UNIVERSITY OF GOTHENBURG Department of Earth Sciences Geovetarcentrum/Earth Science Centre

ISSN 1400-3821 B682 Bachelor of Science thesis Göteborg 2012

Mailing address Address Telephone Telefax Geovetarcentrum Geovetarcentrum Geovetarcentrum 031-786 19 56 031-786 19 86 Göteborg University S 405 30 Göteborg Guldhedsgatan 5A S-405 30 Göteborg SWEDEN

Ore body modeling of magnetic and gravimetric anomalies in

the Dannemora field using Encom Model Vision Pro 10.0

Petter Engvall

 

 

ORE BODY MODELING OF MAGNETIC AND GRAVIMETRIC ANOMALIES IN THE DANNEMORA FIELD USING ENCOM MODEL VISION PRO 10.0

Abstract In Dannemora in eastern south-central Sweden the Dannemora iron ore field has been mined for five centuries. Over the area magnetic and gravimetric studies show large anomalies indicating the presence of high density material with high susceptibility. Although the last mine has been closed since 1992 there is much work done in order to re-open the mine. The main part of this work is to use old geophysical surveys to calculate possible ore reserves. To help with this the software Model Vision Pro can be used. Model Vision uses an iterative process to aid the user when placing bodies in a three dimensional space and setting their density and susceptibility properties. The software handles gravimetric, magnetometric and chemistry data as well as bore hole data. With the help of an earlier mapping –both vertical and horizontal– of ore bodies Model Vision was used to calculate an average density and susceptibility for these bodies. This data was then used when creating potential ore bodies in areas close by with large gravimetric and magnetic anomalies where no mapping had been done. An overall average density of 3.9 g/cm3 and susceptibility of 0.29 for the ore was calculated. The iron content of each body was then calculated using the volume of the body and the density. An overview of the software’s usability when modeling small, deformed bodies was also made.

Sammanfattning I Dannemora i östra delarna av mellansverige har järnmalmen i Dannemora-fältet brutits i fem århundraden. Magnetiska och gravimetriska undersökningar över området visar stora anomalier vilket tyder på att det finns material med hög densitet och hög susceptibilitet. Den sista gruvan har varit stängd sedan 1992 men mycket arbete görs för att kunna öppna den igen. Huvuddelen av detta arbete består i att nyttja gamla geofysiska undersökningar för att beräkna möjliga malmreserver. För att underlätta detta kan programvaran Model Vision Pro användas. Model Vision använder en steg-för-steg process för att hjälpa användaren att placera kroppar i en tredimensionell miljö och ange deras densitet och susceptibilitets-värden. Mjukvaran hanterar gravimetrisk, magnetometrisk och kemidata samt även borrhålsdata. Med hjälp av en tidigare utförd kartering –både vertikal och horisontell- av malmkroppar kunde ett medelvärde på densitet samt susceptibilitet för dessa kroppar beräknas i Model Vision. Dessa värden användes sedan för att skapa kroppar av potentiell malm i närliggande områden med stora gravimetriska och magnetiska anomalier men där ingen kartering fanns tillgänglig. En övergripande medeldensitet för malmen beräknades till 3,9 g/cm3 samt en susceptibilitet på 0,29. Järnhalten för varje kropp beräknades med hjälp av kroppens volym och densitet. Mjukvarans användbarhet vid modellering av mindre, deformerade kroppar testades också.

Keywords Geophysical modeling, gravimetry, magnetometry, Dannemora, iron ore, Model Vision, densi-ty, susceptibility, three dimensional modeling. 

