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By Jorge Cárdenas, Alejandro Luna

In mining simulation for fragmentation results prediction is of utmost importance to study feasibility, ensure safety, and estimate the correct use of resources in drilling an explosive to meet requirements and avoid excessive usage. One critical case is fragmentation prediction, developed through models. Developing a fragmentation model in a mining unit aims to control blasting results to align theoretical and real data and improve correlation. Therefore, it is essential to collect post-blast fragmentation data, organize it, and systematically process it to develop a suitable model that meets variable requirements. Using a robust system of equations, this model should generate the required results with minimal variability between simulation and actual results. Additionally, this model must be adaptive to reduce this variability. Studying the most known and used models in mining resulted in our work correlating Cunningham 2006, Swebrec, and CZM models. Thus, the Simfrag model was created, presenting a robust foundation and combining the most notable advantages of the aforementioned models.

Jan 21, 2025

By Ayman Tawadrous, Hendrik Botha, Simon St J Tose

The early miners and their mules always had the challenge of transporting unstable dynamite underground. The modern pumpable explosives, whilst far safer, still present a major logistics challenge for the mobile charging units (MCU). The challenge today is the efficient explosive delivery into declines, ramps, and vertical shafts, often requiring the MCUs to travel excess distances up and down to surface to re-load. Alternatively, the management of cassettes or ISO containers is utilized to deliver the pumpable base emulsion to the MCUs at the working face. Additionally, local laws and regulations regarding shaft clearance further compound the task and result in pausing other operations in the shaft or decline or ramp until the completion of the explosive transport. This paper examines the research & development challenges of dropping base emulsion down a vertical pipe to depths in excess of 1000 m (3280 ft.), either to an underground storage or directly into the MCU, depending on the depth. The boreholes (with pipes) are drilled in close proximity to the underground work areas. The paper also discusses the rheology of the emulsion within these vertical pipes as well as the economic benefits of such an innovative system. The learnings gained from this work, along with examples demonstrating the significant reduction in MCU travel and the safety benefits, are presented for the industry to consider moving forward.

Jan 21, 2025

By Mario Alvarez

Drilling with tricone drill bits is widely used in the mining industry with a direct impact on drilling safety and costs, however it can be challenging to implement a new supplier of tricone drill bits, choosing a new model of this accessory due to the normal variations of the rock mass or even due to the acquisition of new and modern drilling equipment for open pit blasting operations. This article identifies the most common mechanisms of failure in productive drill holes of tricone drill bits, both in open-pit coal and metal mines, in two South American countries. It also emphasizes the important issues that must be addressed for the optimization of the performance of these accessories, such as the correct identification of the rock mass, the drilling parameters, and the impact of autonomous drilling on new equipment with this technology. The article presents some of the successful actions to economically improve the performance of drill bits considering the close relationship in the field with the supplier's technical representatives and factory designers, as well as the commercial interrelationship between their respective business areas. The article concludes by discussing the future of tricone drill bit design development, its environmental management, and possible new advances in its manufacture.

Jan 21, 2025

By Jorge Blázquez, Paulo Couceiro, Patricio Vergara, Luis Martínez, Juan Navarro

This study introduces the X-2Mill solution, a refined two-step methodology aimed at optimizing blast designs by aligning explosive energy with rock properties. The approach employs the X-4Traits Model, which uses drill-monitoring data from both autonomous and manual drilling modes to develop two critical indexes: the Drilling Rock Factor (DRF) and the Drilling SAG Power Index (DSPI). The DRF integrates the Size-Energy Fan Model with rock fragmentation results and blast design parameters, while the DSPI adjusts Specific SAG Energy (SESAG) based on Bond’s theory, incorporating ore X80 results, SAG mill capacity (TPH), and power draw to estimate milling difficulty. To enhance prediction accuracy, the X-2Mill solution incorporates, to a Principal Component Analysis of the normalized drilling data, a Meta Machine Learning model with a 3D spatial function, accounting for information from surrounding drill holes. This integration improves the precision of the DRF and DSPI estimates. The methodology unfolds in two main steps: Step 1: Bench-Scale Pattern Design, involves defining the target P80 size for ore based on the SESAG and the DSPI. It also establishes target X80 sizes for waste and oxide materials and iterates to determine the optimal Burden x Spacing (BxS) using the Size-Energy Fan Model and the DRF. Step 2: Blast-Scale Selective Explosive Density/Energy focuses on refining explosive density on a hole-by-hole basis to achieve the specified X80 values for ore, waste, and oxide materials. The X-2Mill Solution was developed at Minera Escondida Limitada (MEL) using data from 162,761 blastholes across 356 blasts conducted over three mine expansions. This solution addresses the challenges of blasting harder and more difficult rock, particularly in the lower levels of the mine. By adapting the blast pattern and explosive density to the specific rock properties and ore/waste designation, the X-2Mill Solution aims to achieve precise size distributions and improve overall blasting performance. The results demonstrate that the X-2Mill Solution balances ore fragmentation to meet SAG mill throughput requirements while optimizing powder factor costs for waste material and maintaining digging efficiency. By efficiently distributing explosive energy, the solution not only enhances throughput but also improves blasting efficiency while ensuring stable slopes and minimizing fault activation.

