08 aed explicación

7/21/2019 08 AED Explicacin

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Prof. Orestes GmGeologist Sen

oregomez4 elefono! "#

ANLISIS EXPLORATORIO


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Copyright 2013 - CAE MiningChil S!A!

CONTENIDO)*+! ) -loratory *ata +nalysis )*+! ) -loratory *ata +nalysisContent Content

Geology mo el )*+ / +--lications 0ot )*+, 1ut a 2uic or 5n erstan ing6Chec ing * Pur-ose of )*+ Ma-s! 7ocation, tren s, ...

Sam-le statistics! S-acing, 5sual Gra-hs Chec ing -airs of 8alues

Piechart Chec ing t in holes, gra e :istogram, -ro1a1ility

-lot ;m-ortant for )stimation6Si

elati8e i?erence -lot Chec ing geological 1oun)*+ )n8elo-e >eference to Geological Proces ;m-ortant conce-t GP 4.' Create Geology M

GP #.3 Choose )stimationParameters


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+ goo geology mo el is most im-ortant.Only the geology that tells something a1out themineralization is useful.+ geology mo el consists of se8eral geology o

omain has its o n statistical characteristics thae-en on location Ahomogeneity stationa


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5seful statistics to chec i?erences 1et een o

Multi-le 1o -lots, histograms Multi-le cumulati8e istri1ution ariograms A i?erent irectionsB


"EOLO"# MODEL


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"EOLO"# MODEL& "EOLO"ICAL P


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"EOLO"# MODEL)*+ )*+! Geological Proc

Pur-ose Geological Process #.3 Cmetho an Parameters

*ata familiarization #.3.& Sam-le Com-ositing*etecting -ossi1le errors #.3.3 ) -loratory *ata +naly; entifying6con9rming i?erentmineralizations

#.3.4 Choice of )stimatio

+ns ering 2uestions such as! #.3.# Cutting an 6or ;n icaOr inary or ;n icator Eriging #.3.F +ssess econciliation


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EDA& "EOLO"ICAL PROCESS


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EDA "RAP*S PIEC*ARTS


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EDA "RAP*S *ISTO"RAMS


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EDA "RAP*S M,LTIPLE PRO A ILPLOTS DI..ERENT MINERALI/ATIO


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EDA "RAP*S OXPLOT+ gra-h summarizing a istri1statistics

Multi-le 1o -lots can 1e is-lsame -ageGreat is-layJ0um1er of

ata4K#% &K'#' &'%'& (

Mean 4.F$$ (.&&4 '.F#' $.

St . *e8. &(.%#F $.3(3 3.F&3 3$

Coef. of ar. 4.$'$ #.(## 4.%#% #.Ma imum $K' 3F' 3%K5--er2uartile

&.% '.% '.#

Me ian ( '.&3 '.((7o er2uartile

'.3 '.( '.( '.


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EDA "RAP*S SCATTER"RAM


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5seful to com-are & -o-ulations, say + an


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5seful to in8estigate con itional 1ias 1et een t o-o-ulations, say + an


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+n )*+ en8elo-e is a 3* en8elo-e ithin hich statiscom-ute .

5na en8ol8ente )*+ es una en8ol8ente 3* en el 2ue se caesta Qsticas.

Ihich statistics*eclustere mean, 8ariance.Choice of trimming 8alues.

Choice of in icator cut/o? gra es.ariogram.

>esource 1loc mo el 8ali ation.


EDA EN6ELOPE 18$4


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Ihy an )*+ en8elo-e o restrict statistics to here it matters . >estringir la esim-ortante Rairly tight aroun sam-le locations.


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Cmo e9nir la en8ol8ente )*+0o sea emasia o -reciso.


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EDA EN6ELOPE 38$4


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+lgunas o1ser8aciones!U 7a en8ol8ente )*+ se utiliza -ara calcular los esta QgrU o os los atos entro y fuera e la en8ol8ente se -ue

la eta-a e estimacin.U 0o -ue e ha1er estimaciones fuera e la en8ol8ente )*U + ems e la en8ol8ente tiene 2ue ser consi era o un

geologQa.


