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Non-Linear Theory and Power-Law Models for Information Integration and Mineral Resources Quantitative Assessments

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Abstract

Singular physical or chemical processes may result in anomalous amounts of energy release or mass accumulation that, generally, are confined to narrow intervals in space or time. Singularity is a property of different types of non-linear natural processes including cloud formation, rainfall, hurricanes, flooding, landslides, earthquakes, wildfires, and mineralization. The end products of these non-linear processes can be modeled as fractals or multifractals. Hydrothermal processes in the Earth’s crust can result in ore deposits characterized by high concentrations of metals with fractal or multifractal properties. Here we show that the non-linear properties of the end products of singular mineralization processes can be applied for prediction of undiscovered mineral deposits and for quantitative mineral resource assessment, whether for mineral exploration or for regional, national and global planning for mineral resource utilization. In addition to the general theory and framework for the non-linear mineral resources assessment, this paper focuses on several power-law models proposed for characterizing non-linear properties of mineralization and for geoinformation extraction and integration. The theories, methods, and computer system discussed in this paper were validated using a case study dealing with hydrothermal Au mineral potential in southern Nova Scotia, Canada.

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References

  • Agterberg FP (1989a) Computer programs for exploration. Science 245:76–81. Medline doi:10.1126/science.245.4913.76

    Article  Google Scholar 

  • Agterberg FP (1989b) Systematic approach to dealing with uncertainty of geoscience information in mineral exploration. In: Weiss A (ed) Application of computers and operations in the mineral industry. Proc. 21st APCOM symp. (Las Vegas, Nevada). Colorado Society of Mining Engineers, Littleton, pp 165–178

    Google Scholar 

  • Agterberg FP (1995) Multifractal modeling of the sizes and grades of giant and supergiant deposits. Int Geol Rev 37:1–8

    Google Scholar 

  • Agterberg FP (2001) Multifractal simulation of geochemical map patterns. In: Merriam DF, Davis JC (eds) Geologic modeling and simulation. Sedimentary systems. Kluwer, New York, pp 327–346

    Google Scholar 

  • Agterberg FP (2007a) New applications of the model of de Wijs in regional geochemistry. Math Geol 39:1–26. doi:10.1007/s11004-006-9063-7

    Article  Google Scholar 

  • Agterberg FP (2007b) Mixtures of multiplicative cascade models in geochemistry. Nonlinear Process Geophys 14:201–209

    Google Scholar 

  • Agterberg FP, Bonham-Carter GF (1990) Deriving weights of evidence from geoscience contour maps for prediction of discrete events. In: Proc. 22nd APCOM Symp. (Berlin, Germany), Tech. Univ. Berlin, vol 2, pp 381–396

  • Agterberg FP, Cheng Q (2002) Conditional independence test for weights of evidence modeling. Nat Resour Res 11:249–255. doi:10.1023/A:1021193827501

    Article  Google Scholar 

  • Agterberg FP, Brown A, Cheng Q, Good D (1994) Multifractal modeling of fractures in Lac De Bonnet batholith, Manitoba. In: Proc of IAMG ’94, Mont-Tremblant, Quebec, October, 1994, vol 1, pp 3–8

  • An P, Moon WM, Rencz A (1991) Application of fuzzy set theory for integration of geological, geophysical, and remote sensing data. Can J Explor Geophys 27:1–11

    Google Scholar 

  • Bonham-Carter GF (1994) Geographic information systems for geoscientists: modelling with GIS. Pergamon, Oxford, p 398

    Google Scholar 

  • Bonham-Carter GF, Agterberg FP, Wright DF (1988) Integration of geological data sets for gold exploration in Nova Scotia. Photogramm Eng Remote Sensing 54:1585–1592

    Google Scholar 

  • Chatterjee AK (1983) Metallogenic map of Nova Scotia, ver. 1, scale 1:500,000, Department of Mines and Energy, Nova Scotia, Canada

  • Cheng Q (1989) A quantitative method for evaluating mineral resource of multivariate populations. In: Wang S, Fan J, Cheng Q (eds) Journal of Changchun Univ of Earth Sci, Special Issue (in Chinese with English abstract), vol 19, pp 50–56

  • Cheng Q (1997) Discrete multifractals. Math Geol 29:245–266. doi:10.1007/BF02769631

    Article  Google Scholar 

  • Cheng Q (1999) Multifractality and spatial statistics. Comput Geosci 25:949–961. doi:10.1016/S0098-3004(99)00060-6

    Article  Google Scholar 

  • Cheng Q (2000) GeoData Analysis System (GeoDAS) for mineral exploration: user’s guide and exercise manual. Material for the training workshop on GeoDAS held at York University, Nov. 1 to 3, 2000, p 204. http://www.gisworld.org/geodat

