Ore Reserve Estimation Method by Using Geographic Information Systems

Ore Reserve Estimation Method by Using Geographic Information Systems Hakan Uygucgil & Can Ayday Anadolu University, Turkey

ABSTRACT In this study, a reserve estimation attempt in a silver ore deposit was carried out by the help of Geographic Information Systems (GIS). Using GIS, 3D model of the studied region, most suitable section planes and grade distributions were obtained and reserve estimation by cross-section method was approached. Besides, tabular cutting depth values were stored, and the relationships were encoded between the drillings, lithological units, and cross-section in a GIS database.

1. INTRODUCTION As mining operations become larger and more complex, large volumes of geological and production data, which are almost spatial, must be manipulated and interpreted on a day to day basis. Working with large volume of data brings out the need of sophisticated data storage strategies, and tools for interpretation and visualization in exploration and mining operations. In order to remain competitive, mineral industries must be adopted to the improvement of information technologies. Today, the classical methods used in mining operations are forced to work in a harmony with the information and computer technologies. When spatial data and information technologies were considered together GIS comes to mind, because spatial data from a variety of sources such as bore-hole locations, tabular cutting depth values, geological paper maps, can be captured in a GIS database, manipulated and transformed to extract particular features in the data, and combined together to produce new derived maps that are useful for decision-making and understanding more effectively.

2. OBTAINING DEM of STUDIED REGION In mining environment, almost all activities, such as surveying, drill hole data operations, open-pit design and optimization, underground mine design, mining block model creation, and ore reserve calculations have a 3D character. So a reserve estimation attempt could only be carried out by the help of 3D model of the region. For this purpose to define the studied region in 3D the elevation contours of the region were digitized from a 1:1000 scale map and a DEM was obtained after a computerized interpolation process. First the 1:1000 scale topographic paper map was scanned and it was rectified to obtain a georeferenced raster data. Spatial data that pertain to a location on the earth's surface are often termed georeferenced data. But this raster data could only be called as semi-georeferenced data, because the rectification was made on XY plane and the elevations of the features on the raster data were not known by the computer. So, the features on the map, especially the elevation contours and spot heights, were digitized by using screen digitizing method to obtain a full georeferenced data. The XY coordinates of the contours were held from the semi-georeferenced raster data and the elevation values (Z coordinates) were assigned from the keyboard for each contour, and a vector-based georeferenced topographic map was obtained (Figure.1).

Figure.1 Digital topographic map of the studied region.

Digital elevation data are a set of elevation measurements for locations distributed over the land surface. Several terms have developed that refer to digital elevation data and its derivatives. Digital Terrain Data (DTD), Digital Terrain Models (DTM), Digital Elevation Model (DEM), and Digital Terrain Elevation Data (DTED) are the more commonly used terms (Aronoff, S., 1989). In this case the elevation measurements are the elevation contours and spot heights that was sketched on the topographic paper map. So when the vector-based digital topographic map was used as input, the DEM of the studied region was derived from it in Triangulated Irregular Network (TIN) data model, after a computerized interpolation process (Figure.2). TIN is a vector-based topological data model that is used to represent terrain data. A TIN represents the terrain surface as a set of interconnected triangular facets. For each of the three vertices the XY coordinate (geographic location) and the Z coordinate (elevation) values are encoded (Aronoff, S., 1989).

Figure.2 TIN model of the studied region. DEM can also be represented in a grid format in which an elevation value is stored for each of a set of regularly spaced ground positions. Each data point represents the elevation of the grid cell in which it is located. In order to represent the DEM in a homogeneous structure, the TIN model was converted to grid format.

3. GEOLOGICAL MAP DIGITIZING and BLOCK MODEL CREATION Block models are primarily a presentation tool. They are useful in showing the 3D context of features on a surface, such as lithological units and borehole locations. Block models are the perspective views of DEMs and they are commonly generated as picture outputs or as mesh diagrams. In a mesh diagram the topography is represented as if a grid of regularly spaced lines had been draped over it (Figure.3). Thematic maps or satellite imagery can also be draped over a block model to give a 3D perspective view of the landscape.

Figure.3 Mesh diagram in grid format.

The geological map of the studied region was digitized as similar as the topographic map, except the absence of the elevation values (Figure.4). Figure.4 Geological map of studied region.

Each lithological unit was represented by a closed polygon and the non-graphic data related to the unit were stored as attributes in a GIS database. The geological map and the DEM, which was obtained before, had the same coordinate values as boundaries of the studied region. So it was possible to drape the geological map over the DEM, and in this manner the geological block model was obtained (Figure.5). Figure.5 Geological block model.

4. BOREHOLE LOCATIONS and CROSS-SECTIONS As known, in reserve estimation calculations drilling log data are evaluated to form an opinion about mineralization, but only the surface information from the DEM can be obtained. So, 47 bore hole locations, which were drilled before, were placed on the DEM by entering their XYZ coordinates. In determination of the cross-section paths, it was given importance to locate them in a way that they pass through or near as many boreholes as possible and they are in linear direction (Figure.6).

Figure.6 Locations of cross-section paths.

