Chapter III Research methodology

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This research examined the impacts of resource estimation methods on the MCF. The Mine call factor concept is derived as a percentage in which the gold accounted for, (metal recovered plus the residues) is compared against the metal called for (derived through mineral ore reserve estimation). If the processes of geological mapping, sampling and assaying for gold are perfect, the reserve evaluation process will be based on a perfect geological and resource model. There is also need to have a flawless tonnage measurement system along the mining and reduction plant processes to achieve a 100% (MCF). The MCF theory or concept can be summarized as an efficiency measurement factor that indicates apparent and realistic gold losses along the mining project value chain. The apparent losses are caused by errors introduced during sampling, assaying and resource modelling (geological modelling and survey measurements). Realistic losses are those caused by blasting during mining, tramming, hoisting and also through gold theft from mining to the reduction plant. There is therefore need for a water tight system that avoids gold losses from mining, tramming, hoisting and all the way to the processing plant.

Resource estimations through geological modelling and grade estimation have to be accurate.

The point to note along the process is to remember that an inaccurate interpolation of assay grade values in a mineral resource block will lead to undervalued predictions where sampled assay values are low and overstated values where the sample values are high. Hence a comprehensive sampling and assaying procedure has to be implemented to reduce sampling errors and an appropriate resource estimation method has to be applied to reduce associated errors. The steps subsequent to sampling are creation of a robust resource model, application of appropriate resource estimation methods for high grade narrow reefs in the structurally

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controlled mesothermal deposits, minimization of misclassification of ore blocks which trigger process improvements that may lead to an improved MCF.

This chapter focused on the motivation for the research. It introduced the concept;

background and history of the study area, the statement of the problem which this thesis intended to solve, objectives and scope of the study were also highlighted.

1.1 Background of the Case study Area Location

Mazowe Mine is located approximately 50km north of Harare, in the Mashonaland Central Province and Harare Mining District. (Grid Reference 797674 and Map References:

Concession 1730B4 and 1730D2 in the Harare Mining District.) (See Figure 1.0: Locality Plan)

Access to the mine from Harare is by a wide tarred road 42km to Mazowe Hotel, followed by 8km of narrow tar, to the west of the Harare - Bindura road. A rail line from Harare passes through the mine, linking up, with regional centres like Glendale, Bindura and Shamva.

Figure 1: Illustration of Mazowe mine location.

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6 History of the Study area

The history of Mazowe mine is largely associated with the reef called Jumbo Mine. Prior to 1890, it is estimated that the Ancients extracted at least 150 000 ounces at Jumbo mine. In 1903 the Jumbo Gold Mining Company was floated and this marked the first substantial development of the mine. During the period 1906/1907, a 30 stamp mill was erected and the company secured most of the adjoining claims which include the Jumbo N.E. extension and the Ceowara claims on Amatola farm.

As the Mine increased in depth, pay shoots became shorter and further apart hence development was stopped in 1912. The decline continued until 1917 when milling was stopped. During the years 1906 to 1917 a total of 293 000 tonnes were treated for a yield of 147 587 ounces (4590kg) of gold, giving a recovery grade of 15.7 g/t.

Following closure of the Jumbo Mining Company in 1917, the mine was let out on tribute and was worked until 1931. Between 1932 and 1953, the Jumbo area was a hive of individual, self-contained small workings which included the Carnbrae, Birthday, Connaught, Bojum, Bucks and Flowing Bowl. In 1953 all existing tributes were terminated and holdings were acquired by Lonrho which operated the whole area as a single entity. This was achieved by a system of crosscuts, mined to link the different holdings and today they serve as haulages.

During this period, Nucleus and Carnbrae continued to operate separately under the Murdoch Eaton brothers but were finally acquired by Lonrho in 1962. From 1962 onwards, production became steady and continuous. Production peaked between 1965 and 1973 when it averaged 98kg (3150 oz) per month. After 1973, it declined, reaching its lowest in 1991. In the same year, Independence Gold Mining (Pvt) Limited took over. In 2002, Metallon Gold Corporation, a South-Africa based company acquired Independence Gold Mining and took over Mazowe Mine. Since then, post-Independence Gold Mining production has been rising from a low of 12,125oz (2001) to 15,050oz (2005). After 2005 production went on a decline due to the solid economic conditions that prevailed until the 2009. However production recommenced in 2013 and currently the mine is producing about 1 200ounces per month.

Gold Mineralisation

The gold mineralisation is concentrated around the north-eastern tip of a granodiorite stock, but extends eastwards into feldspar porphyry intrusive (see figure 2). Feldspar porphyries

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occur in the eastern to southern parts of the mine complex. The granodiorites are of very porphyritic nature, consisting of phenocrysts of quartz, plagioclase feldspar, pethite and minor biotite, sericite, epidote and other accessory opaque minerals. To the east, feldspar porphyries grade into metabasaltic rocks of the Upper Greenstones. They are intercalated with banded iron formation in places. Thin ultramafic units/ lithologies are known to occur to the eastern part in the footwall of the Jumbo mineralised shear zone.

The Geology of the Mazowe Mine

Figure 2 (adapted from Mazowe Mine internal reports 1999)

Figure 2 shows the different reef positions in spatial space (highlighted in dotted red boundary) and the geology of the Mazowe gold fields. Mazowe gold deposit multiple shears, have an inter reef spacing ranging between 50m to 100m across strike. The Mazowe gold deposit comprises of multiple east-west striking reefs with some moderate northeast plunge

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sub parallel shear zone hosting high nugget gold. The mine has vast potential as it has a strike length in excess of 2.7 +1km thick and is open ended on strike and down dip.

