Tectonic–geochemical exploration modeling for characterizing geo-anomalies in southeastern Yunnan district, China

Abstract In this paper, a tectonic–geochemical exploration model is constructed to support mineral exploration in the southeastern Yunnan mineral district, China. Fault systems are significant to mineralization in this district because faulting activities have confined magmatic activities into certain spatial scales and temporal stages, which provide both hydrothermal fluids and heat for mineralization within fracture zones. Analysis of fault density using the singularity theory to characterize development of fault systems suggests that spaces produced by faulting activities favored the migration of hydrothermal fluids and mineralization. In addition, the singularity theory is applied to examine singular distributed ore-forming elements. Principal component analysis was used to model the spatial distribution of enrichment of the association of ore-forming elements, which suggests that geochemical haloes are linked with characteristic hydrothermal mineralization in the study area. For modeling mineral prospectivity, student's t -values were estimated by weights of evidence method to depict patterns of fault density and geochemical anomalies that are highly correlated with known mineral deposit occurrences in the study area. By overlaying these patterns, distributions of enrichments of associated ore-forming elements and spaces due to faulting that favored mineralization can be modeled and areas prospective for mineral exploration can be delineated. The consistency of the results with information from published documents demonstrates that the exploration model discussed in this paper is useful and effective for investigating geological issues related with faulting activities.

[1]  Bruce D. Malamud,et al.  The 1993 Mississippi River Flood: A One Hundred or a One Thousand Year Event? , 1996 .

[2]  Xie Xuejing,et al.  Geochemical mapping in China , 1997 .

[3]  H. Pereira,et al.  A case study on geochemical anomaly identification through principal components analysis supplementary projection , 2003 .

[4]  F. P. Agterberg,et al.  Sampling and analysis of chemical element concentration distribution in rock units and orebodies , 2012 .

[5]  G. Bonham-Carter.  Geographic Information Systems for Geoscientists: Modelling with GIS , 1995 .

[6]  L. J. Drew,et al.  Process recognition in multi-element soil and stream-sediment geochemical data , 2009 .

[7]  E. Carranza.  Mapping of anomalies in continuous and discrete fields of stream sediment geochemical landscapes , 2010 .

[8]  H. Kaiser.  The Application of Electronic Computers to Factor Analysis , 1960 .

[9]  Qiuming Cheng,et al.  Singularity analysis of ore-mineral and toxic trace elements in stream sediments , 2009, Comput. Geosci..

[10]  Zoe K. Shipton,et al.  A review of recent developments concerning the structure, mechanics and fluid flow properties of fault zones , 2010 .

[11]  Daniele Veneziano,et al.  Multifractality of rainfall and scaling of intensity‐duration‐frequency curves , 2002 .

[12]  Qiuming Cheng,et al.  A spatially weighted principal component analysis for multi-element geochemical data for mapping locations of felsic intrusions in the Gejiu mineral district of Yunnan, China , 2011, Comput. Geosci..

[13]  Guocheng Pan,et al.  Information synthesis for mineral exploration , 2000 .

[14]  Q. Cheng,et al.  The separation of geochemical anomalies from background by fractal methods , 1994 .

[15]  Qiuming Cheng,et al.  Application of singularity mapping technique to identify local anomalies using stream sediment geochemical data, a case study from Gangdese, Tibet, western China , 2009 .

[16]  E. Carranza.  Geochemical Anomaly and Mineral Prospectivity Mapping in Gis , 2012 .

[17]  F. P. Agterberg,et al.  Multifractal modelling of the sizes and grades of giant and supergiant deposits , 1995 .

[18]  E. Carranza,et al.  Mapping of prospectivity and estimation of number of undiscovered prospects for lode gold, southwestern Ashanti Belt, Ghana , 2009 .

[19]  D. Burt,et al.  Introduction; terminology, classification, and composition of skarn deposits , 1982 .

[20]  E. Carranza.  Analysis and mapping of geochemical anomalies using logratio-transformed stream sediment data with c , 2011 .

[21]  J. Harris,et al.  Effective use and interpretation of lithogeochemical data in regional mineral exploration programs: application of Geographic Information Systems (GIS) technology☆ , 2000 .

[22]  R. Zuo,et al.  Density/area power-law models for separating multi-scale anomalies of ore and toxic elements in stream sediments , 2010 .

[23]  D. Schertzer,et al.  Physical modeling and analysis of rain and clouds by anisotropic scaling multiplicative processes , 1987 .

[24]  Q. Cheng.  Multifractality and spatial statistics , 1999 .

[25]  Qiuming Cheng,et al.  A fractal filtering technique for processing regional geochemical maps for mineral exploration , 2001, Geochemistry: Exploration, Environment, Analysis.

[26]  E. Carranza,et al.  Predictive mapping of prospectivity and quantitative estimation of undiscovered VMS deposits in Skellefte district (Sweden) , 2010 .

[27]  T. Baker,et al.  Active fault and shear processes and their implications for mineral deposit formation and discovery , 2010 .

[28]  A. Ford,et al.  Evaluating geological complexity and complexity gradients as controls on copper mineralisation, Mt Isa Inlier , 2008 .

[29]  E. C. Grunsky,et al.  The differentiation of soil types and mineralization from multi-element geochemistry using multivariate methods and digital topography , 1999 .

[30]  Frederik P. Agterberg,et al.  Fractals, Multifractals, and Change of Support , 1994 .

[31]  B. Mandelbrot.  Possible refinement of the lognormal hypothesis concerning the distribution of energy dissipation in intermittent turbulence , 1972 .

[32]  I. Koukouvelas,et al.  Fault trace parameters as a tool for analysing remotely sensed fault arrays: An example from the eastern Gulf of Corinth, Greece , 2004 .

[33]  E. Carranza.  From Predictive Mapping of Mineral Prospectivity to Quantitative Estimation of Number of Undiscovered Prospects , 2011 .

[34]  Q. Cheng.  Mapping singularities with stream sediment geochemical data for prediction of undiscovered mineral deposits in Gejiu, Yunnan Province, China , 2007 .

[35]  I. Jolliffe.  Principal Component Analysis , 2002 .

[36]  Emmanuel John M. Carranza,et al.  Catchment basin modelling of stream sediment anomalies revisited: incorporation of EDA and fractal analysis , 2010 .

[37]  Jie Zhao,et al.  Analysis and integration of geo-information to identify granitic intrusions as exploration targets in southeastern Yunnan District, China , 2011, Comput. Geosci..

[38]  E. Carranza.  Controls on mineral deposit occurrence inferred from analysis of their spatial pattern and spatial association with geological features , 2009 .

[39]  L. Li,et al.  Characterization of peak flow events with local singularity method , 2009 .

[40]  Renguang Zuo,et al.  Mapping complexity of spatial distribution of faults using fractal and multifractal models: vectoring towards exploration targets , 2011, Comput. Geosci..

[41]  A. G. Darnley,et al.  International geochemical mapping — a review , 1995 .