 

 

INTRODUCTION..................................................................................................................... 1

BACKGROUND .......................................................................................................................... 1 GEOLOGY ................................................................................................................................. 1 ORE FORMATION ....................................................................................................................... 3 SOFTWARE ................................................................................................................................ 3

METHOD .................................................................................................................................. 6

DATA ........................................................................................................................................ 6 SOFTWARE SETUP ..................................................................................................................... 7 BEDROCK MAP.......................................................................................................................... 9 CROSS SECTION ...................................................................................................................... 10 SYNTHETIC MODELING ........................................................................................................... 12 IRON CONTENT ....................................................................................................................... 12

RESULTS ................................................................................................................................. 12

BEDROCK MAP........................................................................................................................ 12 CROSS SECTION ...................................................................................................................... 13 SYNTHETIC MODELING ........................................................................................................... 13

DISCUSSION .......................................................................................................................... 14

ACKNOWLEDGEMENTS ................................................................................................... 17

REFERENCES ........................................................................................................................ 18 

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Introduction

Background As fewer discoveries of large ore fields are reported the importance of smaller deposits or bodies is growing. At the same time the ore processing plants are getting more efficient at extracting the metals which means that ore bodies which earlier was considered uneconomical might now be considered mineable (Evans, 1993). Using geophysical methods, such as magnetometry, it is possible to find new ore bodies and with the help of gravimetry further investigate old ones as well as evaluate ore volumes. Managing and analyzing the results manually can be difficult as the amount of data from for example an airborne magnetic survey easily can amount to more than 60000 sample points (Mussett & Khan, 2000). To help with the interpretation of such surveys the computer software Model Vision was developed by Encom Software (http://www.encom.com.au) to aid geologists and mining companies get a better overview as well as assist when deciding the location for new boreholes. At time of writing, the latest release of Model Vision was version 10.0.

Dannemora mine is an iron ore field deemed uneconomical in 1990 and the mine was shut down in 1992. Due to rising base metal prices during recent years and new technologies for extracting the metals, the mine is now being investigated for re-opening and continued operation. Prospecting in the area was resumed in 2006 (”Projektbeskrivning | Dannemora Mineral AB”, nd). The Dannemora field is considered Sweden's oldest worked iron ore, with known ore production in open pit mines stretching back to the 15th century (Thoweman, 2008). The ore actually consists of at least 25 separate bodies which together comprise the largest known iron ore locality in Uppland, although in the county more than 800 smaller mines are known (Wik, Stephens, & Sundberg, 2006).

In this bachelor thesis I will try to determine the physical representation of two magnetic and gravimetric anomalies in the Dannemora field in terms of geometry, density and susceptibility. I will also explore the features of Model Vision Pro 10 to check if it is suitable when modeling ore bodies using only a limited amount of data. I will, in this case use gravimetric and magnetometric data, but without rock analysis data such as density and magnetic susceptibility. I will try to use the software to extract the values of density and susceptibility by first building a model over an area where the stratigraphy is known and so try to circumvent the problem of ambiguity. These values will then be used to model the subsurface over areas close by with large gravity and magnetic anomalies. To be able to locate the possible ore bodies in these new models the stratigraphy of the Dannemora field will be greatly simplified and rocks with similar densities and susceptibilities will be considered as the same unit. Finally I will try to calculate the iron content in the modeled ore bodies using their density and volume.

Geology Dannemora is found in south-central eastern Sweden, in the north-eastern part of Bergslagen (see Map 1). This area is believed to be an old volcanic arc with 1.9Ga felsic volcanic rock

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metamorphosed under amphibolite facies conditions. Later intrusive granodioritic and granitic rock is common in the area. Because of the generally strong regional deformation during the Svecokarelian orogeny primary structures are rare, though in Dannemora the layers are reasonably well preserved (Lindström, Lundqvist, & Lundqvist, 2011).

The iron ore occurs in an area approximately 600m wide and 3km long called the Dannemora formation (see Map 1). The formation is part of the eastern of two synclines situated 2km apart with an anticline between, all stretching NNE-SSW and with extensive faulting in NNE-SSW and NW-SE directions. The eastern syncline is an isoclinal, overturned fold with layers dipping 80-90 degrees towards NW at the surface and 55-70 degrees at a depth of 350m. Drilling in the area revealed that the bottom of the syncline in the southern part is located at about 550m depth, but it has not yet been found in the northern part. Drilling in the northern area to a depth of 1150m has not yet revealed the bottom. The rock in which the iron is found is dolomitic and calcitic limestone layers following the syncline. The area east of the syncline

Map 1 Bedrock map from SGU with stylized, theoretical syncline‐anticline‐syncline‐formation. 