There are three principal dyke systems in the mine. In the Connaught section, narrow basic dykes have intruded into the mineralised shear zone, often splitting it into two. Cutting across all the principal mineralised shear zone systems is a north-east/south-west quartz porphyry granite dyke dipping at a shallow angle to the south-east with a width of 5m. The youngest dyke in the mine is a dolerite intrusion which also cuts across the principal mineralised shear zones. This seven metre thick dyke has a dome like form and dips flatly to the west in the Connaught to Bucks area and flatly to the south in the Nucleus 2 to Carnbrae area.

The shears are similar, zones of brittle-ductile shearing ranging from 10cm to +2m in thickness which are grouped into different domains in plain view according to parting distances. The shear zones splay and link in an anastomosing pattern both on dip and strike and are connected by linking duplex structures. The shear zones thrust displacements, or oblique thrust displacements which are sinistral. The duplex structures form gold reefs which are sub-parallel, quartz filled shears (see figure 3 below) with a sharp contact to the wall rock.

Mazowe Mine Schematic Cross Section

Figure 3 (adapted from Mazowe mine resource estimation 2013 internal report).

The diagram illustrates different quartz filled shears hosting reefs of Mazowe Mine. The Mazowe gold fields consist of fifteen narrow reefs whose mineralized zones are associated

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with gold occurrences. These are characterized by silicification, sulphide mineralisation (up to15%) and only to a limited degree with quartz vein. Quartz, scheelite, pyrrhotite and arsenopyrite also occur. Where the porphyritic rock hosts the shears, pyrrhotite dominates and there is a tendency to see less quartz within the shear. These reefs pinch and swell with highly variable grade distribution ranging (+1g/t up to +1000g/t). The erratic high grades are intermixed with low grades and averaging 10g/t to 11g/t). Shear zone continuity in relation to the grade continuity has to be understood beyond doubt (5cm to +2m thickness).

Two main mining methods are employed, namely jackhammer breast stoping and underhand stoping. 30m by 30m mining blocks are developed, after which a breast stope is mined away from the block raise or an underhand bench from the top drive breaking into the block raise.

Box raises are mined at 7m apart from the bottom/tramming drive, simultaneously with the advancing face.

Pillar reclamation presently accounts for 30% of the tonnage, with the most appropriate mining method being employed depending on the size and lay out of pillars. In a single stope face, holes are drilled on a chevron pattern, with a burden of 0.8m and a spacing of 0.8m, to a depth of 1.5m and over a 15m long stope panel. A minimum stope width of 80cm is applied.

1.2 Problem Statement

The most important part of any research is the statement of the problem as it gives directions of what has to be investigated. It also outlines the limits within which the study will be conducted to ensure that the research remains on course in terms of addressing the problem.

According to (Leedy and Ormond, 2005 p101), most research problems are too complex to be solved, they need sub research questions to guide the research.

In a high nugget deposit such as Mazowe gold reefs, erratic gold occurrence makes it difficult to decide whether the block is ore or waste due to the low repeatability and reproducibility of the samples. “Therefore the precisions of sampling for these types of mineralization are very sensitive to the sampling method, which should be as accurate as possible” (Chieregati and Pitard, 2009 p109). The Mazowe deposit contains a significant proportion of coarse gold.

Free gold constitutes up to +70% of current gold production which increases the sampling challenge. The randomness introduced by the high nugget effect makes extrapolation difficult, with global estimates likely to be more reliable than local estimates.

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In high nugget narrow reef deposits, ore/ waste classification is a challenge. This may partly explain why the MCF of Mazowe Mine is problematic. According to (Donaldson et al., 2014 p714) “understanding the geology of an orebody is essential in understanding ore forming processes and spatial impacts in order to produce accurate resource estimations”. The major challenges facing Mazowe Mine are poor grade control, low mine call factor (LMCF) and ore/waste classification. These issues result in suboptimal performance. It is deemed these problems are attributable to the nature of the mineralization and ore determination methods.

The MCF is a major measure of the efficiency of the production process. MCF indicates deviation from a perfect mining system where there are no errors in estimation and no material losses along the value chain. Lower than expected MCF is a sign of an imperfect practical situation indicative of very low in-situ gold recovery, presented by Mazowe mine.

The MCF compares the gold estimated in situ by geologists with the amount of gold produced in the plant. Mazowe Mine MCF is generally low ranging between 40% and 60%

i.e. only 40% to 60% of the expected gold from the reserve model is realised in the plant.

Which implies that along the mining value chain 60% to 40% of the expected gold is lost (or unaccounted for) this has an impact on the mine financial model. However, the problem is encountered in most gold mines at different levels.

The low MCF problem has bedevilled the operation for a long time. It has been suggested that the “missing” gold is associated with fines and is still underground in cracks, walls and footwall in old stopes. A chemical mining program to recover the gold is at a feasibility stage.

Mazowe Mine has experienced an increase in the gap, between the estimated block grades and the mill head grade evidenced by the drop in the MCF from 80% in the 1990’s to the current low of 48% (a decrease of 32%). The changes in the MCF cannot be attributed only to gold dust lost into cracks and crevices during mining and also losses during both horizontal and vertical tramming. A lot of resources and time are being invested to explain gold accounting variances, re-assaying to the extent of even trying in situ chemical mining. The easy solution has been to use factors to reduce estimated grades to expected actual results e.g.

if a block is estimated at 2.4 g/t a factor of 0.6 is applied so that the expected grade from the block is 1.44 g/t. However, the actual factors that cause this discrepancy are not understood.

Where situations like this present themselves, it is highly likely that there is a high magnitude of difference between face sample values and mined reserve block values.

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The resource estimation method could be one of the main contributing factors to LMCF.

This is indicated by the number of stopes that are abandoned due to grades lower than estimated. The compliance with mine planning can be as low as 20%.

The estimated resource values of mined blocks will be compared to re-estimation done using the deterministic and geostatistical methods. The results were evaluated against the realised MCF. During the research, the role of geological data associated with resource estimation and interpretation was highlighted. This is according to (Barnes and Gossage, 2014 p185) who highlighted that “The estimation technique is of critical importance in the choice of grade boundary modelling along with the type of mineralisation being modelled”.

