The mine is located in Laochang Township, Xinping County, Yuxi City, Yunnan Province. The deposit is a moderately thick and gently inclined high temperature deposit with submarine volcanic eruption and sedimentary metamorphism. The ore body strike is east-west, with strike length of about 1800m, dip angle of about 1600m, and dip angle of 20 ~ 35, showing layered and quasi-layered output. There are three iron-bearing copper ore bodies (I3, I2, I 1) and four copper-bearing iron ore bodies (Ic, Ib, Ia, I0) in the mining area * *, which are IC → i3 → IB → I2 → IA → I 1 → I0 from top to bottom, respectively, and the top of IC is about 65438. Buried depth 160~750m, elevation 82 1~-29m. Among them, I3 and I2 iron-bearing copper ore bodies are large, which are the main mining targets. The main metal minerals of the ore are chalcopyrite and magnetite, and the main gangue minerals are carbonate (mainly dolomite) and biotite. The ore is generally stable, with f = 8 ~ 65438+. Main faults in the mining area: F 1, F2, F3 and F5. Main industrial indicators of copper mine: cut-off grade ≥ 0.3%; The thickness of stone removal is ≥ 2m; Mineable thickness ≥1m. Main industrial indicators of iron ore: TFe cut-off grade ≥ 20%; The thickness of stone removal is ≥ 2m; Mineable thickness ≥2m.
2. Geological database construction
Collect the original geological data of the deposit, digitize it, establish the orifice table, inclinometer table and sample table, and complete the preliminary data sorting work. The structure of each data table is shown in Table 3 below.
Information table contained in orifice table
Information table contained in inclinometer
Information table contained in sample table
After the above three tables are generated, a geological database can be established in Dimine. Comprises the following four steps: (1) saving the generated Excel file as a TXT tab division file type; (2) Import the tab split file saved as TXT into Dimine③ data for validity check and modification; (4) Establish the association between files and generate geological database.
3. Construction of sedimentary surface model
(1) fault plane model
The deposit studied is a deposit with very complicated geological structure, and 40 complex faults in the mining area cut it into many small ore bodies. Before the fault model is established, the fault is analyzed and sorted through the sections of each exploration line and the geological plan of the middle section containing the fault line, and the fault information on the map is imported into Dimine system software. Then the fault lines are sorted out and a three-dimensional model is established for each fault according to its trend.
(2) Ore body surface model
The surface model of ore body is established through the contour lines of ore body on each section. Classify and sort out the contour lines of ore bodies on each profile, then import them into Dimine digital mining software system, and then modify and determine the contour lines of ore bodies according to the spatial grade display of three-dimensional borehole data, and then connect the contour lines of ore bodies to generate the surface model of ore bodies, as shown in the following figure.
Establishment of ore body surface model
On the surface where contour lines are established, the points of contour lines on adjacent sections are connected by straight lines, but in fact, the fault plane is likely to be a spatial curved surface, so there are some inconsistencies between the fault and the ore body, including the ore body exceeding the fault and the gap between the ore body and the fault. In order to ensure that the fault model is completely consistent with the surface model of the ore body, it is necessary to carry out Boolean operation on the fault surface model and the surface model of the ore body, cut off the redundant ore body with fault plane, and cut off the redundant ore body with fault after extending the ore body with fault gap, so as to ensure the seamless consistency between the ore body and the fault.
As shown in the following figure, one of the two branches of the ore body exceeds the fault; The other one didn't run into trouble. At this time, it is necessary to appropriately increase the extrapolation distance of the branch of the ore body that is not in contact with the fault to make it exceed the fault, and then carry out Boolean operation to remove the excess part, and finally get the completely consistent ore body and fault.
In the process of establishing ore body model, when two contour lines close to each other on the section are reconstructed with the corresponding contour lines on the adjacent section, the two surface models may intersect in space. But in practice, this kind of intersection is impossible, and the intersection of ore bodies has an influence on the calculation of ore quantity, cutting plane section and establishing block model. In order to truly reflect the spatial relationship of ore bodies, in the process of modeling, it is necessary to carry out Boolean operation on the intersecting ore bodies and cut out the intersecting parts to make the ore body models completely consistent. The Boolean operation method between ore body models is the same as that between ore body and fault, but the difference is that the Boolean operation between ore body models is only carried out between models with intersecting parts. The finally established fault and ore body surface model is shown in the following figure.
Position relationship between ore body and fault
Ore bodies and faults after Boolean operation
Ore body and fault plane model
4. Block model of ore deposit and reserve calculation
Block model of (1) deposit
To establish a block model of a deposit, we must first determine the block model range and unit block size. The determined range should include the whole deposit, and the unit block size should be determined according to the mining method. The block model range and unit block size parameters of this deposit are shown in the following table.