EDA EN6ELOPE $8$4


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EDA MAPS& LOCATION MAPS


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EDA MAPS& LOCATIN" ANOMAL


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EDA MAPS& C*EC9IN" TRENDS


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EDA MAPS& PROPORTIONAL E..E


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o S-acing 1et een closest sam-les from &i?erent holes


EDA& SAMPLE SPACIN"S "RAD

Do: in A; Min M < M> & (#,F ',3$ K#,% (> 3 ((,3 ','F $4,$ %,> # (',3 ','( F3,% K,


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o 0um1er of assays a1o8e cut/o?gra es


EDA& SAMPLE SPACIN"S "RAD

1 % : A? Co:po7it 7 - In EDA - Do: in 02 N?:@ r o

Int r; l7 A@o; "r = C?t-OB


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EDA& C*EC9IN" PAIRS O. 6AL,ES

Com-le+naly sis


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EDA& C*EC9IN" T IN *OLES


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EDA& "RADE PRO.ILES:p ri7on o A? Ag C? /n C n= S or DD*1'1


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Su--ort size A-oint, & m sam-le, 1loc , etc.B is im-or*i?erent su--ort sizes V in i?erent 8aria1ilities.


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COMPOSITIN" 183


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Com-ositing may 1e re2uire if!Sam-le lengths are much i?erent! a8erage length of (.#'cm long sam-les centere on high gra e 8eins.


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Com-osite length shoul 1e such that!)nough 8aria1ility is retaine hen estimating.0o geological 1oun ary crossing.*o not e cee 1loc size!# m 1enches! &63 m com-osites OEX # m is ma imum

;f -ossi1le, com-osite only hat is nee e , i.e. lea8e untoucom-osites if in s-eci9e Min6Ma limits.


COMPOSITIN" 283


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;m-act of com-ositing!7ose original sam-lesXGra e 8aria1ility re uce X0um1er of sam-les re uce XGeological contacts can 1e smeare out.

;f an original sam-le length is 8ery long, com-ositing ill many regular smaller lengths.

OE if the original gra e is 8ery lo .

Pro1lem if original gra e is 8ery high, 1ecause the lochigh gra e is un no n.


COMPOSITIN" 383


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5seful chec ! is-lay rill holes ith the com-osite graon one si e an the original gra e histogram on the otherGeological Process #.3.& Sam-le Com-ositing


COMPOSITIN" 383


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)l agru-amiento e muestras son comunes en lain ustria minera.


DESA"R,PAMIENTO& INTROD,CC

Pro1lema -otencial!7os agru-amientos encuentran en las zgra o. Su im-acto -so1reestimacin grame ia y la 8aria1iltienen en cuenta.

Solucin!*esagru-ar.)l o1Teti8o es re ucca a ato agru-a-ro-orcin a la


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Cel a e asagru-amientoSu-er-oner una reTilla e cel as en los atosX

)l tamaYo e las cel as -ue e ser ms o menos la istre e muestreo,. 7a i ea es lograr 8alores me ios e -or cel a, on e hay agru-amiento. 7a cel a -ue e ser


DECL,STERIN"& MET*ODS


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*esagru-amiento -olygonal)n &*, los -esos esagru-a os son -ro-orcionales a los

e inZuencia e los atos corres-on ientes.)n 3*, el mismo -rinci-io se a-lica con carcter e 1anc


DESA"R,PAMIENTO& M TODOS

DESA"R PAMIENTO& M TODOS


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9rig F)l ErigeaTe es una e elente herramienta esagru-a ora A8er5na reTilla e cel as regular es su-erim-uesta so1re los atosla cel a no im-orta mucho.

7as cel as son rigea as usan o las muestras. 7os -esos e usa as en el rigeaTe -ue en ser guar a os en memoria.)l -eso esagru-a o e una muestra a a es la suma e los -corres-on ientes el rigeaTe, guar a os en memoria.

