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Cui N.,China University of Geosciences | Cui N.,Beijing Key Laboratory of Development and Research for Land Resources Information | Chen J.,China University of Geosciences | Chen J.,Beijing Key Laboratory of Development and Research for Land Resources Information
Geological Bulletin of China | Year: 2015

In the light of the age of big data, the authors put forward the strategic significance of geological study of unstructured data. Through the analysis of the characteristics of geological data, the authors found that these data have the nature of "big data". And then, taking the image of JPG maps as an example, the authors analyzed the current industrial and research situation both in China and abroad. The usage of the geological image of JPG was analyzed. Finally, the strategy planning was proposed for the data such as the geological image of JPG. ©, 2015, Science Press. All right reserved. Source


Shi R.,China University of Geosciences | Shi R.,Beijing Key Laboratory of Development and Research for Land Resources Information | Chen J.,China University of Geosciences | Chen J.,Beijing Key Laboratory of Development and Research for Land Resources Information | Wang G.,China University of Geosciences
Acta Petrologica Sinica | Year: 2013

The North China Craton is the largest and oldest block in China, which has complicated geological evolution history. It is the distributive province of the important iron deposits resource. Under the guidance of regional metallogenic regularity, the multisource data sets including metamorphic formations, ore-controlling structure, ore-induced magnetic anomaly, geochemical and natural heavy minerals were extracted with GIS technology. The prospecting model of sedimentary metamorphic iron deposits was built based on it. Then weights for each layer were calculated to identify the posterior probabilities for each cell of the study area under weights of evidence module. According to the posterior probabilities, six prospecting areas were delineated, which were divided into two grades. Three prospecting areas of grade A are eastern Hebei Province, eastern Liaoning Province and Wutai-Lvliang; Three prospecting areas of grade B are Daqingshan-Se'ernengtengshan, Lushan-Wuyang and western Shandong Province. Due to the similar metallogenic conditions with the known iron deposits, around the known deposits, these areas still have great metallogenic potential. So they deserve more attention in future mineral exploration. Source


Liu X.-L.,China University of Geosciences | Liu X.-L.,Beijing Key Laboratory of Development and Research for Land Resources Information | Chen J.-P.,China University of Geosciences | Chen J.-P.,Beijing Key Laboratory of Development and Research for Land Resources Information
Wutan Huatan Jisuan Jishu | Year: 2010

The factor analysis is an effective mediod to study the symbiotic combination of elements, and each of these factors indicated diat a relationship of combination among elements. So, when people study the mineralization or the metallogenic prediction, they can get some clues from the relationship. In this paper, the author collected the geochemical data of zhiduozaduo region in soudhem Qinghai province, and selected 17 elements to do R-factor analysis. Then, the audior get 5 different factors indicating die combination features of several elements, and drawing die contour maps based of factors scores. The next important diing is die analysis of factors widi die actual geological background of favorable ore-forming. Moreover, the audior hope diat diis results of die analysis can provide clues and basis for metallogenic prediction. Source


Yu P.,China University of Geosciences | Yu P.,Beijing Key Laboratory of Development and Research for Land Resources Information | Chen J.,China University of Geosciences | Chen J.,Beijing Key Laboratory of Development and Research for Land Resources Information | And 5 more authors.
Geological Bulletin of China | Year: 2015

In the context of the situation that big data science has become a new scientific paradigm, this paper presented the new method of model-driven quantitative prediction and evaluation of mineral resources and the new idea of modeling techniques throughout the entire process of mineral resources prediction based on geological big data concept. This study truly realized the data mining and quantitative prediction and evaluation of mineral resources for the geological big data by two main lines of geological theory guiding geological big data analysis and computer technology achieving geological big data mining. The application study of this methodology was carried out in different regions, different types of mineralization and different minerals like the Qimantag iron and copper polymetallic deposits of Qinghai Province, the Jiaojia gold deposit of Shandong Province and the Gejiu tin-copper polymetallic deposit of Yunnan Province. The authors designed and implemented the prospecting model workflow, sufficiently analyzed and extracted favorable mineralization information and obtained good results which could provide new idea for digital geological studies and quantitative prediction and evaluation of mineral resources in the big data age. ©, 2015, Science Press. All right reserved. Source


Chen J.,China University of Geosciences | Chen J.,Beijing Key Laboratory of Development and Research for Land Resources Information | Yu P.,China University of Geosciences | Yu P.,Beijing Key Laboratory of Development and Research for Land Resources Information | And 5 more authors.
Earth Science Frontiers | Year: 2014

Mineral resources are the material basis of human survival and the fundamental guarantee of the progress of human society. In recent years, with the reduction of shallow deposits, looking for deep concealed ore bodies is increasingly urgent. By collating and summarizing the previous studies, and based on modern metallogenic theory, modern metallogenic prediction theory and mineral resources prospecting and evaluation theory, this paper explores a set of methods and processes suitable for three-dimensional quantitative prediction and evaluation of regional concealed ore bodies, which rely on database technology, 3S technology, 3D visualization technology and modern mathematical theory and methods, and integrating multi-information as geology, geophysics, geochemistry, remote sensing, etc. This paper presented new methods of quantitative expression of ore-controlling factors by combining the basic geology and ore geology concept, new methods of extractions of new variables like unconformity and carbonate rock stratum, and new method of division of favorable mineralization interval according to statistical convergence. This work combines the traditional two-dimensional regional metallogenic prediction methods and advanced visualization technologies successfully, extends the prediction of mineral resources within the region to three-dimensional space, makes it more conducive to concealed ore delineation work within the region, and also provides a reference for future three-dimensional prediction. Source

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