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Fractal Geometry in Geosciences

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Encyclopedia of Mathematical Geosciences

Part of the book series: Encyclopedia of Earth Sciences Series ((EESS))

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Definition

A fractal is an object or feature characterized by its fractal dimension that differs from the integer Euclidian dimension of the space in which the fractal is imbedded. On the one hand, fractals are often closely associated with the random variables studied in mathematical statistics; on the other hand, they are connected with the concept of “chaos” that is an outcome of some types of nonlinear processes. Fractals are phenomena measured in terms of their presence or absence in boxes belonging to arrays superimposed on the domain of study in 1-D, 2-D, or 3-D space. Several phenomena that originally were thought to be fractals turned out to multifractals, which are “measures” representing of how much of a feature is present within the boxes used for measurement. Multifractals are spatially intertwined fractals.

Introduction

The word “fractal” was coined by Mandelbrot (1975). Evertsz and Mandelbrot (1992) explain that fractals are phenomena measured in terms of their presence...

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References

  • Agterberg FP (1974) Geomathematics. Elsevier, Amsterdam

    Google Scholar 

  • Agterberg FP (1980) Mineral resource estimation and statistical exploration. In: Facts and principles of world oil occurrence. Canadian Society of Petroleum Geology Memoir 6, pp 301–318

    Google Scholar 

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

    Article  Google Scholar 

  • Agterberg FP (2012) Sampling and analysis of element concentration distribution in rock units and orebodies. Nonlinear Process Geophys 19:23–44

    Article  Google Scholar 

  • Agterberg FP (2013) Fractals and spatial statistics of point patterns. J Earth Sci 24(1):1–11

    Article  Google Scholar 

  • Agterberg FP (2014) Geomathematics: theoretical foundations, applications and future developments. Quantitative geology and geostatistics 18. Springer, Heidelberg

    Book  Google Scholar 

  • Agterberg FP (2017a) Pareto-lognormal modeling of known and unknown metal resources. Nat Resour Res 26:3–20. (with erratum on p. 21)

    Article  Google Scholar 

  • Agterberg FP (2017b) Pareto-lognormal modeling of known and unknown metal resources. II. Method refinement and further applications. Nat Resour Res 26(3):265–283

    Article  Google Scholar 

  • Agterberg FP (2018a) Can multifractals be used for mineral resource appraisal? J Geochem Explor 189:54–63

    Article  Google Scholar 

  • Agterberg FP (2018b) Statistical modeling of regional and worldwide size-frequency distributions of metal deposits. In: Handbook of mathematical geosciences. Fifty years of IAMG. Springer, Heidelberg, pp 505–527

    Chapter  Google Scholar 

  • Agterberg FP (2018c) New method of fitting Pareto-lognormal size-frequency distributions of metal deposits. Nat Resour Res 27(1):265–283

    Google Scholar 

  • Agterberg FP (2020) Multifractal modeling of worldwide and Canadian metal size-frequency distributions. Nat Resour Res 29(4):539–550

    Article  Google Scholar 

  • Agterberg FP, Cheng Q, Wright DF (1993) Fractal modeling of mineral deposits. In: Application of computers and operations research in the mineral industry. Canadian Institute of Mining, Metallurgy and Petroleum Engineering, Montreal, pp 43–53

    Google Scholar 

  • Arias M, Gumiel P, Martin-Izard A (2012) Multifractal analysis of geochemical anomalies: a tool for assessing prospectivity at the SE border of the Ossa Morena Zone, Variscan Massif (Spain). J Geochem Explor 122:101–112

    Article  Google Scholar 

  • Burnett AI, Adams KC (1977) A geological, engineering and economic study of a portion of the Lloydminster Sparky Pool, Lloydminster, Alberta. Bulletin of the Canadian Society of Petroleum Geology 25(2):341–366

    Google Scholar 

  • Carranza EJM (2008) Geochemical anomaly and mineral prospectivity mapping in GIS. In: Handbook of exploration and environmental geochemistry 11. Elsevier, Amsterdam

    Google Scholar 

  • Chen Z, Cheng Q, Chen J, Xie S (2007) A novel iterative approach for mapping local singularities from geochemical data. Nonlinear Process Geophys 14:317–324

    Article  Google Scholar 

  • Cheng Q (1994) Multifractal modeling and spatial analysis with GIS: gold mineral potential estimation in the Mitchell-Sulphurets area, northwestern British Columbia. Unpublished doctoral dissertation, University of Ottawa, Canada

    Google Scholar 

  • Cheng Q (1999) Spatial and scaling modelling for geochemical anomaly separation. J Geochem Explor 65:175–194

    Article  Google Scholar 

  • Cheng Q (2006) Multifractal modelling and spectrum analysis: Methods and applications to gamma ray spectrometer data from southwestern Nova Scotia, Canada. Science in China: Series D Earth Sciences 49(3):283–294

