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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 M. Ganster

Austria’s biggest supplier of oil and gas, transports gas through the West Austria Gasline for domestic consumption. In addition, the OMV also works as gas carrier and ensures the transit into neighbouring countries.

Jan 1, 2010

By Ravi Sahu, Kris Jeremiah

This paper aims to study the benefits of using Post Processed Kinematics(PPK) surveying methodology combined with Drone photogrammetry to achieve highly precise positioning (X, Y, Z) of drill holes based on the drill pattern and to highlight innovative workflow of transmitting the drill plan to smart drills for accurate drilling.

Feb 1, 2020

By Carlos Campos Junior, Leonardo Soares Chaves, Raul Carretero Hoz, Renato Jacome Costa, Davi Bastos Martins de Oliveira

The Vale’s Serra Sul mine, also known as S11D project, is one of the world’s largest open pit iron ore mines, located in Brazil’s Amazon region. The mine produces around 90 Mt of high-quality iron ore annually. Its unique orebody enabled the S11D project to adopt a truckless mining system with In-Pit Crushing and Conveying (IPCCs) for ore exploitation and waste stripping. The IPCCs system requires crushing the waste, mainly composed by the jaspilite lithology, and is also conveyed to waste deposits several kilometers away from the mine. Due to Amazon’s environmental restrictions, the project was designed with preliminary geological knowledge, leading to the installation of primary crushers not designed for the hardest jaspilite, with uniaxial compressive strength (UCS) up to 500 MPa. This resulted in low waste crushing performance, affecting stripping ratio and threatening future production. A project was developed to improve the fragmentation of the jaspilite, allowing higher waste IPCC production, and reducing the risk to the production due to low performance of waste crushing and conveying. The first challenge was the independence of the geological and the geomechanical models, while only the geological model was considered in blast designs, the geomechanical model describes six waste groups of jaspilite classified according to their strength. A new geological model was then created to incorporate the geomechanical classification, allowing different blasting design according to the rock strength of the jaspilite. The blasting pattern on most compact jaspilite was reduced 27%, from 22m² to 16m² in 9 7/8” diameter holes, with a proposed theoretical reduction of 23% of the P80, from 326mm to 250mm. The second challenge was the implementation of the new design, as this pattern size and the high powder factor (2.9 kg/m3) were paradigms for such a large iron ore mine. The measured results have shown 25% reduction of the P80, the crushing rate was increased by 17% (230t/h), saving around $2.4 million annually in crushing and conveying system maintenance.

Jan 21, 2025

By Patricio González Santis, Jacopo Seccatore

This paper documents drilling and blasting activities from gold mining in Ecuador and Chile. First, are described the outdated and often non-rational techniques employed by miners, to provide a general framework of the current methods. Then, it is shown what can be improved and how the current methods can be modified. Finally, are shown some field applications and the comparisons of the results obtained

Feb 1, 2020

By Cristian Castro, Patricio Gomez, Jason Furtney, Augusto Lucarelli

Understanding the effect of blast-induced damage on wall stability is critical to safe and economical operation of a large open pit mine. In this paper, a numerical modeling methodology is used to investigate damage to rock at distances of greater than 10 m (30 ft) from a blast. Two applications of the model are demonstrated. First, the method is applied at a zinc mine to investigate the effects of pit blasting on underground stopes. The model predictions are compared with the scaled distance formula. Next, the model is used to investigate a common problem in which unfavorable jointing creates a rock wedge on the bench above a blast. The numerical predictions of wedge stability are compared to the wedge energy model described by Wong & Pang (1992).

By Cristian Castro, Patricio Gomez, Jason Furtney, Augusto Lucarelli

Understanding the effect of blast-induced damage on wall stability is critical to safe and economical operation of a large open pit mine. In this paper, a numerical modeling methodology is used to investigate damage to rock at distances of greater than 10 m (30 ft) from a blast. Two applications of the model are demonstrated. First, the method is applied at a zinc mine to investigate the effects of pit blasting on underground stopes. The model predictions are compared with the scaled distance formula. Next, the model is used to investigate a common problem in which unfavorable jointing creates a rock wedge on the bench above a blast. The numerical predictions of wedge stability are compared to the wedge energy model described by Wong & Pang (1992).