The author’s aim was that the research should indicate method suitability and lead to a better way of estimating the mineral resource and understanding of the reef characteristics. This will culminate in an improved resource model and effective estimation strategies for the typical Mazowe deposit. The resource model will indicate realistic expectations based on geology and data density that account for data extremities in the context of geology and grade continuity. Mines with similar deposits and facing similar challenges will also benefit.

According to (Dusci et al., 2005 p103) “Geological and resource variability and uncertainty is a fundamental source of risk, often having the greatest economic impact on a mining project.

Poorly understood geological and grade models and inappropriate mineral resource estimation methods lead to uneconomic properties being declared as economic resulting in investment losses. The high gold nugget, together with the mining process complexities makes it difficult to pinpoint the source of major problems along the value chain.

It is against this background that the statement of the problem can be stated as to examine whether the resource estimation method is a major contributing factor to low Mine Call Factor.

1.3 Literature Review

Researching on the effects of Low Mine Call Factor (LMCF) in narrow gold reefs is not a new research area in the mining industry. The history of LMCF draws way back to the evolution of gold mining. Over the years, geologists and engineers have failed to eradicate the problem. Generally, many researchers have proposed ways of mitigating against the LMCF at different deposit types, however, the problem is more prevalent in high nugget shallowly dipping gold narrow deposits. Hence most mining houses who have ventured in

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such deposits have employed stope sweeping to reduce gold losses. Intensified stope sweeping in some cases has improved the MCF. In 2015, Mazowe MCF improved from 40%

to 65% (an increment of 25%) however, it remained below the expected best practice which should range between 94% and 106%. This implies that there could be apparent loses manifesting in the MCF.

According to (Dominy, 2003 p242) “High-nugget effect gold–quartz reefs are one of the most challenging styles of mineralisation to evaluate and exploit. Within the high nugget environment, confidence in the tonnage estimate is variable depending upon geological continuity, though it is usually higher than the confidence in the grade estimate”. This implies that most metal deposits have geological continuity which does not necessarily imply grade continuity. The author further argued that “a reef may have good vertical and horizontal global continuity; however, if its width varies both erratically and significantly on a local scale, the tonnage estimate will be poor if the drilling density is insufficient to pick up such variations.” Taking note of Dominy’s (2003) arguments, comprehensive standard operating procedures for, sampling and survey measurements as well as weightometer calibrations have to be put in place so as to reduce erroneous estimations. Due diligence is required during resource estimation to prevent reckless evaluations from masking the real MCF.

It is possible to estimate the appropriate MCF through improving resource estimation, by applying a suitable estimation method, be it deterministic or geostatistical. Spatial data derived through drilling samples or channel samples is converted to point locations through compositing is used to estimate values of non-sampled positions through spatial interpolation.

(Luo et al., 2008 p947) highlighted that “a variety of deterministic and geostatistical interpolation methods are available to estimate variables at non- sampled locations but, depending on the spatial attributes of the data, accuracies vary widely among methods.”

Methodology applicability and suitability of purpose has to be considered to ensure that apparent losses do not inflate the MCF. Methodology applicability can be verified, as highlighted by (Parker, 2012 p721) who stated that “the inaccuracy in estimating mineral resources and Ore reserves is determined by comparing depletions from the long-range model to short-range model”

The geostatistical methods are considered as an unbiased and are advantageous over other methods because of their ability to measure variability; this was highlighted by (Krige1981 p25). Variability can either be chaotic or orderly (related to distance and known direction)

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occurs over different (long or short) scales. Geostatistical methods estimate and model variability and make use of it in the estimation process for grade interpolation. However, the major assumption would be that the input is of a good quality and accurate issues surrounding the data are taken care of.

Reconciliation of the estimated grade against the mined grade and the comparison of sampled (“actual”) grade value to estimated value for the blocks by the polygonal, deterministic and the geostatistical estimated methods are the other mitigation ways to increase MCF in high nugget narrow gold quartz reefs.

1.4 Justification

LMCF is actually a cause of concern in most gold deposits and the problem is more prevalent in shallowly dipping high nugget deposits and varies from deposit to deposit. It is also affected by the mining processes implemented at each mining site. Geologist and mining engineers seem to have failed to find a permanent solution to the problem. Chieregati and Pitard (2009, p108) discussed that metal losses may arise from poor resource estimation, inappropriate grade control measures; unreliable, inaccurate and less representative assay results; non-adherence or improper sampling and assaying procedures; inaccurate recoveries and residue estimation and inaccurate weightometer calibrations leading to understating or overstating of milled tonnages. The significance of the apparent losses has to be highlighted and be mitigated against.

Within the turn of the century, very few economically viable gold deposits have been discovered and generally across the world, the cost of mining and processing a tonne of gold ore has increased. Hence there is need to mitigate LMCF effects by finding out the major contributing factors so as to reduce their adverse impact (high risk to business associated with high nugget deposits).

1.5 Objectives

Authorities define objectives as short statements of intend. In this research, objectives meant what the researcher intended to achieve through carrying out the research. The study seeked to attain the following objectives;

 Asses the resource model which in turn should indicate geological continuity, reef geometry and grade continuity.

 Assess the application of deterministic and geostatistical methods in resource estimation of high nugget gold narrow reef deposit.

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 Trigger resource estimation process improvements.

1.6 Definition of Terms

Mine Call Factor is the ratio, expressed as a percentage, of the gold called for from all sources to the gold recovered plus residues in the metallurgical plant. An efficiency of 100%

would equate to complete success and a system under control, but values ranging between 94 to 106 % would be considered acceptable.

Mineral Resource is a known quantity in terms of mass or volume and quality (grade) of a non-metallic or metallic deposit which can be approximated and interpreted from specific geological evidence and knowledge and with reasonable prospects for economic extraction.

