Ore Reserve Estimation Research Articles

Geostatistical Models and Estimation of Laterite Nickel Ore Reserves, Marombo Block, South Sulawesi

Abstract Geostatistical modeling in this study requires a distribution of drill points that have a fixed dimension so that they can produce a reserve accuracy match that is the same as the variograph. The choice of reserve estimation method is prioritized by determining the geological domains of limonite, saprolite and bedrock through a geostatistical approach, namely ordinary krigging (OK) and inverse distance weight (IDW) with the JORC standard (2012), for the accuracy of the limonite and saprolite zone boundaries. The reserve model has shown a definite model of the limonite and saprolite zones and can be used further. By using simulations on cut-off grade (COG) to calculate resources and classify mineral resources, the estimation results obtained mean nickel levels above 1.40% so that the CoG to be used must be greater than Ni 0.90% for limonite, and Ni 1.10% for saprolite. The results of modeling the geometry of laterite nickel ore obtained that the total tonnage shown in limonite was 0.36 wmt (wet metric ton), inferred 0.10 wmt, and indicated in saprolite was 0.58 wmt, inferred was 0.40 wmt.

Occurrence and lithogeochemical composition of iron ore in Ngororero District, Rwanda

This research aimed to investigate the occurrence and lithogeochemical composition of iron ore in the Ngororero District of Rwanda, with a specific focus on assessing its suitability as a raw material for iron and steel production. The objective was to determine the elemental composition, mineral species, and morphology of the iron ore samples collected from the study area. Eleven samples were collected and analyzed using Inductively Coupled Plasma-Mass Spectrometry (ICP-MS), X-ray diffractogram (XRD), and Optical Light Microscopy. The study shows that Ngororero iron ore is a medium-grade hematite (Fe2O3) ore with iron content ranging from 58.3 % to 65.8 %. Importantly, it contains minimal impurities (less than 3.7 % SiO2 and less than 0.4 % Al2O3) and low levels of detrimental elements (P less than 0.02 % and S less than 0.19 %). While the sulfur (S) content slightly exceeds standard limits, the phosphorus (P) content falls within the acceptable range for commercial iron ores. These findings, marking the first report of iron ore occurrence in the Ngororero District, have significant implications for the potential exploitation of Ngororero iron ore as a valuable raw material in iron and steel production and its suitability for industrial applications. To confirm its economic potential and assess its viability for iron and steel production in Rwanda, the study recommends that additional thorough exploration activities be conducted in this area using both geology and geophysical investigation as well as exploration drilling for iron ore reserve estimation in the study area.

Linear Geostatistical Estimating Methods Compared Using Annual Average Daily Traffic Data from Low-Volume Roads in Minnesota

Geostatistical methods are utilized to analyze and predict values associated with spatial or spatiotemporal phenomena. These techniques incorporate both the spatial and, in some cases, temporal coordinates of the data. The mining industry prefers these methods for ore reserve estimation, and they have also gained popularity in other specialized fields. Notably, the transportation industry is gradually adopting them to estimate annual average daily traffic (AADT). Although researchers use various predictive techniques to estimate AADT, many of them are experiential or based on simple subjective assessments, especially for low-volume roadways. The shortcomings of these assessment techniques include high margins of error, non-integrated spatial and temporal variability in the datasets, and inadequate consideration of total coverage. Geostatistical techniques are superior predictive tools in many fields because their algorithms account for these limitations. Moreover, geostatistical methods can predict data at both sampled and unsampled locations with minimal available data. Therefore, the crucial question arises as to which method best estimates AADT. This paper focuses on investigating linear univariate geostatistical methods, namely empirical Bayesian Kriging (EBK), ordinary Kriging (OK), simple Kriging (SK), and universal Kriging (UK), along with proportional valuations, to estimate AADT on low-volume roadways and provides a recommendation based on the findings. The study utilizes AADT data from 1,486 and 2,731 locations on low-volume roads throughout Minnesota in 2009 and 2016, respectively. The results obtained from this investigation hold significant systematic and practical implications for estimating AADT on low-volume roads and can be adapted for high-volume roadways as well.

