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The application of PGNAA borehole logging for copper grade estimation at Chuquicamata mine
ARTICLE IN PRESS
Applied Radiation and Isotopes 60 (2004) 771–777
The application of PGNAA borehole logging for copper grade estimation at Chuquicamata mine J. Charbucinskia,*, O. Duranb, R. Frerautc, N. Heresid, I. Pineyrod a CSIRO, Exploration and Mining, P.O. Box 883, Kenmore, QLD 4069, Australia Comision Chile de Energia Nuclear (CCHEN), Casilla 188-D, Codigo, Postal 6500087, Santiago, Chile c CODELCO Chile, Codelco-Norte Division, Duplex 158, Chuquicamata, Chile d Instituto de Innovacion en Mineria y Metalurgia (IM2), Avenida del Valle 738, Ciudad Empresarial, Huechuraba, Santiago, Chile b
Received 18 September 2003; received in revised form 28 November 2003; accepted 11 December 2003
Abstract The field trials of a prompt gamma neutron activation (PGNAA) spectrometric logging method and instrumentation (SIROLOG) for copper grade estimation in production holes of a porphyry type copper ore mine, Chuquicamata in Chile, are described. Examples of data analysis, calibration procedures and copper grade profiles are provided. The field tests have proved the suitability of the PGNAA logging system for in situ quality control of copper ore. r 2004 Elsevier Ltd. All rights reserved. Keywords: PGNAA; Copper ore; Logging
1. Introduction There are relatively few papers presenting the results of the application of prompt gamma neutron activation (PGNAA) borehole logging for in situ estimation of copper grade (Nargawalla et al., 1977; Moxham et al., 1972). The PGNAA borehole logging method and instrumentation, described in an earlier paper (Charbucinski et al., 2003), were recently tested in a number of a large diameter blast holes at CODELCO’s Chuquicamata open-cut copper mine in Chile. In general, timely information about copper grade (obtained in blast holes) would improve almost every stage of copper mining and mineral processing. In the early stages of mining and during mineral processing, knowledge of the copper grade and information on the various impurities present in the ore are fundamental to the optimum exploitation of the ore deposit.
Grade control in blast holes is usually conducted by sampling cuttings deposited on the surface in the form of a cone around the perimeter of the blast hole to obtain borehole geochemistry data. It is important to recognise that there are critical differences between geophysical borehole logging data (for example, PGNAA data) and borehole geochemistry data. Both methods have advantages and disadvantages and in many cases provide complementary information in a particular application. One important issue to consider is the direct comparison of assay and geophysical data, particularly when attempting to develop geophysically derived grade calibrations based on known assay data. The following points should be considered: *
*Corresponding author. Fax: +61-7-3327-4455. E-mail address: [email protected] (J. Charbucinski). 0969-8043/$ - see front matter r 2004 Elsevier Ltd. All rights reserved. doi:10.1016/j.apradiso.2003.12.007
Borehole geochemistry is generated from sampling and analysing the drill cuttings obtained during the drilling process. In contrast, nuclear borehole geophysical methods use the drill hole for access but collect information about the ore/rock surrounding the borehole. Strictly speaking the techniques are not directly comparable because the measurements are made on different ore/rock material. However, in deposits where there is a relatively small ‘nugget
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effect’, the difference in chemical composition between material removed from the drill hole and material immediately adjacent to the drill hole (spatial distribution of ore grade) would be expected to be minimal. Borehole geochemical techniques generally comprise two basic steps—a sampling component and an analytical component. There are errors in both steps; however, substantially greater error is associated with sampling. The ore/rock cuttings generated from a single blast hole can easily exceed 1000 kg yet in many cases the sample weight used for analysis is only 5 g and is rarely more than 100 g. As a result, major errors in the accuracy of a geochemical estimate for blast holes can arise if the sampling process is not rigorous. There are many techniques used for sampling blast hole cuttings and generally each mine employs a procedure that satisfies their individual needs and circumstances.
CCHEN, CODELCO and IM2 with the assistance of IAEA and CSIRO, Exploration and Mining have designed and implemented a project with the main objective of developing a geophysical method for use in blast hole logging for real-time in situ estimation of copper grade. PGNAA logging was selected to be tested with and fulfill the above objective. The PGNAA technique possesses good depth penetration into the rock and instruments based on the PGNAA technique are successfully implemented in the coal, iron ore and cement industries. The neutron-gamma reactions produced by thermal neutrons result in gamma-rays specific to the chemical elements found in the ore. Copper, iron and silicon (the main constituents of the ore) have relatively large thermal neutron-capture crosssections and produce identifiable gamma rays that can be used to determine their respective concentrations in the ore. It is estimated that CSIRO’s SIROLOG PGNAA probe samples the ore/rock mass adjacent to a drill hole out to approximately 0.5 m from the borehole wall in all directions, depending on ore density and moisture content. The estimate of the depth of investigation is based on laboratory tests performed in large geophysical models of copper ore. As a result, PGNAA estimates the composition of a substantially larger volume of the ore/ rock mass than does geochemistry. For the Chuquicamata mine, where 300 mm diameter blast holes of 23 m depth and an average rock mass density of 2.54 gm/cm3 are used, the blast hole would generate approximately 4100 kg of ore/rock cuttings for sampling, whereas SIROLOG PGNAA measures the geophysical response from approximately 33,000 kg of ore/rock surrounding the blast hole.