Resource Estimation Method is the technique used to approximate the tonnage and grade of a given mineral.

1.6 Research Questions

Leed (1972, p234) defines research questions as “all sub questions which when answered help to answer the main question under investigation”. This research was guided by the following research questions;

 Does the geological model reflect both geological reef geometry and grade continuity?

 Does reef thickness have an impact on mineral resource estimation and classification?

 Do the results from the different mineral resource estimation methods indicate significant difference?

 Do the results of the mineral resource estimation methods assessed warrant any changes to the current system?

1.7 Delimitations

Hakim C (1987, p243) defines delimitations as ‘those factors that limit the scope and define the boundaries of the research study. The physical boundary of this research is Mazowe Mine gold deposit. The theoretical boundaries will be the body of knowledge under scrutiny, and for this research the area to be scrutinized affects the resource estimation methods on MCF in a narrow reef high nugget deposit.

1.7.1 Limitations

Tuckman (1972, p132) defines limitations as “all factors that hinder the collection of all possible research data”. Any research has limitations emanating from methodology and

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implementation problems. This study has some limitations that have to be noted which are either technical, temporal and most of them are aligned to data acquisition and storage. The foreseen limitations in this study included;

 Time consuming to collect historical data, hence to save time the researcher selected reefs whose mining historical data was stored in the mine main database system.

 The data capturing process would require training and payment of data captures.

However, since the data was compared to the current system, it was prudent to use what is already available.

 The data acquisition process presented challenges since the mine does not have a robust resource database. To mitigate the issues surrounding the data collection issues, only reefs with representative data were used in this research.

 The resource estimation methods may not be easily compared due to their own shortfalls or because of the sampling procedures. The available geological descriptive data was used to mitigate apparent shortfalls.

1.7.2 A research roadmap

Figure 4: shows thesis road map for the research project.

Figure 4 above shows thesis road map as from proposal formulation to poster presentation of the final project. There are numerous steps involved upon confirmation of the thesis proposal

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up until poster presentation and these include introduction, literature review, data collection, data analysis and validation, methods comparison and compilation and finalisation of the thesis.

Each chapter is introduced separately with a separate conclusion which in turn link subsequent chapters. This causes redundancy which is less significant compared to the benefits of linking chapters.

Literature review is however a continual process throughout the scope of the project since it involves researching on work previously done around the proposed topic. Data collection is the most time consuming process since the author is required to gather all necessary information. Data analysis and validation are basically done during and after data collection since not all data is information, it is required to go through a filtering process of winnowing, selecting only important data. Resource estimation methods comparison suitability will be done since a method can predict values better than another method depending on the deposit characteristics as indicated by (Luo et al., 2008, p947). In this research, geostatistical and deterministic methods estimation results were compared against mined block grade and finally compilation and finalisation of the thesis was done.

1.8 Assumptions

According to (Babbie 1998, p124) defines an assumption as, “a proposition which an individual takes to be true without having provided or considered evidence in relation to it”.

This study is guided by the following assumptions;

 The mine management and technical services team would be ethical by giving accurate available data without trying to protect their back sights.

 The technical staff associated with mineral resource and mineral reserves compilation and related data collection would be professional accepting constructive criticism along the process.

 The sampling method did not change over the years.

 The assay data quality is similar as well over the years.

 The method comparisons would yield the intended results.

1.9 Conclusion

This chapter basically introduced the background information of the study, statement of the problem, objectives and justification of the research project. The background information

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gave a location, history and brief description of the nature of the Mazowe mine deposit. The problem statement then highlighted the importance of understanding the geological model and the importance of selecting an appropriate resource estimation method. Poorly understood geological, grade models and inappropriate mineral resource estimations methods lead to uneconomic properties being declared as economic resulting in investment losses.

High nugget gold, compounded with the mining process complexities makes it difficult to pinpoint the source of major problems along the value chain. As according to (Dusci et al., 2005 p103) “Geological and resource variability are a fundamental source of risk, often having the greatest economic impact on a mining project”. The subsequent chapter 2 will focus on the review of the related literature.

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Chapter II

Literature Review 2.0 Introduction

This chapter covers relevant literature reviewed in the study. According to (De Vos 2002, p103), literature review is an integral part of empirical research which enables exposure to the most authoritative empirical research findings applicable to the subject being researched and prevents duplication of previous studies. It is only after the verification of past research and engagement of subsequent research that a researcher may contribute to new academic knowledge. In this research, LMCF, reconciliation factors, mineral sampling concepts and resource estimation concepts are reviewed.

2.1 Mine Call Factor Overview

Researching causes of LMCF in narrow gold reefs is not a new topic in the mining industry.

The history of lower than expected MCF draws back to the evolution of gold mining. It occurs at varying extents in all gold mines. This was also highlighted by (Pitard 2014, p749) who stated that “major discrepancies between mine estimates and estimates from plant metallurgical balances are a common problem in many gold and base metal mines the world over.” However this research will not concentrate on the usual causes related to loss of gold fines into cracks and crevices but will assess the estimation process and methodologies as a main contributing factor. The estimation process commences with the sampling process. This resource estimation process is one of the key processes at the beginning of a mining process.

This is because the mine planning process is based on estimates, not real values where blocks are classified as ore or waste based on again estimates rather than real values.

The mining technical staffs (geologists and engineers) have failed to eradicate the problem and generally resort to stope sweeping to mitigate the problem. However, loss of gold in fines and theft cannot explain it all, apparent gold is a possibility. Therefore apparent losses should be understood so that efforts to mitigate only realistic loses are implemented. A mining project has to make a profit in the shortest time possible because of fluctuations in metal prices, hence the need to understand the process complexities in time so as to use the knowledge base as a competitive advantage. The knowledge base will help in cost reduction and increase profit margins. This is why reconciliation is carried out to understand variances so that they can be minimised.