Feb 1, 2020

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 Scott G. Giltner, Alex Schwenk

An iron operation sought to extend the life of the mine by conducting a major pit pushback in an area close to several public structures and the neighboring town. The result of the pushback would make millions of tonnes of ore available for mining allowing many additional years of taconite mining. This paper discusses the initial development blasts conducted for the pit pushback. For the development blasts, it was determined that no fly rock should leave the mine site and that the blast vibrations should be as low as possible, but specifically under 19 mm/s (0.75 in/s) at a nearby sewage treatment plant. One issue complicating the blast design was the variation in hole depth within any given blast. For the initial sinking shot, the hole depths varied from 6.4 m (21 ft) to 12.5 m (41 ft). In the subsequent blasts the hole depths within each blast could vary up to 5.8 m (19 ft). Various tools were employed to design the blasts to ensure there was no fly rock and that the blast vibrations were as low as possible. UAV surveys of the blast areas were conducted to provide a 3-D representation of the free faces and bench surface. The 3-D point cloud produced from this was used to measure the shape of the free faces. Once the shape of the free faces was quantified, it was possible to establish proper placement of the crest holes and develop a custom explosive load for each blast hole. In addition, signature hole analysis was performed for each blast to determine the optimum delay time that balanced the need for minimal vibration, prevent fly rock, and a well fragmented muck pile. Electronic detonators were applied to achieve the necessary control of the blast that balances these three concerns. The results of the seven blasts conducted to date provided the desired results. The peak vibration level at the sewage treatment plant for the seven blasts was 10 mm/s (0.40 in/s). The only fly rock occurred when there was a miscommunication in the blast design resulting in under burdened holes on the front row. To date, the mine has been able to safely expand the pit into an area that will add many years to the mine life. The muck piles have been well fragmented with reports from the shovel that they have all dug well.

Jan 21, 2025

By Christoph Muller, Geoffrey Liggins, Mohan Hensman

Modern commercial blasting is as much a technical process as it is a business one. As with most processes both aspects of blasting are driven by and generate new data. The time-critical nature of commercial blasting in mining and construction projects, dictate the timely exchange of information so as not to impede production or commerce. Up-to-date information about the blast to be undertaken can help suppliers: meet customers’ expectations to address challenging ground conditions; react to a market where quickly changing orders occur regularly; and address as-drilled blast patterns as opposed to baseline plans. “Real-time” data exchange into and out of the blasting process supports the whole-of-mine data management that the industry is migrating to.

Jan 1, 2010

By Gungor Tuncer, Ali Kahriman, Abdulkadir Karadogan, Umit Ozer

The environmental problems such as vibration, and air blast are often faced, and discussed on mining, quarrying, civil constructions, shaft-tunnel, pipeline, and dam operations where blasting is inevitable. It is necessary to establish national standards towards to minimize the environmental problems induced by blasting and judicial matters in our country as it is in USA, EU countries and the other developed countries. This necessity and the obligatory of accepting the European Union criteria for Turkey that has started the procedure of joining to EU emphasize the importance of this study. In other words, the establishment of a particular national standard related with this subject is inevitable for Turkey. This will be possible only by studying, applying scientific methods and techniques by the experts.

Jan 1, 2010

By Andrew Palangio, Blessing Taiwo

Understanding rock mass structural features is essential for optimizing blast design, highwall control, and evaluating post-blast performance in both surface and underground mining operations. This paper presents a comprehensive methodology utilizing image-based structural mapping to accurately characterize geological discontinuities including joints, faults, and lineations captured from both terrestrial and aerial imagery at varying scales. Key structural parameters such as joint orientation, spacing, and apparent in-situ block size are extracted to understand rock mass classification and enhance blast design inputs with greater geotechnical precision. The study introduces a significant enhancement to the existing discontinuity assessment algorithm by integrating a deep learning-assisted detection process. This improvement enables more accurate, quantitative and consistent identification of pre-existing cracks and surface features across complex bench free faces. The enhanced system facilitates better evaluation of how structural features influence blast fragmentation, energy distribution, and slope stability. A case study from a limestone quarry illustrates the use of a derived comminution factor based on the relationship between joint-controlled pre-blast block sizes and post-blast fragmentation to evaluate blast performance and optimize future design strategies. The results highlight the value of structural analysis in reducing overbreak, minimizing underbreak, and improving fragmentation predictability. This paper emphasizes the importance of integrating structural assessments into the blasting workflow to enable a more data-driven, geotechnically informed, and performance-optimized approach to modern blast design and evaluation.

Jan 26, 2026

By Jennifer Williams, Donald J. Berger

Originally built between 1913 and 1916, the Ashton Dam & Hydroelectric Facility has experienced various seepage and piping incidents since completion. Ashton Dam is located within 15 miles (24 km) of the historical Teton Dam failure site and about 2.3 miles (3.7 km) west of Ashton, Idaho. Numerous repairs conducted over the years ranged from filling sinkholes on the crest of the dam to placement of rockfill on the upstream slope to improve seismic stability. In addition, the existing low level outlet works was grouted full and abandoned in 1991 due to significant vibrations induced on the dam during its operation.

