Blast Fragmentation Modelling of the Codelco-Andina Open Pit Expansion

Transcription

1 Blast Fragmentation Modelling of the Codelco-Andina Open Pit Expansion F. Mardones GeoBlast S. A., Chile C. Scherpenisse GeoBlast S. A., Chile I. Onederra The University of Queensland, Sustainable Minerals Institute, W H Bryan Mining and Geology Research Centre, Qld 4072 Australia ABSTRACT: In large scale metalliferous mining, there is significant evidence to suggest that by providing an appropriate size distribution to crushing and grinding circuits, a measurable increased throughput and/or reduced power draw can be obtained. Tailoring blast designs to suit specific fragmentation requirements is now common place at both the pre-feasibility and feasibility study stages. This is particularly the case when significant increases in ore production rates are being considered. As part of the feasibility study of the open pit expansion project of Codelco s Andina operation, a comprehensive blast monitoring program was conducted in the currently mined secondary ore domains of the Don Luis pit. The objective of this program was to calibrate and implement a site specific blasting model to enable the prediction of fragmentation trends in the deeper, more competent ore zones, also referred to as primary rock domains. This paper gives a brief description of the blast fragmentation monitoring program conducted and discusses the calibration and application of a stochastic blast fragmentation modelling framework. Results from several simulations have highlighted the key differences in fragmentation if current blast designs are applied in the more competent primary rock domains. A number of blast design options have been evaluated and recommendations made in order to achieve specific ore handling and processing targets. 1 INTRODUCTION Blasting activities in major mining operations have been placing significant emphasis on the ability to tailor fragmentation to improve downstream processes. In many of these operations, the impact of fines has been clearly identified. At the conceptual and feasibility stages, fragmentation modelling studies which support future Mine to Mill strategies can be conducted through the calibration of empirical models using existing data; and if need be, through the implementation of specific trials. An important pre-requisite is the adequate classification and characterisation of the blasting domains of interest. As part of the feasibility study of the open pit expansion project of Codelco s Andina operation, a comprehensive blast monitoring program was conducted in the currently mined secondary ore domains of the Don Luis pit. The objective of this program was to calibrate and implement a site specific blasting model to enable the prediction of fragmentation trends in the deeper, more competent ore zones 2 DESCRIPTION OF BLASTING DOMAINS The main geotechnical units forming the core of the mining environment of current and future operations at Andina have been grouped into Primary Rock, Secondary Rock and Riolite and Dacite chimneys. This study is mainly concerned with the calibration of an empirical fragmentation model in secondary rock and simulations in primary rock. Primary rock masses have been described as hard and competent with well healed gypsum or Anhidrite filled fractures, typical RMR values are in the range of 60 to 80. Secondary rock masses can also be described as hard, however fractures are generally open and hence reduce the competency of the rock mass with characteristic RMR values in the range of 42 to 50. Relevant to blast fragmentation modelling is the degree of in situ fracturing. As shown in Figure 1, total spacing statistics derived from fracture frequency data show that the degree of fracturing is clearly more intense in the secondary rock mass domains. Results from the available core logging data indicated that total fracture spacing may be as wide as 0.4 m in the secondary domain and 0.91 m in the primary rock domain. The analysis shows that the variability in fracture intensity appears to be greater in the primary rock domain.