Jan 21, 2025

By J. Rafael Otaíza, Francisco Mardones

This work has addressed the problem of creating a predictive model of the maximum particle velocities in the rock mass (PPV). The model designed specifically can model the subsequent vibrations of blasting based on geometric parameters, explosive loading, and the blasting process itself. Models based on artificial intelligence (AI) algorithms can find useful non-linear patterns to solve classification, regression, clustering, among other problems. They are flexible mathematical transformations adaptable to various objectives and types of data. With their different levels of abstraction, they can find a function that relates the input variables to the sought-after response. These models have been successfully used in similar contexts (Prashanth, (2018)) and have achieved state-of-the-art results in the field (Lawal, (2021)). The main challenge is to adapt them to the context of Chilean mines, in addition to including the geometric information of the blasting and the heuristic to obtain the set of optimal parameters, it is proposed to follow the work of (Simonyan, (2013)) and obtain "saliency maps" adapting it to tabular variables. We implemented an Artificial Neural Network (ANN) with a large number of neurons in the hidden layers. Models based on neural networks can find useful non-linear patterns to solve classification, regression, clustering, among other problems. They are flexible mathematical transformations adaptable to various objectives and types of data. With their different levels of abstraction, they can find a function that relates the input variables to the sought-after response. The literature shows that, for the problem of rock type identification, basic neural networks perform well (Simonyan, (2013)), but lack uncertainty estimates. This is a data-driven model, and in this sense, the model training was carried out using data from multiple operations in the large copper mining industry in Chile. In these databases, data consistency and the balance of the various independent variables that have the greatest impact on the model were ensured. With the above, the optimal hyperparameters of the model were determined, obtaining a predictive R-squared of 0.94.

Jan 21, 2025

By Anderson Meireles, Vladimir Carrasco, Carlos Feliciano

Adopting new technology in drill and blast requires a structured implementation process, as it represents a significant change in a traditionally conservative industry. It involves addressing initially unknown implications. As the problem is not yet acutely felt, developing a market strategy must be approached from the customer’s perspective, considering how the product can optimize their activities or enhance flexibility. To achieve this, it is essential to have a comprehensive understanding of the context of the customers identified in the deployment process pipeline. This paper discusses aspects of introducing wireless initiation technology - the initiation of primers through a magnetic field without physical connections - in Brazil. Additionally, it presents a case study of the application of a structured process of sales with purpose in an underground mine. By identifying key opportunities that were highly profitable for the client, the necessary awareness was created, leading them to recognize the technology as an enabler for exploring their mineral deposits in a new way which allowed a successful change management process. Based on the applicable technique, a preloading project was developed to maintain inaccessible areas with high-grade precharged with the area loaded with wireless primers acting as a temporary pillar and controlling dilution throughout the orebody. Once the excavation of the stope was completed, the pillar was successfully blasted and the material - once considered lost in the original plan as a rib pillar - was recovered after serving its structural function. Through this method, the metallic recovery of the stope increased without dilution losses. Demonstrating economic viability and stablishing the previously unknown technology as a strategic tool for optimizing stope recovery.