Machine Learning-Based Delineation of Geodomain Boundaries: A Proof-of-Concept Study Using Data from the Witwatersrand Goldfields

Machine-aided geological interpretation provides an opportunity for rapid and data-driven decision-making. In disciplines such as geostatistics, the integration of machine learning has the potential to improve the reliability of mineral resources and ore reserve estimates. In this study, inspired by existing geostatistical approaches that use radial basis functions to delineate domain boundaries, we reformulate the problem into a machine learning task for automated domain boundary delineation to partition the orebody. We use an actual dataset from an operating mine (Driefontein gold mine, Witwatersrand Basin in South Africa) to showcase our new method. Using various machine learning algorithms, domain boundaries were created. We show that based on a combination of in-discipline requirements and heuristic reasoning, some algorithms/models may be more desirable than others, beyond merely cross-validation performance metrics. In particular, the support vector machine algorithm yielded simple (low boundary complexity) but geologically realistic and feasible domain boundaries. In addition to the empirical results, the support vector machine algorithm is also functionally the most resemblant of current approaches that makes use of radial basis functions. The delineated domains were subsequently used to demonstrate the effectiveness of domain delineation by comparing domain-based estimation versus non-domain-based estimation using an identical automated workflow. Analysis of estimation results indicate that domain-based estimation is more likely to result in better metal reconciliation as compared with non-domained based estimation. Through the adoption of the machine learning framework, we realized several benefits including: uncertainty quantification; domain boundary complexity tuning; automation; dynamic updates of models using new data; and simple integration with existing machine learning-based workflows.

Risk factors limiting access to formal financing: Perceptions from artisanal and small-scale mining (ASM) operators in Nigeria

This paper reflects critically on why individuals engaged in artisanal and small-scale mining (ASM) struggle to obtain formal loans. Several studies have concentrated on the perceptions of formal lenders on the risks associated with providing loans to this group of miners. It is argued in this paper that understanding more about the limiting factors from the perspectives of ASM operators will provide better guidance when formal lenders scrutinise the requirements for issuing loans to this group of borrowers. In this study, face-to-face interviews were conducted with senior management officers at the Nigeria Bank of Industry (BOI) and a selected number of miners within the study area. The findings indicate that the inability of ASM operators to prove the feasibility of their operations, lack of knowledge of efficient ore reserve estimation methods, as well as lack of physical collateral are amongst the factors that make them unfavourable clients to formal lenders. The paper recommends that government considers strengthening miners’ organisations and cooperatives as a way of enhancing the access of ASM operators to formal finance.

Arbitrary estimation of uranium ore reserves in Qattar–V, North Eastern Desert, Egypt using geographic information system

The qattar - V (G-V) uranium occurrence occurs at the contact areas between Gabal Qattar (G - Qattar) granite and Hammamat sedimentary rocks. The aim of this study is to estimate uranium ore reserves using a geographic information system by analyzing all the exploration data sets at G-V. Several geological investigations, including field and mineralogical observations, geochemical and radiometric surveys, have been performed for this uranium occurrence. Integrate these investigations with new radiometric and geochemical measurements to cover all the investigated areas has been done in this study. Using GIS it is possible to visualize the results and to extract the spatial features indicative of uranium mineralization's over G-V uranium occurrence. Our methodology involves the generation of prediction maps for the favorable host rock, structure control of uranium mineralization, alterations in intimate association with uranium, radiometrical and geochemical measurements. Combining all these spatial features leads to the differentiation between the areas with economical and for grades of uranium and the generation of a potential uranium map. From this map, the estimation of uranium ore quantity and quality at G-V uranium occurrences can be calculated using cuboids of constant widths, different lengths, and heights. This method gave arbitrary but reasonable estimates of uranium in selected blocks.

A scalar-geometric approach for the probable estimation of the reserve of some Pb-Zn deposits in Ameri, southeastern Nigeria

The Cretaceous sedimentary sequence of the Asu River Group in Ameri, southeastern Nigeria play host to lead-zinc ore deposits in irregular mineralized veins of non-uniform geometry. Two deposits (designated DEPOSIT A and DEPOSIT B) were economically assessed using an integrated approach. This was performed by employing a geometry-based classical scheme involving the mathematical relationship between the three cardinal variables of ore reserve estimation namely: surface area, thickness and density. Firstly, detailed and extensive geological mapping was carried out to establish the geological attribute of the mineral deposits. Since reserve estimation extends beyond exposed faces, spontaneous potential traverse, vertical electrical sounding and horizontal profiling, being orthogonal to the trend of the enclosing veins were used to characterize the existing sub-surface stratification and create forward models that revealed the concealed ore geometry (limiting depth, lateral extents and thickness variations). Subsequent to delineation, the depth to the top of the target ore lodes was obtained by implementing the Peter's half slope technique on self-potential curves. Thickness values of the ore bodies of interest were applied in three numerical classical integration techniques, i.e. Trapezoidal, Simpson's and Simpson's third-eight rule, for volume estimation. To overcome the non-uniqueness problem of DC resistivity data interpretation, the available drilling data was applied. Samples retrieved from each lode were subjected to mass and volume analysis using the CS200 electronic balance and water displacement technique, to determine the average density of each lode. Results from 2D subsurface resistivity sections showed the lead-zinc deposits as zones of low resistivity in a background of high resistivity. The 1D stratigraphic models reveal a mean thickness estimate of 11.85 m and 10.50 m for DEPOSITs' A and B, respectively. Sample densities correlate well with the average density of pure galena. Applying the scalar-geometric rule, a combined estimate of 10,778.95tonnes was obtained, representing a relatively economically viable quantity worthy of medium scale extraction.

