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G EOP HYSI CS, VOL . 62, NO. 5 (SEPTEMB ER -OCTOB ER 1997); P. 1419–1431, 15 FIG S.

Inversion of geophysical data over a coppergold porphyry deposit: A case historyfor Mt. Milligan

Douglas W. Oldenburg∗, Yaoguo Li∗, and Robert G. Ellis∗

ABSTRACT

In thispaper,we invert magnetic,D C resistivity, induc-ed polarization (IP), and airborne electromagnetic (EM)

data from the Mt. Milligan copper-gold porphyry de-

posit and jointly interpret the inversion results with

available geological and mineralization data. The

inversions are carried out over an area that encloses

a n int rusive st ock, know n a s t he M B X St ock, a nd

the resulting mineralization zone surrounding it. The

earth model is discretized into a large number of cells

having constant physical properties, and d istributions of

magnetic susceptibility, conductivity, and chargeability

are obtained by minimizing a model objective function

subject to adequately fitting the corresponding data. A

3-D magnetic susceptibility model is obt ained d irectly

by inverting surfa ce t ot a l field a noma ly da t a . 3-Dconductivity and chargeability models are formed by

compositing 2-D sections recovered by inverting D C/IP

pole-dipole data. The airborne EM data are inverted

w ith a 1-D a lgorit hm a nd composited int o a 3-Dconductivity model. The physical property models are

compared with a rock model constructed from geologic

information from 600 drill holesa nd with a 3-D model of

gold concentration. The physical property models have

features that correlate with various geologic boundaries

and rock units. More notably, the recovered chargeabil-

ity and susceptibility seem to reflect the distribution

of mineralization: chargeability highs coincide with the

greatest gold concentration, w hile the susceptibility

displays an anticorrelation with it.

Overall, our inversion results are consistent with the

geology and mineralization models for the Cu-Au por-

phyry deposit, while the anticorrelation between gold

concentration and susceptibility provides an importantconstraint that helps define the distribution and geo-

chemical control of the orebody.

THE MT. MILLIGAN DEPOSIT

Mt. Milligan is a Cu-Au porphyry deposit situated in north

central British Columbia. The deposit lies within the Early

Mesozoic Q uesnel Terrane tha t hosts a number of Cu-Au

porphyry deposits and it occurs within porphyritic monzonite

stocks and ad jacent volcanic rocks of the Takla group. Exten-

sive knowledge about the geology and mineralization has been

achieved through a major drilling program. The initial deposit

model consists of a vertical monzonitic stock intruding into avolcanic host.D ykesextend out from the stock and cut through

the porous trachytic units in the host. The original structure

and mineralization essentially displayed a symmetry a bout the

vertical axis but subsequent geologic activity has caused the

system to rotate 45◦ eastward and the whole system is further

complicated by faulting and erosion.

Ma nuscript received by the E dito r D ecember 11, 1995; revised ma nuscript received D ecember 23, 1996.∗U B C—G eophysical Inversion Facility, D ept. of E arth a nd Ocean Sciences, U niversity of B ritish C olumbia, 129–2219Main M all, Vancouver, BritishCo lumbia, Ca nada V6T1Z4. E -mail add resses: [email protected] a nd [email protected] 1997 Society of Exploration G eophysicists. All rights reserved.

Emplacement of a monzonite intrusivestock isa ccompanied

by intensive hydrothermal a lteration primarily in the region

near the bound aries of the stock and in and around the porous

trachytic units. A general model for porphyry systems, taken

from McMillan (1991) a nd reprod uced in Figure 1, shows that

both potassic and propylitic alteration can be expected. Potas-

sic alteration, which produces chalcopyrite, bornite and mag-

netite, occurs in a region surrounding the initial stock and its

intensity decreases away from the boundary. The initial stock

containsaccessory magnetite and a lterationproductsa nd thesewould b e expected both in the host and in the intrusive. Pro py-

litic a lteration, w hich produces pyrite and minor amounts of

magnetite, existso utward s from the potassic altera tion zone. It

is expected that the pyrite content increases markedly as one

proceeds from a potassic to a propylitica lteration zone.For the

MB X d eposit at Mt. Milligan the simple conceptual pattern of

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1420 Oldenburg et al.

potassic alteration occurring close to the stock and in the tra-

chytic units, and propylitic alterat ion occurring in a broa d ha lo

surrounding the potassic alteratio n is complicated by the real-

ity that there were a number of altera tion events with different

locations, intensities, and time scales. It is also likely that there

was overprinting of propylitic alteration in regions that had

already undergone potassic alteration and vice versa.