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The MCF used as a modifying factor when estimating reserves as well as a technical performance indicator which depends on how well a system is understood and managed. If a LMCF is prevalent like in the case of Mazowe mine (see figure 12), it has an adverse impact on the breakeven value, because a LMCF also has a negative financial impact (impact of fixed costs against achieved production. Currently, the cut-off grade (breakeven value) is +4g/t. This reduces the minable reserves preferring selective mining (low tonnage high grade); which is tantamount to mineral resource sterilisation and wastage.

Accurate geological modelling is essential in deposits like Mazowe so as to understand the shear zone structural complexities. The geological and mining models should be updated continuously, without that, it is highly possible to miss the targeted reef and follow splays.

Mining which is not spatially compliant in three dimensional spatial space is usually detrimental to the grade and cost profile and reserve estimation as well. The problem statement indicated that the Mazowe style of gold occurrence is a high-nugget-hosted mesothermal deposit in a structurally complex Achaean Harare greenstone belt. Free gold occurs in fractures, angular to shear bands and such gold is amenable to liberation by blasting and therefore tends to be left behind in stopes with the fine ore fraction (“fines”).

High nugget due to sampling errors is very problematic at Mazowe mine due to the nature of gold occurrence. Sixty percent of the gold deposit is from coarse and clusters of fine gold.

The issues surrounding coarse gold sampling problems cannot be totally resolved but if the problem is understood then mitigation measures can be put in place. The Mazowe mine gold deposit systems has a lot of free gold + 60% which present serious challenges to resource estimators (see figure 5). This is typical of what was highlighted by (Dominy and Platten, 2007 p131) who noted that the “general observations from other authors on numerous mesothermal/lode-gold vein-type deposits suggest that coarse gold is relatively common and may represent more than 10% of the total gold population”.

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Figure 5: (Adapted from Mazowe internal metallurgical report, 2008).

Figure 5 is a microscopic view showing different particle sizes of free gold after grinding to a finesse of 80% passing through 850micron size sieve meaning there is a lot of coarse gold in the Mazowe deposit (see particles highlighted in green).

2.1.0 Mazowe Mine Reef Characteristics and Causes of Low Mine Call Factor

It is thought that the ore zones were formed by pulsating hydrothermal solutions, migrating along structurally controlled channels resulting from reverse dextral shearing in an imbricate thrust shear zone system (duplex). In most cases, the gold is intimately associated with sulphide mineralisation and only to a limited degree with vein quartz. This forms clearly distinguishable zones of quartz –sulphide mineralization with well defined, sharp and discrete contacts. The country rock is visibly different from the mineralized zone typical quartz-pyrite mineralisation widths varying in width from less than a centimetre to about 20cm, in shear zones of widths of +1m. These are zones of weakness and during blasting they experience the most shock resulting in the material getting more pulverised than the barren country rock there-by liberating some of the free gold.

Due to the nature of the reef, detailed geological observation can only be made available through mining and drilling which avails indicative data. The sulphides presents the reef with a yellowish tint (see figure 6).

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21 2.1.1 Causes of Low Mine Call Factor

Table 1 illustrates causes of Low Mine Call Factor at Mazowe Mine:

Known causes Suspected Causes

Losses of fines during tramming which is worsened by multiple handling of ore.

Inappropriate grade estimation methodology.

Ore left in benches due to excessive flying rocks Incorrect specific gravity.

Gold fines which are left behind due to lack of effective stope sweeping

Applying wrong cut off grades during estimation.

Gold theft of unknown magnitude Insufficient sampling to confirm grade continuity.

Poor quality control during sampling and assay analysis.

The pictures shown in figures 6 to 9 show gold lost in drives and haulages during lashing and tramming and in the shaft during hoisting. Ground at or near stope boxes, ore pass boxes and shaft bottom become high grade spots, confirming some of the known causes illustrated in table 1.

Figure 6: Different sizes of rock fragments of Mazowe reef left in the Flowing Bowl stope.

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Figure 7: Area close to a dilapidated old box showing different sizes of rock fragments and fines.

Figure 8: Area encircled in red shows a speck of gold.

The picture illustrates an old stope picture showing the different fragment sizes left behind after scrapping.

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Typical losses along drives and cross-cuts (drains) to the sump and some just remain in the underground developments. Water used for drilling and watering down is a transport media for fine gold accumulating concentrating in drains, sumps and underground dams (see figure 9 below).

Figure 9: White specks of gold bearing sulphides and free gold, in a Flowing Bowl crosscut drain.

The evidence of some real losses are so glaring, however currently even after such losses are mitigated by stope sweeping the MCF remains lower than expectation. This leads to the suspicion that there could be some apparent losses, pointing out to issues like poor block resource estimation, volume variance effect (larger size sample values normally show less variability compared to small sample size values). Hence, it is prudent in this research not to check MCF (comparison which is derived from actual gold calculated to be in the blocks as reported at the mill) alone but also to look at the block factor (gold content derived from face

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samples). Theoretically, if everything is on course, volume variance should not be an issue;

the gold content should not differ a lot no matter how the deposit is subdivided.

2.2 Technical Issues

Resource estimation is not an exact calculation; however this estimation has to be based on right quantities and good quality data for it to make a realistic practical contribution to business. This process does not start when resource tonnages and grades per block are computed as all geological sampling processes are part of the estimation process. If the quality of data is poor it is best not to use it to run resource estimation but use it just as an indicator, the same applies to data that lacks an audit trail. This indicates that the sampling process is a very important process that precedes resource estimation computation. According to the system in practice at Mazowe mine, when the mine call factor is low the gold accounted for (banked gold and gold in tailings) is invariably lower than the indicated gold based on mill feed grade and tonnage. This is caused at times by flawed processes along the value chain which lead to both realistic and apparent gold losses.