2. SIROLOG PGNAA logging system The main components of the logging system are presented in Fig. 1: a logging tool, portable winch with a single conductor cable, and a 252Cf source container with a 252Cf a neutron source of 5 mg (100 MBq) activity. The logging tool has a diameter of 100 mm and a casing made of carbon fibre. A 75 mm 75 mm BGO scintillation detector is used. BGO, due to its high density and high effective atomic number, has greater gamma-ray stopping power and provides higher efficiency for gamma-ray detection than other scintillators commonly used in spectrometric equipment. The logging system incorporates stabilizer algorithms to prevent temperature drift from affecting the measurement spectrometric stability (gain drift). The digitized output data are transferred from the logging tool to the up-hole single wire interface supply system (SWISS) interface and a laptop computer. The recorded spectrometric data are stored in 480 pulse height (energy) channels. There is also an option to record incoming pulses in 960 channels. A single extreme-duty 12 V battery powers all of the equipment. A more detailed description of the logging system can be found elsewhere (Charbucinski et al., 2003).
Fig. 1. SIROLOG PGNAA logging system used for static laboratory measurements (a portable winch and 12 V battery are mounted on the A-frame for laboratory work).
ARTICLE IN PRESS J. Charbucinski et al. / Applied Radiation and Isotopes 60 (2004) 771–777
count-rate (cps)
25
20
15 low grade medium grade high grade
10
5 250
300
350
400
450
Energy (channel No.)
Fig. 2. Spectra (>5.4 MeV) recorded in three models having various copper ore grades.
3. Laboratory feasibility tests Laboratory tests were carried out to assess the feasibility of the application of the PGNAA method and logging instrumentation for copper grade estimation in large diameter blast holes. The laboratory tests were conducted at CCHEN laboratory using three large geophysical models (shown in Fig. 1) containing copper ore of various grades. The drums containing the samples were arranged to replicate borehole geometry by placing a card-board tube coincident with the axis of each drum of external diameter equal to the Chuquicamata mine blast hole diameter. Each drum of 1000 l volume contained approximately 2200 kg of copper ore. Static measurements were performed for each model with the recording point of the tool placed in the geometrical centre of the drum. The size of the models represented approximately 90% of the depth range for the SIROLOG PGNAA tool. High-energy sections of the recorded spectra are presented in Fig. 2. The combined Cu+Fe peak is centred around channel 409, whilst the 5.92+6.02 MeV Fe peak appears around channel 314. The spectrometric response of the logging tool varied sufficiently with copper ore grade to warrant the field trials at production benches at Chuquicamata copper mine. Also, the reproducibility tests conducted confirmed the long-term stability of the logging system. The spectra collected in the same model but on various days, during laboratory tests, were practically identical. The results of the field trial reproducibility tests are presented in Section 5 (Fig. 8).
4. Field trials
special sampling procedure, applying Chuquicamata mine protocols and devices, was conducted. In this procedure, four sample increments (designated CA1, CA2, CB1 and CB2) from four wedge-type samplers were collected. Two of these samplers are shown in Fig. 3. By mixing together the increments obtained from the opposing pairs of samplers, two homogenised large samples (on average between 100 and 300 kg) were obtained from each hole. The two homogenised samples were chemically analysed in the mine laboratory for copper grade and also for a number of other elements, including Fe, S, Si and Al. There was no observed correlation between Cu concentrations and concentrations of Fe, Si, Al or S. The results of chemical assays for the two-sample streams correlate very well with each other, as shown in Fig. 4. The standard deviation for the regression (0.14% Cu) is a measure of the error associated with the sampling procedure. Geophysical logging operations followed the sampling. The entire lengths of blast holes (B15–30 m) were logged. The control system was preset to transfer the accumulated digital spectral information (in 480 energy
Fig. 3. Sampling of production blast holes at Chuquicamata mine.
% Cu (basedon channels CA2+CB1) vs %Cu (based on channels CA1+CB2) 3 %Cu = mass-weighed average of CA1+CB2
Static laboratory tests 30
773
2.5 2
R = 0.9636 2
SD = 0.14 %Cu 1.5 1 0.5 0 0
Over 50 blast holes were sampled and subsequently logged during the field trials. The blast holes were selected to provide a wide range of copper grade variation for the calibration of the logging system. A
0.5
1
1.5
2
2.5
3
%Cu = mass-weighed average of CA2+CB1
Fig. 4. Correlation between copper grade results obtained from chemical analysis of samples collected applying dual sampling protocol (57 blast holes).
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channels) after continuously logging 10 cm increments of blast holes, thereby collecting a full energy spectrum for each 10 cm depth increment. A logging speed of 1.5 m/ min was used to provide sufficient counting statistics for the recorded spectra. The logging speed can be increased when using a neutron source of higher activity. Fig. 5 shows a logging operation at one of the production bench blast holes at Chuquicamata mine. Logging operations were conducted with a centralised tool by equipping the tool with a pair of Al-polyurethane centralisers designed for the diameter of blast holes routinely drilled at the mine. A portable logging winch, neutron source container and mechanically operated boom were mounted on the back of a standard utility vehicle commonly utilised at the mine. Movement of the winch was remotely controlled and rotation of the boom was mechanically operated from a distance by applying steel wires, significantly improving radiological safety of the logging operations. Implementation of a remotely controlled hydraulic boom would further reduce the amount of manual handling of the tool and also would reduce the amount of time necessary to commence and complete logging operations at each hole. Productivity of logging operations, using a dedicated logging truck and a suitable hydraulic boom with a wireless remote control, is significantly improved since one person can efficiently conduct the logging.