The cutting depth values were evaluated to generate the lithological unit boundaries on cross-sections. Three main lithological units, named Dolomite, Schist and Tuff, were chosen for this application. Due to the fact that the other sub- units, such as silicified, altered, or semi-altered tuff, were found as very thin bands in drilling logs, they were generalized as Tuff. In the generation of geological cross-sections a small macro, which was written in Pascal Programming Language, was used. The tabular cutting depth values were read and the Z coordinates of the cutting depths on the XZ plane were calculated by the macro. Then a small line segment for each depth was placed and an annotation near the segment that defines the lithological unit was put on the drilling log. Afterwards, the output of the macro, which is in (AutoCAD Data Exchange Format) DXF format, were opened in a CAD software and the lithological unit boundaries were digitized manually by taking the three main lithological units (Dolomite, Schist, Tuff) and the faults of the region into consideration. As a result, the tabular cutting depth values were converted to graphic format, so the graphical data, which were obtained from this process, represent the geological maps on XZ plane for each cross-section (Figure.7). Figure.7 An example to cross-section map.

5. GIS DATABASE In the geological cross-sections the closed polygons which represent the lithological units were cut with the influence area boundaries of the drillings. Henceforward, rebuild process, that is used to build topology, was applied to the new polygons. Topology is a mathematical method used to define spatial relationships, and it is the most widely used method of encoding spatial relationships in a GIS (Aronoff, S., 1989). Unique IDs were assigned to all polygons at the GUI (Graphical User Interface) part of the software, in order to identify them in the database. A database is a collection of information about things and their relationships to each other (Aronoff, S., 1989). Drillings, lithological units and cross-sections are in a relationship with each other. So, a database structure was built, in order to store this collection of information with its relationships (Figure.8).

Figure 8. Database structure. In this figure the headings are the table names and the items below them are the data fields. In a logical manner, one cross-section can contain many lithological units, and also one lithological unit can be cut by many drillings. But lithological units were divided by the influence area borders of drillings, and named litho-polygons, so in this approach one litho-polygon can only be cut by one drilling. A drilling can cut many litho-polygons (vertically) and it can also contain many cuttings. In this database structure, many to one relationship was used and the relationships were encoded by keyfields.

6. CALCULATIONS In calculations, primarily the weighted average method was applied to cutting depths by grade values of each drilling, in order to obtain the average grade values of drillings. Afterwards, the same method (weighted average method) was applied to average grade values of drillings by area values of litho-polygons to obtain average grade values of each litho- polygon. Henceforth, to obtain the average grade values of each cross-section, again weighted average method was applied to the average grade values by the area values of litho-polygons. All these calculations were made on XZ plane, and the average grade and the total area values of cross-sections were obtained. For reserve estimation volume and density parameters must be included into calculations. To include the volume parameter into calculations the width of a block (on XY plane) must be obtained. Therefore, in order to obtain the influence area borders of cross-sections the same method, which was applied to the drillings, was applied to the cross-section paths. The borders were drawn from the midpoint of the perpendicular distance between the neighbor sections, so the widths of the blocks (on XY plane) were obtained. In order to obtain the volumes of the blocks the width values were multiplied by the area values of cross-sections. Also the average grade values of cross-sections were assigned to the blocks. Finally to express the reserve estimation in tones, the volumes and the average grade values of them multiplied by the rock density of the region.

7. CONCLUSIONS All these complicated and dense calculations were done by formulized equations encoded in the GIS database, without any calculation error risk. As a result, by using GIS techniques the calculations for reserve estimation can be done in a very short time and the results are more accurate than the classical approaches. In this study GIS techniques were applied to a classical method as an example, and the accuracy of this method can be discussed, but the benefits of the information technologies to mining and mineral industries can not be belittled. Today, a wide variety of software tools, which are very powerful, have entered the mining and mineral industries. Consequently, the improvement of the information technologies, which is very fast, must be followed and adopted to the mineral industries to remain competitive.

REFERENCES ARONOFF, S., 1989, Geographic Information Systems: A management Perspective, WDL Publications, Canada, 288 p. BONHAM-CARTER, G.F., 1994, Geographic Informatin Systems for Geoscientists: Modelling with GIS, Elsevier Science Publications, Canada, 398 p. CANER, G., 1983, Maden Ekonomisi, Mineral Kaynaklarinin Degerlendirilmesi, Teknik ve Ekonomik Kavram Deger Kriter ve Yontemler, Maden Tetkik ve Arama Enstitusu Yayinlari Egitim Serisi, Ankara, 206 p. UYGUCGIL, H., 1994, Usage of Geographic Information Systems in Mining Engineering, Unpublished M.Sci. Thesis, Osmangazi University, Turkey, 50 p.

AUTHORS DETAILS Hakan Uygucgil Anadolu University Satellite & Space Sciences Research Institute 26470, Eskisehir, TURKEY. Tel: +90 (222) 322-2059 Ext:105 Fax: +90 (222) 322-1619 e-mail: [email protected] Can Ayday Anadolu University Satellite & Space Sciences Research Institute 26470, Eskisehir, TURKEY. Tel: +90 (222) 322-2059 Ext:105 Fax: +90 (222) 322-1619 e-mail: [email protected]