In-situ estimated grades derived from assaying channel samples cannot be accepted; once the basic rule of correct sampling according to the laid out correct procedures have not been adhered to. Poorly estimated grades can be indicative of an inferior sampling protocol that causes samples not to be representative. A sample is said to be representative if all parts of the material being sampled have the same chances of being sampled to be part of the final analysis, (Minnitt 2010, p65). This was supported by (Krige 1981, p3) who stated that “the method of sampling may also contribute to the extent to which a sample may be unrepresentative mainly in the sense of introducing a bias.” This is possibly attributed to the fact that many existing practices are based on practical protocols that are faulty.

The picture shown in figure 10 shows the reef thickness at a position, where the reef is more than 30cm wide showing both the shear tinted by sulphides (brownish) and the greyish quartz reef with visible coarse gold.

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Figure 10: Visible gold-bearing veins in the Wimbledon footwall reef, the white specks are coarse gold particles seen on the mining face.

It has to be noted that no matter how well the channel samples are collected, they may have low support due to sample size. This was noted by (Petersen and Dominy 2005, p57) who said “Within the high-nugget environment, small support sampling (e.g. chip/channel sampling) is notoriously variable and does not reflect local grade distribution.” Issues surrounding high nugget environment sampling were also noted by ( Hargreaves and Morley 2014, p741) when they emphasized that “a high nugget effect means that samples taken together are highly variable due to the inherent heterogeneity of the ore body.” If the assay value measurements are not perfect due to difficulties encountered during sampling and sub-sampling because of the heterogeneity, reconciliations are usually poor and in turn, this usually manifests as a LMCF. It is now an accepted phenomenon that efficiency factors are a problem faced by every mine where a vast difference between face sample values and the mined ore block values. In such cases, misguiding samples can lead to block misclassification and ore will be discarded as waste and the reverse is also possible. Accordingly, (Krige 1981, p17) said “ any imperfect measurement or prediction of the value of ore along a stope face or within an ore block will on average understate the true value of such ore in the lower grade categories, and overstate it in the higher grade categories.” This indicates that it is very difficult to estimate the grades of high-nugget deposits based on assay values only and

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implies the importance of modelling other geological attributes which are associated with the metal occurrence in the deposit. If the estimation accuracy is poor it distorts the expected gold from a given block, leading to a poorly reconciled block value when the achieved productions shows a high negative or positive conditional bias. The reason for this is that the size of samples collected is only a small fraction of the total tonnage of the block to be mined. This alone highlights the importance of sampling in the estimation process.

2.2.1 Sampling

The objectives of ore-body modelling involve recognising that payable and unpayable zones may occur anywhere in an ore deposit. Suitable design of mining operations and the beneficial extraction of mineral resources necessitate a pre-knowledge of the tonnage and mean grade of blocks of ore in the deposit. Fulfilling this objective requires a sampling program, of which the results are compiled and analysed. The main methods of underground sampling are face, channel/chip, and sludge, grab, diamond drilling and reverse circulation sampling. The inferences about distributions and other mathematical derivations such as mean grade of recoverable resources can only be drawn from this data.

According to (Rose and Fahey 2014, p680) it is critical to establish a sampling method that

“produces representative samples within the constraints of the mining schedule.” They proposed that there are two sorts of sampling, that is, predictive and checking. “Predictive sampling is to confirm areas of resource model prior to mining to ensure that the grade of the area is estimated to an acceptable level of confidence and checking sampling is used to confirm that the right mining decisions have been made.” “Checking sampling includes face, muck pile and stockpile sampling.” At Mazowe Mine diamond core and channel sampling constitute predictive sampling while checking sampling consists of face, muck pile and stockpile sampling.

Sampling and resource estimation methodologies are interlinked in such a manner that the resource estimation method selection is also affected by sample spacing. (Klein geld and Nicholas 2007, p229) suggested that “for geostatistical purposes, a sampling campaign must be designed to yield sufficient sampling data at a lateral and vertical frequency that allows a meaningful experimental variogram to be modelled”.

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2.2.1.1 Sampling Principles for representative sampling

According to (Minnitt 2010, p65), a sample is said to be representative if all parts of the material being sampled have the same chances of being sampled to be part of the final analysis. Resource estimation for high-nugget gold occurrence style cannot be based on drill hole samples alone for the Mazowe deposit. Drill hole samples are not representative well enough to depict the deposit mineralisation characteristics. The samples are widely spaced, small in size (reef with less than 10 centimetres), and at times the drill hole may miss the reef due to the complexities caused by vein structure, geometry and thickness. Hence the dependency on channel samples which are generally closely spaced along strike compared to drill holes. Sampling procedures should vary from deposit to deposit and are supposed to be based on the reef type. For instance, this study is on a high nugget narrow reef therefore the procedure should be designed in a manner that takes the high nugget character into cognisance. There is need to understand the theory of sampling (TOS) which provides a definition of the concept of sampling correctness, an attribute which must be always observed. TOS introduces the Fundamental Sampling Principle (FSP) and provides the first complete scientific definition of sampling representativeness.

If the “theory is understood and procedures are put in place, there is need to document the process to ensure that personnel changes will not affect the system results” (Minnitt 2010, p65). Unexpected variations are bound to occur during sampling due to heterogeneity especially in high nugget deposits. Inappropriate sampling is costly and may emanate from design and implementation actual sampling and sub- sampling.

2.2.1.2 Predictive Sampling Method Channel sampling

During channel sampling, a wedge of material is cut between two diamond saw cuts. This method reduces errors through delimitation and extraction. This method is a modified version of the original chip sample method. Chip sampling is more applicable in stratified geology but in narrow reefs it leads to issues linked to lack of sample mass. However, it produces better results if applied properly compared to chip sampling.

Channel sampling is used to delineate mineral resources at Mazowe mine because due to the nature of the narrow reef, drillhole samples can only be used as an indicator of reef continuity. At Mazowe mine, a measured mineral resource block is fully exposed on at least

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three adequately sampled sides in adjoining drives, raises, winzes or stopes with spacing not exceeding 30m and one or two levels/sublevels developed at intervals not more than 25m.