A scalar-geometric approach for the probable estimation of the reserve of some Pb-Zn deposits in Ameri, southeastern Nigeria

The Cretaceous sedimentary sequence of the Asu River Group in Ameri, southeastern Nigeria play host to lead-zinc ore deposits in irregular mineralized veins of non-uniform geometry. Two deposits (designated DEPOSIT A and DEPOSIT B) were economically assessed using an integrated approach. This was performed by employing a geometry-based classical scheme involving the mathematical relationship between the three cardinal variables of ore reserve estimation namely: surface area, thickness and density. Firstly, detailed and extensive geological mapping was carried out to establish the geological attribute of the mineral deposits. Since reserve estimation extends beyond exposed faces, spontaneous potential traverse, vertical electrical sounding and horizontal profiling, being orthogonal to the trend of the enclosing veins were used to characterize the existing sub-surface stratification and create forward models that revealed the concealed ore geometry (limiting depth, lateral extents and thickness variations). Subsequent to delineation, the depth to the top of the target ore lodes was obtained by implementing the Peter's half slope technique on self-potential curves. Thickness values of the ore bodies of interest were applied in three numerical classical integration techniques, i.e. Trapezoidal, Simpson's and Simpson's third-eight rule, for volume estimation. To overcome the non-uniqueness problem of DC resistivity data interpretation, the available drilling data was applied. Samples retrieved from each lode were subjected to mass and volume analysis using the CS200 electronic balance and water displacement technique, to determine the average density of each lode. Results from 2D subsurface resistivity sections showed the lead-zinc deposits as zones of low resistivity in a background of high resistivity. The 1D stratigraphic models reveal a mean thickness estimate of 11.85 m and 10.50 m for DEPOSITs' A and B, respectively. Sample densities correlate well with the average density of pure galena. Applying the scalar-geometric rule, a combined estimate of 10,778.95tonnes was obtained, representing a relatively economically viable quantity worthy of medium scale extraction.

Integrating Geophysical Attributes with New Cuckoo Search Machine-Learning Algorithm to Estimate Silver Grade Values–Case Study: Zarshouran Gold Mine

The exploration methods are divided into the direct and indirect categories. Among these, the indirect geophysical methods are more time- and cost-effective compared with the direct methods. The target of the geophysical investigations is to obtain an accurate image from the underground features. The Induced polarization (IP) is one of the common methods used for metal sulfide ore detection. Since metal ores are scattered in the host rock in the Zarshouran mine area, IP is considered as a major exploration method. Parallel to IP, the resistivity data gathering and processing are done to get a more accurate interpretation. In this work, we try to integrate the IP/RS geophysical attributes with borehole grade analyses and geological information using the cuckoo search machine-learning algorithm in order to estimate the silver grade values. The results obtained show that it is possible to estimate the grade values from the geophysical data accurately, especially in the areas without drilling data. This reduces the costs and time of the exploration and ore reserves estimation. Comparing the results of the intelligent inversion with the numerical methods, as the major tools to invert the geophysical data to the ore model, demonstrate a superior correlation between the results.

