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By Brent A. Elliott, J. Richard Kyle

Texas is a major producer of industrial mineral resources required by the state’s ever-growing population that now exceeds 28 million. Texas typically ranks in the top three states for the value of non-fuel mineral production with a total value of $5.2 billion in 2017, accounting for 6.9% of the total US mineral value. Almost 90% of current Texas industrial mineral value comes from the production of cement, crushed stone, industrial sand, and construction sand and gravel. Construction material consumption is focused in the 25 metropolitan areas of the state with populations of > 100,000 residents. Industrial mineral consumption is dominated by the four most populous regions of the state—Houston, Dallas-Fort Worth, San Antonio-New Braunfels, and Austin-Round Rock—with an aggregate population of more than 18 million. More than 11,000 employees work in Texas mining and processing operations. Texas produces more crushed stone than any other state from more than 200 quarries; a similar number of operations produce sand and gravel. Specialty industrial sand production for use as proppants in hydraulic fracturing for enhanced petroleum production serves as an excellent example of how developments in one industry sector can markedly affect another industry; the production of industrial sand in Texas has markedly increased over the past decade, reaching $1.3 billion in 2014. With Texas’ population projected to reach 50 million by 2050, continuing in-state development and production of industrial minerals will be required to supply its residential, commercial, and industrial users. Favorable geology and economic factors provide opportunities for identification and development of new industrial mineral production sites.

By Bruce Bryant

Silver ore was discovered at Aspen in 1879, but the district did not reach full production until 1888 after lawsuits were settled and railroads furnished less expensive transportation to the outside world. The boom years were 1888-92; production declined thereafter. From the middle 1920's until 1950, the Midnight mine in the Richmond Hill district furnished most of the output in the Aspen quadrangle. Since 1950, little mining has been done at Aspen. The metals produced were silver, lead and zinc. Native silver dissolved from the sulfide ores was redeposited by waters circulating as deep as 300 m below the land surface, resulting in great secondary enrichment of many of the deposits. Over 100 million ounces of silver were produced in the Aspen quadrangle. Low-grade lead-zinc deposits remain between the old workings locally, and data available suggest that primary ore below levels mined is also of low grade. The ore occurs in the Mississippian Leadville Limestone and the lower part of the Pennsylvanian Belden Formation in sites that were made favorable for deposition by a number of stratigraphic and structural factors.

Jan 1, 1982

Several years ago, Hudco Industrial Products began experimenting with the idea of levitating a conveyor belt with a film of air, much like the puck on an air-hockey table. While conducting its research, the company found out that some Russian and Dutch companies attempted the concept during the 1970s. After studying those conveyors, Hudco determined that its design was better. The Hudco advanced air-supported conveyor consists of an air-tight plenum, or chamber, that runs the length of the belt. The topside of the plenum has a formed trough. It corresponds to the profile of conventional troughing rollers. Low-pressure air is provided to the sealed plenum from a low horsepower blower. This pressurized air is metered and released through the central portion of the trough and reacts against the underside of the belt. The differential pressure between the top and bottom surfaces creates the lift to support the loaded belt. Airtight covers are installed to seal the transported materials in the plenum trough.

Jan 1, 2002

By G. Roberts, S. S. Klima, W. R. Reed, J. Deluzio, G. Ross, A. Mazzella

The abstract discusses the problem of silicosis among roof bolter operators in coal mines due to respirable quartz dust (RCS) exposure. It presents a study comparing a new wet box collection system to the traditional dry box system. The wet box system uses water to saturate collected material, reducing RCS exposure during cleaning. The study found that the wet box system significantly reduced RCS exposures and quartz content in samples compared to the dry box system.

May 11, 2022

By W. Rogers

Blast-induced rock mass displacement can have a significant impact on ore loss & dilution. The mischaracterisation of the grade boundaries both prior to, as well as a result of blasting can lead to significant financial losses on account of ore loss and dilution. Ore dilution occurs when waste material is miscategorised as ore and sent for processing or stockpiling, diluting the run of mine head grade and recovery. Ore loss takes place when valuable mineral is miscategorised as waste and sent to the waste dumps, thus never being processed and recovered. Extensive research has been conducted at the University of Queensland over the last fifteen years to understand the impact of blast movement on ore loss and dilution. Recent outcomes of this research have developed innovative tools and techniques to measure and model blast movement. These techniques have been implemented at Ahafo gold mine in Ghana to understand blast movement dynamics and to implement solutions to reduce blast-induced ore loss and dilution. These solutions are validated through controlled trials and have been incorporated into site standard operating procedures to sustain the benefits.