The individual rock units and a lteration products have phys-

ical properties that can be detected with geophysical surveys.

Magnetite content w ill alter the ma gnetic susceptibility; pyrite,

chalcopyrite, and bornite affect chargeability; and significant

mineralization and fluid filled fractures will alter the electrical

conductivity. G eophysicalsurveyshave the potential to provide

quantitative information about the distribution of these phys-

ical properties, and magnetic, D C resistivity, IP, and a irborne

EM data have been collected at Mt. Milligan. In this study we

concentrate on a 1.2 km × 1.0 km a rea over the top of the

MB X E ast deposit. We begin with a general description of our

inversion methodo logy and t hen proceed with the inversion of

magnetic, D C resistivity, IP, airborne E M da ta. The recovered

physical property models are then compared with the rock and

Au mineralization models found by direct sampling. Compar-

isons suggest an unexpected correlation between abundances

of magnetite, pyrite, and gold. This issue is discussed and we

also use this hypothesis to carry o ut coopera tive inversions of

the magnetic and IP da ta.

INVERSION METHODOLOGY

Individual geophysical data sets at Mt . Milligan are inverted

by using standard approaches in inverse theory. The earth is

FIG. 1. Mineralization system associated with a typical Cu-Au Porphyry system extracted fro m McMillan (1991).D iagram (a) indicates the metallic mineral distribution. The solid line in the middle represents the initial stock.The areas of potassic and propylitic alteration are shown in (b).

divided into rectangular cells having constant physical proper-

ties. The number of cells generally greatly exceeds the num-

ber of data, and in general, there are many distributions of

the physical property which, when forward modeled, produce

predicted responses that a re in adeq uate a greement with the

observations. To confront this nonuniquess the inverse prob-

lem is formulated so as to minimize an objective function of

the model subject to adequately fitting the data. To some de-

gree, the output of the inversion algorithm depends upon the

choice of objective function and an important aspect of our in-

versions involves decisions regard ing which objective function

should be minimized for each problem. G enerally we choose

to find minimum structure models since these are more eas-

ily interpreted, but the generalized objective function used

here allows flexibility to generate a variety of models and

also to incorporate a dditional information into the inversion

process.

The magneticda ta have been inverted using a 3-D algorithm,

the D C resistivity and IP dat a have been inverted using a 2-D

algorithm, and the airborne EM data have been inverted us-

ing a 1-D algorithm. The method adopted for solving individ-

ual inverse problems depends upon the size of the matrix to

be inverted and the amount of computational effort req uired

to form individual sensitivities. For 1-D problems, the matrix

equations can be solved with direct methods, while for 2-D

problems and for the 3-D magnetic problem we have used a

generalized subspace method . Nevertheless all inversions can

be cast into the following methodology.

Let the data be denoted generically by the symbol d a nd

the model by m. To carry out fo rward modeling to generate

theoretical responses, and also to attack the inverse problem,

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A Case History for Mt. Milligan 1421

we d ivide our model domain into M rectangular cells and as-

sume that the physical property is constant within each cell.

Our inverse problem is solved by finding the vector m =

{m1,m2, . . . ,m M } which adequately reproduces the observa-

tions d0 = (d 01, d 02, . . . , d 0 N ).

The inverse problem is posed as a standard optimization

problem:

minimize ψm(m, m0) = W̃m(m− m0)2

subject t o ψd (d, d0) = ˜Wd (d− d0)

2 = ψ ∗d .