Fig. 5. Logging operations at Chuquicamata mine.
5. Data handling and calibration The first step in data handling is to match the ‘geophysical’ depth interval with that of the sampling interval. Usually, a 15 m blast hole would be over-drilled by 1–2 m, but, a sample is collected from the depth interval corresponding to 0–15 m. It is necessary therefore, to consider only logging information obtained from the first 150 10 cm-depth increments (splits) for comparison to a sample-derived copper grade value for this hole. In addition, the vast majority of the logged blast holes were dry, but, a few holes, situated on the lower benches of the mine, were partially water filled. Since there is no possibility of applying the same calibration equation for dry and water-filled holes, the partially water-filled blast holes were excluded from the pool of data used for the calibration. Fig. 6 presents a logging profile recorded in partially water-filled borehole. The horizontal axis corresponds to energy (expressed in channel number), whilst the vertical axis indicates depth (in split number). Changes of colour (or intensity of grey in B&W picture) reflect variations of count rate recorded at a given depth. The water level at a depth of 17.6 m (split No. 86) is readily identifiable, through a significant reduction in a count rate recorded above the H-peak (channel 111) and increased intensity recorded around this peak to the bottom of the hole. The changes in count rate are caused by a strong absorption of thermal neutrons in water surrounding the probe inside the 300 mm diameter hole. As the sample from that hole was collected from the 0 to 25 m depth interval, logging information from 0 to 17.6 m would cause the PGNAA-derived Cu grade for the blast hole to be different than the copper grade established using blast hole sampling (for the 25 m thickness of copper ore). Therefore, that hole, together with the few other
Fig. 6. Spectrum bar representation of PGNAA spectra recorded in Hole 2039. The horizontal axis is spectrum channel and vertical channel is spectrum sample (split) measured from the bottom of the hole.
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partially water-filled holes, have been excluded from the calibration data pool. Next, the geophysical data are integrated to match the depth intervals of assay data being used to create the calibration model, for example, an assay interval from 0.5 m to 15.0 m should nominally contain 145 separate geophysical measurement intervals if a 10 cm logging interval is being used. The various interactions of fast and thermal neutrons with the nuclei of the elements present in copper ore result in a large background spectrum relative to the size of the signal resulting from neutron-gamma reactions involving Cu and Fe nuclei. Thus, background removal (Charbucinski et al., 2003) is important and enhances the prompt-gamma peaks of Cu, Fe, Si and H. The resulting ‘background removed composite spectra’ are used to select the best spectral variable(s) to be applied in the calibration equation. The low-energy resolution of BGO detectors prevents the use of narrow spectral windows encompassing the peaks characteristic of a given element (for example copper). Instead, wider spectral windows were used. A number of spectral windows of various widths encompassing characteristic features of the recorded spectra, termed regions of interest (ROI), were selected. Subsequently, spectral ratios (RAT) based on earlier selected ROI were created. All RAT and ROI selected for a given model form a subset of spectral variables. A large number of spectral variables were defined. The numerical values of these spectral variables were established using software. All of the ROI and RAT set up for the estimation of copper grade were then modelled using regression analysis to evaluate the best fit that could be obtained for that parameter. Only the variables having sound physical meaning and relatively low cross correlation were considered for further use. An equation based on the optimum correlation of two variables was chosen as the calibration equation. The calibration equation is % Cu ¼ 0:0446 þ 18:758 RAT5 16:469 RAT3 The variables applied in this equation are: RAT 3 ¼ ROIðch:300 330Þ=ROIðch:101 123Þ; and RAT 5 ¼ ROIðch:375 400Þ=ROIðch:101 123Þ: RAT 5 represents the area under the 7.63 and 7.65 MeV Fe-peaks together with 7.64 and 7.91 MeV Cu-peaks, normalised to the area under the hydrogen 2.23 MeV peak. RAT 3 represents the area under the Fe-only peaks at 5.92 and 6.02 MeV (free of Cu influence, after background removal) normalised to the area under the H-peak. Both spectral variables (RAT 3 and RAT 5) have a physical meaning since the second variable (RAT 3, with
775
a negative coefficient) provides a correction to a joint copper and iron response obtained from the first variable (RAT 5). The normalisation to the H-peak is necessary to correct for neutron flux variations. As the BGO detector-collected spectra have not featured welldefined Cu peaks there was a need to apply RAT based on ROI encompassing Fe 7.63 and 7.65 MeV peaks together with Cu 7.64 and 7.91 MeV peaks. This calibration procedure was intended to strip out the iron response from the combined copper and iron spectral window. Gamma radiation originating from inelastic neutron scattering, prompt gamma capture and delayed gamma activation of other common elements present in copper ore do not affect the high-energy spectral windows (ROI) used in the calibration equation, with the exception of Al prompt gamma radiation. However, due to the very narrow range of Al content variations in Chuquicamata copper ore, this did not affect adversely copper grade estimations. Fig. 7 presents a cross-plot between the logging-derived copper grades and those obtained from chemical assays. The standard deviation of the regression between the values of % Cu-geophysics and % Cu-geochemical, should not solely be interpreted as the error in the PGNAA logging derived prediction. There are two major contributions to the total error of regression: (1) the geostatistical variation error between the sample taken from the inside of the hole and the volume outside the hole which corresponds to that sample (ore heterogeneity); and (2), the sampling error. The drill cuttings from each hole were manually sampled and the samples subsequently chemically analysed by instrumental laboratory assay methods. The sampling error depends on both the sample-collecting error and the error of instrumental chemical analysis. The error of instrumental chemical analysis of geochemical samples is very small, in comparison to the sample-collecting error, and thus, can be neglected. The standard deviation for the PGNAA loggingderived predictions can be assessed when sassay is available, as follows: sPGNAA ¼ ðs2regression s2assay Þ1=2 ; where CALIBRATION OF PGNAA LOGGER FOR CHUQUICAMATA MINE 3 2.5
2
R = 0.9239 σ (regression) = 0.19% Cu σ (PGNAA-log) = 0.14% Cu
2 1.5 1 0.5 0 0
0.5
1
1.5
2
2.5
3
% Cu - chemical
Fig. 7. Cross-plot of log-derived Cu grade vs. % Cu assays.