  • Cheng Q (2003) Fractal and multifractal modeling of hydrothermal mineral deposit spectrum: application to gold deposits in the Abitibi Area, Canada. J China Univ Geosci 14:199–206

    Google Scholar 

  • Cheng Q (2004a) Weights of evidence modeling of flowing wells in the Greater Toronto Area, Canada. Nat Resour Res 13:77–86. doi:10.1023/B:NARR.0000032645.46747.48

    Article  Google Scholar 

  • Cheng Q (2004b) A new model for quantifying anisotropic scale invariance and for decomposition of mixing patterns. Math Geol 36:345–360. doi:10.1023/B:MATG.0000028441.62108.8a

    Article  Google Scholar 

  • Cheng Q (2005) Multifractal distribution of eigenvalues and eigenvectors from 2D multiplicative cascade multifractal fields. Math Geol 37:915–927. doi:10.1007/s11004-005-9223-1

    Article  Google Scholar 

  • Cheng Q (2006) GIS-based multifractal anomaly analysis for prediction of mineralization and mineral deposits. In: Harris J (ed) GIS for the earth sciences, Geological Association of Canada, Tri-Co Group, Ottawa, pp 285–296

    Google Scholar 

  • Cheng Q (2007a) Mapping singularities with stream sediment geochemical data for prediction of undiscovered mineral deposits in Gejiu, Yunnan Province, China. Ore Geol Rev 32:314–324. doi:10.1016/j.oregeorev.2006.10.002

    Article  Google Scholar 

  • Cheng Q (2007b) Multifractal imaging filtering and decomposition methods in space, Fourier frequency and Eigen domains. Nonlinear Process Geophys 14:293–303

    Google Scholar 

  • Cheng Q (2007c) Log-probability model vs. logistic model for weights of evidence method. In: Zhao PD Agterberg FP Cheng Q (eds) Proceedings of IAMG’07: Geomathematics and GIS analysis of resources, environment and hazards, China, August 26–31, 2007. China University of Geosciences Printing House, Wuhan, pp 66–69

    Google Scholar 

  • Cheng Q (2008a) A new combined model for prediction of river flow. J Hydrol 352:157–167. doi:10.1016/j.jhydrol.2008.01.017

    Article  Google Scholar 

  • Cheng Q (2008b) Local singularity analysis of river peak flow. Nonlinear Process Geophys (submitted)

  • Cheng Q (2008c) Modeling local scaling properties for multi-scale mapping. Vadose Zone J (in press)

  • Cheng Q (2008d) Comparison between Tau model and weights of evidence model. Math Geosci (submitted)

  • Cheng Q, Agterberg FP (1996) Multifractal modeling and spatial statistics. Math Geol 28:1–16. doi:10.1007/BF02273520

    Article  Google Scholar 

  • Cheng Q, Agterberg FP (1999) Fuzzy weights of evidence method and its application in mineral potential mapping. Nat Resour Res 8:27–35. doi:10.1023/A:1021677510649

    Article  Google Scholar 

  • Cheng Q, Agterberg FP (2008) Singularity analysis of ore-mineral and toxic trace elements in stream sediments. Comput Geosci (in press)

  • Cheng Q, Bonham-Carter GF, Agterberg FP, Wright DF (1994a) Fractal modeling in the geosciences and implementation with GIS. In: Proc of the 6th Canadian conference on GIS, Ottawa, June 6–10, vol 1, pp 565–577

  • Cheng Q, Agterberg FP, Ballantyne SB (1994b) The separation of geochemical anomalies from background by fractal methods. J Geochem Explor 51:109–130. doi:10.1016/0375-6742(94)90013-2

    Article  Google Scholar 

  • Cheng Q, Agterberg FB, Bonham-Carter GF, Sun J (1994c) Artificial intelligence model for integrating spatial patterns for mineral potential estimation with incomplete information. In: Proc of 6th Can conf on GIS, Ottawa, June 6–10, 1994, vol 1, pp 261–274

  • Cheng Q, Agterberg FP, Bonham-Carter GF (1996) Fractal pattern integration method for mineral potential mapping. Nonrenew Res 5:117–130. doi:10.1007/BF02257585

    Article  Google Scholar 

  • Cheng Q, Xu Y, Grunsky EC (2001) Integrated spatial and spectrum analysis for geochemical anomaly separation. Nat Resour Res 9:43–51. doi:10.1023/A:1010109829861

    Article  Google Scholar 

  • de Wijs HJ (1951) Statistics of ore distribution, part I. Geol Mijnb 13:365–375

    Google Scholar 

  • Harris DP (1984) Mineral resources appraisal—mineral endowment, resources, and potential supply: concepts, methods, and cases. Oxford University Press, New York, p 455