Eastern synclineAnticline

Surface leveltoday

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consists of a zone of metamorphosed volcanic rocks of rhyolitic composition approximately 300m wide, and beyond this granitic rock. To the west the volcanic rocks continue some 2km before the granitic rock is found (Lager, 2001).

Ore formation The ore is thought to have formed when subsidence and uplift of the area led to transgression and regression of the sea resulting in evaporites (Sabkha plateaus). Hydrothermal fluids containing dissolved metals driven by the volcanic activity migrated to these evaporite pans and precipitated metals, mainly iron and manganese. Volcanic activity buried the plateaus creating layers enriched in iron. So far 8 stratigraphically different layers containing iron ore have been found. This indicates that the ore forming process with subsidence and uplift was repeated at least 8 times. The layers were subsequently folded creating the anticline and synclines (the Dannemora formation). Extensive faulting in the area has displaced the layers and the iron ore is now found in lens shaped bodies in the limestone layers (Lager, 2001).

The ore has traditionally been divided into manganese poor and manganese rich iron ore with an iron content between 30 and 50 percent and a manganese content of 0.2-1 and 1-6 percent respectively. The predominant Fe-mineral is magnetite, though minerals such as knebelite (Fe end member in olivine group) and manganogrunerite (an amphibole that was named dannemorite when first found in 1855 (Barthelmy, 2010)) are also found. As these minerals harbor iron and manganese, they could potentially have an impact on both gravimetric as well as magnetometric surveys. In Dannemora though, they are found in such low quantities that they are disregarded in this model. The large ore bodies are found in limestone layers but smaller ones exists in skarn layers, though these layers are usually no more than 1-7 meters wide with an iron content of less than 30 percent and are therefore currently of less significant economical value (Lager, 2001).

Software Model Vision Pro 10 (from here on referred to as MVPro) have been developed for modeling of ore bodies and geology on a small to regional scale, the software can also be used for bedrock and strata mapping as well as borehole logging. The software makes it easy to present input data of a wide range such as geochemical, magnetic, gravimetric and radiological surveys as profiles. With the possibility of interpolating data between survey lines the software can present color coded as well as contoured maps. A wide range of filters such as low pass, high pass and upward continuation filters can be used to reduce data.

Imported survey line coordinates fall into the category of 'Lines' whereas the actual sampling data from the survey is called 'Channels' (table 1). In this way a project can have a very large number of lines imported with the data easily manageable as channels. For example a survey can have sampled magnetometry, gravimetry, and gold content which make the line have at least 6 columns in raw format. MVPro divides the data into geographical coordinates (lines, first 4 columns in table 1) and 3 channels of sampling data now accessible each by itself (last 3 columns in table 1). Data can also be imported as points without the need for line numbers, each point is then treated as a separate entity with an ID-tag.

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Table 1 Example of data in line and channel format 

ID# Line X Y Mag Grav Au

001 1 2100 500 50643 12 0.2

002 1 2200 500 50523 7 0.1

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Interpolation of channel data between lines or points results in a grid which is presented in map format (see figure 1). On this grid the user can create new lines called 'Synthetic Lines'

whereby MVPro uses the interpolated values of the grid data underneath the synthetic line to create a profile for modeling of bodies. Before the modeling of bodies can be initiated the user has to provide the software with some additional information, such as density of the surrounding rock, magnetic remanence and the geographic position of the survey as well as background values for the magnetic field. These values can be taken from literature or sampled in the field. MVPro has a record of the International Geomagnetic Reference Field coupled with a map of the world (IGRF-function) which can be used to set geographical position as well as magnetic background field values.

Modeling can be done using predefined shapes such as rectangles, prisms and spheres as well as drawing free hand using the 'Polygon' option to create an irregularly shaped body. The software handles 3 dimensions by stretching 2 dimensional representations of bodies in a third dimension where X and Y represents the two horizontal directions (usually west-east and south-north respectively) and the depth of the third dimension is represented by Z (see figure

Survey Line 

Interpolated contour lines

North 

Figure 1 Magnetic survey lines and interpolated contour lines. The contour lines have been color coded for 

clarity; red=high, yellow=medium and blue=low magnetic anomaly values. 