Mo= lo 6 Gino MH7 C rG no7os atos son usa os -ara estimar un mo elo e cel as61lo2

atos mas cercanos son usa os -ara estimar ca a 1lo2ue.7a istri1ucin resultante es la istri1ucin e los 1lo2ues es7a forma e la istri1ucin resultante es muy similar a la for

istri1ucin el -oligono esagru-a o.entaTas! Pue e usarse con iferentes soft are -or eTem-lo ulcan, etc.Copyright 2013 - CAE Mining

Chil S!A!


DECL STERIN"& MET*ODS


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*esagru-amiento automtico ecel as


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0ota (!+lgunos -esos e esagru-amiento -ue en ser muy altos

)l rea el -oligono es muy gran e Aso1re la franTaB7ocalizaciones es-ecilas e muestras Ainicio6y 9n el

7a solucin consiste en!;ntro ucir un 8alor alto cuan o esagru-amos*esagru-ar entro e una en8ol8ente e +)*





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0ota &!7a esagru-ac8in -oligonal es incom-leta e1i o al un ra

e esagru-amiento en los -oligonos -e2ueYos.7a solucin consiste en!

Ma-as e che2ueo e reas a esagru-ar.;ncremetar los ra ios e asagru-amiento y usar en8ol+)* -ara controlar las franTasChe2ueo e los -esos e asagru-amiento y e8entualmre ucirlos.





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isualizaciones [tiles:istogramas e los -esosMa-as e los 8alores e los -esosMa-as e las reas esagru-a as

Geological Process #.3.3 ) -loratory *ata +nalysis7et 0 +5 8alues \zA iB,i ] l,...,0^ an \ i,i ] (,...,0^ rescale

eights such



DECL STERIN"& STATISTICS


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7et 0 +5 8alues \zA iB,i ] l,...,0^ an \ i,i ] (,...,0^ rescaleeights such


DECL,STERIN"& STATISTICS

ariance!Means!

DECL STERIN"& STATISTICS


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ariance!Stan ar e8iation! Me ian! the 8alue z 50 such thaeclus tere eights of the 8alues less than z 50 is

0ote! if -airs of 8alues are a8aila1le, the co8ariance AsstatisticsB can also 1e eclustere .


DECL,STERIN"& STATISTICS

DECL STERIN"& EXAMPLE 1834


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DECL,STERIN"& EXAMPLE 1834

ery fe e cessi8e eights. Eee- as is, or trto 4'.



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DECL,STERIN & EXAMPLE 2834

/(4 _ change in gra



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DECL,STERIN & EXAMPLE 3834

;ncom-lete 0orthern -ortan in elongaSI.

DECL STERIN"& EXERCISE )


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7et the follo ing sam-ling situation!


DECL,STERIN & EXERCISE )

Ihat oul 1e a reasona1leeclustering size

TRIMMIN" 8 C TTIN" O TLIERS 1


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TRIMMIN 8 C,TTIN O,TLIERS 1` Ihen com-uting statistics ithin a geological

omain, e ma e the assum-tion that there is only one

-o-ula/ tion an that all sam-les 1elong to that -o-ulation.

` Outliers or e treme 8alues are often o1ser8e .

heir im-act can 1e a serious o8erestimation of! / the a8erage gra e an its 8aria1ilityX / the mean, 8ariance, 8ariogram, 1loc mo el esti/ mates, etc.

` 0ote that the outliers im-act all estimates, e8enthe

tra itional ones such as -olygonal an l6 &.` arious solutions!

/ Outliers are erroneous! elete or correct themX / Outliers are from i?erent -o-ulation !

/ e9ne ne geology omainX / trim them o n -rior to com-utingstatisticsX

/ restrict their inZuence uring estimationAl6 &

or rigingBX / use in icator riging.

` Geological Process #.3.# Cutting an 6or ;n icator Classes .

` he main 2uestions are!/ ;s trimming6cutting a/ ;f yes, hich 8alueAsB

` he ans ers are su1Tecti8e` he follo ing gra-hs might

/ *ecile analysis./ +ctual 8ersus smootheholes./ :istogram an cumulat/ ;n icator correlation -l/ Coe cient of 8ariation/ =uantity of metal -lot.