2 From a drilling and blasting perspective the secondary and primary domains can be classified as fractured and blocky rock masses respectively. Fracture spacing statistics were used to provide first pass estimates of the potential range of the mean size of in situ blocks. This is a required input parameter that is further defined through back-analysis or the model calibration process. material data collected by the geology and geotechnical department of Andina provided the necessary input to reliably implement a stochastic modelling approach. Table 1. Summary of intact rock properties in secondary and primary domains. Figure 1. Total spacing statistics of secondary and primary rock masses. The rock types or lithological units of concern to this study include Granodiorita Cascada (GDCC) and Brecha de Turmalina (BXT). Both rock types are found in the secondary and primary rock domains. In both cases, the degree of alteration appears to be the main factor that affects strength and stiffness. Analysis of the geotechnical information provided by Andina allowed the definition of the average intact rock material and rock mass parameters used in the calibration and modelling of different blasting scenarios. Table 1 gives a summary of the domain and properties of the GDCC and BXT rock types. Table 1 shows that the intact rock material in the primary domain is slightly stiffer than in the secondary domains. In terms of compressive strength, there are no significant differences between the GDCC rock in the secondary and primary domains with mean values of 161 and 156 MPa respectively. A more pronounced difference is observed in the BXT rock with mean values of 135 and 158 MPa respectively. From a drilling and blasting perspective, all rock material can be classified as hard and competent. In these hard competent conditions incipient damage defined by peak particle velocity is estimated to be in the range of 900 to 1100 mm/s; and breakage is expected to be in the range of 3600 to 4400 mm/s. The overall breakage and fragmentation potential is expected to be driven by the degree and condition of fracturing; and therefore differences in the intermediate and coarse end of the fragmentation distribution are expected between secondary and primary rock masses. It should be noted that the rock 3 OVERVIEW OF MONITORED BLASTS The detailed monitoring of production blasts in secondary rock masses has been an important and necessary component of the model calibration and verification process. As summarised in Table 2, a total of four production blasts were monitored in the Don Luis pit of the Andina operation, three were located in the GDCC domain and one in the BXT domain. Table 2. Design parameters of monitored production blasts. * The explosive Apex 150 is a Heavy ANFO (50% Emulsion) product supplied by Orica Chile. 4 FRAGMENTATION ASSESSMENT A detailed fragmentation assessment program was conducted during this study. The detailed program included the acquisition of images during the excavation of muckpiles as well as the sieving of a limited number of samples taken from selected regions. As illustrated in Figure 2, the assessment procedure

3 consisted of sampling lines and profiles taken at different stages of extraction. This procedure is consistent with best practices in fragmentation assessment using image analysis methods. Table 3. Summary of fragmentation images samples taken during the monitoring of blasts in the GDCC and BXT domains. 5 BLAST FRAGMENTATION MODELLING The expected distribution of fragments in the fines and coarse regions is modelled by two separate distributions based on the recently published Swebrec function (Ouchterlony, 2005). The Swebrec function has recently shown to be far superior in fitting fragmented rock in the intermediate and finer end of the fragmentation curve than previous models. The main modelling framework includes the ability to consider a range of values to key input parameters through the explicit definition of distribution functions. In this way stochastic simulations can be conducted to determine a predictive fragmentation envelope that takes into account the variability of rock material, rock mass, blast geometry and explosive performance parameters. The current approach also incorporates modelling parameters that can simulate the impact of inter-hole delay timing on fragmentation (Onederra, 2008). Figure 2. Example plan view of sampling lines of blast 3724_12. Detailed analysis included both manual editing and the definition of site specific fine correction factors. These factors were determined directly by the sampling and sieving of fragments in the areas of interest. Blasting literature shows that reliable estimates of Run of Mine (ROM) fragmentation can be obtained following procedures similar to those incorporated in this study (Latham et al 2003 and Sanchidrian et al 2005). The data obtained from the monitored areas were used in this study to calibrate and verify the blast fragmentation models implemented in this study. The total number of samples taken in both the GDCC and BXT domain are summarised in Table Calibration results in secondary ore As has been extensively discussed in the literature, one of the main limitations of empirical fragmentation models is their requirement for site specific calibration. This necessary process generally involves the back analysis or prediction of fragmentation based on measured data and monitored practices. As mentioned earlier, four production blasts covering GDCC and BXT secondary rock domains were used to calibrate the proposed fragmentation modelling framework. The calibration process involved the refinement of estimates associated with rock mass parameters likely to impact on uniformity, mean fragmentation outcomes and the propensity of the rock fabric to generate fines during the fracturing process. Figure 3 summarises the results of comparisons between predicted and measured fragmentation outcomes for one of the blasts in the GDCC domain (3724_10). In this analysis, statistics associated with rock material input parameters, pattern geometry and explosive performance were included to generate an expected fragmentation bounded by envelopes of minimum, maximum and 95% confidence. It is important to note that the fragmentation envelope given by each simulation is a function of the level of un-