(1)

In equation (1) m0 is a ba se model and˜

Wm is a general weight-

ing matrix that is designed so that a model with specifi c charac-

teristics is produced. The minimization of the mo del o bjective

function ψm yields a modelthat isclose to m0 withthemetricde-

fined by˜

Wm and so the characteristics of the recovered model

are controlled directly by these two quantities. The choice of

ψm is crucial to the solution of the inverse problem but we defer

the details until later.˜

Wd is a da tum weighting matrix. We shall

assume that the noise contaminating the j th observation is an

uncorrelated G aussian rando m variable having zero mean and

standard deviation j . As such, an appropriate form for the N × N matrix is

˜Wd = diag {1/1, . . . , 1/ N }. With this choice,

ψd is the random variable distributed as chi-squared with N

degrees of freedo m. Its expected value is approximately eq ual

to N and accordingly, ψ ∗d , the target misfit for the inversion,

should be a bout this value. The a ppropriate objective function

to be minimized is

ψ(m) = ψm(m, m0) + µ

ψd (d, d0) − ψ∗d

, (2)

where µ is a La grange multiplier.

B ecause of nonuniqueness the character of the final model is

heavily influenced by the model objective function. Our choice

fo r ψm is guided by the fact that w e often wish to find a model

that has minimum structure in the vertical and horizontal di-rections and at the same time is close to a base model m0. This

model, because it is “ simple” in some respect, may b e rep-

resentative of the major ea rth structure. O ther earth models

however, might be closer to reality and it is necessary that the

objective function have the capability to produce a variety of

models and be flexible enough to incorporate additional infor-

mation that the interpreter has about the model. An objective

function that can a ccomplish these goals is

ψm(m, m0) = αs

vol

ws(m−m0)2 d v+

vol

α xw x

∂(m − m0)

∂ x

2+α yw y

∂(m − m0)

∂ y

2+α zw z

∂(m − m0)

∂ z

2d v. (3)

In equation (3) the functions ws, w x , w y, w z are specified by

the user, the constant αs controls the importance of closeness

of the constructed model to the base model m0, and α x , α y, α zcontrol the roughness of the model in the horizontal and ver-

tical directions. The discrete form of eq uation (3) is

ψm = (m− m0)T

αs˜WT s

˜Ws + α x

˜WT x

˜W x

+ α y˜

WT y˜

W y + α z˜WT z

˜W z

(m− m0)

≡ (m− m0)T

˜WT m

˜Wm(m− m0) (4)

and this defines the matrix˜

Wm in equation (1). The base

model can be omitted from a ny of the terms in equation (3) if

desired.

INVERSION OF MAGNETIC DATA

In a ground based magnetic survey at Mt.Milligan, total field

data were collected at 12.5 m intervals along east-west lines

spaced 50 m apart. A regional fi eld, derived from da ta ta kenover a larger area , was removed from the observations and the

reduced data were then down-sampled to a 25 m interval to

form the fina l set of 1029 observations. The da ta were upwa rd

continued to a height of 20 m in accordance with our practice

of inverting magnetic data at a height that is about equal to

a cell dimension. These data are shown in Figure 2. Each da-

tum is assigned a standard error of 5% plus 10 nT. To invert

these data, we first discretize the 1.2 km by 1.0 km by 450 m

model domain into cells havingconstant, but unknown, suscep-

tibilities. Cell w idths are 25 m in the horizonta l directions and

thickness varies fro m 12.5 to 25 m. Surrounding this core re-

gion, the model is extended laterally outward by two large cells

so that the resultant mo del consists of 43 428 cells. Topography

that varies by about 100 m over the a rea w as included in themodeling.

The magnetic fi eld at Mt. Milligan is H 0 = 58193 nT, I = 75◦

a nd D = 25.7◦. We assume that there is no remanent magne-

tization contributing to the observations and that demagne-

tization effects are negligible. Consequently, the relationship

between the tota l field anomaly da ta a nd the susceptibility is

given by

˜Gκ = d, (5)

where the matrix˜G has elements G i j which quantify the

contribution to the i th datum due to a unit susceptibility

in the j th cell. The model objective function is that given

in equation (3) with the exception that an additional depth

weighting function, ba sed upon the natural decay of theelements of˜G, is applied to each component. This is a crucial

aspect of the objective function since it causes the recovered

susceptibilities to be distributed with depth whereas without

it, the susceptibilities tend to be b iased tow ard the surface. To

invoke the inverse methodology we set m = κ , m0 = 0, and

(αs, α x , α y, α z) = (.0005, 1., 1., 1, ). The resultant system of

equa tions is solved using a subspace technique with a require-

ment that the susceptibility remain positive. Further details

and discussion regarding t he magnetic inversion algorithm are

given in L i and Oldenb urg (1996).