    Google Scholar 

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

    Article  Google Scholar 

  • Cheng Q (2008) Non-linear theory and power-law models for information integration and mineral resources quantitative assessments. Math Geosci 40(5):503–532

    Article  Google Scholar 

  • Cheng Q (2012) Singularity theory and methods for mapping geochemical anomalies caused by buried sources and for predicting undiscovered mineral deposits in covered areas. J Geochem Explor 122:55–70

    Article  Google Scholar 

  • Cheng Q (2014) Generalized binomial multiplicative cascade processes and asymmetrical multifractal distributions. Nonlinear Process Geophys 21:472–482

    Article  Google Scholar 

  • Cheng Q (2016) Fractal density and singularity analysis of heat flow over ocean ridges. Nat Sci Rep 6:1–10

    Google Scholar 

  • Cheng Q, Agterberg FP (1995) Multifractal modeling and spatial point processes. Math Geol 27:831–845

    Google Scholar 

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

    Google Scholar 

  • Cheng Q, Agterberg FP (2009) Singularity analysis of ore-mineral and toxic trace elements in stream sediments. Comput Geosci 35:234–244

    Article  Google Scholar 

  • Cheng Q, Agterberg FP, Ballantyne SB (1994) The separation of geochemical anomalies from background by fractal methods. J Geochem Explor 51:109–130

    Article  Google Scholar 

  • Chhabra A, Jensen RV (1989) Direct determination of the f (α) singularity spectrum. Phys Rev Lett 62(12):1327–1330

    Article  Google Scholar 

  • Cressie NAC (1991) Statistics for spatial data. Wiley, New York

    Google Scholar 

  • Crovelli RA (1995) The generalized 20/80 law using probabilistic fractals applied to petroleum field size. Nonrenewable Resour 4(3):233–241

    Article  Google Scholar 

  • Daya Sagar BS, Rangarajan G, Veneziano D (2004) Fractals in geophysics. Chaos, Solitons Fractals 10(2):237–239

    Article  Google Scholar 

  • De Wijs HJ (1951) Statistics of ore distribution, I. Geol Mijnb 30:365–375

    Google Scholar 

  • Diggle PJ (1983) Statistical analysis of spatial point patterns. Academic Press, London

    Google Scholar 

  • Drew LJ, Schuenemeyer JH, Bawiee WJ (1982) Estimation of the future rates of oil and gas discoveries in the western Gulf of Mexico. U.S. geological survey professional paper 1252, Washington, DC

    Google Scholar 

  • Evertsz CJG, Mandelbrot BB (1992) Multifractal measures. In: Chaos and fractals. Springer, New York

    Google Scholar 

  • Feder J (1988) Fractals. Plenum, New York

    Book  Google Scholar 

  • Ford A, Blenkinsop TG (2009) An expanded de Wijs model for multifractal analysis of mineral production data. Mineral Deposita 44(2):233–240

    Article  Google Scholar 

  • Gonçalves MA, Mateus A, Oliveira V (2001) Geochemical anomaly separation by multifractal modeling. J Geochem Explor 72:91–114

    Article  Google Scholar 

  • Herzfeld UC, Overbeck C (1999) Analysis and simulation of scale-dependent fractal surfaces with application to seafloor morphology. Comput Geosci 25(9):979–1007

    Article  Google Scholar 

  • Herzfeld UC, Kim II, Orcutt JA (1995) Is the ocean floor a fractal? Math Geol 27(3):421–442

    Article  Google Scholar 

  • Kaye BH (1989) A random walk through fractal dimensions. VCH Publishers, New York

    Google Scholar 

  • Kleiber C, Kotz S (2003) Statistical distributions in economics and actuarial sciences. Wiley, Hoboken

    Book  Google Scholar 

  • Korvin G (1992) Fractal models in the earth sciences. Elsevier, Amsterdam

    Google Scholar 

  • Krige DG (1966) A study of gold and uranium distribution pattern in the Klerksdorp goldfield. Geoprocessing 4:43–53

    Google Scholar 

  • Lorentz EN (1963) Determinist nonperiodic flow. J Atmos Sci 20:130–141

    Article  Google Scholar 

  • Lovejoy S, Schertzer D (2007) Scaling and multifractal fields in the solid Earth and topography. Nonlinear Process Geophys 14:465–502

    Article  Google Scholar 

  • Lovejoy S, Schertzer D (2018) The weather and climate: emergent laws and multifractal cascades. Cambridge University Press, New York

    Google Scholar 

  • Mandelbrot BB (1975) Les Objects Fractals: Forme, Hazard et Dimension. Flammarion, Paris

    Google Scholar 

  • Mandelbrot BB (1977) Fractals: form, chance, and dimension. Freeman, San Francisco

    Google Scholar 

  • Mandelbrot BB (1983) The Fractal geometry of nature. Freeman, San Francisco

    Book  Google Scholar 

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

    Article  Google Scholar 

  • Matheron G (1962) Traité de Géologique Appliquée. Mémoire BRGM 14. Éditions Technip, Paris

