Skip to main content
SpringerLink
Log in

Modelling spatial anisotropy of gold concentration data using GIS-based interpolated maps and variogram analysis: Implications for structural control of mineralization

  • Published:
Journal of Earth System Science Aims and scope Submit manuscript

Linear trends of anomalously high gold values in the Florida Canyon gold deposit, Nevada have been identified using a combination of contour maps of gold (Au) concentration developed with a geographic information system (GIS) and variogram maps created using a geostatistical analysis package. These linear trends are interpreted to represent major fault zones that exerted a prinicipal control on gold mineralization and therefore imparted a spatial anisotropy to gold concentrations.

Oxidation state information such as oxide, sulfide or mixed was used initially to map and contour the lower limit of the oxidation zone. Linear trends on this surface suggest the location and trend of major structural elements in the deposit that guided late oxidizing fluids. Subsequently, four contour maps of gold concentrations in oxidized rocks were produced, each map representing 500 ft vertical intervals starting at 3500 ft above mean sea level (msl). Relatively high concentrations of Au that form linear trends on these maps suggest the presence of structural features, such as shear zones that controlled mineralization. Finally, to validate the observed trends, variogram maps of gold concentrations were derived through geostatistical analysis and the major axes of anisotropy were determined for each map.

The results that emerge suggest linear trends of northeast, northwest and, less prominently, north–south orientations. The north–south and northeast trends match those of known and mapped major structures associated with the Florida Canyon deposit. However, the results imply a stronger control on mineralization by northwest-trending structures than previously recognized and the location of possible structures of all trends not previously mapped. They also serve to identify faults that controlled both early hydrothermal fluids and late oxidizing fluids since the gold distribution represents the time integrated effects of both fluid events.

The linear trends derived by spatial analysis (contour maps, variogram maps) of geochemical data (i.e., gold concentration), combined with the results of the field observations prove to be advantageous in understanding the structural control of gold mineralization. Such spatial analyses of geochemical concentration data are particularly useful in the field of mineral exploration.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  • Adams D 2006 Geochemical Sampling and Geostatistics – Notes, Delta Mine Training Center; http://www.dmtcalaska.org/course_dev/explogeo/class12/notes12.html (accessed December 10, 2006).

  • Armstrong M 1998 Basic Linear Geostatistics (Berlin: Springer), pp. 18–19.

    Book  Google Scholar 

  • Bruckner A, Kandelerb E and Kampichlerc C 1999 Plot-scale spatial patterns of soil water content, pH, substrate-induced respiration and N mineralization in a temperate coniferous forest; Geoderma 93(3–4) 207–223.

    Article  Google Scholar 

  • Drew L J, Karlinger M R, Schuenemeyer J H and Armstrong T R 2003 Hydrogeologic significance of the association between well-yield variography and bedrock geologic structures, Pinardville Quadrangle, New Hampshire; Natural Resour. Res. 12(1) 79–91.

    Article  Google Scholar 

  • Drew L J, Southworth S, Sutphin D M, Rubis G A, Schuenemeyer J H and Burton W C 2004 Validation of the relation between structural patterns in fractured bedrock and structural information interpreted from 2D-variogram maps of water-well yields in Loudoun County, Virginia; Natural Resour. Res. 13(4) 255–264.

    Article  Google Scholar 

  • Erickson T A, Williams M W and Sommerfeld RA 2000 Spatial statistics of snowmelt; In: Computational methods in water resources (eds) Bentley L R, Sykes J F, Brebbia C A, Gray W G, Pinder G F (Rotterdam: Balkema) 2 1147–1152.

  • GEMCOM 2006 Help file, Gemcom Software, Vancouver, Canada.

  • Harris J R, Grunsky E C and Wilkinson L 1997 Developments in the effective use and interpretation of lithogeochemistry in regional exploration programs: Application of GIS technology, In: Proceedings of Exploration 97: Fourth Decennial International Conference on Mineral Exploration (ed.) Gubins A G, Prospectors & Developers Association of Canada, pp. 285–292.

  • Hastings J S, Burkhart T H and Richardson R E 1988 Geology of the Florida Canyon gold deposit, Pershing County, Nevada; In: Bulk Mineable Precious Metal Deposits of the Western United States, Symposium Proceedings (eds) Schafer R W, Cooper J J and Vikre P G, Geological Society of Nevada, pp. 433–452.

  • Isaaks E H and Srivastava R M 1989 An Introduction to Applied Geostatistics (New York: Oxford University Press) 561 pp.

    Google Scholar 

  • Kumke T, Schoonderwaldt A and Kienel U 2005 Spatial variability of sedimentological properties in a large Siberian lake; Aquatic Sci. 67 86–96.

    Article  Google Scholar 

  • Larsen R 2007 Personal communication regarding the mining operations at Florida Canyon Mines.

  • Lin Y B, Tan Y C, Liu C W, Lin Y P and Hung C J 2004 Geostatistical method to delineate anomalies of multi-scale spatial variation in hydrogeological changes due to the ChiChi earthquake in the ChouShui River alluvial fan in Taiwan; Environ. Geol. 47 102–118.

    Article  Google Scholar 

  • McClenaghan M B, Thorleifson L H and DiLabio R N W 1997 Till geochemical and indicator mineral methods in mineral exploration; In: Proceedings of Exploration 97: Fourth Decennial International Conference on Mineral Exploration, (ed.) Gubins A G, Prospectors & Developers Association of Canada, pp. 233–248.