Figure 3 displays one plan view and three vertical cross-

sections of the recovered susceptibility. From the plan section,

two concentrated susceptibility highs a re observed in the

central region. Surrounding them are three linear anomalies

trending northea st. In the cross-sections, the ma jor anoma lies

are seen at moderate depth but considerable variation in the

depth to the top is evident. There are also smaller anomalies

extending to the surface. In general, the models show more

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detailed structure near the surface and become smoother at

depth.

INVERSION OF DC RESISTIVITY DATA

The pole-dipole D C resistivity a nd IP surveys over Mt. Milli-

gan w ere carried out alo ng east-west lines spaced 100m apart.

The dipole length was 50 m and data for n = 1 to 4 were col-

lected. This yields a t otal o f 86 dat a fo r each line.The governing eq uation for t he dc resistivity potent ials is

∇ · (σ ∇ φ) = − I δ(r − r s), (6)

where σ is the electrical conductivity and r s denotes the lo-

cation of the current electrode. To invert the D C data, we

adopt a 2-D assumption a nd invert data from each line sep-

arately. E quation (6) is a nonlinear relationship between the

observed potentials and the conductivity and hence a n itera-

tive techniq ue is used. We use the subspace technique out lined

in Oldenburg et al. (1993). The model objective function is

that given in equation (3) with neglect of the y-variable and

volumetric integrals replaced by areal integrals over x a nd z.

Since conductivity varies over ord ers of magnitude and is also

positive we choose m = nσ as the variable in the inversion.The refe rence mo del is a unifo rm ha lf-space o f 1.67 mS/m and

(αs, α x , α z) = (.0002, 1.0, 1.0). The model is discretized into

1600 cells with cells in the central region of the section ha ving

a w idth of 25 m and a t hickness of 10 m.

FIG. 2. The magnetic data to be inverted are shown in the toppanel. The predicted responses from the inverted model areshown belo w. The gre y scale is in nT.

There are 86 observations for each survey line and ea ch da-

tum is assumed to have a standard error of 5%. An exam-

ple of the data, shown as an apparent conductivity pseudo-

section, is given in Figure 4. D epth informat ion is difficult to

infer from this plot, and lineations are caused principally by the

pole-dipole nat ure of dat a collection. The inverted cond uctiv-

ity model, shown in that figure, has a central resistive zone

with high conductivitieso n both sides. Co nductive features are

limited to depths of a bout 100 m. Features below this do not

significantly affect the data and the conductivity approaches

that of the base model. This limited depth of investigation of

about 100 m is in accordance with the fact that the maximum

distance between the current electrode and potentia l electrode

is 250 m. The predicted d ata are shown in Figure 4 and agree

well w ith the observations. Eleven east-west lines spaced at

100 m intervals were inverted and the resulting models were

combined to form a composite 3-D model. One plan view and

three cross-sections a re shown in Figure 5. The individual in-

versions did not include topography effects but for display pur-

poses the resultant conductivity sections have been vertically

FIG. 3. A plan view o f the inverted ma gnetic susceptibility ata depth of z = 80 m is shown at the top. Three east-westcross-sections at x = 9400, 9500, and 9600 m are given below.The grey scale is magnetic susceptibility in SI units.

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adjusted by the local topography. This is a valid methodology

since topo graphy is minor a nd limited t o gentle slopes.