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sassay ¼ ðs2sampling þ s2ore
1=2 heterogeneity Þ
ssampling for the blast hole data, included in calibration data, was found to be 0.11% Cu and sore heterogeneity has been indirectly assessed as 0.07% Cu. This value was based on the assessment of sore heterogeneity for the ore grade variations along the borehole depth. Therefore, the resulting sassay is 0.13% Cu and sPGNAA has a value of 0.14% Cu. The obtained calibration is valid for porphyry type of copper ore and for copper grade determination in %Cu predictions from repeated logs in hole 261 1
Mean % Cu = 0.70% 0.9
SD = 0.026% Cu
0.8 0.7 0.6 0.5 0.4 0.3 0.2 1
2
3
4
5
6
Log No.
Fig. 8. Copper grade predictions from repeated logs in one of the test holes.
300 mm diameter blast holes. A change of nominal borehole diameter would require re-calibration of the logging system. However, small variations in borehole diameter caused by rugosity of walls do not affect significantly copper grade estimations. To assess the precision of PGNAA logging for estimation of copper grade, reproducibility tests were performed in a number of blast holes. Fig. 8 presents values of logging-derived copper grade estimations obtained through a series of logging operations 30 min apart in one of the test blast holes. The standard deviation of 0.026% Cu is a good indicator of the precision of copper grade estimation by spectrometric PGNAA logging. The trials were mainly focused on the calibration of geophysical logs for estimating the copper grade of the entire blast hole interval. However, the logging system collected data at 10 cm intervals (this interval can be varied) and it is possible to provide mine staff with a semi-quantitative estimate of copper throughout the blast hole profile. Fig. 9 displays the copper grade profiles derived for one of the blast holes. The left-hand side displays estimated copper grade on a split-by-split basis and the right-hand side displays integrated estimates for 1 and 2 m depth intervals. The grade estimates interpreted
Copper grade for hole 2005
Copper grade for hole 2005
0
0
2
2
4
0.79
4
6
0.69
0.59 1.05
1.13
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1.07 8 Depth (m)
Depth (m)
8
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12
12
14
14
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1.07 0.92 0.71
0.53 0.96 1.14
1.31 1.22
0
1
2 % Cu
3
4
0
1
2 % Cu
Fig. 9. Profiles of copper grade estimates derived from PGNAA logging.
3
4
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from the split-by-split profiles are indicative only, as at each given split the tool records spectral information from at least five splits below and above this point. The accuracy of the PGNAA derived grade estimates become more quantitative as the depth interval for integration of logging data increases. Copper grade estimates profiles can be particularly useful for the mine staff when the quality of ore varies significantly with depth, as in the example shown in Fig. 9.
*
*
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grade values for discrete sample intervals, for example, every 2 m. For certain applications, SIROLOG PGNAA logging has the capacity to deliver timely and cost effective results that can be integrated into the existing mine database. Validation tests performed in a large number of blast holes should establish the accuracy of copper grade predictions and the limitations of this technique.
References 6. Conclusions *
*
*
The field tests performed in a large number of production blast holes at Chuquicamata mine have proved the suitability of the PGNAA logging system for in situ quality control of copper ore. The excellent reproducibility of the logging data indicates the good precision of the PGNAA logging instrumentation. In addition to providing copper grades on a per-hole basis, PGNAA logging can also deliver additional information on grade changes down-hole, as well as
Charbucinski, J., Malos, J., Rojc, A., Smith, C., 2003. Prompt gamma neutron activation analysis method and instrumentation for copper grade estimation in large diameter blast holes. Appl. Radiat. Isot. 59, 197–203. Moxham, R.M., Senftle, F.E., Boynton, G.R., 1972. Borehole activation analysis by delayed gamma-rays using a 252Cf neutron source. Econ. Geol. 67, 579. Nargawalla, S.S., Kung, A., Legrady, O.J., Strever, J., Csilag, A., Seigel, H.O., 1977. Nuclear metalog grade logging in mineral deposits. Proceedings of the IAEA Symposium on Nuclear Techniques, Mineral Resources 1977, Vienna, March 1977, pp. 229–263.