Potential copper production through 2035 in Chile

In the long term, primary and secondary supply of refined copper satisfies demand. Numerous models exist to explain and predict demand and secondary supply; however, the projection of primary supply relies mostly on detailed knowledge of potential mining projects and on existing ore reserves and resources. Much discussion has occurred historically regarding the availability of resources and reserves for the future. Chile, being the largest copper producer, also has the largest reserves in the world; therefore, it retains its potential to be a key player in future supply. This article explores some of the most relevant resource and technological challenges that may emerge with an accelerated development of brownfield and greenfield copper mining projects in Chile through 2035, without considering economic, regulatory, and environmental constraints. A “Full Scenario” was created to accommodate these conditions and restrictions. It includes estimates of future ore reserves, copper production, plant capacity, ore grades, energy and water consumption, greenhouse gas (GHG) emissions, and generation of tailings. Maximum production would exceed 10 million tons of contained copper from 2027 to 2030, with a resulting decrease of ore grades and the growth of energy and water consumption. The growth of indirect GHG emissions through 2035 is estimated at 18.4% less than copper production growth, because all new electric energy for this scenario would be based on renewable energy. Also, all new water used by 38 out of the 42 mining projects considered would be seawater, and some of the continental water used in 2019 would cease to be used in mining.

Delineation of ore zones using the concentration-volume fractal method in the Dagh Dali Zn-Pb (±Au) prospect, north of Takab (Iran)

The Dagh Dali Zn-Pb (±Au) hydrothermal prospect is located in the north-west of Iran. Identification of mineralized zones is essential in ore deposit exploration. Different methods have been developed and applied to separate mineralized zones from barren host rocks based on mineralogical and petrographical studies, alteration and host rock changes as well as statistical and geostatistical parameters. This study uses the ordinary kriging technique and the concentration-volume fractal (C-V) method to model the ore body and recognize the ore grade distribution. These techniques were applied on the drillcore data and C-V fractal modelling, values of various ore zones being determined. Four breakpoints were found in the log-log plots which correspond to concentrations of 5.4, 10.5, and 17.8 wt.% Zn. The extractable ore zone for Zn is considered to be in the concentration range of 5.4 to 17.8 wt.%. Compared to the amount of reserve obtained from the geostatistical method (303,685 tons), it seems that the fractal method is more precise and accurate in the estimation of ore reserves.

A scalar-geometric approach for the probable estimation of the reserve of some Pb-Zn deposits in Ameri, southeastern Nigeria

The Cretaceous sedimentary sequence of the Asu River Group in Ameri, southeastern Nigeria play host to lead-zinc ore deposits in irregular mineralized veins of non-uniform geometry. Two deposits (designated DEPOSIT A and DEPOSIT B) were economically assessed using an integrated approach. This was performed by employing a geometry-based classical scheme involving the mathematical relationship between the three cardinal variables of ore reserve estimation namely: surface area, thickness and density. Firstly, detailed and extensive geological mapping was carried out to establish the geological attribute of the mineral deposits. Since reserve estimation extends beyond exposed faces, spontaneous potential traverse, vertical electrical sounding and horizontal profiling, being orthogonal to the trend of the enclosing veins were used to characterize the existing sub-surface stratification and create forward models that revealed the concealed ore geometry (limiting depth, lateral extents and thickness variations). Subsequent to delineation, the depth to the top of the target ore lodes was obtained by implementing the Peter's half slope technique on self-potential curves. Thickness values of the ore bodies of interest were applied in three numerical classical integration techniques, i.e. Trapezoidal, Simpson's and Simpson's third-eight rule, for volume estimation. To overcome the non-uniqueness problem of DC resistivity data interpretation, the available drilling data was applied. Samples retrieved from each lode were subjected to mass and volume analysis using the CS200 electronic balance and water displacement technique, to determine the average density of each lode. Results from 2D subsurface resistivity sections showed the lead-zinc deposits as zones of low resistivity in a background of high resistivity. The 1D stratigraphic models reveal a mean thickness estimate of 11.85 m and 10.50 m for DEPOSITs' A and B, respectively. Sample densities correlate well with the average density of pure galena. Applying the scalar-geometric rule, a combined estimate of 10,778.95tonnes was obtained, representing a relatively economically viable quantity worthy of medium scale extraction. • An integrated approach to the quantitative evaluation of some Pb-Zn deposits is discussed. • Arithmetic alliance between the three cardinal variables of ore reserve assessment is employed. • To validate the result of geophysical schemes, drilling information is applied. • Ore bodies are characterized by low resistivity values. • Evaluated deposits proved fairly viable sequel to qualitative analysis.

