Thank you for all your suggestions!. Best regards
Oriol Pierre Goovaerts wrote: > To account for the proportion p of the facies, just rescale the > semivariogram by the quantity p(1-p).. hence the different > semivariograms should be comparable. > The fact that the dominant facies tends to be over-represented in the > interpolated map is well-known and frequent when using a maximum likelihood > classification, see > * Goovaerts, P. 1996. Stochastic simulation of categorical variables > using a classification algorithm and simulated annealing. Mathematical > Geology, 28(7): 909-921. > > * Goovaerts, P. and A.G. Journel. 1996. Accounting for local > probabilities in stochastic modeling of facies data. SPE Journal, 1(1): 21-29. > > If you want to avoid the smoothing effect and reproduce target proportions > for the different facies, you may want to use stochastic simulation > as described in the aforementioned papers. > > Pierre > > Pierre Goovaerts > Chief Scientist at BioMedware Inc. > Courtesy Associate Professor, University of Florida > President of PGeostat LLC > > Office address: > 516 North State Street > Ann Arbor, MI 48104 > Voice: (734) 913-1098 (ext. 8) > Fax: (734) 913-2201 > http://home.comcast.net/~goovaerts/ > > ________________________________ > > From: Oriol Falivene [mailto:[EMAIL PROTECTED] > Sent: Sat 7/15/2006 10:45 AM > To: Pierre Goovaerts; [email protected] > Subject: Re: [Fwd: Re: AI-GEOSTATS: Re: generalize kriging > variancetoaverage-basedestimators different than] > > Thank you, > > I will try with the variograms as you suggested, however as the proportions > of each facies are different in the different maps to compare (because of the > smoothing), also the > sills of the indicator variograms will be different making the comparision > non-straightforward. > > And what about using the proportions of each facies, this seams even more > simpler measure of smoothing to me than computing the indicator variograms. > For example; as the > smoothing increases, the proportions of the dominant facies also increase > from that of the original hard data, and the more smoothing the largest the > increase. Do you think > that computing the proportion of the dominant facies would be of any > statistical sense in order to quantify the smoothing effect? > > Thanks again > > Oriol > > Pierre Goovaerts wrote: > > > Hello, > > > > If you want to quantify the smoothness of an interpolated map of facies, > > you should use measure of spatial connectivity. For example, the indicator > > semivariogram provides information on the probability of transitioning > > from one facies to another, as a function of the separation distance. > > Superimposing the variograms computed from different interpolated maps > > would allow a quick visual comparison of the degree of smoothness of the > > different maps. > > > > Pierre > > > > Pierre Goovaerts > > Chief Scientist at BioMedware Inc. > > Courtesy Associate Professor, University of Florida > > President of PGeostat LLC > > > > Office address: > > 516 North State Street > > Ann Arbor, MI 48104 > > Voice: (734) 913-1098 (ext. 8) > > Fax: (734) 913-2201 > > http://home.comcast.net/~goovaerts/ > > > > ________________________________ > > > > From: [EMAIL PROTECTED] on behalf of Oriol Falivene > > Sent: Sat 7/15/2006 10:07 AM > > To: [email protected] > > Subject: [Fwd: Re: AI-GEOSTATS: Re: generalize kriging variance > > toaverage-basedestimators different than] > > > > Hi Dr Goovaerts, > > > > > It is not clear what you want to do with the kriging variance you > > > obtain... > > > Probably you want to quantify the degree of reliability of the allocation > > > of a particular location to a given facies. This could be measured by the > > > variance > > > or entropy of the distribution of probabilities of occurrence of facies > > > at that > > > location, see my book page 354. This probability distribution is easily > > > computed > > > by indicator kriging or you can use truncated Gaussian simulation if > > > there is > > > any physical ordering of your facies. > > > > I'm trying to get a measure of the smoothing effect related to a > > particular algorithm (truncated kriging, truncated inverse square > > distance, indicator kriging,...) and a particular algorithm set up > > (searching conditions or number of neighbours used to obtain each facies > > estimate), applied to interpolate facies distribution in a dense coal > > mine dataset. > > > > A good measure would be the variance of the estimated property, but > > since I am working with a categorical property (i.e. facies), it is not > > direct to get this variance (one must assume a certain facies ordering > > and attribute values to facies, and I'm not sure which would be the > > effect of this assumptions int the variance of measures). And therefore > > I was looking for other options like kriging estimation variance. > > > > > > > > For your last question, look at Journel and Huijbregts "Mining > > > Geostatistics" > > > page 451 for the "smoothing relations" that link the average kriging > > > variance to the > > > variance of observations and the variance of kriging estimates. > > > > thank you, I will take a look to this. > > > > Oriol > > + > > + To post a message to the list, send it to [email protected] > > + To unsubscribe, send email to majordomo@ jrc.it with no subject and > > "unsubscribe ai-geostats" in the message body. DO NOT SEND > > Subscribe/Unsubscribe requests to the list > > + As a general service to list users, please remember to post a summary of > > any useful responses to your questions. > > + Support to the forum can be found at http://www.ai-geostats.org/ > > > > ------------------------------------------------------------------------ > > Name: winmail.dat > > winmail.dat Type: Surfer Worksheet > > (application/x-unknown-content-type-Surfer.Worksheet) > > Encoding: base64 > > > > ------------------------------------------------------------------------ > > No virus found in this incoming message. > > Checked by AVG Free Edition. > > Version: 7.1.394 / Virus Database: 268.10.1/389 - Release Date: 14/07/2006 > > -- > > ______________________________________ > > Oriol Falivene > [EMAIL PROTECTED] > http://www.ub.es/ggac > > tel. (+34) 93 4034028 > fax (+34) 93 4021340 > > Fac. de Geologia, > Univ. de Barcelona > > -- > No virus found in this incoming message. > Checked by AVG Free Edition. > Version: 7.1.394 / Virus Database: 268.10.1/389 - Release Date: 14/07/2006 -- ______________________________________ Oriol Falivene [EMAIL PROTECTED] http://www.ub.es/ggac tel. (+34) 93 4034028 fax (+34) 93 4021340 Fac. de Geologia, Univ. de Barcelona + + To post a message to the list, send it to [email protected] + To unsubscribe, send email to majordomo@ jrc.it with no subject and "unsubscribe ai-geostats" in the message body. DO NOT SEND Subscribe/Unsubscribe requests to the list + As a general service to list users, please remember to post a summary of any useful responses to your questions. + Support to the forum can be found at http://www.ai-geostats.org/