  • Ouyang Y, Nkedi K P, Mansell R S and Ren J Y 2003 Spatial distribution of DDT in sediments from estuarine rivers of central Florida; J. Environ. Qual. 32(5) 1710–1716.

    Article  Google Scholar 

  • Pannatier Y 1996 VARIOWIN: Software for Spatial Data Analysis in 2D (New York, NY: Springer-Verlag) ISBN 0-387-94679-9.

    Google Scholar 

  • Person G et al 2008 Hydrologic models of modern and fossil geothermal systems in the Great Basin: Genetic implications for epithermal Au–Ag and Carlin-type gold deposits; Geosphere 4(5) 888–917; doi: 10.1130/GES00150.1.

    Article  Google Scholar 

  • Preuss N E, Fifarek R H and Thomason R E 1997 Hydrothermal and vapor-related alteration at the Florida Canyon epithermal gold deposit, Pershing County, Nevada in Abstracts with Programs; Geol. Soc. Am. 29(6) 207.

    Google Scholar 

  • Raines G L, Sawatzky D L and Conners K K 1996 Great basin geoscience data base [computer file], United States Geological Survey digital data series: DDS-041.

  • Reis A P, Sousa A J, Ferreira da Silva E, Patinha C and Fonseca E C 2004 Combining multiple correspondence analysis with factorial kriging analysis for geochemical mapping of the gold–silver deposit at Marrancos (Portugal); Appl. Geochem. 19(4) 623–631.

    Article  Google Scholar 

  • Sahin A, Ghori S G, Ali A Z, El-Sahn H F, Hassan H M and Al-Sanounah A 1998 Geological controls of variograms in a complex carbonate reservoir, eastern province, Saudi Arabia; Math. Geol. 30(3) 309–322.

    Article  Google Scholar 

  • Samal A R and Fifarek R H 2006a Modeling structural control of gold mineralization at the Florida Canyon epithermal gold deposit, Nevada: A 3-D GIS approach; Geol. Soc. Am. Abstr. with Programs 38(7) 372.

    Google Scholar 

  • Samal A R and Fifarek R H 2006b Geological evolution of the Florida Canyon epithermal gold deposit, Nevada; In: The Power of Mining: Energy’s Influence, 2007 SME Annual Meeting & Exhibit and Colorado Mining Association 109th National Western Mining Conference, Denver, USA, pp. 60.

  • Samal A R and Fifarek R H 2007 Origin of the amagmatic low-sulfidation epithermal Florida Canyon Au–Ag deposit, Pershing County, Nevada; Geol. Soc. Am. Abstr. with Programs 39(6) 606.

    Google Scholar 

  • Samal A R, Fifarek R H and Thomason Robert E 2005 Steam-heated alteration at the Florida Canyon epithermal gold deposit, Nevada: Assemblages, timing and possible fluid sources; Geol. Soc. Am. Abstr. with Programs 37(7) 420, GSA 2005 Annual Meeting.

    Google Scholar 

  • Smith M L and Williams R E 1996 Examination of methods for evaluating remining a mine waste site. Part I. Geostatistical characterization methodology; Engg. Geol. 43 11–21.

    Article  Google Scholar 

  • Sutphin D M, Drew L J, Schuenemeyer J H and Burton W C 2000 Characteristics of water-well yields in the Blue Ridge of Loudoun County, Virginia; Open-File Report 00-280, U.S. Geological Survey.

  • Thomason R E 2002 Geology and mineralization of the Florida Canyon Mine, Pershing County, Nevada; In: Precious metal deposits of the Humboldt Range: New discoveries in an old district, (ed.) Wendt C; Geol. Soc. Nevada, Spec. Publ. 36 192.

  • Turner D D 1997 Predictive GIS model for sediment-hosted gold deposits, north-central Nevada, U.S.A.; In: Proceedings of Exploration 97: Fourth Decennial International Conference on Mineral Exploration, (ed.) Gubins A G; Prospectors & Developers Association of Canada, pp. 115–126.

  • Wackernagel Hans 2003 Multivariate Geostatistics (3rd edn.) Springer.

  • Yager D B and Folger H W 2003 Map showing copper concentrations from stream sediments and soils throughout the Humboldt river basin and surrounding areas, northern Nevada; U.S. Geological Survey miscellaneous field studies map mf-2407, e version 1.0.

Download references

Author information

Author notes

  1. Abani R Samal

    Present address: , 9063 West Phillips Drive, Littleton, CO, 80128, USA

Authors and Affiliations

  1. Department of Geology, Southern Illinois University, Carbondale, IL, 62901–4324, USA

    Abani R Samal & Richard H Fifarek

  2. Department of Geography, McGill University, 805 Sherbrooke St. W, Montreal, QC, H3A 2K6, Canada

    Raja R Sengupta

Authors
  1. Abani R Samal
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Raja R Sengupta
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Richard H Fifarek
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Abani R Samal.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Samal, A.R., Sengupta, R.R. & Fifarek, R.H. Modelling spatial anisotropy of gold concentration data using GIS-based interpolated maps and variogram analysis: Implications for structural control of mineralization. J Earth Syst Sci 120, 583–593 (2011). https://doi.org/10.1007/s12040-011-0091-4

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12040-011-0091-4

Keywords.

Search

Navigation