INVERSION OF IP DATA

IP data were collected simultaneously with the DC resis-

tivity data. The secondary potentials have been converted to

apparent chargeab ilitiesa nd an example pseudosection for the

9600N line is shown in Figure 6. Each datum is assigned a con-stant standard deviation that isabout 5%of theaverageof allIP

dat a. Inversion of IP d ata is a tw o-step process. In the first step,

D C resistivity data are inverted to generate a ba ckground con-

ductivity. B y making the assumption tha t the chargea bilities,

represented b y the symbol η , are small then the relationship

between the apparent and intrinsic chargeabilities is given by

ηa =˜ J η. (7)

In equation (7) J i j is i j th element of the sensitivity matrix for

the D C resistivity problem. That is, J i j = −∂nφi [σ ]/∂nσ j

where σ is the conductivity mod el obtained f rom the dc inver-

sion. The second step of the IP inversion solves a linear inverse

problem using equat ion (7) as the constra ints.

The cell discretization and model o bjective function for the

IP inversion are identical to t hose used in the D C resistivity in-

version. Ho wever, the background mod el is set to zero and the

model parameter chosen for the inversion is m = η . Po sitivity

FIG. 4. The a pparent conductivity data for n = 1 , 4 for apole-dipole survey at 9600N a re shown at the to p. The recov-ered conductivity ob tained from the 2-D inversion is shownin the middle panel and the predicted data are given at thebot tom . The grey sca le deno tes conduct ivities in mS/m.

on chargeability is invoked using the subspace technique and

deta ils regarding the inversion can be fo und in Oldenburg and

Li (1994).

The recovered chargeability model at line 9600N is shown

in Figure 6. There is a strong chargeab le zone at depth tow ard

the east and another chargeable zone near the surface to the

west. The predicted da ta shown in that fi gure agree well with

the observations. D epth limitations for the I P structure are the

same as those for DC resistivity and hence chargeab le features

are seen only to about 100 m depth. Inversions for the eleven

lines were carried out a nd composited to form a 3-D model.

One plan view a nd three cross-sections are shown in Figure 7.

INVERSION OF AIRBORNE EM DATA

A D IG HE M airborne EM survey wa s flown in north-south

lines 100 m a part. I n-phase and phase da ta at frequencies 900,

7200, 56 000 Hz were taken about every 10 meters along the

flight line.The six data a t each sourcelocation were inverted us-

ing a 1-D inversion algorithm to produce a conductivity depth

distribution.In performing thisoperation theearth was divided

into 14 layers and the model o bjective function wa s that given

in equation (3) but now relegated to 1-D so α x = α y = 0.

FIG. 5. A plan view of the electrical conductivity at z = 90 mobtained from inverting dc resistivity data is shown at the top.Three east-west cross-sections at x = 9400, 9500, and 9600 mare given below. The grey scale denotes conductivities in mS/m.

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The model parameter for inversion was m = log σ , the ref-

erence model corresponded to a halfspace of 3.16 mS/m a nd

(αs, α z) = (0.4, 0.6). The in-phase and qua drature dat a a t 900,

7200, 56 000 H z da ta w ere a ssigned re spective errors of 20, 25,

70, 50, 65, and 50D IG H EM units. The high ma gnetite content

in the rocks caused in-phase values to decrea se and, in certa in

locations, to become negative. In an attempt to minimize the

contaminat ing effect of ma gnetic susceptibility on the conduc-

tivity inversion, we thresholded the data so that the minimum

in-phase da tum value was 5.3 for 900 H z a nd 64 for 7200 H z.

These thresholds correspond t o in-phase values ob tained for a

half -space of 1.67 mS/m an d hence should be cha ract eristic of

the lowest va lues expected.

Rather than attempting to fit each data set to the same de-

gree, we have carried out all inversions by minimizing the same

objective function φ = φm + µφd . This is a useful procedure

when inverting many data sets in which the errors are not

known a s they are in this case since the 1-D assumption is as-

suredly violated. The reader is referred to E llisa nd Shekhtman

(1994) for more d etailed information abo ut the inversion. The

results of the 1-D inversions carried a long a line 12625 E are

shown in Figure 8. The o bserved a nd predicted da ta, shown

at the top are in relatively good agreement. The conductiv-

ity model is at the bottom. Carrying out the 1-D inversion for

the eleven north-south lines and compositing the results yields

FIG. 6. The apparent chargeability data for n = 1, 4 for apole-dipole survey at 9600N a re shown at the to p. The recov-ered chargeability obtained from the 2-D inversion is shownin the middle panel and the predicted data are given at thebotto m. The grey scale d enotes chargea bilities in percent.

a 3-D model. One plan view a nd three cross-sections of the

conductivity model a re shown in Figure 9. C omparing these

conductivities with those in the top 100 m in Figure 5 shows

reasonable agreement in the general features.

