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2128RE: [ai-geostats] modelling trend and kriging type

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  • ABREU Carlos Eduardo
    Jul 1, 2005
      Dear Els

      A good reference on geostats in the oil industry is the excelent book from
      Olivier Dubrule "Geostatistics for Seismic Data Integration in Earth
      Models", where you will also find KDE aplications.

      Actually, it is the reference book of a 1 day course offered by SEG (Society
      of Exploration GEophysicists)/EAGE (European Association og Geoscientists
      and Engineers).


      Carlos Eduardo ABreu

      -----Message d'origine-----
      De : Els Verfaillie [mailto:els.verfaillie@...]
      Envoyé : vendredi 1 juillet 2005 10:55
      À : Pierre Goovaerts; Recep kantarci; ai-geostats@...
      Objet : RE: [ai-geostats] modelling trend and kriging type

      Dear AI-list,

      in which context KED is mostly used? I have found examples of this
      methodology in the context of soil science and climatology:

      Bourennane, H., King, D. and Couturier, A., 2000. Comparison of kriging with
      external drift and simple linear regression for predicting soil horizon
      thickness with different sample densities: Geoderma, v. 97, p. 255-271.

      Bourennane, H. and King, D., 2003. Using multiple external drifts to
      estimate a soil variable: Geoderma, v. 114, p. 1-18.

      Goovaerts, P., 1999. Using elevation to aid the geostatistical mapping of
      rainfall erosivity: Catena, v. 34, p. 227-242.

      Hudson, G. and Wackernagel, H., 1994. Mapping temperature using kriging with
      external drift: theory and an example from Scotland: International Journal
      of Climatology, v. 14, p. 77-91.

      Martinez-Cob, A. and Cuenca, R.H., 1992. Influence of elevation on regional
      evapotranspiration using multivariate geostatistics for various climatic
      regimes in Oregon. Journal of Hydrology 136, 353–380.

      Are there other interesting references for this methodology in the same or
      other application fields?

      Best wishes,

      Els Verfaillie, PhD student
      Renard Centre of Marine Geology - Ghent University
      Krijgslaan 281-S8
      B-9000 Gent - Belgium
      tel: +32-9-2644573 fax: +32-9-2644967
      e-mail: Els.Verfaillie@...

      -----Original Message-----
      From: Pierre Goovaerts [mailto:Goovaerts@...]
      Sent: donderdag 30 juni 2005 16:54
      To: Recep kantarci; ai-geostats@...
      Subject: RE: [ai-geostats] modelling trend and kriging type

      To add to the excellent comments by Edzer and Gregoire,

      1. Universal kriging = kriging with a trend. The second terminology has been
      proposed by Andre
      Journel who felt that the term "universal" was vague and misleadingly

      2. Kriging with an external drift (KED) is mathematically the same as
      universal kriging (UK). Secondary variables
      are simply replacing the spatial coordinates used in UK.

      3. Regression kriging denotes all the techniques where the trend is modeled
      outside the kriging algorithm.
      There are various methods that can be used to model that trend, ranging from
      linear regression
      to neural networks. Kriging is used to interpolate the residuals. In
      practice these techniques have more
      flexibility than universal kriging in term of modeling the trend: multiple
      variables either categorical or
      continuous can be incorporated easily and many sofwtare are available for
      this trend modeling.
      The only limitation is that the trend is modeled globally (i.e. the
      regression coefficients are constant
      in space) while in KED the coefficients are reestimated within each search



      Pierre Goovaerts

      Chief Scientist at Biomedware

      516 North State Street

      Ann Arbor, MI 48104

      Voice: (734) 913-1098
      Fax: (734) 913-2201


      -----Original Message-----
      From: Recep kantarci [mailto:recep_kantarci_1978@...]
      Sent: Thu 6/30/2005 9:38 AM
      To: ai-geostats@...
      Subject: [ai-geostats] modelling trend and kriging type

      Dear ai-geostats members

      When the data used has a trend, it is needed to model trend and in
      this case there exists various types of kriging to apply (universal kriging,
      kriging with a trend, regression kriging etc).
      If this is the case, does one should use the same type of kriging or
      different depending on modeling the trend using coordinates of target
      variable or using other (namely, secondary or auxillary) variables such as
      elevation or topography ? That is , are there a dinstinction depending on
      the type of variables to model the trend while kriging?

      Best regards


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