4 certainty or variability assigned to the available input data. Figure 3. Summary of calibration results based on monitored production blasts. 5.2 Fragmentation modelling of primary rock A total of 14 simulations were conducted to quantify relative changes in ROM fragmentation in primary rock. Table 4 gives a summary of the pattern geometries and powder factor ranges investigated. As shown, powder factors reflect the use of pattern geometries similar to those currently implemented at Andina, as well as more aggressive designs which include both reductions in burden, spacing and stemming lengths. All simulations have maintained the use of 270 mm diameter blastholes using Apex 150 and Apex 165 as the base case explosive products. It should also be noted that a single hole firing mode was assumed with inter-hole delays of 10 ms. As discussed earlier, the adopted stochastic approach has allowed the inclusion of distribution functions to rock material and rock mass input parameters as well as design specific parameters such as hole and charge lengths. The Latin Hypercube sampling technique was used with simulations set to 500 iterations. 6 RESULTS AND DISCUSSION Fragmentation modelling results for GDCC and BXT primary ore domains are summarised in Figures 4 and 5 respectively. Note that only the expected size distribution curves are shown for comparison purposes. Modelling results demonstrate the influence that changes in pattern geometry may have on fragmentation, particularly in the intermediate and finer size fractions. Differences between domains and designs are also summarised in Table 5. For similar pattern geometries and corresponding powder factors, modelling results suggest that blasting in the GDCC domain has the potential to generate more fines than in the BXT domain. Relative differences may be of the order of 3% to 5% between these two domains. As expected, designs D3 and D6 give the finest fragmentation in the GDCC domain; and designs D9 and D12 give the finest fragmentation in the BXT domain. By comparing designs D2 and D2A, modelling results suggest that by decreasing stemming lengths by approximately 1 m, a 1% gain is expected in the amount of fines generated in the GDCC domain. In the BXT domain however the gain is only approximately 0.5%, as shown by comparing designs D8 and D8A. It is important to note that model calibrations in the BXT domain were only based on a single production blast. More data may be required to improve the predicted capabilities of the model in this particular domain. Table5. Summary of fragmentation modelling results in primary ore conditions. Table 4. Summary of pattern configurations for GDCC and BXT primary ore domains. * The explosive Apex 165 is a Heavy ANFO (65% Emulsion) product supplied by Orica Chile. Figure 4. Comparison between designs in GDCC primary ore.

5 Figure 5. Comparison between designs in BXT primary ore. As discussed earlier, single hole firing conditions were adopted in the modelling calculations, in this case, a 10 ms inter hole delay was assumed based on estimations of minimum response time (Onederra, 2007). The current modelling framework was used to investigate potential gains in fines generation by introducing shorter delays (e.g. 2 ms to 10 ms). Designs D2 and D8 were used as base cases for the GDCC and BXT domain respectively. Results of the analysis for the expected values in GDCC are summarised in Figure 6. As shown, for the ½ and 1 size fractions with the use of inter hole delays of 2 ms, gains of approximately 2 % and 3.5 % may be achieved in the GDCC. The use of very short inter hole delays (e.g. 2 ms) demonstrates gains in the intermediate and fine fractions, however as shown in Figure 6, these gains may not be significant if one is to consider the variation associated with modelling predictions, and in particular the lower limit predictive envelope. It should also be noted that the inter hole delay adjustment factors proposed in the current modelling framework (Onederra, 2008) are based on limited data and further validation will still be required in primary rock conditions. Although fragmentation may be improved, it is important to note that high intensity blasting with the use of short inter hole delays may be counter productive if the risk of rock mass damage is increased and loading productivity is influenced by the lack of muckpile looseness. Preliminary modelling results have highlighted the need to further quantify the potential impact of short delays on near field damage and downstream loading productivity. This should be considered a priority if short inter hole delays are to be used in primary rock production blasting. Figure 6. Modelling results showing the potential influence of short inter-hole delay times on fines for design D2 (GDCC Domain). It is important to note that simulations are indicative of what may be achieved if all measured and assumed modelling conditions are met. Actual measurable results will undoubtedly be influenced by the field implementation process. For this reason, the implementation of a Quality Assurance / Quality Control strategy (QA/QC) was strongly recommended, particularly as improved designs are implemented in both current and future domains (Secondary and primary rock). The impact on fragmentation outcomes given by variations in pattern geometry is demonstrated for design D2 in Figure 7. In this case, a standard deviation of 0.5 m was assumed for the mean values of burden and spacing. Results show a widening of the predictive envelope, which can translate into coarser or more bi-modal fragmentation outcomes. Figure 7. Potential impact on fragmentation outcomes given by simulated variations in pattern geometry