The channel samples are taken perpendicular to the strike at 2 metre intervals. Sample widths are determined by the geology but should not exceed 50cm and samples are cut using a diamond saw. The channel should be 2cm wide and 2cm deep and evenly cut. However, quite often 2cm depth is not achieved and channel is uneven. Due to the nature of the mineralization, characterized by a high nugget effect, a large sample is required in order for the samples to be representative. To this end, a larger sample can be achieved through increasing the channel width to 4cm. This would somewhat compensate for channel depth which is often less than 2cm. The sampling protocol has to also focus on quality rather than just quantity of samples taken. The geological contacts are sharp; hence sample lengths along the channel should be determined by geology.

Since the channel samples are used for resource estimation, it is therefore critical that the sampling is representative in order to provide reliable results for decision making. The fact that at Mazowe mine stopes are sometimes prematurely abandoned could be indicative of a sampling protocol that is faulty, yielding unrepresentative samples leading to unreliable estimation results.

Diamond drill core

Diamond drill core sampling is used to test down-dip and strike continuity of mineralized shear zones. Sampling and sample support has its role to play and geostatistical methods which also predict the error margin and have to be considered as first choice resource estimation methods in complex reefs. In wide orebodies, diamond drilling offers samples of a better support which are not easy to contaminate. In narrow reefs, core from drilling is used to assess geological continuity, while channel sampling from underground development is the effective sampling method for grade analysis. In the case of deposits like the Mazowe type only consistent and regularly spaced underground drill holes indicating geological continuity, along strike and up dip within the mining model can be used to estimate indicated resources.

Drillhole intersections are used to delineate inferred and indicated mineral resources.

Diamond drilling samples are considered as high quality samples, however the sample volume is substantially low compared to channel sampling in narrow reefs like the Mazowe deposit. Since the sample length is determined by the shear zone width, with a minimum of 5cm, a sample from the sterile hanging wall and footwall is taken to make sure that the

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sampling process is exhaustive. Assay results are captured on drill hole log sheets, where a composite value is calculated for the intersection. This information is plotted on 1.500 survey and geology plans, and it’s crucial that the raw data be stored in a database.

These assays are useful for indicating the continuity of mineralization but are not reliable because erratic nature of the mineralization which is compounded by the small sample owing to core size. The core recovery is good, ranging between 90 and 100%. However, the Mazowe gold reefs continuity ranges between 7.5m to10m. According to (Dominy 2003, p242) to create a sampling grid sufficient enough to capture such variability extents, “the drill grid needs to be less than two-thirds of the feature size”. The optimum sampling interval would be less than 5m which will be very expensive hence the need to use channel samples for resource estimation.

2.2.1.3 Checking Sampling

Grab Samples

The larger the sample the more representative it becomes. This process generally produces poor quality samples and should not be used for resource estimation. Grab samples are collected by hand or shovel from box holes on tramming level tips and chutes, scoops of broken ore are collected from the centre and four corners of the Cocopan. The samples collected are put in a container, and at the end of the shift a bulk sampling is mixed and quartered. The subsample is submitted for assay as part of the grade monitoring process.

This type of sample useful in homogeneous deposits has to be used with due care considering the sampling limitations. This is because errors introduced at the sampling stage cannot be reversed no matter how detrimental they are. The analytical errors can be corrected through re-assaying.

In the writer’s opinion, this type of sampling does not produce representative samples in high nugget deposits because during blasting, fines are lost. Therefore no matter how good the sampling process is, the sample will not be very useful. Grab sampling is assigned to mining personnel who are not well trained in sampling and at the same time preoccupied with their core duties. They may forget to sample most of the coco-pans then just collect large samples from a few coco-pans. This definitely results in unrepresentative samples being sent for assaying. The sampling would be better if it was carried out by trained samplers who would

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sample both coco-pans and fine material swept from the stopes. A more representative sample would give a better indication of the mill fed grade.

At Mazowe Mine, fines are associated with higher gold values. In fact when gold fines’

sweeping in stopes is carried out effectively the MCF increases (see table 2 below).

Consequently, the grab sampling which is biased towards fines, yield assays that overestimate the grade of the trammed ore. Individual results cannot be relied upon.

Face Sampling

The face of a producing stope is sampled at least once a week as a grade monitoring measure.

The procedure is the same as for sampling development. However, at times the samplers compete for services, with mining and are forced to take chip samples instead of channel samples. This may result in unrepresentative samples which are far spaced. Another concerning issue is that the sample bags are washed and reused. This constitutes a source of contamination. The face samples are used to estimate the block factor and grade control, hence, the need to implement stope practises which reduces the sample type’s reliability.

Contamination also reduces the authenticity of the check sample.

Sampling should be representative enough to capture the reef variability (geology and grade continuity). Hence once there are sampling issues, a robust estimation method will not mask the problems already created. Usually a system that over-states high grade areas has a tendency to understate low grades. This affects the accuracy and reliability of the resource estimation process. The sampling frequency should be monitored so that each bench slice is sampled. This will improve the reliability of the Block call factor (BF). If the samples are too few compared to block sampling the BF affected by the volume variance becomes an issue.

However the major assumption made in this study is that, the samples are representative in both quality and quantity (accurate, precise, and reliable) and that the fundamental error is minimized in sampling process.

2.2.1.4 Quality Control and Quality Assurance (QAQC) Procedures at Mazowe Mine.

Blanks, coarse duplicates, pulp duplicates and Certified Reference Materials (CRMs) from Rock labs for exploration projects sampling and Home made reference (prepared by a consultant using samples collected from underground) for all other sampling campaigns are inserted into the sample stream:

Standards are inserted appropriately. In the researcher’s opinion a sufficient range of CRMs

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over an appropriate range of grades were inserted. These were inserted into the sample batches at a rate of +5%. Blanks were obtained from a known barren dolerite sill. A blank was inserted into the start of each sample batch to check for contamination, and another was included immediately after any expected high grade zone. Pulp blanks are also inserted to check the analytical stage.