Parameter list of block model range and unit block size
(2) Statistical analysis of original sample data
The statistical analysis of the original sample data includes the histogram of grade value distribution of copper, total iron, fusible iron, gold and silver in the sample and the statistical eigenvalue of various data, in which the histogram of copper and iron is shown in the following figure, and the statistical eigenvalue is shown in the following table.
Histogram of copper grade in original borehole samples
Statistical Table of Elements of Original Bored Samples Unit:%
Histogram of total iron grade in original borehole samples.
Grade histogram of soluble iron in original borehole samples.
(3) abnormal value processing
At present, the commonly used method is to replace ultra-high grade with critical value. Extra-high grade can be identified by histogram auxiliary empirical data. The critical value of ultra-high grade copper in this deposit is determined to be 3%.
(4) Sample combination and its statistical analysis
The average length of the combined sample is 1. 15m. The histogram of elements after sample merging is shown in the following figure, and the statistical characteristic values are shown in the following table.
Statistical Table of Elements of Drilling Combination Sample Unit:%
Histogram of copper grade of drilling combined samples
As can be seen from the above chart, compared with the statistical parameters of the original samples, the average and standard deviation of the element grades before and after the sample combination are basically the same, indicating that the samples have not changed much after the ultra-high grade treatment combination.
(5) Calculation and fitting of variogram
The calculation of the variation function of this deposit is divided into two steps: the first step is to calculate the experimental variation function; The second step is to fit the theoretical variogram. According to the characteristics of the deposit, the variogram is calculated and analyzed from strike, dip angle and thickness. The theoretical variogram curve finally fitted is shown in the following figure, and the parameters are shown in the following table.
Histogram of total iron grade in drilling combined samples
Grade histogram of soluble iron in drilling combined samples
Fitting of variogram of copper strike theory
Variation function fitting of copper trend direction theory
Table of calculation parameters of variogram
The variation function model of Cu theory is cross-verified by ordinary kriging method. According to the results of cross-validation, the average error ME is 0.0 1, the average variance MSE is 0. 13, and the average variance rate MSER is 0.992 1.
The experimental variogram of TFe and SFe is calculated by the same method and fitted. The theoretical variogram parameters are as follows: TFe, spherical model, C0 = 4.95, C = 36.68, and the range parameters A in three directions are 5 1, 30,18 respectively; SFe, spherical model, C0 = 3. 1, C = 40. 13, and the distance parameters a in three directions are 47, 27, 17 respectively.
Fitting of variogram of copper thickness direction theory
(6) Kriging valuation
The adjacent data search area of unit block grade interpolation is an ellipsoid, and the length of major axis, minor axis and minor axis of ellipsoid should consider the range of variogram on the one hand and the influence of exploration grid on the other. If the ellipsoid is too small, the unit block has no or insufficient adjacent data, and the block model will produce blank unit blocks, which will affect the estimation effect. The direction of each axis of the ellipsoid is consistent with the direction of the variogram to which the strain path belongs, that is, the long axis direction is consistent with the strike of the deposit, and the short axis and short axis are consistent with the dip and thickness direction respectively.
In the actual interpolation process, the unit blocks of the block model are not completely interpolated at one time. Generally, adjacent data are searched at three different levels: proof (33 1), control (332) and inference (333). The size of the search ellipsoid is controlled from small to large, which is more in line with the actual production needs of the mine, and the calculated grade value can better meet the production needs. During each interpolation, the length of each semi-axis of the search ellipsoid depends on the distance between the nearest adjacent item and the unit block and the range of variogram in all directions of the deposit.
As shown in the following figure, considering the most special case, when the unit block is very close to an item, the unit block is controlled by the items on both sides, that is, the grade value of the unit block is determined by the sample data of the items on both sides. At this time, the length of the semi-axis of the ellipsoid is equal to the projection distance. As shown in the figure, ellipses A, B and C respectively represent the search ranges with different degrees of control. Generally, only one engineering sample can be found in the ellipsoid of the unit block at the edge of the ore body, such as ellipse D in the figure, and the resource category of the unit block can be inferred.
According to the exploration grid of the deposit and the range of variogram, and according to the type of resource grade, the search parameters of adjacent area data for Cu element interpolation are determined as follows: proven, ellipsoidal semi-axis 50m, minor semi-axis 50m, minor semi-axis 25m, and the minimum engineering number is 2; For controlled and inferred, the ellipsoid size is enlarged by 1 times, and the minimum number of inferred items is 1. Once the search parameters are determined, kriging grade interpolation can be performed on the block model.
Find the relationship between the length of ellipsoid half shaft and engineering spacing.
(7) Calculation of deposit reserve
Using the established model, the average grade, ore quantity and metal quantity of each element in the deposit are counted according to different standards, and the average grade, ore quantity and metal quantity of each cut-off grade and elevation are calculated (the calculation result is omitted).