ROCK MODEL, GEOLOGIC CROSS-SECTIONS

AND GOLD MODEL

Validation of our inversions is ideally made if in-situ mea-surements of physical properties are a vailable. U nfortunat ely,

none exist at Mt. Milligan, and therefore we look for correla-

tionsw ith available geologic and mineralization data. G eologic

logsfrom 600d rill holesin the analysis region were used to con-

struct a 3-D rock model that conta ined overburden, fault loca-

tion, and five of the most common rock types including mon-

zonite, tra chytes, and lat ites. A cross-section at 9600N is shown

in Figure 10. The major elements are: (1) the monzonite stock

that is truncated o n the left by t he H arris Fault, (2) the arcuate

feature, called the R ainbow D yke, extending from the stock to

the surface on the right, and (3) trachyte dykes between the

R ainbow dyke a nd the central monzonite unit. In addition to

our rock model, we obtained a geologic cross-section at 9600N

FIG. 7. A plan view of chargeability at z = 90 m obtainedfrom inverting IP data is shown at the top. Three east-westcross-sections at x = 9400, 9500, and 9600 m are given below.The grey scale denotes cha rgeabilities in percent.

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from D eL ong et a l. (1995), and this is reprod uced in Figure 10.

In D eLong’s cross-section, the trachyte dykes are mo re clearly

visible, and t hey have ab out a 45◦ plunge that corresponds ap-

proximately to the rotation that the porphyry deposit has un-

dergone subsequent to the initial emplacement of the stock

and mineralization. The reasonable agreement b etween ma jor

features in our rock cross-section and the D eLong model pro-

vides confidence that either of these geologic descriptions can

be used in our interpretation. Subsequent d iagrams will use

both as overlays.

Also available for comparison is a 3-D Au model for the

MB X depo sit that w as composited from a ssayed va lues of drill

core. The Au grade is given in categories 1 through 4, with 4

being the highest. Figure 11 displays the Au contours in plan

view and in cross-sections.

FIG. 8. Co nductivities obta ined by carrying o ut 1-D inversion along the line 12625E. Ob served data are plottedwith assigned error bars and in-phase and quadrature predicted data are plotted in solid and dashed lines,respectively. (, , ◦) refer re spectively to 56 000, 7200, and 900 H z. The cond uctivity is given at the b ott om. Theheight of the receiver above the ground, as recorded by an altimeter, is given in the middle.

JOINT INTERPRETATION OF GEOPHYSICAL,

GEOLOGICAL,A ND MINERALIZATION DATA

Our information base consists of: (1) a rock model con-

structed from drill logs and a geologic cross-section a t 9600N;

(2) conductivity models from D C resistivity and a irborne E M

inversions; (3) chargeability from IP inversion; (4) susceptibil-

ity from ma gnetic inversion; and (5) a 3-D gold distribution. It

is expected that our inversion results may be correlated with

the rock type or they may be correlated with alteration prod-

ucts. We examine both of these possibilities.

Figure 12 displays respectively the overlay of essential ge-

ological features on the recovered conductivities, chargeabil-

ity, and susceptibility. Major fea tures such a s the H arris Fault,

MB X Stock, R ainbow D yke are identified by the labels. On the

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hypothesized hydrothermal fl uid for temperatures abo ve 350◦.

In summary,for this first stage potassic alteration,w e would ex-

pect that Cu/Au ratios would be relatively constant near 15000,

and areas with high Cu and Au grades would be associated with

high susceptibility because of an abundance of magnetite and

with moderate chargeability because of the presence of chal-

copyrite.