Applied Radiation and Isotopes 60 (2004) 771–777
The application of PGNAA borehole logging for copper grade estimation at Chuquicamata mine J. Charbucinskia,*, O. Duranb, R. Frerautc, N. Heresid, I. Pineyrod a CSIRO, Exploration and Mining, P.O. Box 883, Kenmore, QLD 4069, Australia Comision Chile de Energia Nuclear (CCHEN), Casilla 188-D, Codigo, Postal 6500087, Santiago, Chile c CODELCO Chile, Codelco-Norte Division, Duplex 158, Chuquicamata, Chile d Instituto de Innovacion en Mineria y Metalurgia (IM2), Avenida del Valle 738, Ciudad Empresarial, Huechuraba, Santiago, Chile b
Received 18 September 2003; received in revised form 28 November 2003; accepted 11 December 2003
Abstract The field trials of a prompt gamma neutron activation (PGNAA) spectrometric logging method and instrumentation (SIROLOG) for copper grade estimation in production holes of a porphyry type copper ore mine, Chuquicamata in Chile, are described. Examples of data analysis, calibration procedures and copper grade profiles are provided. The field tests have proved the suitability of the PGNAA logging system for in situ quality control of copper ore. r 2004 Elsevier Ltd. All rights reserved. Keywords: PGNAA; Copper ore; Logging
1. Introduction There are relatively few papers presenting the results of the application of prompt gamma neutron activation (PGNAA) borehole logging for in situ estimation of copper grade (Nargawalla et al., 1977; Moxham et al., 1972). The PGNAA borehole logging method and instrumentation, described in an earlier paper (Charbucinski et al., 2003), were recently tested in a number of a large diameter blast holes at CODELCO’s Chuquicamata open-cut copper mine in Chile. In general, timely information about copper grade (obtained in blast holes) would improve almost every stage of copper mining and mineral processing. In the early stages of mining and during mineral processing, knowledge of the copper grade and information on the various impurities present in the ore are fundamental to the optimum exploitation of the ore deposit.
Grade control in blast holes is usually conducted by sampling cuttings deposited on the surface in the form of a cone around the perimeter of the blast hole to obtain borehole geochemistry data. It is important to recognise that there are critical differences between geophysical borehole logging data (for example, PGNAA data) and borehole geochemistry data. Both methods have advantages and disadvantages and in many cases provide complementary information in a particular application. One important issue to consider is the direct comparison of assay and geophysical data, particularly when attempting to develop geophysically derived grade calibrations based on known assay data. The following points should be considered: *
*Corresponding author. Fax: +61-7-3327-4455. E-mail address: [email protected] (J. Charbucinski). 0969-8043/$ - see front matter r 2004 Elsevier Ltd. All rights reserved. doi:10.1016/j.apradiso.2003.12.007
Borehole geochemistry is generated from sampling and analysing the drill cuttings obtained during the drilling process. In contrast, nuclear borehole geophysical methods use the drill hole for access but collect information about the ore/rock surrounding the borehole. Strictly speaking the techniques are not directly comparable because the measurements are made on different ore/rock material. However, in deposits where there is a relatively small ‘nugget
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effect’, the difference in chemical composition between material removed from the drill hole and material immediately adjacent to the drill hole (spatial distribution of ore grade) would be expected to be minimal. Borehole geochemical techniques generally comprise two basic steps—a sampling component and an analytical component. There are errors in both steps; however, substantially greater error is associated with sampling. The ore/rock cuttings generated from a single blast hole can easily exceed 1000 kg yet in many cases the sample weight used for analysis is only 5 g and is rarely more than 100 g. As a result, major errors in the accuracy of a geochemical estimate for blast holes can arise if the sampling process is not rigorous. There are many techniques used for sampling blast hole cuttings and generally each mine employs a procedure that satisfies their individual needs and circumstances.
CCHEN, CODELCO and IM2 with the assistance of IAEA and CSIRO, Exploration and Mining have designed and implemented a project with the main objective of developing a geophysical method for use in blast hole logging for real-time in situ estimation of copper grade. PGNAA logging was selected to be tested with and fulfill the above objective. The PGNAA technique possesses good depth penetration into the rock and instruments based on the PGNAA technique are successfully implemented in the coal, iron ore and cement industries. The neutron-gamma reactions produced by thermal neutrons result in gamma-rays specific to the chemical elements found in the ore. Copper, iron and silicon (the main constituents of the ore) have relatively large thermal neutron-capture crosssections and produce identifiable gamma rays that can be used to determine their respective concentrations in the ore. It is estimated that CSIRO’s SIROLOG PGNAA probe samples the ore/rock mass adjacent to a drill hole out to approximately 0.5 m from the borehole wall in all directions, depending on ore density and moisture content. The estimate of the depth of investigation is based on laboratory tests performed in large geophysical models of copper ore. As a result, PGNAA estimates the composition of a substantially larger volume of the ore/ rock mass than does geochemistry. For the Chuquicamata mine, where 300 mm diameter blast holes of 23 m depth and an average rock mass density of 2.54 gm/cm3 are used, the blast hole would generate approximately 4100 kg of ore/rock cuttings for sampling, whereas SIROLOG PGNAA measures the geophysical response from approximately 33,000 kg of ore/rock surrounding the blast hole.
