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Geostatistics analysis of anisotropic gold ore bodies used in computer-aided and block-based modeling
Geostatistics analysis of anisotropic gold ore bodies used in computer-aided and block-based modeling

Dr. V.S. Balakhonov, D.V. Balakhonov

Science-Industrial Enterprise "GeoInfoComФ

The only wealth of a mining enterprise is its mineral resources. The basis of profitable production under the conditions of rigid competition and changeable market conjuncture is a strict control over their economic use, continuous and flexible planning of mining works whose final target is to allow shareholders to receive benefit.

TodayТs life requires from mining enterprises to move up to the world level of technology that is to apply information technologies which help to get maximum possible effect from the use of mineral raw materials [4].

Therefore effective operation of mining enterprises is impossible without accurate, complete and up-to-date information on subsurface resources that will make it possible to manage mineral resources and their quality during their development. This purpose can be achieved if a subsurface user possesses the technology of construction of a block-based (geostatistic) model of the field.

To construct a three-dimensional block-based (geostatistic) model of a field it is necessary to study the morphology of ore bodies with sufficient degree of accuracy, make sure that survey network is rather dense and study the structure variability (anisotropy) of geological objects (anisotropy of the structure of geological objects is understood as a difference in speed changes of elements of the geological structure in various directions inside a geological object [1,5].

A computer block-based model of the Garbuzovskoye gold ore field was built on the basis of the above-mentioned information with the use of GIS "MicromineФ.

The Garbuzovskoye field is located within the Samolazovskoye ore field in the Yukhtino-Purikanskoye ore area in the central part of the Aldanian shield [3]. Spatially the field is related to the contact zone of the Yukhtinskiy Mesozoic alkaline massive with dolomites of Ust-Yudomsk Vendian suite imbedded among hydrothermally altered tremolite marbles, aegirite-augite syenites and diopside-phlogopite scarns. Gold-productive processes of ferromanganese and silicon-potassium metasomatism affect all rocks of intrusion contact aureole. Formed as a result of these processes metasomatic rock associations accompanied by gold mineralization are related to gold jasperoid ore formations and appropriate geologic-mining type of fields according to the genesis of typomorphic minerals. They have a complex geological structure. Gold ore deposits consist of small bodies of various thicknesses. Gold distribution in deposits is irregular.

At an initial stage of computer block modelling a special attention was paid to reservesТ delineation. It was carried out gradually - in exploration intersections, exploration-evaluation pits and longitudinal planes of deposits. Their association with certain geologic structural elements was used as geological criteria for ore bodiesТ allocation. For mineralized areas these elements were steeply dipping zones of tectonic breccia in metasomatically altered syenites and for deposits - flat lying zones of tectonic fracture in scarns or intrusive rocks, carbonate and silicate rock contacts. аTo avoid conventionalities during matching ore bodies in longitudinal planes reservesТ geometrization was carried out in productive deposit outlines. The deposit is understood as spatially contiguous ore bodies united by one industrial contour in accordance with the accepted conditions. Block-based modeling was carried out by means of filling continuous wire-frame models of ore bodies with joint blocks. The size of blocks (10x10x2,5m) was chosen on the basis of cluster analysis of sampling data according to mining requirements, exploration grid density and morphology of ore bodies. The factor, that is its proportion within the wire-frame field model, was calculated for every block. Eight gold ore deposits were revealed. According to the degree of exploration and uniformity of geological structure they were divided into 11 estimation blocks of category C1 and 9 blocks of category C2.

The estimation of spatial continuity of gold ore mineralization was carried out in main directions of anisotropy within the field (variogram analysis) with the use of geostatistical apparatus.

Various groups of geologic elements forming their own structure in the object are located on the field. Depending on the specificity of genesis the anisotropy of structures of various groups of elements differ from each other. The anisotropy of content variability in an ore body for different ore components is often dissimilar due to peculiarities of its formation stages [2]. So the study of anisotropy can give additional information about the structure and genesis of a geological object.

In geostatistical analysis the structure of a field is understood both as spatial distribution of contents and their correlativity depending on the direction and distance between sampling points. An experimental variogram was used at the beginning of this investigation. It was built on the basis of sampling results (data on exploration profiles Ц 93 wells), that is for all samples without regard to directions between them. It indicates the presence of anisotropy in gold distribution on the field. Then the spatial continuity of mineralization (gold content, g/t) was estimated in various directions Ц in wells and along drilling lines within bulk ore bodies.

While constructing variograms different parameters varied: lag Ц interval, distance between a pair of samples; offset; class quantity Ц amount of search iterations; azimuth and angle of dip of search axis; search cone angle (spread).

These characteristics were selected in an interactive mode in Micromine by means of modeling a certain continuous theoretical function approximating the discrete experimental variogram. In geostatistics there are several functions which are used as models of real variograms: nugget effect, linear, square, spherical, circular (2D spherical), exponential and Gaussian models [4]. Model matching was carried out both visually and by means of regression analysis methods.

When the distance between samples increases, variogram values also rise but this growth lasts until a certain limit after which the function varies around the horizontal line. This limit - "sillФ (D, ?2) - equals to dispersion of a studied characteristic. The distance between samples at which the variogram reaches the "sillФ is a "rangeФ (a) that is a distance at which the correlation between contents in samples remains [2.4].