` +lso useful!/ 0um1er of trimme 6cu

TRIMMIN" 8 C TTIN" O TLIERS 3


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Gra e -ro9les along holesOutliers stan out ith res-ect to

smoothe gra e -ro9le.


TRIMMIN 8 C,TTIN O,TLIERS 3

Similar ta--lie in

&*! contoresi u3*! s3* esresi u

+ 8antagoutliers.

TRIMMIN" 8 C TTIN" O TLIERS $


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Gra e -ro9les along holesOutliers stan out ith res-ect to

smoothe gra e -ro9le.


TRIMMIN 8 C,TTIN O,TLIERS $

+ -ossi1le trimminghere the his togra

1e isolate on the hoPossi1le trimming 8K' g6t.

TRIMMIN" 8 C TTIN" O TLIERS %


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Cumulati8e AlogB-ro1a1ility-lots.


TRIMMIN 8 C,TTIN O,TLIERS %

+ single -o-ulation re-resente on the -loincreasing line.;f the -o-ulation is Alcur8e is a straight linAlogB-ro1a1ility -a-eof secon ary im-orta+ in or a 1reain icate t o -o-ulatiooutliers.

TRIMMIN" 8 C TTIN" O TLIERS '


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TRIMMIN 8 C,TTIN O,TLIERS + -ossi1le trimming6aroun the in 61rea-o-ulation AoutliersB gPossi1le trimming 8alug6t.

*ecile +nalysis;ntro uce 1y )ng., +-r. %F.See ne t -age fthum14'6(' rule to 1e

ecile 6 -ercentifull com-lemen

TRIMMIN" 8 C TTIN" O TLIERS (


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TRIMMIN 8 C,TTIN O,TLIERS (*ecile +nalysis ACont .B

;f o- ecile contains!More than 4'_ of metal, orMore than t ice the metal of -re8ious ecile

S-lit it in (' -ercentiles;f to- -ercentile contains!More than ('_ of metal

rimming is arranteSuggeste trimming 8alue is then!

:ighest 8alue of -re8ious -ercentileGenerally conser8ati8ePossi1le trimming 8alue from gra-h

0ote that last ecile 6 -ercentile not full . rimming may 1e arrante .Pre8ious -ercentiles 3 8alues! $(, ('%, ((' g6tPossi1le trimming 8alue! ('' g6t

TRIMMIN" 8 C TTIN" O TLIERS )


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;n icator correlation-lot.


TRIMMIN 8 C,TTIN O,TLIERS ) his -lot sho s tcoe cient of t o a Tasam-le in icators for inc

;n icator! i c (x) =

here z c is the cut/o? threshol B.

+s the cut/o? z c increcorrelation ecreases.+ -ossi1le trimming6cu

hen the correla tion close to '.

TRIMMIN" 8 C TTIN" O TLIERS +


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Coe cient of 8ariation-lot.


TRIMMIN 8 C,TTIN O,TLIERS +

his -lot sho s the coe cienthe gra es 1elo cut/o? Acut+s cut/o? increases, coe ciincreases.+ -ossi1le trimming6cuttingcoe cient of 8ariation cucontrol.Possi1le trimming 8alue from

TRIMMIN" 8 C,TTIN" O,TLIERS 1


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=uantity of metal-lot.



his -lot sho s the relati8emetal containe ithin theo n sam-les for 8arious t8alues.5seful to no the 2uantit

iscar e 1y trimming%3 _ of metal corres-on i

trimming 8alue.]d F _ of metal loss if lag6t +u sam-les are trimmeg6t.



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rimming6Cutting Summary a1le



:istogram

Pro1a1ility Plot

*ecile +nalysis (

;n icator Correlation

Coe cient of ariation ('

Rinal Choice

0um1er of *ata rimme 4 oMetal 7oss

*ARD 8 SO.T "EOLO"ICAL O,ND


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M5SS)7I:; ) / Com-arison of Consecuti8e *o n:ole +ssays


8 SO. O O C O,

*ARD 8 SO.T "EOLO"ICAL O,ND


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Not &mineralizaticontact.Geological

+ssess


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08 aed explicación

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