Synthetic line

NE

‐

Y 

NW‐SE  X 

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2). In the modeling window (called X-section) the sampled values from the survey is shown as a profile. MVPro then places a fictional, flat, profile over the sample value profile. MVPro initially assumes a subsurface where density and susceptibility is uniform expressed by the fictional profile being a flat line. When a new body is created with properties (for example density) different from its surroundings the software computes the impact this body will have on the fictional profile. The user then has the possibility to change one or more parameters of the body to make the fictional and actual profiles agree. When a reasonable fit has been achieved the 'Inversion'-function can be utilized to make the match between the profiles better. This function works by changing a parameter a fraction and comparing the result with the original model. If the resulting match is better the change is kept and another parameter is changed. Inversion is time and computer power consuming and so should be performed on bodies which already have a good match to the profile. To restrict the cycle time the user can control how many times (iterations) the software may change parameters as well as what parameters to change before stopping. The quality of the inversion is measured as a Root Mean Square (RMS) value between the modeled and the real profile where a low value indicates a better match than a high value. The RMS value is not, however, an indicator to the quality of the model (Pitney Bowes Software Ltd Pty, 2010).

Method

Data Data acquisition was performed at two different periods in time, the magnetic data was collected in 1971 using a ground based proton precession magnetometer. Gravity data was collected in 1961 with a ground based gravimeter and is in the form of Bouguer anomalies which corrects for altitude and latitude, no terrain correction was done. The magnetic data is in nT-anomalies of the regional magnetic field at Dannemora in 1971 (Hegardt, personal communication), this means that the data is corrected for diurnal fluctuations in the magnetic field and also that the earth magnetic field value have been subtracted from the data. The data consists of a number of NW-SE trending lines, 1-2km long with a line spacing of 40-80m and sampling distance of 20-40m with the higher resolution assigned to the magnetic survey. Survey lines were carried out in a local coordinate system used by the earlier mine company which deviates 31 degrees clockwise from true north. Although local grids are not used to the same extent today, profiles are usually laid perpendicular to the known strike of potential ore bodies to get as steep a curve as possible when plotting the results. This also makes it possible to calculate the depth to the object being investigated (Reynolds, 2011). The local coordinate system has a resolution of one square meter where X conforms to the NW-SE and Y the NE-SW direction. These coordinates can be converted into the Swedish Grid (RT90) using equations 1 and 2.

Figure 2 The three dimensions are 

represented by X, Y and Z.

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NESW)(–NWSE+=EastRT *51320.51177604*52470.85927278091614421.9190

(Eq. 1 Conversion of local grid X to RT90 2.5 gon V east-coordinate)

NESW+NWSE+=NorthRT *52470.85927278*51320.51177604746678000.8190

(Eq. 2 Conversion of local grid Y to RT90 2.5 gon V north-coordinate)

Figure 3a and b shows the area where the survey was done with the sampling stations marked, note that the magnetic survey covered a slightly larger area than the gravimetric survey. Interpolation of the magnetic and the gravimetric values over the area is shown in figure 3c and 3d.

Software setup A density value from the literature (Stephens et al., 2009) was used for the granodiorite bedrock found around the survey area as well as beneath the syncline. As no data on magnetic remanence was found this was not included. The IGRF-function built into MVPro was used to set geographic position as well as magnetic field values (see table 2).