    Google Scholar 

  • Kemp LD, Bonham-Carter GF, Raines GL, Looney CG (2001) Arc-SDM: Arcview extension for spatial data modelling using weights of evidence, logistic regression, fuzzy logic and neural network analysis. http://www.ige.unicamp.br/sdm/

  • Li Q, Cheng Q (2004) Fractal singular value decomposition and anomaly reconstruction. Earth Sci 29:109–118. (In Chinese with English abstract)

    Google Scholar 

  • MacDonald MA, Horne R, Corey MC, Ham L (1992) An overview of recent bedrock mapping and follow-up petrological studies of the South Mountain Batholith, Southwestern Nova Scotia. Atl Geol 2:7–28

    Google Scholar 

  • Malamud BD, Turcotte DL, Barton CC (1996) The 1993 Mississippi river flood: a one hundred or a one thousand year event? Environ Eng Geosci II:479–486

    Google Scholar 

  • Malamud BD, Turcotte DL, Guzzetti F, Reichenbach P (2004) Landslide inventories and their statistical properties. Earth Surf Process Landf 29:687–711. doi:10.1002/esp.1064

    Article  Google Scholar 

  • Mandelbrot BB (1989) Multifractal measures, especially for the geophysicist. Pure Appl Geophys 131: 5–42. doi:10.1007/BF00874478

    Article  Google Scholar 

  • McCammon RB, Botbol JM, Sinding-Larsen R, Bowen RW (1983) Characteristic analysis—1981: final program and a possible discovery. Math Geol 15:59–83. doi:10.1007/BF01030076

    Article  Google Scholar 

  • Reynolds PH, Elias P, Muecke GK, Grist AM (1987) Thermal history of the southwestern Meguma zone, Nova Scotia, from an 40Ar/39Ar and fission track dating study of intrusive rocks. Can J Earth Sci 24:1952–1965

    Article  Google Scholar 

  • Rogers PJ, Mills RF, Lombard PA (1987) Regional geochemical study in Nona Scotia. In: Bates JL, MacDonald DR (eds) Mines and mineral branch, report of activities 1986, vol 87-1, pp 147–154

  • Schertzer D, Lovejoy S (1985) The dimension and intermittency of atmospheric dynamics—multifractal cascade dynamics and turbulent intermittency. In: Launder B (ed) Turbulent shear flow. Springer, New York, pp 7–33

    Google Scholar 

  • Schertzer D, Lovejoy S (1987) Physical modeling and analysis of rain and clouds by anisotropic scaling of multiplicative processes. J Geophys Res 92:9693–9714. doi:10.1029/JD092iD08p09693

    Article  Google Scholar 

  • Schertzer D, Lovejoy S, Schmitt F, Chigirinskaya Y, Marsan D (1997) Multifractal cascade dynamics and turbulent intermittency. Fractals 5:427–471. doi:10.1142/S0218348X97000371

    Article  Google Scholar 

  • Singer DA (1993) Basic concepts in three-part quantitative assessments of undiscovered mineral resources. Nonrenew Res 2:69–81. doi:10.1007/BF02272804

    Article  Google Scholar 

  • Singer DA (2008) Mineral deposit densities for estimating mineral resources. Math Geosci 40:33–46

    Article  Google Scholar 

  • Sornette D (2004) Critical phenomena in natural sciences: chaos, fractals, selforganization and disorder, 2nd edn. Springer, New York

    Google Scholar 

  • Turcotte DL (1997) Fractals and chaos in geology and geophysics, 2nd edn. Cambridge University Press, Cambridge

    Google Scholar 

  • Turcotte DL (2002) Fractals in petrology. Lithos 65:261–271. doi:10.1016/S0024-4937(02)00194-9

    Article  Google Scholar 

  • Veneziano D (2002) Multifractality of rainfall and scaling of intensity-duration-frequency curves. Water Resour Res 38:1–12

    Google Scholar 

  • Xie S, Cheng Q, Chen G, Chen Z, Bao Z (2007) Application of local singularity in prospecting potential oil/gas targets. Nonlinear Process Geophys 14:285–292

    Google Scholar 

  • Xu Y, Cheng Q (2001) A multifractal filter technique for geochemical data analysis from Nova Scotia, Canada. J Geochem Explor, Anal Environ 1:1–12

    Google Scholar 

  • Zhao P (1998) Geoanomaly and mineral prediction: modern mineral resource assessment theory and method. Geological Publishing House, Beijing, p 300 (in Chinese)

    Google Scholar 

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Correspondence to Qiuming Cheng.

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Cheng, Q. Non-Linear Theory and Power-Law Models for Information Integration and Mineral Resources Quantitative Assessments. Math Geosci 40, 503–532 (2008). https://doi.org/10.1007/s11004-008-9172-6

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