Jan 21, 2025

By Diogo Fonseca, José Manuel, Nuno Fernandes, Blessing Taiwo

This research focuses on enhancing the synergy between blasting and primary crushing operations in quarries. A blast operation at dstgroup aggregate quarry in northern Portugal was simulated to fine-tune blasting techniques aimed at optimizing fragmentation indicators. The methodology involves conducting precise blast drill hole surveys, generating detailed terrain 3D models, and integrating these models into blast simulation software to enhance accuracy and optimize production efficiency. The study applies these simulations to test blasts, evaluating improvements in cost-effectiveness, crusher power consumption, and fragmentation efficiency using both aerial and terrestrial image analysis technology. The quarry key performance indicators (KPIs) guide the blast design simulations, ensuring practicality and relevance. The case study blast revealed that implementing optimum blasting techniques can enhance crusher throughput, reduce operational costs, and improve safety. This paper is part one of a three-part technical series where we aim to create a sampling procedure and establish a reliable baseline for the current state of operation. This baseline will be used in subsequent follow-up technical papers to make recommendations and improvements. The outcome of this study provides a framework for quarry operations seeking to enhance their efficiency.

Jan 21, 2025

By Dr. Anurag Agrawal, Fathur Rozaq, Nella Lubis, Relinda Sanistya, Herry Saputra, Rudolf Sitorus

In mining operations, basic drone applications such as pre- and post-blast photo comparisons, blast video recordings, and sample-based fragmentation analysis are often used to assess blast performance. However, these methods lack the depth needed for comprehensive evaluations, leading to suboptimal results. This study explores the innovative integration of drone mapping technology with artificial intelligence (AI) at the Martabe Gold Mine in North Sumatra Province, Indonesia, to address these limitations. High-resolution drones and ground control points (GCPs) are utilized to create detailed orthomosaic maps, and advanced AI algorithms are applied to enhance the accuracy of blast performance insights. Field experiments reveal substantial improvements in comprehensive blast performance evaluations through this integrated approach. Enhancements include improved pre- and post-blast evaluations, AI collar detection, fragmentation size measurements, heave muckpile profiles, cast material measurements, floor prediction models, and muck pile topography volume, which is vital for ore tonnage predictions. Notably, this method achieves an average volume accuracy of 1% compared to light detection and ranging (LiDAR) technology. While LiDAR is known for its precision, the drone-based method offers a highly accurate, cost-effective, and user-friendly alternative suitable for mining applications. Despite LiDAR's superior precision, our approach provides a practical solution due to its accessibility and ease of implementation. In conclusion, the integration of advanced drone mapping and AI technologies has the potential to revolutionize blasting operations. By addressing the limitations of previous methods, this approach meets the evolving needs of the mining industry and sets new standards for accuracy and effectiveness in blast performance assessment. The combination of high-spectral drone images and AI-based software analysis demonstrated nearly 99% accuracy in ore tonnage prediction models compared to LiDAR, showcasing its promising capabilities.

Jan 21, 2025

By Jair Alarcón, Lucas Steffen, Leopoldo Muñoz

Flyrock is one of the most significant hazards associated with blasting in open pit mining, especially for blasting operations near communities. Flyrock can lead to severe injuries, fatalities, and property damage, compromising the license to operate. For this reason, defining exclusion zones is critical to ensure the safety of people and equipment. A very large radius will reduce the risk of flyrock; however, excessive exclusion zones can significantly impact the productivity of the operation and, in some cases, compromise the extraction of ore in critical sectors. Many mine sites use distances derived from pre-established standards, experiences from other mines, or still use simple methods for analysis, like recording blasts with a terrestrial camera and performing deterministic calculations to determine exclusion areas, applying an arbitrarily safety factor for people and equipment. In this paper we present a new approach that allows the calculation of the exclusion zone by measuring critical flyrock parameters with a high degree of accuracy through a new video analytics technology, this data then is used as input to calibrate probabilistic flyrock models to have more robust calculations, allowing optimized and safe exclusion zones. The proposed methodology leverages high-accuracy data and continuous monitoring to dynamically adjust D&B designs and exclusion zones, ensuring maximum safety without unnecessarily restricting operational efficiency. A case study is presented where the application of these new digital technologies allows precise prediction and control of flyrock trajectories, enhancing the accuracy of exclusion zone boundaries. In this case we successfully reduced the exclusion zone radius to 100m, allowing the ore extraction in a critical region close to the community safely. The study shows notable improvements in safety and productivity, including zero flyrock incidents and enhanced protection for nearby communities. The adaptive nature of these digital tools offers scalable solutions for various blasting environments. The paper concludes by recommending the integration of these tools into standard blasting protocols, highlighting the potential for widespread adoption in the industry to mitigate flyrock risks effectively.