Density (granodiorite) 2.8 g/cm3 Magnetic remanence N/A Position N 60° 12.256’

E 17° 51.613’ IGRF 50290 nT Local grid deviation from true north 31°

Table 2 Data used in modeling of Dannemora area

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Figure 3 (a) Magnetic sample points. (b) Gravimetric sample points. (c) Interpolated values of 

magnetic anomalies. (d) Interpolated values of gravimetric anomalies.

a b 

c d 

Centralshaft 

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Bedrock map MVPro has a built in function that makes it possible to use a bedrock map of the area to contour the margins of the rock units and then let the software extrapolate the surface downwards into a three-dimensional body. This requires not only a bedrock map but also the dip of the rock units. The map used (see figure 4) depicts the layers of the Dannemora syncline on the 300-350m level in the mine. Because the map displays the subsurface, rather than the surface, the first rock units have to be inverted and stretched upwards instead of downwards. To place this map correctly the location of the Dannemora mine central shaft was first found using the map with survey lines (figure 3a and b) where an absence of sample points is found between local grid coordinates -360 and -420 X and -280 Y. This position corresponds very well with the known geographic position of the shaft when converted to RT90 (N 6677967, E 1613951 (Jansson & Åkerhammar, 2010)). The bedrock map was then positioned correctly in MVPro.

Figure 4 Bedrock map with known iron ore bodies. Modified from Lager, 2001.

N 

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Next the bedrock margins were contoured over an area 800m wide and 200m long situated approximately 300m north of the central mine shaft, approximately corresponding to the line called ‘Section 2’ in figure 4. The contoured rock units were stretched upwards to ground surface with a dip of 85 degrees (mean dip angle of upper layers) and a negative extrapolation factor of 350m. A second unit was then created from the same bedrock map, covering the same area, using a positive extrapolation factor of 150m with a mean dip angle of 66 degrees (mean dip angle of lower layers. Dip angles for upper and lower layers from Lager, 2001). The resulting unit can be seen in figure 5. With the units created, a synthetic survey line was created in the map window covering the units with values from both the magnetic and gravimetric interpolated channels extracted for modeling This synthetic profile was then modeled using the inversion-function allowing the software to change the density and susceptibility of the bodies freely to make the two profiles (synthetic and modeled) match. No other parameters were allowed to be changed by the inversion process. When a good match had been achieved the values of rock density and susceptibility were used to calculate a mean value for the ore units.

Cross section An image can also be used to create bodies in a lateral direction where the rock units are stretched in the Y-direction rather than Z-direction. By placing an image in the modeling window (instead of the map window) contouring of bodies in the vertical rather than horizontal direction can be done. The image acts as a cross section when creating bodies and should represent what the site actually looks like. A 600m wide cross section of the syncline mapped 300m north of the central mine shaft was used (figure 6). First an 800m long synthetic survey line was created at the same position as the cross section depicts, then the cross section image was placed in the modeling window and contouring of the bodies was

Figure 5 A 3 dimensional view of the rock units from the bedrock map contouring.

Surface level 

350m level  Central mine shaft 

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done. The rock outline was then stretched in the Y-direction to an extent of 150m (figure 7). With the help of the inversion-function running with density and susceptibility as the only free parameters, the densities and susceptibilities of the units were calculated. MVPro calculated the susceptibility of one unit to be negative which could be explained by the folding of the layers during deformation and overturning of the syncline (Butler, 1992). To correct for this the magnetic properties of this unit were turned 180 degrees resulting in a positive rather than negative susceptibility value. The susceptibility values as well as the density values were used to calculate a corresponding mean value for the ore units.

Figure 6 Cross section used for contouring. The area called ‘Section 2’ has been used. Modified 

from Lager, 2001. 

Figure 7 A 3 dimensional view of the rock units from the cross section contouring. Blue elongated 

shape in foreground represents the central mine shaft. 

Central mine shaft 

350m level 

Surface level 

350m level

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(Equation 3)

Synthetic modeling Two new synthetic lines were created over areas with elevated gravimetric anomalies, one to the south and one to the north of the previously used line. On these new synthetic lines, profile modeling was done using the density and susceptibility mean value for the ore extracted from the bedrock map and cross section methods used earlier. These models were simplified by merging rock types with similar properties to get a clear signature from the potential ore bodies. Using the polygon function ore bodies and surrounding rock units were added and shaped to fit the profile. When a reasonable fit had been achieved between the synthetic and modeled profiles the inversion-function was used by setting the distance and depth parameters free but with a very limited span.