2. SIROLOG PGNAA logging system The main components of the logging system are presented in Fig. 1: a logging tool, portable winch with a single conductor cable, and a 252Cf source container with a 252Cf a neutron source of 5 mg (100 MBq) activity. The logging tool has a diameter of 100 mm and a casing made of carbon fibre. A 75 mm 75 mm BGO scintillation detector is used. BGO, due to its high density and high effective atomic number, has greater gamma-ray stopping power and provides higher efficiency for gamma-ray detection than other scintillators commonly used in spectrometric equipment. The logging system incorporates stabilizer algorithms to prevent temperature drift from affecting the measurement spectrometric stability (gain drift). The digitized output data are transferred from the logging tool to the up-hole single wire interface supply system (SWISS) interface and a laptop computer. The recorded spectrometric data are stored in 480 pulse height (energy) channels. There is also an option to record incoming pulses in 960 channels. A single extreme-duty 12 V battery powers all of the equipment. A more detailed description of the logging system can be found elsewhere (Charbucinski et al., 2003).
Fig. 1. SIROLOG PGNAA logging system used for static laboratory measurements (a portable winch and 12 V battery are mounted on the A-frame for laboratory work).
ARTICLE IN PRESS J. Charbucinski et al. / Applied Radiation and Isotopes 60 (2004) 771–777
count-rate (cps)
25
20
15 low grade medium grade high grade
10
5 250
300
350
400
450
Energy (channel No.)
Fig. 2. Spectra (>5.4 MeV) recorded in three models having various copper ore grades.
3. Laboratory feasibility tests Laboratory tests were carried out to assess the feasibility of the application of the PGNAA method and logging instrumentation for copper grade estimation in large diameter blast holes. The laboratory tests were conducted at CCHEN laboratory using three large geophysical models (shown in Fig. 1) containing copper ore of various grades. The drums containing the samples were arranged to replicate borehole geometry by placing a card-board tube coincident with the axis of each drum of external diameter equal to the Chuquicamata mine blast hole diameter. Each drum of 1000 l volume contained approximately 2200 kg of copper ore. Static measurements were performed for each model with the recording point of the tool placed in the geometrical centre of the drum. The size of the models represented approximately 90% of the depth range for the SIROLOG PGNAA tool. High-energy sections of the recorded spectra are presented in Fig. 2. The combined Cu+Fe peak is centred around channel 409, whilst the 5.92+6.02 MeV Fe peak appears around channel 314. The spectrometric response of the logging tool varied sufficiently with copper ore grade to warrant the field trials at production benches at Chuquicamata copper mine. Also, the reproducibility tests conducted confirmed the long-term stability of the logging system. The spectra collected in the same model but on various days, during laboratory tests, were practically identical. The results of the field trial reproducibility tests are presented in Section 5 (Fig. 8).
4. Field trials
special sampling procedure, applying Chuquicamata mine protocols and devices, was conducted. In this procedure, four sample increments (designated CA1, CA2, CB1 and CB2) from four wedge-type samplers were collected. Two of these samplers are shown in Fig. 3. By mixing together the increments obtained from the opposing pairs of samplers, two homogenised large samples (on average between 100 and 300 kg) were obtained from each hole. The two homogenised samples were chemically analysed in the mine laboratory for copper grade and also for a number of other elements, including Fe, S, Si and Al. There was no observed correlation between Cu concentrations and concentrations of Fe, Si, Al or S. The results of chemical assays for the two-sample streams correlate very well with each other, as shown in Fig. 4. The standard deviation for the regression (0.14% Cu) is a measure of the error associated with the sampling procedure. Geophysical logging operations followed the sampling. The entire lengths of blast holes (B15–30 m) were logged. The control system was preset to transfer the accumulated digital spectral information (in 480 energy
Fig. 3. Sampling of production blast holes at Chuquicamata mine.
% Cu (basedon channels CA2+CB1) vs %Cu (based on channels CA1+CB2) 3 %Cu = mass-weighed average of CA1+CB2
Static laboratory tests 30
773
2.5 2
R = 0.9636 2
SD = 0.14 %Cu 1.5 1 0.5 0 0
Over 50 blast holes were sampled and subsequently logged during the field trials. The blast holes were selected to provide a wide range of copper grade variation for the calibration of the logging system. A
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Fig. 4. Correlation between copper grade results obtained from chemical analysis of samples collected applying dual sampling protocol (57 blast holes).