6 7 CONCLUSIONS A comprehensive production blast monitoring program was conducted in secondary ore domains of the Don Luis pit at the Codelco-Andina operation. The objective of this program was to calibrate and implement a site specific blast fragmentation model to predict fragmentation outcomes in primary rock domains. The rock types or lithological units of main concern to this study included Granodiorita Cascada (GDCC) and Brecha de Turmalina (BXT). A total of four production blasts were comprehensively monitored in secondary rock, three were located in the GDCC domain (i.e. 3724_10, 3724_12 and 3724_09) and one in the BXT domain (i.e. 3708_3). The calibration process allowed the definition and refinement of estimates associated with key rock mass indices which impact on the expected uniformity, mean fragment size and the propensity of the rock fabric to generate fines. The calibrated model used in this study can be best described as a two component model utilising the Swebrec fragmentation distribution function. The adopted approach is stochastic and therefore allows the inclusion of distribution functions to rock material and rock mass input parameters as well as design specific parameters such as hole and charge lengths. The modelling framework also incorporated modelling parameters that can simulate the impact of inter hole delay timing on fragmentation. 14 simulations were conducted to quantify relative changes in ROM fragmentation in primary rock (GDCC and BXT rock types). A range of pattern geometries and corresponding powder factors were investigated. The analysis indicated that for similar pattern geometries, blasting in the GDCC domain has the potential to generate more fines than in the BXT domain. Relative differences may be of the order of 3% to 5% between these two domains. As expected, designs D3 and D6 gave the finest fragmentation in the GDCC domain; and designs D9 and D12 gave the finest fragmentation in the BXT domain. By comparing designs D2 and D2A, modelling results suggested that by decreasing stemming lengths by approximately 1 m, a 1% gain is expected in the amount of fines generated in the GDCC domain. In the BXT domain however the gain was only approximately 0.5%, as shown by comparing designs D8 and D8A. Model calibrations in the BXT domain were only based on a single production blast. More data may be required to improve the predicted capabilities of the model in this particular domain The current modelling framework was used to investigate potential gains in fines generation by introducing shorter delays (e.g. 2 ms to 10 ms). Designs D2 and D8 were used as base cases for the GDCC and BXT domain respectively. Results showed that for the ½ and 1 size fractions with the use of inter hole delays of 2 ms, gains of approximately 2 % and 3.5 % may be achieved in the GDCC domain. The use of very short inter hole delays (e.g. 2 ms) demonstrates gains in the intermediate and fine fractions, however these gains may not be significant if one is to consider the variation associated with modelling predictions, and in particular the lower limit predictive envelope. Preliminary modelling results have highlighted the need to further quantify the potential impact of short delays on near field damage and downstream loading productivity. This should be considered a priority if short inter hole delays are to be used in primary rock production blasting. It is important to note that proposed changes in blasthole configurations and geometry (i.e. tighter patterns) may be restricted by operational matters. These types of constraints should be reviewed and assessed at the operational level.

7 REFERENCES C. V. Cunningham: Fragmentation estimations and the Kuz-Ram model - Four years on. Proceedings of the second international symposium on rock fragmentation by blasting, Keystone, Colorado, 1987, I. Onederra, S. Esen, and A. Jankovic: Estimation of fines generated by blasting - applications for the mining and quarrying industries. IMM transactions, Mining Technology, Vol 113, 2004, No.4: F. Ouchterlony: The Swebrec function: linking fragmentation by blasting and crushing. IMM transactions, Mining Technology, Vol 114, March 2005, No1:A29-A44. J. P. Latham, J. Kemeny, N. Maerz, M. Noy, J. Schleifer and S. Tose: A blind comparison between results of four image analysis systems using a photolibrary of piles of sieved fragments. FRAGBLAST - International Journal of Blasting and Fragmentation 2003, 7: I. Onederra: Empirical charts for the estimation of minimum response time (Tmin) in free face blasting. IMM transactions, Mining Technology, Vol 116, March 2007, No 1: 7-15 I. Onederra: A delay timing factor for empirical fragmentation models. IMM transactions, Mining Technology, February Vol 116, No 4, J. A. Sanchidrian, P. Segarra and L. M. Lopez: A Practical Procedure for the Measurement of Fragmentation by Blasting by Image Analysis. Rock Mechanics and Rock Engineering, November GeoBlast S:A, Final Report PRO ASP 246/07-E, Modelamiento de la Fragmentación Resultante de Tronadura en Roca Primaria''. Emitido para: Proyecto Expansión Andina, CODELCO, Abril 9, 2008.