Iron content By using a linear relationship between the surrounding rock and the modeled ore bodies the magnetite content of the bodies will be calculated (Magbody). The total iron content (FeTot.) of the modeled ore bodies will be calculated by multiplying the ore body volumes with their magnetite content and density of magnetite and the amount of iron in magnetite (Femag), (equation 3). Density of magnetite (rMag) used is 5.18 g/cm3 and the iron content of magnetite (Femag) used is 72%.

.

Results

Bedrock map The resulting profile of the bedrock map contouring can be seen in figure 8. Modeling on lines over the area resulted in a mean ore density value of 3.85 g/cm3, the susceptibility values however, are not probable. As can be seen on the magnetic profile in figure 8 the magnetic response of the bodies when running MVPro inversion is clearly erroneous. For this reason, these susceptibility values were not used in subsequent modeling.

Figure 8 Profile model with gravimetric (top) and magnetic (middle) inversion results. Black line is synthetic profile, blue 

and red lines are the calculated responses from the bodies (see inset circle in top window), note the erroneous magnetic 

result in the middle. The rock units are shown in the bottom part of the figure.

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Cross section The cross section profile yielded useful density and susceptibility data for the ore. A mean density value of 3.95 g/cm3 was calculated. After correction for the negative susceptibility value had been done, the mean susceptibility value for the ore was calculated to 0.29. The modeled profile can be seen in figure 9.

Synthetic modeling An average ore density of 3.9 g/cm3 was calculated using data from the bedrock map and cross section models. The two new profiles with ore bodies using properties calculated with the inversion-function are shown in figure 10 and 11. To make the lines match additional

Figure 9 Profile model with gravimetric (top) and magnetic (middle) inversion results. Lines as in figure 8.

Figure 10 Northern profile with gravimetric (top) and magnetic (middle) response of the ore bodies. S = 

susceptibility [nT], D = density [g/cm3]. 

Density 2.65 Suscept. 0.001 

Density 3.8 Suscept. 0.3 

Density 2.87 Suscept. 0.001 

:0 

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bodies were added (units 1, 2 and 3 in figures 10 and 11). For the northern line (figure 10) the profiles show a fairly good match between synthetic and modeled gravity profile. The modeled susceptibility profile is smoother than the synthetic profile but the two peaks visible in the in synthetic data also appear in the modeled one. The southern synthetic profile (figure 11) show a good correlation between the gravity lines but the synthetic susceptibility line show an abrupt change in the pattern at around 400m, above the main ore body, which is not reflected in the modeled line.

 

Figure 11 Southern profile with gravimetric (top) and magnetic (middle) response of the ore bodies. Note 

change in pattern at arrow in middle window.

Discussion

Due to the faulting and deformation of the mineralized zones, the Dannemora iron ore field geology is complicated and difficult to model. By using a horizontal and a vertical cross section as a map the problem of ambiguity is reduced and the approximate densities and susceptibilities of the mineralized zones could be calculated. These values were successfully used when creating new bodies of potential ore in profiles across areas with strong gravimetric and magnetic anomalies. The reason for the change in the susceptibility pattern in the southern profile (figure 11) could be that there are several large buildings in this area possibly interfering with the magnetic survey. The rock units necessary to add to the profiles in order to get a good match between synthetic and modeled lines have the same dip as the rock units from the literature (Lager, 2001). The yellow units also have similar density as volcanic rocks from the region (Stephens et al., 2009). The green units in the synthetic modeling have a slightly higher density than what could be expected from limestone (2.7 g/cm3). This could be appointed to the possibility that some of the original sabkha plateau layers had small inclusions of magnetite mineralization increasing the density. The rock

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around the modeled ore bodies have a density of 2.7 g/cm3 which corresponds well with limestone (Nesse, 2000).

Figure 12 shows a linear density relationship between surrounding rock with density 2.7 g/cm3 and magnetite with density 5.18 g/cm3 (Nesse, 2000). The density of the modeled ore bodies are marked with black lines. From these lines, the iron content can be read as 49%. By using equation 3 the total iron content is calculated and the results shown in table 3.