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channels) after continuously logging 10 cm increments of blast holes, thereby collecting a full energy spectrum for each 10 cm depth increment. A logging speed of 1.5 m/ min was used to provide sufficient counting statistics for the recorded spectra. The logging speed can be increased when using a neutron source of higher activity. Fig. 5 shows a logging operation at one of the production bench blast holes at Chuquicamata mine. Logging operations were conducted with a centralised tool by equipping the tool with a pair of Al-polyurethane centralisers designed for the diameter of blast holes routinely drilled at the mine. A portable logging winch, neutron source container and mechanically operated boom were mounted on the back of a standard utility vehicle commonly utilised at the mine. Movement of the winch was remotely controlled and rotation of the boom was mechanically operated from a distance by applying steel wires, significantly improving radiological safety of the logging operations. Implementation of a remotely controlled hydraulic boom would further reduce the amount of manual handling of the tool and also would reduce the amount of time necessary to commence and complete logging operations at each hole. Productivity of logging operations, using a dedicated logging truck and a suitable hydraulic boom with a wireless remote control, is significantly improved since one person can efficiently conduct the logging.
Fig. 5. Logging operations at Chuquicamata mine.
5. Data handling and calibration The first step in data handling is to match the ‘geophysical’ depth interval with that of the sampling interval. Usually, a 15 m blast hole would be over-drilled by 1–2 m, but, a sample is collected from the depth interval corresponding to 0–15 m. It is necessary therefore, to consider only logging information obtained from the first 150 10 cm-depth increments (splits) for comparison to a sample-derived copper grade value for this hole. In addition, the vast majority of the logged blast holes were dry, but, a few holes, situated on the lower benches of the mine, were partially water filled. Since there is no possibility of applying the same calibration equation for dry and water-filled holes, the partially water-filled blast holes were excluded from the pool of data used for the calibration. Fig. 6 presents a logging profile recorded in partially water-filled borehole. The horizontal axis corresponds to energy (expressed in channel number), whilst the vertical axis indicates depth (in split number). Changes of colour (or intensity of grey in B&W picture) reflect variations of count rate recorded at a given depth. The water level at a depth of 17.6 m (split No. 86) is readily identifiable, through a significant reduction in a count rate recorded above the H-peak (channel 111) and increased intensity recorded around this peak to the bottom of the hole. The changes in count rate are caused by a strong absorption of thermal neutrons in water surrounding the probe inside the 300 mm diameter hole. As the sample from that hole was collected from the 0 to 25 m depth interval, logging information from 0 to 17.6 m would cause the PGNAA-derived Cu grade for the blast hole to be different than the copper grade established using blast hole sampling (for the 25 m thickness of copper ore). Therefore, that hole, together with the few other
Fig. 6. Spectrum bar representation of PGNAA spectra recorded in Hole 2039. The horizontal axis is spectrum channel and vertical channel is spectrum sample (split) measured from the bottom of the hole.
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partially water-filled holes, have been excluded from the calibration data pool. Next, the geophysical data are integrated to match the depth intervals of assay data being used to create the calibration model, for example, an assay interval from 0.5 m to 15.0 m should nominally contain 145 separate geophysical measurement intervals if a 10 cm logging interval is being used. The various interactions of fast and thermal neutrons with the nuclei of the elements present in copper ore result in a large background spectrum relative to the size of the signal resulting from neutron-gamma reactions involving Cu and Fe nuclei. Thus, background removal (Charbucinski et al., 2003) is important and enhances the prompt-gamma peaks of Cu, Fe, Si and H. The resulting ‘background removed composite spectra’ are used to select the best spectral variable(s) to be applied in the calibration equation. The low-energy resolution of BGO detectors prevents the use of narrow spectral windows encompassing the peaks characteristic of a given element (for example copper). Instead, wider spectral windows were used. A number of spectral windows of various widths encompassing characteristic features of the recorded spectra, termed regions of interest (ROI), were selected. Subsequently, spectral ratios (RAT) based on earlier selected ROI were created. All RAT and ROI selected for a given model form a subset of spectral variables. A large number of spectral variables were defined. The numerical values of these spectral variables were established using software. All of the ROI and RAT set up for the estimation of copper grade were then modelled using regression analysis to evaluate the best fit that could be obtained for that parameter. Only the variables having sound physical meaning and relatively low cross correlation were considered for further use. An equation based on the optimum correlation of two variables was chosen as the calibration equation. The calibration equation is % Cu ¼ 0:0446 þ 18:758 RAT5 16:469 RAT3 The variables applied in this equation are: RAT 3 ¼ ROIðch:300 330Þ=ROIðch:101 123Þ; and RAT 5 ¼ ROIðch:375 400Þ=ROIðch:101 123Þ: RAT 5 represents the area under the 7.63 and 7.65 MeV Fe-peaks together with 7.64 and 7.91 MeV Cu-peaks, normalised to the area under the hydrogen 2.23 MeV peak. RAT 3 represents the area under the Fe-only peaks at 5.92 and 6.02 MeV (free of Cu influence, after background removal) normalised to the area under the H-peak. Both spectral variables (RAT 3 and RAT 5) have a physical meaning since the second variable (RAT 3, with