At theMB X E ast Zone, where ouranalysiswas carried out,it

wa s observed that the Cu/Au ratios are signifi cantly lower than

those at the MBX West Zone (see Figure 14) despite the fact

that the mod e for this assay population is also 15000 (Stanley,

1993). To acco unt for this, it wa s postula ted th at a secon d stage,

lower temperature,event occurred. At lower temperatures, Au

forms a strong bisulphide (HS −) complex, but Cu does not and

Au-only precipitation w as thought to occur via the reaction:

Au(HS)−2 + Fe

+2 → Au0 + FeS 2 + 2H + e−. (9)

This would decrease the Cu/Au ratio and increase the charge-

ability because of the added pyrite but it would not alter the

susceptibility. The low susceptibilities seen in the inversion

model, and which coincided with the region of highest gold

concentration, thus presented an enigma. Stanley’s (pers. com-munication, 1996) resolution was to hypothesis that the Au

precipitation probably occurred alone during propylitic alter-

ation (chlorite, pyrite, epidote) by the following reaction in

which magnetite is converted to pyrite:

Au(HS)−2 + Fe3O 4 → Au

0 + FeS 2 + [Fe2O 3]+ H 2O +e−.

(10)

FIG. 10. Cro ss-section at 9600N of the 3-D rock model o bta ined from d ata from 600 drill holes is shown a t thetop. The geologic section from D eLong is shown b elow.

The ferric iron produced by this reaction is taken up in epi-

dote, which has been omitted in this reaction b ecause of the

bala ncing complexity introduced by the additional elements in

epidote. Textural evidence supporting this reaction (pyrite and

epidote, with gold, replacing magnetite) has been observed in

the ad jacent 66 Zone a t M t. Milligan (D eLong, pers. comm.,

1994). This reactio n wo uld decre ase th e C u/Au rat io thr ough

the addition of Au, increase the chargeability through the ad-

dition of pyrite, and lower the susceptibility through the d e-

struction of magnetite a nd format ion of epidote. Bot h of these

geophysical predictions are in accordance with the inversion

results.

The geophysical inversion results are theref ore shown to b e

consistent with the tw o stage process of a new thermodyna mic

model for mineralization and hydrothermal alteration at Mt.

Milligan. This consistency is of mutual benefit as predictions

from one study are corroborated b y those of the other. From

our perspective it provides additiona l confid ence that the geo -

physical inversions a re producing mea ningful results.

COOPERATIVE INVERSION

An initial objective with the Mt. Milligan da ta was to carryout joint a nd/or coopera tive inversion of the various da ta sets

to a rrive at a fi nal geological model that is compatible with all

of the da ta. B y “ cooperative inversion” we mean using infor-

mation from one dat a set to affect the inversion of another da ta

set. Computat ionally, the output of a fi rst inversion is incorpo-

rated as a weighting in the objective function in equation (3)

and then the second inversion is performed. As an example

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we carry out a cooperative inversion that was stimulated by

the results in Figure 13 and the geochemical analysis in the

previoussection.In theregionof theR ainbow dykethereis rel-

atively low susceptibility a nd high chargea bility. Furthermore

the stock tends to have high susceptibility and low chargeab il-

ity. This leads to a hypothesis that there is a general a nticorre-

lation between chargeability and susceptibility. We adopt this

hypothesis. Cooperative inversions then can be carried out by

using the distribution of chargeability as a weighting when in-

verting the magnetic da ta o r using the distribution of suscepti-

bility as a weighting when inverting the IP data. We show the

latter here. The inverted magnet ic susceptibility is scaled to the

range (0, 1) and used as a w eighting function ws in equa tion (3)

in the inversion of IP dat a. The cross-section of the w eighting

function at 9600N is shown in Figure 15. The weighting func-

tion is 1.0 in the region where t he susceptibility is small, and it

increases to 10.0 at the center of the susceptibility high. This

weighting function forces the IP inversion to place chargeabil-

ity away from regions of high magnetic susceptibility if the

resulting model still adequately fits the data. We have car-

ried out the weighted inversion using an approximate 3-D IP

FIG. 11. A plan view of gold concentration at z = 90 m ob-tained from drill holes is shown at the to p. Three east-westcross-sections at x = 9400, 9500, and 9600 m a re g iven below.The grey scale denotesgold concentrationtha t hasbeen binnedinto categories 1 through 4, with 4 indicating the highest value.

inversion a lgorithm, a nd the cross-section at 9600N is shown

in Figure 15. For comparison the same cross-section obta ined

from the generic inversion without weighting is also shown. In

the weighted inversion the chargeability is moved toward the

surface and the single anoma ly in the generic inversion is split

into two parts.