Coarse duplicates are used to monitor sample batches and also to assess inherent sample nugget effect. Pulp duplicates were obtained from laboratory rejects and used to check repeatability. A percentage difference greater than 20% is normally investigated.

Audits are in the form of random checks which include but are not limited to:-

 Sampling quality and mass.

 Numbering sequence of samples.

 Verification of all samples to ensure that no samples are lost.

 Validation of samples against the sampler’s field book.

 Assaying and quality control procedures in the laboratory.

The audits also help in identifying problems that may compromise the quality of samples.

Samples are transported under close supervision to the assay laboratory.

2.2.1.5 Data Management System

The use of a reliable geological database management system has to be implemented first to ensure that data can be easily interrogated and interpreted in a Geographical information system for proper integration with other non-geological data. This is required for reconciliation and subsequent decision making. The data used in resource estimation should come out of a successful digital information system.

When such a system is developed there are multiple opportunities to check and fix the data quality issues including the Metadata (e.g. drill hole diameter, sample type and sampling method). Metadata is important since it describes the characteristics of the real data. It can then be used for quality checks. (Longley et al., 2005, p397) highlighted that “Investing in database quality is important from creation onwards”, if data quality is poor no matter how applicable and good the estimates are they will not be representative and it will manifest as metal loss.

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Reconciliation in this context refers to the comparison of measurements and estimates along the value chain at different points in time, in order to track and optimise metal recovery through process improvements so as to produce an end-to-end accounting system (see figure 11 below). Reconciliation can also be viewed as an objective test of ore reserves, mining and milling performance for the sake of protecting the mineral asset throughout the value chain up to financial reflection there-off in the balance sheet. The reconciliation process ensures that practical targets for modifying factors such as (MCF), dilution and recovery are identified through measurement and analysis. Hence the second major and bold assumption is that the plant process measurements are not flawed (especially weightometer measurements and mill feed sampling).

Figure 11: Indicates the key points for reconciliation and each stage is used as a numerator when compared to the previous component in the chain.

The diagram(figure 11) also shows that all various components of a mine reconciliation can be rationalized and compared.

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The reconciliation process highlights common sources of problem which leads to justification of processes’ improvements to current practices, accuracy of forward planning. It is from this process that the MCF is derived by comparing mine production to plant product and tails.

During reconciliations, there is need to check if the areas that were in the mine plan are the ones that were actually mined since spatial compliance also has an impact on the MCF. This indicates that systems should not just pay lip service to reconciliations. The issues like low MCF should be taken seriously through considering the dollar value of the indicated gold losses. MCF can only be a useful indicator if the comparison between estimated tonnages and mined tonnages are +100% within the 6% allowable variances.

However the MCF is used to estimate metal content to be expected (e.g. the reserves and grade control predictions). The use of the MCF can be detrimental to the business as argued by (Chieregati and Pitard 2009, p107) who indicated that the “application of the factor (MCF) will often disguise the causes of error responsible for the discrepancy”. This shows the urgency required to resolve the underlying problem and the need to take timely corrective measures rather than depending on the questionable factors.

The other factor that is used to directly compare block resource value against the face value is the block factor. Block factor is generally accepted as the ratio, expressed as a percentage, of the specific mineral content of the ore broken from a Mineral Resource or Mineral Reserve block as indicated by current sampling results versus the estimated Mineral Reserve block content.

BF = Current sampling contents x 100%

Estimated block contents

The block factor trend can be compared to the MCF to check estimation performance against production performance. However it has also been noted by (Donaldson et al., 2014, p717) that “decreasing MCF is also attributable to, increasing dilution”. A common fact that has to be remembered is that one highlighted by (Minnitt 2014, p68) who stated that “over- statement of sampling values is the principle contributing factor to” LMCF.

Mazowe Mine Call Factor Compared to a Wide orebody and a moderately narrow reef Sister Mine Graph is shown overleaf.

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Figure 12: (Adapted from Metallon Gold 2013 internal report).

Figure 12 above shows that even though gold losses are a common problem, the losses are high; the team managing the Mazowe system cannot afford to be complacent. There is need to investigate all major system processes along the value chain. The resource estimation method has to be looked into starting from sampling procedures to actual sampling followed by data management system up to block estimation. This implies that all critical systems along the value chain should be continually evaluated against best practice and standard operating procedures to ensure that they remain in sync.

An understanding of why and where the variances occur between measuring and proper reconciliations is a necessity. Monthly reconciliations may not be enough to show the exact trends in high nugget deposits like Mazowe mine, but a year of rigorous reconciliations will yield results.

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Figure 13: Illustrates the trend of built up head grade, block factor and overall MCF acquired over the years, (Updated and modified from the Metallon Gold 2015 internal report).

Figure 13 above illustrates the relationship between MCF and BF against built up head grade.

In this case there is need to understand why MCF is decreasing as BF increases from year 2001 to 2015. During the same period the BF is showing that there is more gold than what has been estimated and the MCF is indicating less than what was expected and received at the mill (see 2014 performance).

The BF and MCF (also commonly referred as assay plan factor APF) trends indicate independence of the factors from gold grades. This is an indicator that when checking estimations, factors affecting block volume estimation such as reef thicknesses and bulk density could be also contributing to volume variance effect.

The BF indicates a significant difference between the face samples (relatively fewer samples) and block grades (relatively more samples), could be indicating a function of volume variance effect. The block volumes are not based on face samples. These discrepancies or correlation between face samples and block estimates is referred to as conditional bias which is also a consequence of different variability within a reef. This was noted by (Alastair et al

Chapter III Research methodology

Contents

Chapter 1

General Introduction

Chapter II