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a negative coefficient) provides a correction to a joint copper and iron response obtained from the first variable (RAT 5). The normalisation to the H-peak is necessary to correct for neutron flux variations. As the BGO detector-collected spectra have not featured welldefined Cu peaks there was a need to apply RAT based on ROI encompassing Fe 7.63 and 7.65 MeV peaks together with Cu 7.64 and 7.91 MeV peaks. This calibration procedure was intended to strip out the iron response from the combined copper and iron spectral window. Gamma radiation originating from inelastic neutron scattering, prompt gamma capture and delayed gamma activation of other common elements present in copper ore do not affect the high-energy spectral windows (ROI) used in the calibration equation, with the exception of Al prompt gamma radiation. However, due to the very narrow range of Al content variations in Chuquicamata copper ore, this did not affect adversely copper grade estimations. Fig. 7 presents a cross-plot between the logging-derived copper grades and those obtained from chemical assays. The standard deviation of the regression between the values of % Cu-geophysics and % Cu-geochemical, should not solely be interpreted as the error in the PGNAA logging derived prediction. There are two major contributions to the total error of regression: (1) the geostatistical variation error between the sample taken from the inside of the hole and the volume outside the hole which corresponds to that sample (ore heterogeneity); and (2), the sampling error. The drill cuttings from each hole were manually sampled and the samples subsequently chemically analysed by instrumental laboratory assay methods. The sampling error depends on both the sample-collecting error and the error of instrumental chemical analysis. The error of instrumental chemical analysis of geochemical samples is very small, in comparison to the sample-collecting error, and thus, can be neglected. The standard deviation for the PGNAA loggingderived predictions can be assessed when sassay is available, as follows: sPGNAA ¼ ðs2regression s2assay Þ1=2 ; where CALIBRATION OF PGNAA LOGGER FOR CHUQUICAMATA MINE 3 2.5
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R = 0.9239 σ (regression) = 0.19% Cu σ (PGNAA-log) = 0.14% Cu
2 1.5 1 0.5 0 0
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% Cu - chemical
Fig. 7. Cross-plot of log-derived Cu grade vs. % Cu assays.
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sassay ¼ ðs2sampling þ s2ore
1=2 heterogeneity Þ
ssampling for the blast hole data, included in calibration data, was found to be 0.11% Cu and sore heterogeneity has been indirectly assessed as 0.07% Cu. This value was based on the assessment of sore heterogeneity for the ore grade variations along the borehole depth. Therefore, the resulting sassay is 0.13% Cu and sPGNAA has a value of 0.14% Cu. The obtained calibration is valid for porphyry type of copper ore and for copper grade determination in %Cu predictions from repeated logs in hole 261 1
Mean % Cu = 0.70% 0.9
SD = 0.026% Cu
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Fig. 8. Copper grade predictions from repeated logs in one of the test holes.
300 mm diameter blast holes. A change of nominal borehole diameter would require re-calibration of the logging system. However, small variations in borehole diameter caused by rugosity of walls do not affect significantly copper grade estimations. To assess the precision of PGNAA logging for estimation of copper grade, reproducibility tests were performed in a number of blast holes. Fig. 8 presents values of logging-derived copper grade estimations obtained through a series of logging operations 30 min apart in one of the test blast holes. The standard deviation of 0.026% Cu is a good indicator of the precision of copper grade estimation by spectrometric PGNAA logging. The trials were mainly focused on the calibration of geophysical logs for estimating the copper grade of the entire blast hole interval. However, the logging system collected data at 10 cm intervals (this interval can be varied) and it is possible to provide mine staff with a semi-quantitative estimate of copper throughout the blast hole profile. Fig. 9 displays the copper grade profiles derived for one of the blast holes. The left-hand side displays estimated copper grade on a split-by-split basis and the right-hand side displays integrated estimates for 1 and 2 m depth intervals. The grade estimates interpreted
Copper grade for hole 2005
Copper grade for hole 2005
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Fig. 9. Profiles of copper grade estimates derived from PGNAA logging.
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from the split-by-split profiles are indicative only, as at each given split the tool records spectral information from at least five splits below and above this point. The accuracy of the PGNAA derived grade estimates become more quantitative as the depth interval for integration of logging data increases. Copper grade estimates profiles can be particularly useful for the mine staff when the quality of ore varies significantly with depth, as in the example shown in Fig. 9.
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grade values for discrete sample intervals, for example, every 2 m. For certain applications, SIROLOG PGNAA logging has the capacity to deliver timely and cost effective results that can be integrated into the existing mine database. Validation tests performed in a large number of blast holes should establish the accuracy of copper grade predictions and the limitations of this technique.
References 6. Conclusions *
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The field tests performed in a large number of production blast holes at Chuquicamata mine have proved the suitability of the PGNAA logging system for in situ quality control of copper ore. The excellent reproducibility of the logging data indicates the good precision of the PGNAA logging instrumentation. In addition to providing copper grades on a per-hole basis, PGNAA logging can also deliver additional information on grade changes down-hole, as well as
Charbucinski, J., Malos, J., Rojc, A., Smith, C., 2003. Prompt gamma neutron activation analysis method and instrumentation for copper grade estimation in large diameter blast holes. Appl. Radiat. Isot. 59, 197–203. Moxham, R.M., Senftle, F.E., Boynton, G.R., 1972. Borehole activation analysis by delayed gamma-rays using a 252Cf neutron source. Econ. Geol. 67, 579. Nargawalla, S.S., Kung, A., Legrady, O.J., Strever, J., Csilag, A., Seigel, H.O., 1977. Nuclear metalog grade logging in mineral deposits. Proceedings of the IAEA Symposium on Nuclear Techniques, Mineral Resources 1977, Vienna, March 1977, pp. 229–263.