Zn, and Ag are enriched in the Upper Triassic coal-bearing strata of the Xujiahe Formation; and Pt, As, and Pb are enriched in the lignite of the Pliocene Ciying Formation. Combining analyses of the sedimentary environment and local volcanic activity reveal that the coal- bearing strata in the Xuanwei Formation are possibly related to the Permian Emeishan basalt.

The recently discovered Damoqujia gold deposit is a large shear zone-hosted gold deposit of disseminated sulphides located in the north of the Zhaoping fault zone, Jiaodong gold province, China. In order to distinguish the temperature range of cluster inclusions from different mineralization stages and measure their compositions, 16 fluid inclusions and 5 isotopic geochemistry samples were collected for this study. Corresponding to different mineralization stages, the multirange peaks of quartz decrepitation temperature (250–270, 310–360 and 380–430 °C) indicate that the activity of ore-forming fluids is characterized by multistage. The ore-forming fluids were predominantly of high-temperature fluid system (HTFS) by CO₂-rich, and SO₄^2--K⁺ type magmatic fluid during the early stage of mineralization and were subsequently affected by low-temperature fluid system (LTFS) of CH₄-rich, and Cl⁻-Na⁺/Ca²⁺ type meteoric fluid during the late stage of mineralization. Gold is transferred by Au-HS⁻ complex in the HTFS, and Au-Cl⁻ complex can be more important in the LTFS. The transition of fluids from deeper to shallow environments results in mixing between the HTFS and LTFS, which might be one of the most key reasons for gold precipitation and large-scale mineralization. The ore-forming fluids are characterized by high-temperature, strong-activity, and superimposed mineralization, so that there is a great probability of forming large and rich ore deposit in the Damoqujia gold deposit. The main bodies are preserved and extend toward deeper parts, thereby suggesting a great potential in future.

Two phenomena of similar objects with different spectra and different objects with similar spectrum often result in the difficulty of separation and identification of all types of geographical objects only using spectral information. Therefore, there is a need to incorporate spatial structural and spatial association properties of the surfaces of objects into image processing to improve the accuracy of classification of remotely sensed imagery. In the current article, a new method is proposed on the basis of the principle of multiple-point statistics for combining spectral information and spatial information for image classification. The method was validated by applying to a case study on road extraction based on Landsat TM taken over the Chinese Yellow River delta on August 8, 1999. The classification results have shown that this new method provides overall better results than the traditional methods such as maximum likelihood classifier (MLC).

Void ratio measures compactness of ground soil in geotechnical engineering. When samples are collected in certain area for mapping void ratios, other relevant types of properties such as water content may be also analyzed. To map the spatial distribution of void ratio in the area based on these types of point, observation data interpolation is often needed. Owing to the variance of sampling density along the horizontal and vertical directions, special consideration is required to handle anisotropy of estimator. 3D property modeling aims at predicting the overall distribution of property values from limited samples, and geostatistical method can be employed naturally here because they help to minimize the mean square error of estimation. To construct 3D property model of void ratio, cokriging was used considering its mutual correlation with water content, which is another important soil parameter. Moreover, K-D tree was adopted to organize the samples to accelerate neighbor query in 3D space during the above modeling process. At last, spatial configuration of void ratio distribution in an engineering body was modeled through 3D visualization, which provides important information for civil engineering purpose.

Spatial distribution patterns of element concentrations can reflect the information of the mineralization processes. Both the Hurst exponent calculated by R/S analysis and the generalized fractal dimension calculated by using the multifractal model are important parameters for describing the spatial distribution of elements. Five long drill holes, named as M1, S1, S2, S3, and S4, have been selected in the Shizishan skarn orefield in Tongling, Anhui Province, China. Marbles are well developed around M1 and skarn rocks are largely distributed along S1, S2, S3, and S4 drill holes. The drill holes were sampled evenly with an interval of 10 m and 16 trace elements have been measured. The mean of the ΔD(q) (the height of the generalized dimension spectrum) in the M1 drill hole is the lowest. In addition, the mean of the Hurst exponents of the 16 elements in the M1 drill hole is also much smaller than that of S1, S2, S3, S4 drill holes, which is in accordance with the analysis of the generalized dimension. It is indicated by the generalized dimension and Hurst exponent that the distribution of trace elements in the marbles is more random than that in the skarn. The result suggests that the mineralization process can change the randomness and persistence features of the element distribution.

The Gejiu deposit is a superlarge tin-copper polymetallic ore-forming concentration area characterized by excellent metallogenic geological settings and advantageous ore-controlling factors. The deposit displays diverse mineralization properties due to different minerals and mineral deposit types. Based on the principal metallogenic factors, metallogenic mechanisms, mineralized components, and occurrence of mineral deposits or ore bodies, the Gejiu mineral district can be divided into 2 combinations of metallogenic series, 4 metallogenic series, 8 subseries, and 27 mineral deposit types. Spatial zonality is evident. The distribution regularity of the elements in both plane and section is Be-W, Sn (Cu, Mo, Bi, Be)-Sn, Pb, Ag-Pb, Zn around a granitic intrusion. The metallogenic epoch is mainly concentrated in the late Yanshanian. During this period, large-scale metallogenic processes related to movement caused by tectonics and magmatism occurred, and a series of magmatic hydrothermal deposits formed. The ore-forming processes can be divided into 4 stages: the silicate stage, the oxide stage, the sulphide stage, and the carbonate stage. Based on the orderliness and diversity (in terms of time, space, and genesis) of the mineralization, the authors have developed a comprehensive spectrum of ore deposits in the Gejiu area. This newly proposed diversity of mineralization and the spectrum developed in this work are useful not only for interpreting the genesis of the Gejiu deposit but also for improving mineral exploration in the area, and in particular, for finding large deposits.