Jan 21, 2025

By Chanhwi Shin, Hyeongmin Kang

Mine optimization is a key strategy in the mining industry that focuses on improving the efficiency, productivity, and sustainability of mining operations. To achieve mine optimization, digitalization is essential for modernizing mining operations and attaining optimal performance. Due to the importance of mine digitalization, various software and platforms have been released to support this effort. Furthermore, by integrating these advanced technologies, mines can enhance processes, leading to significant economic and operational benefits. However, integrating data from various sources and collaborating across different platforms remains a significant challenge in the mining industry. Generally, data for mine optimization, such as mapping, smart drilling, FMS (Fleet Management Systems), fragmentation analysis, or vibration analysis, are collected and analyzed separately on different platforms. This separation makes it difficult to aggregate and utilize data comprehensively for overall mining process optimization. During the digitalization process, obstacles arise due to these complexity, variability, and sharing issues of data across different maker, sources, and methods. These challenges highlight the need for seamless integration to achieve optimal mining operations. Thus, this study applied a total solution that can cover the entire Drilling and Blasting (D&B) processes. The blast design was performed using actual terrain mapping data, and drilling and charging were conducted following a guide based on the blast design plan. After blasting, loading and hauling distances and fuel consumption were measured, and fragmentation for each blast was evaluated. All measurement tasks were automated to minimize human error. By collecting all data in one server, it became possible to perform an overall evaluation for each blast, allowing the identification of optimal values. In conclusion, to evaluate the optimization effects for each mining process, one month of integrated data collected on a single server was used. Compared to the period before the Total solution was implemented, there were notable improvements: a 25% enhancement in hole spacing, a 60% improvement in floor flatness, a 23% reduction in average fragment size, and a 19% improvement in fragment uniformity. Regarding cost savings per blasting volume, the improvements were 11.7% in drilling, 9.3% in explosives, 7.6% in loading, and 17.5% in hauling.

Jan 21, 2025

By Anderson da Cunha Meireles, Pedro Garcia, Ernst Young, Leandro Coelho, Carlos Eduardo Soares Feliciano, Key Fonseca de Lima

Rock blasting is a crucial technique employed in mining construction and quarrying industries to fragment large rocks into smaller, more manageable pieces. However, it often generates ground vibrations that can pose significant challenges. This study explores the application of Conformal Prediction (CP) in the context of rock blasting to develop predictive models that estimate blasting-induced vibrations and quantify the associated uncertainties. Various machine learning models were integrated within the CP framework using MAPIE and CREPES libraries. The results demonstrated the effectiveness of CP in providing statistically reliable prediction intervals, making it particularly useful for applications where the stakes of underestimating uncertainty can be high.

Jan 21, 2025

By Javier Illanes, Felipe Moroni

In recent years, implementation of Artificial Intelligence and Machine Learning model technology has gained ground in almost every aspect of human activities. The mining industry has not been foreign to these applications, with advantages including the creation of new optimization methods and the elimination of repetitive tasks. Those applications have been implemented in multiple operative areas, from preventive conveyor belt maintenance to energy optimization for minimizing environmental impact. The blasting process aims to use the energy liberated by the detonation of explosives to break the rock mass according to specifications that facilitate the comminution process. To optimize this process, the energy delivered must correspond to the necessary amount to exceed the tensional and compressional resistance of the rock mass. If the energy applied is insufficient, the rock will not reach the desired fragmentation level and the processing plant may incur additional costs. On the other hand, if the energy level required is exceeded, we incur increased blasting costs that correspond to excess explosive used. Optimization of this aspect of the mining process has major impact in the processing chain reflected in lower costs, efficient resources consumption and environmental impact. The Design for Outcome technology (DfO), developed by Orica, is used to characterize the rock mass in detail to classify, borehole by borehole, the rock mass relative hardness to deliver the adequate energy level to achieve optimal fragmentation. This technology uses information collected by drill sensors, producing data typically referred to as Measure While Drilling (MWD) data to classify the rock mass into domains that can later be used to apply optimal blast designs. In DfO, the data flow is fully automated, starting with the data produced by the drilling system and uploaded to the cloud, which is then domained using Machine Learning (ML) techniques, and then published for consumption using a web interface. Automated explosives loading rules are then generated for each rock mass domain, ensuring that for each borehole, the adequate explosive energy is delivered to achieve the desired fragmentation results with unprecedented accuracy. The application of machine learning techniques allows us to optimize the blasting process results by leveraging a deeper understanding of the rock mass. Applying these optimization techniques, we obtain considerable economic benefits, decrease resources consumption, and achieve a more sustainable mining operation. The application of DfO in a Chilean mining operation allowed the characterization of their rock mass into four domains and established specific explosive loading rules for each one. A 60kUSD reduction in explosives cost was achieved during the test period, while maintaining the desired fragmentation results and expected dig rate. These outcomes were the result of a comparison between the blasting costs used applying the technology mentioned above and a “traditional” classification of the rock mass with the corresponding blasting practices.