Jan 1, 2014

By Robert Lee, Pertti Paavola

Automated vibration monitoring and web-based data distribution has proven itself on the largest single construction project ever undertaken in Finland. The excavation for the Kamppi Center Project in the center of Helsinki was completed in November of 2003 and involved the removal of over 200,000 m3 (260,000 yd3) of rock and over 1,700 individual blasts. A system was installed, incorporating 37 discrete monitoring points located throughout an underlying metro station, and other surrounding underground and surface facilities. After every blast, vibration data was automatically transferred from the monitoring network to a server database. Stakeholders were able to access and review vibration reports on a password-protected website within 90 seconds of each blast. This allowed engineers to verify that recorded levels were in compliance with established limits, before proceeding with subsequent blasts. The data was also imported into a semi-automated Scaled Distance tool for analysis using linear regression techniques. This was used to determine, and adjust for trends in blast-induced vibration.Copyright

Jan 1, 2004

By C. K. McKenzie

Presents outline of flyrock model and a field procedure to validate predictions of maximum projection distance. Field results are presented from 13 field tests with two different hole diameters.

Feb 1, 2020

By Claudio Lechuga, Carlos Scherpenisse, Juan Rafael Otaiza

From the analysis of drilling process, Block Model information, drilling pattern data and expected fragmentation targets; GBlast® software optimizes the explosive charge design in order to standardize the particle size of each blast.

Feb 1, 2020

By Pharis E. Williams

The ability of voids, microballoons, and even solids to sensitize explosives has been known and used for many years. This phenomenon has generally been studied and reported under the terminology of "hot spots" because of the increase in local pressure and temperature when a shock wave encounters such sensitizers. A method for treating this phenomenon in detonation theory or in a detonation model has been studied for almost the same length of time. Perhaps because of the complexity and non-linearity of the void, or microballoon collapse, several of these studies have used the expediency of including additional terms in the burn rate law to account for the influence of hot spots. The detonation model proposed here considers the sensitization due to discontinuities in the shock impedance to be a mechanical phenomenon to be accounted for in the mechanical equations governing the detonation and not in the burn rate law. While this is not a new contention, the method for handling this non-linear phenomenon within the proposed model is new. The model also includes a method which accounts for the manufacturing variables of emulsion matrix cell size, microballoon size and type, as well as energetic additives.

Jan 1, 1992

By Huang Daguang, Paulo Couceiro, Juan Navarro

Mining is typically conducted through a set of interdependent unit-operations, which commonly include drilling, blasting, digging and hauling, in order to deliver the required ore material into the comminution circuit and to remove waste rock with minimum impact in the operation. In such complex environment, the identification of critical paths, and respective interfaces between different unit-operations, are necessary to determine a sustainable long-term operational program. Facing this challenge, adaptive cost optimization strategies are required to increase productivity and revenue while minimizing potential environmental impacts. Since the overall mining efficiency can be strongly impacted by blasting outcomes, an operating method based on the searching of the ideal blast design is required in order to minimize the mine total cost of ownership. The implementation of a consistent continuous improvement program requires specific care in terms of design, control and execution of the different stages of blasting. For that, the application of the most advanced technologies for rock characterization, based on drill monitoring systems, and smart explosive products, allows the improvement and control of blast results by adapting the explosive energy distribution to the rock condition, so as to optimize the performance of downstream stages such as digging, hauling and comminution. This paper describes the application of a heuristic optimization approach, where blast parameters are used as decision variables to evaluate the potential impact of several blasting scenarios on subsequent unit operations, under the continuous ability of modelling, measuring and calibrating operational performances along of the mine cycle.

Feb 6, 2023

By Joshua Hofman, Braden Lusk, Erin Morris

Explosions in urban environments, whether of accidental or malicious cause, often result in extensive injuries, loss of life, and property damage. The ability to predict the damage inflicted by these events is highly sought after; in order to predict damage, the behavior of blast waves within these environments must be quantified and understood. Urban constructs such as buildings and roadway intersections affect the natural propagation of a blast wave, intensifying or rarefying the wave depending on their arrangement.

Jan 1, 2012

By S. M. Geerts, M. T. Wild

In this paper the performance effects of various shaped charge liner designs will be discussed. Several different charges will be tested and the liner design will be reviewed based on the performance in testing. The first type of shaped charge to be tested is a conical charge with dual confinement. For the purpose of this paper, dual confinement is a shaped charge with two liners but containing one explosive charge. Several charges with different dual confinement designs will be tested. Variations in configuration include charges with similar angle and similar diameter. The second type is a double conical shaped charge configuration. A double shaped charge will be considered to be two complete charges formed into a single cone. The goal of the project is to determine if any of the designs increase the efficiency and/or effectiveness of the shaped charge in comparison to the standard conical shaped charge. A standard conical charge will be detonated against a witness plate to get a standard depth of penetration or a baseline. All charges will have a seven cone diameter standoff, allowing the data to be compared to the control charge. Computer modeling will be used to predict the results of the testing that will be conducted. The actual results will be compared to the computer simulation for validation.

Jan 1, 2010