    Google Scholar 

  • Meneveau C, Sreenivasan KR (1987) Simple multifractal cascade model for fully developed turbulence. Phys Rev Lett 59(7):1424–1427

    Article  Google Scholar 

  • Nickless E, Bloodworth A, Meinert L, Giurco D, Mohr S, Littleboy A (2014) Resourcing future generations white paper: mineral resources and future supply. International Union of Geological Sciences. http://www.americangeosciences.org/community/resourcing-future-generations-white-paper

  • Pahani A, Cheng Q (2004) Multifractality as a measure of spatial distribution of geochemical patterns. Math Geol 36:827–846

    Article  Google Scholar 

  • Patiño Douce AE (2016a) Metallic mineral resources in the twenty first century. I. Historical extraction trends and expected demand. Nat Resour Res 25:71–90

    Article  Google Scholar 

  • Patiño Douce AE (2016b) Metallic mineral resources in the twenty first century. II. Constraints on future supply. Nat Resour Res 25:97–124

    Article  Google Scholar 

  • Patiño Douce AE (2016c) Statistical distribution laws for metallic mineral deposit sizes. Nat Resour Res 25:365–387

    Article  Google Scholar 

  • Patiño Douce AE (2016d) Loss distribution model for metal discovery probabilities. Nat Resour Res. https://doi.org/10.1007/s11053-016-9325-2

  • Perrin J (1913) Les Atomes. NRF-Gallimard, Paris

    Google Scholar 

  • Poincaré H (1899) Les methodes Nouvelles de la mécanique celeste. Gauthier-Villars, Paris

    Book  Google Scholar 

  • Quandt RE (1966) Old and new methods of estimation and the Pareto distribution. Metrica 10:55–82

    Article  Google Scholar 

  • Reed WJ (2003) The Pareto law of increases: an explanation and an extension. Physica A 319:579–597

    Article  Google Scholar 

  • Reed WJ, Jorgensen M (2003) The double Pareto-lognormal distribution. A new parametric model for size distributions. Comput Stat: Theory Methods 33(8):1733–1753

    Google Scholar 

  • Ripley BD (1976) The second-order analysis of stationary point processes. J Appl Probab 13:255–266

    Article  Google Scholar 

  • Sinclair AJ (1991) A fundamental approach to threshold estimation in exploration geochemistry: probability plots revisited. J Geochem Explor 41(1):1–22

    Article  Google Scholar 

  • Singer DA, Menzie DW (2010) Quantitative mineral resource assessments. Oxford University Press, New York

    Google Scholar 

  • Stanley H, Meakin P (1988) Multifractal phenomena in physics and chemistry. Nature 335:405–409

    Article  Google Scholar 

  • Steinhaus H (1954) Length, shape and area. Col. Math., III: 1–13

    Google Scholar 

  • Stoyan D, Stoyan H (1994) Fractals, random shapes and point fields. Wiley, Chichester

    Google Scholar 

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

    Book  Google Scholar 

  • USGS Mineral Commodity Summaries, 2015. http://minerals.usgs.gov/minerals/pubs/mcs2015.pdf

  • Vening Meinesz FA (1951) A remarkable feature of the Earth’s topography. Proc KNAW Ser B Phys Sci 54:212–228

    Google Scholar 

  • Vening Meinesz FA (1964) The earth’s crust and mantle. Elsevier, Amsterdam

    Google Scholar 

  • Whittle P (1962) Topographic correlation power-law covariance functions and diffusion. Biometrika 49:305–314

    Article  Google Scholar 

  • Xiao F, Chen J, Zhang Z, Wang C, Wu G, Agterberg FP (2012) Singularity mapping and spatially weighted principal component analysis to identify geochemical anomalies associated with Ag and Pb-Zn polymetallic mineralization in Northwest Zhejiang, China. J Geochem Explor 122:90–100

    Article  Google Scholar 

  • Xie X, Mu X, Ren T (1997) Geochemical mapping in China. J Geochem Explor 60:99–113

    Article  Google Scholar 

  • Yu C (2002) Complexity of earth systems – fundamental issues of earth sciences. J China Univ Geosci 27:509–519. (in Chinese; English abstract)

    Google Scholar 

  • Zuo R, Wang J (2016) Fractal/multifractal modeling of geochemical data: a review. J Geochem Explor 164:33–41

    Article  Google Scholar 

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Cheng, Q., Agterberg, F. (2021). Fractal Geometry in Geosciences. In: Daya Sagar, B.S., Cheng, Q., McKinley, J., Agterberg, F. (eds) Encyclopedia of Mathematical Geosciences. Encyclopedia of Earth Sciences Series. Springer, Cham. https://doi.org/10.1007/978-3-030-26050-7_9-1

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  • DOI: https://doi.org/10.1007/978-3-030-26050-7_9-1

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