Jan 21, 2025

By Karl Dufresne

Blasting in geothermally high temperature ground and/or extremely reactive ground is an increasing common challenge for surface and underground mines. Many current PETN based non-electric and electronic detonators have manufacturer published in-hole temperature limits ranging from 55°C to 65°C (131°F to 150°F) and prescribed in-hole residence times on the order of days. When confronting blasthole temperatures above the manufacturer published limits, operations may request site-specific guidance and qualification for use. The advised safe loading window for in-hole PETN based detonators is often too short to be practicable for production blasting. To overcome limitations of PETN based initiation systems, surface mines with high temperature ground and/or reactive ground are known to load blastholes with a qualified high temperature bulk emulsion that are top primed with a cartridge of temperature qualified detonator sensitive emulsion plus an RDX detonating cord downline. As there is no in-hole delay detonator in this system, blasthole timing is accomplished with surface delays. Although this system is safe, top priming and surface delaying does influence floor quality and top size fragmentation, and safe loading windows times reduce blast block size and increase blasting frequency. The DynaEnergetics IGNEO high temperature electronic initiation system is rated for in-hole use in ground up to 150°C (302°F) for 48 hours. The detonator consists of a high strength detonator with an HMX base charge and thermally resistant downline. To make up a primer, the detonator is inserted into a booster charge assembly that is fitted with a small HMX shape charge. This high energy primer is designed to be compatible and reliable for firing bulk emulsions, including those with high percentages of urea inhibition to combat reactive ground. Up to 1000 detonators may be programmed in 1ms increments up to 1500ms. The system is controlled by a digital firing panel that can be used with either a wired or wireless trigger. The system enables high temperature and/or reactive ground sites to utilize in-hole delay initiation and realize the associated performance benefits. An underground mine in Western USA has several areas in their development heading with very high temperature, in view of this, they decided to use the IGNEO detonators in order to evaluate the effectiveness and performance of the system.

Jan 21, 2025

By Anderson Meireles, Leonardo Soares Chaves, Raul Carretero Hoz, Carlos Eduardo Soares Feliciano, Renato Jacome Costa

The large iron deposits in the northern region of Brazil located in the Amazon Craton have in common the presence of natural cavities. These cavities primarily occur in the upper layer of the ore body, formed above hematite mineralization. Their origin remains a topic of debate, often associated with hydrothermal drainage processes and erosive evolution. Over time, these cavities have become integral to the local environment, each contributing to the regional ecosystem of fauna, flora, and the significance of speleothems found within them. Managing these cavities poses a significant challenge for iron mines in the area. On one hand, they must preserve the cavities from anthropogenic actions, while simultaneously handling heavy equipment and large volumes. In 2023, the development of the mine took place towards the cavity under study, revealing systematic deviations in vibrations recorded during nearby detonations as the blasting got nearer. To address this, a work plan was put in place, emphasizing a straightforward approach: constructing lithology-specific vibration models, defining charge abacuses, and optimizing timing to reduce charge amplification. Implementing this methodology significantly improved adherence to the vibration limit, resulting in an around 50% reduction in standard error. This paper presents the consolidated work that allowed mining activities to continue in the area through controlled blasting, effectively mitigating potential anthropogenic damage in sensitive areas.