Table 3 Total iron content for each body 

Ore body Volume [m3] Magbody [m3] FeTot. [metric ton]

Ore:0 2573490 1261010 4703063

Ore:1 2482626 1216486 4537006

Ore:2 1388426 680328 2537351

Ore:3 674613 330560 1232857

Figure 12 Linear density relationship between limestone and magnetite. Y‐axis is magnetite‐percentage from 

0 (pure limestone) to 100 (pure magnetite). X‐axis is density where 2.7 is the density of limestone with 0 

percent magnetite and 5.18 is the density of magnetite. 

0

10

20

30

40

50

60

70

80

90

100

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Even though MVPro handles bodies in three dimensions, the options when creating these bodies are rather limited. The polygon function is the most versatile tool for creating bodies and gives the user total control and freedom of two dimensions when creating figures. But when a three dimensional body is to be created from these 2 dimensional figures, the software computes straight lines for the body in the third dimension. This means it is difficult to create bodies where none of the three axes are right angled. See figure 12 for an example of a unit with a large extension in the E-W directions where the edges should not be parallel to a N-S direction, they should have a 31 degree clockwise deviation from north. This means the whole unit is spun 31 degrees with the left edge ending up north and the right edge south of the profile line. Smaller bodies which are supposed to be part of the unit are also seen but because

the bodies all turn around their own central axis they are displaced with regard to the central unit. This makes it difficult to conveniently model smaller, deformed potential ore bodies or zones of mineralization. To be able to do this one has to increase the resolution of the model by adding more profiles with smaller bodies. Because of these limitations I consider the correct nomenclature should be 2.5-D modeling rather than 3-D modeling.

It is important to remember that MVPro is not a CAD software and as such is less useful when designing and planning a mine. It is a tool for evaluating geophysical data in an early stage of exploration. For example creating magnetic anomaly maps of the survey area which makes it possible to quickly identify certain areas of interest. These areas could then be investigated further by high resolution magnetometric and gravimetric surveys. As the software in itself is small and does not need a powerful processor (apart from the inversion-function) it should present no problems using it in the field when the survey is being done. The possibility of modeling bodies in the field could be a great aid when deciding in what directions to extend the survey.

Figure 13 Example of a rock unit consisting of several smaller bodies all turned 31 degrees clockwise from 

north. Unit is seen from above with X‐axis in east‐west direction and Y‐axis in north‐south. 

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Acknowledgements

I would like to thank my supervisor Erik Sturkell at Geovetarcentrum for his encouragement and help, Lennart Björklund at Geovetarcentrum for being my examiner, Eric Hegardt at Bergab for supplying the survey data and help with coordinate conversion, Martin Persson at Geovetarcentrum for excellent tips during coffee breaks, Natalie for being my opponent, my wife for correcting doubtful English and finally my fellow students for their general good humor!

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References

Barthelmy, D. (2010). Manganogrunerite Mineral Data. Retrieved April 22, 2012, from

http://webmineral.com/data/Manganogrunerite.shtml

Butler, R. F. (1992). Paleomagnetism: Magnetic Domains to Geologic Terranes (First.).

Tucson: Blackwell Scientific Publications.

Evans, A. (1993). Ore geology and industrial minerals (3rd ed.). Boston: Blackwell Scientific

Publications.

Jansson, H.-G., & Åkerhammar, P. (2010). Detaljavgränsning av riksintresset Dannemora i

Östhammarskommun, Uppsala län, enligt 3 kap. 7 § andra stycket miljöbalken (Beslut

No. 461403/2010). Uppsala: Sveriges Geologiska Undersökning. Retrieved from

http://www.sgu.se/dokument/riksintressen/46-1403-2010_beslut.pdf

Lager, I. (2001). The Geology of the Palaeoproterozoic limestone-hosted Dannemora iron

deposit, Sweden (No. 107). Rapporter och meddelanden. Östervåla: Sveriges

Geologiska Undersökning.

Lindström, M., Lundqvist, J., & Lundqvist, T. (2011). Sveriges geologi från urtid till nutid

(Second.). Lund: Studentlitteratur.

Mussett, A., & Khan, M. (2000). Looking into the earth : an introduction to geological

geophysics. New York: Cambridge University Press.

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