Ore Reserve Estimation of Saprolite Nickel Using Inverse Distance Method in PIT Block 3A Banggai Area Central Sulawesi

Reserve estimation is one of important work in evaluating a mining project. It is estimation of the quality and quantity of the presence of minerals have economic value. Reserve calculation method plays an important role in determining the efficiency in commercial exploration of a deposit. This study was intended to calculate ore reserves contained in the study area especially Pit Block 3A. Nickel ore reserve was estimated by using detailed exploration data, processing by using Surpac 6.2 by Inverse Distance Weight: Squared Power estimation method. Ore estimation result obtained from 30 drilling data was 76453.5 ton of Saprolite with density of 1.5 ton/m3 and COG (Cut Off Grade) Ni ≥ 1.6 %, while overburden data was 112,570.8 tons with waste rock density of 1.2 ton/m3 . Striping Ratio (SR) was 1.47 : 1 smaller than Stripping Ratio ( SR ) were set of 1.60 : 1.

An integrated 3D simulation and MCDM for estimation of ore deposits

The success of a mining project depends largely on accurate design and production planning as well as the optimization of mines, which involves a precise simulation and estimation of ore reserves. In this research, given the great importance of simulating and estimating reserves, a new hybrid approach is presented for 3-D simulations based on kriging and multi-criteria decision-making (MCDM) with a focus on determining the most accurate volumetric model of ore deposits. To illustrate this approach, the Gharehaghaj titanium ore deposit was considered as a case study. This ore deposit has different challenges, such as the lack of a regular exploration drilling network within the ore extension area. A 3-D crude model of the titanium ore deposit was first prepared based on exploration data and variograms. Then, the parameters affecting the shape and in-depth extension of the reserve were determined with regard to volume, amount, and distribution of exploration data. Accordingly, seven volumetric sub-models were developed with different characteristics that most closely corresponded with the main volumetric model derived from the original crude model. Finally, using the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method, the best volumetric model with the greatest fitness compared with the actual ore deposit was determined, which included 92 million t of ore at a grade of 5.64%. The reserve determined from this model was the highest compliance to the normal curve based on grade distribution. It was also concluded that the grade results obtained by the approach are 87% in accordance with the real grade obtained from the on-site sampling and assaying.

Utility of Large Scale Photogrammetric Techniques for 3-D Mapping and Precision Iron Ore Mining in Open Pit Areas

Precision mining and optimization of ore mining practise are gaining more importance as the global demand and competition for exploring the raw mineral material has grown manifold with increased industrialization world-wide. The overall process of mining activity involves ore identification, estimation, planning, excavation, transportation etc. The activity requires accurate mapping, monitoring and proper management of information pertaining to ore stockpile, mining pits and infrastructure of the areas on a regular basis. Of late, advancements in remote sensing techniques have paved a way for digital management of the mining activity. Especially, use of photogrammetric techniques for open pit mining are found to be highly accurate and effective in capturing, monitoring, mapping, managing the information pertaining to mining in a three dimensional (3D) space. Capturing of information pertaining to mines in 3-D perspective with respect to a specific location on the terrain is highly effective in accurate estimation of ore reserves, exploration and reclamation planning, ore continuity mapping and decision making. However, precision mining requires the use of large scale photogrammetric techniques with high resolution imagery of gigabytes size at mapping scales range from 1: 1000 to 1: 5000. In addition to that, the entire procedure involves the use of state-of-theart software and hardware for fast processing of data and subsequent digital output generation. Above all, involvement of skilled photogrammetric experts with specialised knowledge on open pit mining is very much essential for accurate interpretation and delineation of the resources. A project was carried out for the 3D mapping of iron ore stockpiles, pits and infrastructure areas at various sites. The stockpile and pit mapping is used for very precise volume measurements and the infrastructure mapping is used for general mine planning activities. High accuracy is critical, as the data and volume reports are used to calculate the value of the ore being extracted, and any errors in the mapping data can result in incorrect payments of large amounts of money. Since, the timeline specified to complete the task is very short, it is crucial that the staff doing the final volume computations and downstream processing should receive the accurate data, correctly coded and mapped according to the standards outlined. The study has demonstrated a typical workflow for the effective use of close range photogrammetric techniques for 3D mapping and iron ore mining in open pit areas. The study also sees a brighter outlook and challenges of upcoming aerial and terrestrial photogrammetric technology for precision mining.

Defining Mineral Exploration Works

When mineral exploration starts, a number of problemshave to be dealt with. They refer to the density of sampling (samples, drill-holes, drifts) so as to have a reliable estimation of the reserves, the decision to extend the exploration campaign, especially with works of high cost, when the first results are interesting and, of course, the risk that is taken when investing in this venture. When exploration has been carried out with state funding, in some countries’ legislation it is stated thatthere has to be a call for tender if the explored deposit is to be rented and if mineral exploration works have been carried out. The present paper attempts to introduce a method of estimation of ore reserves during the various phases of exploration, how to deal with the decision of extending the exploration and to define the notion of “mineral exploration works”. The attempt aims to the point all involved in mineral exploration and mining to have a common understandable language.