CONCLUSION

The Mt. Milligan deposit area is complex both from a ge-

ologic perspective and because o f its history of alteration

episodes. Physical properties are affected by rock type and by

alteration state, and thus making inferences about either rock

type or mineralization directly from the geophysical data is

not easily done. In this paper, we have inverted four geophys-

ical data sets from Mt. M illigan to recover 3-D distributions

of physical properties. The distribution of electrical conduc-

tivity is useful in differentiating b etween t he monzonitic stock

and the host ma terial and also in delineating fa ult regions. The

combination of conductivity and susceptibility provides good

estimates for location of the intrusive stock. C hargeability is

governed primarily by amo unts of chalcopyrite and pyrite. The

most intensive gold deposition should be associated with potas-

sic alteration close to the stock and in dykes extending from

the stock. B oth pyrite and chalcopyrite are a ssociated w ith this

potassic alteration. However, pyrite concentration might be

expected to increase away from the stock as one enters re-

gions of propylitic alteration. The greatest chargeability may

therefore be expected to lie somewhat outbo ard of the primary

mineralization. We note that even drilling the chargeability

high along the line 9600N w ould have found the major gold

region in the R ainbow D yke area. Ad ditionally, the geophys-

ical inversion results in the MBX East Zone support a recent

thermodyna mic model for Cu-Au porphyry deposits in which a

second stage low tempera ture event deposited Au in a reaction

that consumed magnetite. Combining all of the above informa-

tion leads to a model in which the location of largest Au con-

centration should be associated with relatively low magnetic

susceptibility a nd tha t the highest Au concentration should lie

inboard from the chargeability high. A drill hole, spotted on

the basiso f thisjoint interpretation of the geophysical and geo-

logical data , would have penetrated the area of the highest gold

concentration.

ACKNOWLEDGMENTS

This work was supported by an NSERC IOR grant and an

industry consortium “Jo int and Co operative Inversion of G eo-

physical and G eological D ata.” Pa rticipating companies are

Placer D ome, BH P, Noranda, Cominco, Falconbridge, INCO,

HB E&D, Kennecott, Newmont,WMC,a nd CR A E xploration.

We thank Cam DeLong for supplying the geologic cross-

section at 9600N and tha nk Cliff Stanley a nd Ca m D elong for

providing informat ion on the geochemistry of Mt. Milligan and

for patiently explaining the results to us. We are grateful to

Dale Sketchley and Peter Kowalczyk for providing much of

the background information about Mt. Milligan and helping

us piece to gether a consistent interpretat ion. We tha nk Pla cer

D ome for pro viding the 3-D gold mod el and d rill-hole results

and both Noranda and Placer D ome for providing the geo-

physical data.

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a)

b)

FIG. 14. Cu-Au abunda nces for the MB X West Z one is shown in (a). The relatively high Cu-Au correlation and magnitude of themoda l C u/Au ratio suggest that a single, high temperature pota ssic alteration Cu-Au mineralization event occurred in this area. I ncontrast, the less well-correlated concentrat ions for the MB X E ast Z one shown in (b), suggest that more tha n one mineralizationevent occurred there. An overprinting propylitic alteration Au-only mineralization event resulted in the d isplacement of samplesupward, o ff the line corresponding to a Cu/Au ratio o f 15000 which probably a pproximates the distribution of these samples afterthey were a ffected by t he earlier, high temperature C u-Au mineralization event. B ubble sizes are proportiona l to sample frequencyand the figures are obtained from Stanley (1993).

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FIG. 15. Co operative inversion of ma gnetic and IP dat a. A cross-section of a 3-D weighting function obta inedfrom the inversion of ma gnetic data is shown a t the to p. This weighting is used in a 3-D inversion of I P d ata and across-section of the recovered chargea bility at 9600N is shown in the middle panel. That model can be compa redwith the model at the b ottom that was the original inversion of the IP data along that line.

REFERENCES

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