Jan 21, 2025

By Raúl Carretero de la Hoz, Leonardo Soares Chaves, João Paulo Soares Toneli, Francisco Felipe da Silva Dantas, Marcos Peres Lopes, Marcus Vinicius da Silva Gonçalves

The mining activity results in environmental impact and thus requires the adoption of techniques to minimize its effects. The rock blasting process is required to break up and move the rock enabling the haulage of the material, however, it might also cause undesirable effects such as flyrock, overbreak, excessive ground vibration or air-blast at the neighboring communities and damage to civil or geological structures located nearby. The Serra Sul mine, commonly referred to as S11D project, has obligations to preserve two natural tropical montane lakes and several maximum relevance natural cavities whose legal preservation radius represents constraints to the mine development and operation. Controlling measures are undertaken to ensure preservation of the cavities, especially during rock blasting stage, with limitations of the maximum instantaneous charge (MIC) and ground vibration control. The demand for high productivity and the large areas with hundreds of blastholes to charge are challenging factors to the charge control. This work presents the development and field application of a map for limiting explosive charges in the rock blasting process at the Serra Sul mine, used for the definition of maximum charges according to the blast location, ensuring the preservation and compliance with the defined ground vibration limits for each cavity. The map is applied at the mine for every blast and when there is a charge constraint, the map helps to define the areas with different charging profiles in the field contributing to higher charging productivity.

Jan 21, 2025

By Tyler Rockley, Carla Reyes

Autonomous fragmentation measurement systems designed for shovels have been in operation for nearly two decades, however fragmentation systems capable of performing in the dynamic conditions of the front-end loaders (FEL) were only recently introduced to the market. This paper presents an in-depth evaluation of an automated digital fragmentation measurement system specifically designed to perform under the dynamic operational conditions of the FEL in two of Teck’s mine sites. As early adopters of this novel application, Teck embarked on a Proof-of-Concept (PoC) trial phase, defining a set of key performance indicators (KPIs) to qualify the performance of the digital solution in tough mining operating environments. The KPIs focused primarily on the hardware robustness, quality of image and segmentation, both day and night, availability of the system and sample ratio. The benefits expected from using this technology include increasing the safety of the current fragmentation measurement process, improving the quality of the analysis, increasing the sample representativeness, and using the attributes of the system to create an oversize detection alert to inform the loading operation process. A critical part of the evaluation was verifying the system’s effectiveness on the particle segmentation algorithm as this element often gets overlooked, especially when dealing with the large number of samples autonomous systems can generate; minor misclassifications due to inadequate segmentation are often dismissed as they might not be statistically significant, however systematic misclassifications can cause unacceptable deviation in the data and limit the intended application of the technology. The system’s performance was further validated through several tests that involved identifying objects of known sizes to ensure the reliability on the consistency of the particles’ segmentation.

Jan 21, 2025

By Romel B. Villanueva

At the Yanacocha gold mine, in the Andes of northern Perú, the first instrumental tests were carried out in October 2019 to detect the initiation sequence of a production blast by detecting the EMF signal produced by the detonation from each blast hole in the sequence. Several experimental tests were carried out to choose the correct antenna and find the best setup of the high-speed Data Acquisition device (DAD) to detect these electromagnetic waves. Finally, the first measurement was obtained. With the instrument recording at a rate of 1 million samples per second, the initiation sequence was detected with 99.5% accuracy. It was found that it corresponded, without a doubt, to the designed scheme. The main result is that these tests provide us with a method and instrumentation to verify if the planned initiation sequence is carried out correctly in the field. In this way we can find operational deviations and detect possible misfires. This method has proven to be accurate, fast and easy to implement, mainly requiring an EMF signal capture equipment that can record at very high speed, something that is increasingly easier to satisfy with the development of microcontrollers. On the other hand, the type of antennas used in this method are low cost and very commercial. These tests have improved our understanding of the nature of detonation and have marked a new milestone in the development of blasting instrumentation in Peru.

Jan 21, 2025

By Carlos Alvarado, Hernan Narea, Jhon Silva, Bryan Townsend, Katherine Gil, Brayan Caceres, Felipe Pontanilla