Determination of bulk density, methods and impacts, with a case study from Los Bronces Mine, Chile

Mineral resource and ore reserve estimates are founded on two sources of data: tonnage and grade. The tonnage is a product of volume and density; both of which are estimates. Density impacts numerous operational factors, which include, but are not limited to, mine design, mine planning, equipment selection and operational performance. Hence, density is a significant parameter and its determination requires similar care as the measurement of grade. This paper provides an overview of methods used to determine density within the Anglo American Group. It is not the purpose of this paper to identify a preferred method, but to highlight the importance of choosing the best suited practice for a project or mine site. In addition, a case study comparing two different density determination methods applied to the same rock samples from the Los Bronces Copper mine in Chile was undertaken and the results of that study are presented here. Selecting the most appropriate method to determine density and comparing results from two or more techniques against each other, together with other suitable quality control procedures, is considered to be essential for mining operations and exploration projects in order to reduce risk and to improve operational performance, which in turn increases profit margin.

Aspects of resource estimation for mineral sands deposits

Mineral sand deposits being economically exploited around the world fall into three main deposit styles; palaeo shorelines and marine placers, dunal and aeolian deposits, and alluvial deposits. Resource estimation for mineral sands follows standard estimation principles as applied to commodities throughout the Mineral Resource sector. There are, however, characteristics of mineral sands that require a slightly different approach and more emphasis on the geometallurgical characterisation to support the evaluation, Resource estimation and eventual reporting of the Mineral Resource estimate. Drilling is the main exploration and Resource definition tool used in the mineral sands industry and aside from logging and sampling, observation of hardness and induration attributes are critical aspects of drilling mineral sands deposits. Assaying is conducted on drill samples for heavy mineral (HM) content and for various particle size ranges and then further assaying or mineralogical assessment is undertaken on the HM to determine valuable heavy mineral components (typically zircon, ilmenite, rutile). The estimation of mineral sands resources requires a sound geological model before the determination of any geometallurgy based sub-domains within the mineralisation. Understanding the mineralogy and quality characteristics of deposits influences the confidence in subsequent Mineral Resource and Ore Reserve estimation and will in turn assist the Competent Person to select the appropriate cut-off-grade for Mineral Resource reporting.

Predicting the Concentration Characteristics of Itakpe Iron Ore for cut-off Grade Estimation

Concentration characteristics of an ore are very critical to the estimation of cut-off grade of a deposit. A mathematical model that can lead to their quick prediction will significantly enhance ore reserve estimation, mine planning and the economy of the mining venture as a whole. In this paper attempts have been made to establish a functional relationship between ore grades and concentration characteristics of Itakpe Iron ore. The Wilcoxon signed rank test has been used to establish a significant level of correspondence between actual values and values obtained from the model. The model has shown that the performance characteristics of the processing plant and the grade of the ore both play vital roles in deciding the concentration characteristics of an ore. ©JASEM

Fault detection in 3D by sequential Gaussian simulation of Rock Quality Designation (RQD)

Gazestan phosphate ore deposit (Central Iran) is an apatite deposit which is instrumental in selecting the method of excavation. The position of fault systems and the condition of rock quality also play a role in the method used for mineral resources and ore reserves estimation. Conversely, the Rock Quality Designation (RQD) is a parameter that provides a quantitative judgment of rock mass quality obtained from drill cores. This factor can be applied to detect the fractured zones which occur due to fault systems. Additionally, the faulted areas can be determined by surface geological map and a few by core drilling. Some of the faulted areas are not distinguishable in the surface and are covered by soils, especially within 3D modeling and visualization. In this study, an attempt has been made to establish a relationship between the RQD percentages which were geostatistically simulated and faulted areas through the region. In comparison, the results showed that low RQD domains (RQD 50 %) correspond to less fractured areas, and the contact between high and low RQD domain is gradual. Therefore, this categorization of RQD domains can be incorporated to detect the faulted zones in 3D models for mine design. Based on the categorization, the uncertainty within the area was calculated to introduce two new core drilling points for the completion of this phase of exploratory grid from the fault structural viewpoint, in order to have a proper model of ore reserve to estimate. It was concluded that this procedure can be utilized for conceptual comprehension of fault trends in 3D modeling for the method selection of excavation and complete the estimation procedure phase.