Variogram investigations (structural analysis) helped to discover the presence of the "structureФ in gold concentration distribution within the field. The sequence of scarn interbeds (diopside and tremolite phlogopite) with superimposed sulphide mineralization, quartz-feldspar metasomatites with gold content from 0,05 to 0,2-0,4g/t is observed near granosyenite stocks. In these areas the variogram has a "nugget effectФ which indicates that gold distribution is irregular. The zone of influence (range) a = 1 m, that is the correlation between gold content in adjacent samples remains only at this distance. When the distance between samples (that is in the direction from contact zones to ore bodies) increases, gold dispersion gradually grows down.

Another regularity is revealed near ore deposits. At the distance of 15-20m from ore bodies there are impurities in the structure of gold content variability (variogram model Ц "impurity effectФ). This variogram type shows that there is a zonality of gold distribution that is periodic sequences of "poorФ and "richФ zones (a1 = 3,2m and a2 = 8,0m). This effect is characterized by relative amplitude which is determined by the ratio of the maximum value of the variogram (on the top) to its threshold and the distance at which the maximum value is achieved. So the periodicity of gold distribution zonation appears at the interval of 6,0m (fig. 1).

Fig.1Variogram with "effect of impuritiesФ at the distance of 15-20m from ore deposits of the Garbuzovskoye field (zones of influence (range) - a1=3,2, a2=8,0 m)

The regularity of periodicity interval decrease is revealed in frontal zones of near-surface ore deposits (zones of metasomatically altered rocks). The periodicity interval (lag) in these zones is 3,0 m and zones of influence a1 = 1,7 m, a2 = 3,5 m (fig.2).

Fig. 2 Variogram with "effect of impuritiesФfor frontal zones of near-surface ore deposits of the Garbuzovskoye field (zones of influence (range) a1 = 1,7 m, a2 = 3,5 m)

Fig. 3 Spherical variogram along the planes of ore occurrences (a = 6,5 m).

While studying the anisotropy along the strike of ore bodies the structure function type was determined as spherical (fig. 3). Interpreting this variogram model we may state that there is a correlation between gold contents along the planes of ore occurrences at the distance of 6,5 m (a=6,5m). The dispersion of gold contents gradually grows up only at this interval and then it greatly increases.

A more complicated type of anisotropy (zonal) is observed in the vertical direction (along thickness indices of ore bodies). The variogram is represented as "nested structuresФ (fig. 4).

Fig. 4 Variogram of "nested structuresФ indicating the presence of processes operating in various scales (vertically within the deposits р1 = 1,5 m, р2 = 7,0 m)

There are two zones of influence (range) (р1 = 1,5 m and р2 = 7,0 m) which differ greatly from each other. "Nested structuresФ indicate the presence of processes operating in various scales. This is a variability caused by transition from one mineral aggregate to another. аThe influence zone р1 =1,5 m shows that there is a correlation between gold contents in samples only at this distance (mineral aggregate level) and at the level of ore deposits there is one more type of variability (in a vertical direction) in points of transition from the intervals enriched in gold to thin interbeds of waste rocks or metasomatically altered rocks with less gold contents. In this case лthe influence zone (range)╗ reaches р2 = 7,0 m (fig. 4).

The created computer block model of the Garbuzovskoye gold ore field (in "MicromineФ) has the following advantages:

- fully and authentically describes the shape of the deposit (as far as exploration grid density permits) due to which the reliability of calculation of ore bodiesТ volume (and hence metal reserves) is higher than when using a cartographical model;

- takes into account the peculiarities of spatial distribution of components regulating the quality of mineral resources and consequently helps to estimate their content in any point of the deposit;

- interpolation methods used in generation of the block module makes it possible to estimate the degree of the field exploration and errors in reserves estimation in any point of the deposit;

- helps to create contours of an open-cast mine Ц dynamic mine-surveying model reflecting the progress of mining works and changes in the general plan of an open-cast mine for every date of mine-surveying;

- gives the possibility of selective field development.
The study of directional variograms, determination of their parameters, and revelation of the structure of anisotropic ore bodies at the Garbuzovskoye field made it possible to define more exactly the categorization of reserves of the object.


1. V.S. Balakhonov. Methods of spatial computer analysis for prediction and determination of local regularities of mineralogical-geochemical fields // Geology and mineral resources of the European territory of Russia and the Urals. Materials of regional geological conference of the European territory of Russia and the Urals. Yekaterinburg, 2000.p.32-33.

2. V.S. Balakhonov. Geostatistical models and prediction of the reliability of mapping and average content during field exploration //Mining-metallurgical complex of Russia: condition, development prospects. Materials of the 2nd all-Russia scientific-practical conference. Vladikavkaz, 2003. p. 52-55.

3. G.P. Dvornik, V.S. Balakhonov, A.N. Ugryumov. Metasomatism and gold-jasperoid mineralization of the Samolazovskoye ore field (the Aldanian shield) //News of the Ural state Academy of Mining and Geology. Issue 15. Series: Geology and geophysics. 2002. p. 91-98.

4. Y.E. Kaputin. Mining computer technologies and geostatistics. S.-Petersburg: Subsurface, 2002. 424p.

5. L.I. Chetverikov. Estimation of anisotropy of geological objects// Bulletin of the Voronezh University. Series: Geology. 2000. Issue 9. p. 26-31.

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