With the promising development of new technologies, automation in Drill and Blasting (D&B) is on the horizon. The data generated in all D&B activities, which is currently segregated, can be linked to become information and carry a logical meaning. This information can be used to identify critical activities and make decisions regarding corrective measures to accomplish the goals of D&B. Minera Caserones, supporting Alert2Gain (A2G), and Dyno Nobel, has been working on the development of a quality assurance and quality control (QAQC), system for the mine involving all D&B activities. The main variables in the model for D&B include data from the geology of the deposit, drilling, explosive products, and material loading, among others. To create the model, the mine is divided into blasting polygons. Those polygons are part of a block model. The block model is assembled following different rules, such as: • Block sizes of 4m x 4m x 15m, • Classification of the blocks to a particular blasting polygon using a geospatial intersection algorithm, • Algorithms connect all the pieces of data automatically with the minimum of human intervention and populate the block model, Because measuring data for each block is impossible, another set of rules and algorithms completes the model. Dyno Nobel generates an essential set of data for the QAQC system. Explosive truck loading rates and explosive products, among other data, are also included in the system. The system autogenerates reports every hour, and a summary of the results of each mining day (a mining shift of 12 hours) is distributed by email to all responsible persons to identify the critical tasks and then to make the proper adjustments to accomplish the goals of D&B. The information is updated every hour and available through a dashboard for easy and straightforward interpretation. This paper explains the conceptual details of the QAQC system implemented in Minera Caserones, how the data is aggregated automatically from the different sources, shows examples of the type of information in the dashboard, and presents a successful case where a deviation was detected, and the corrective measures that were implemented to keep the performance of the D&B activity. The paper finally discusses the next steps toward an autonomous D&B system based on new AI technologies, with minimum human intervention.

Jan 21, 2025

By Jorge Cárdenas, Luis Huaroc, Máximo Cari, Nestor Delgado

In Peru, after four years of pandemic, some mining companies have chosen to install integrated operating centers in central offices where through network technology and video surveillance it allows them to carry out their activities remotely, this has become a disruptive strategy to promote a safer and smarter mining industry. Our fundamental value is to improve the quality of life, safety and well being of our collaborators, that is why we have created the remote blasting engineering control center " Core" that allows us to humanize mining. Core is an integration of experience, security, technology, quality of life and artificial intelligence; it has media technology connected directly to the mining operation, specialist engineers and technical assistants in team they seek to create optimal proposals of drilling and blasting designs remotely that generate added value to customers. In the planning process the team suggests drilling meshes, in the loading process there are optimized, digitized designs and efficiency in the factory trucks finally in the safety process allows us to identify inadequate pipes within the blasting project, deviation of procedures, remote inspections, identify operating conditions to prevent future risks that may arise in the blasting process. The remote communication systems allow you to monitor mining operations remotely to identify and alert any operational or security deviation that was not identified by the personnel present in the operation, as well as to store images in case investigations are required. The results obtained have allowed us to reduce the exposure of personnel to any risk of the mining operation, to optimize times in the activities of our engineers who are in the mining operations since there is the permanent support of centralized specialists to face every challenge that arises in the operation, for the engineers who are in the offices of Core can be very close to the family and do not lose it, and for our customers it is to meet their needs with engineers specialists in the drilling and blasting process, as well as in safety to be able to proactively cope with any deviation that arises.

Jan 21, 2025

By I. James, R. J. Durrheim, M. S. D. Manzi, O. Valeshin, J. Lepine, L. V. Socco, C. Colombero, A. Malehmir, M. K. Rapetsoa, M. Sihoyiya

The FUTURE project aims to enhance seismic surveying in South African mining by integrating advanced acquisition technologies. In this paper, we detail surface and underground seismic surveys at the South Deep gold mine as part of the project. Surface seismic acquisition used co-located broadband micro-electromechanical sensors, one and three component recorders connected to geophones, distributed acoustic sensing using a straight fibre optic cable, along with a 6 ton broadband seismic vibrator operating with 4–180 Hz linear sweeps. In addition, underground surveys employed a combination of straight, and helically wound fibre optic cables, cabled-based and nodal sensors, along with a 500 kg drophammer mounted on a skid steer bobcat. The surface and underground seismic arrays were time synchronised using a GPS-time transmitter to allow for accurate seismic data recording in a GPS-denied environment. Results show the efficacy of these techniques in acquiring high-resolution seismic data, revealing detailed subsurface geological structures and mineralisation down to 3500 m below ground surface. Surface data revealed clear seismic reflections corresponding to the Black Reef and Ventersdorp Contact Reef. An underground P-wave velocity model exhibits low velocity anomalies that are associated with fracturing, while a P-wave reflection stack section shows significant reflections and a degree of faulting below the tunnel floor that was not observed on the surface reflection seismic data. We highlight the potential of these technologies to enhance safety, efficiency, and sustainability in mining. This study sets a benchmark for future reflection seismic surveys, paving the way for safer, more efficient, deep mineral exploration and extraction practices.

Jan 12, 2025