Jan 1, 2012

By Matthew E. MacGregor, Hugh T. Kelly

I.H. 635 (LBJ Freeway) was constructed as a loop freeway around the city of Dallas in the late 1960s and early 1970s with a design capacity of 160,000 vehicles per day (vpd). Today’s facility is carrying over 270,000 vpd. To help mitigate community concerns with regard to right-of-way issues, noise, safety, and traffic disruption, the Texas Department of Transportation (TxDOT) is planning a number of significant improvements. The West Section improvements include the construction of managed HOV/Toll lanes. Within this 8-mile section, TxDOT is planning two mined tunnels(1.5 and 1.9 miles long) beneath the LBJ Freeway. The mined tunnels will connect to cut-and-cover box sections in both the east and west directions. This paper presents an overview of the project development from the design schematic, through the geotechnical investigations, into the current design stage. The project is being planned for implementation by use of a Comprehensive Development Agreement.

Jan 1, 2005

By Rambabu Pothina, Rajive Ganguli

The economics of a mineral processing circuit is dependent on the numerous sensors that are critical to optimization and control systems. The sheer volume of sensors results in mines not being able to keep the sensors calibrated. When a sensor goes off calibration, it results in errors which can severely impact plant economics. Normally, these errors are not detected until the error grows and becomes a large (“gross”) error. Undetected errors are not remedied until the next calibration, which on average are a year apart Beamex (2019) [1] across all industries. Classical statistical methods that depend on linear relationships between input and response variables are typically used to find gross errors, but are not effective for highly non-linear and non-stationary operations in mining and mineral processing industries. Calibration of sensors is time-consuming and generally requires physical intervention that results in equipment downtimes causing production losses. Therefore, in situ detection methods are warranted that do not require physical removal of sensors to compare with standard measurements or well-calibrated sensors. Data-mining based techniques and algorithms have high success rate in tackling such problems. This paper presents results from a groundbreaking multi-year big data research project whose goal was to develop data-mining-based original techniques in a multi-sensor environment to identify when sensors start to stray, rather than wait for errors to grow. The carbon stripping (gold) circuit in the Pogo Mine of Alaska was selected for this project. Maintaining strip vessel temperatures at optimum levels is crucial for maximizing gold recoveries at Pogo, and hence the focus was on the temperature sensors of the two strip vessels. An automated algorithm to detect errors in strip vessel temperature sensors was developed that exploited data from multiple sensors in the strip circuit. This algorithm was able to detect with a high success rate when bias errors of magnitude as low as ± 2% were artificially induced into strip vessel temperature data streams. The detection times of about 1 month were much less than the industry average calibration frequency of 1 year. Thus, the algorithm helps detect errors early, without stopping the circuit. The algorithm alarms can serve as triggers when calibrations are done. Experimental methodology along with results, limitations of algorithms, and future research are also presented in this paper.

By Rambabu Pothina, Rajive Ganguli

The economics of a mineral processing circuit is dependent on the numerous sensors that are critical to optimization and control systems. The sheer volume of sensors results in mines not being able to keep the sensors calibrated. When a sensor goes off calibration, it results in errors which can severely impact plant economics. Normally, these errors are not detected until the error grows and becomes a large (“gross”) error. Undetected errors are not remedied until the next calibration, which on average are a year apart Beamex (2019) [1] across all industries. Classical statistical methods that depend on linear relationships between input and response variables are typically used to find gross errors, but are not effective for highly non-linear and non-stationary operations in mining and mineral processing industries. Calibration of sensors is time-consuming and generally requires physical intervention that results in equipment downtimes causing production losses. Therefore, in situ detection methods are warranted that do not require physical removal of sensors to compare with standard measurements or well-calibrated sensors. Data-mining based techniques and algorithms have high success rate in tackling such problems. This paper presents results from a groundbreaking multi-year big data research project whose goal was to develop data-mining-based original techniques in a multi-sensor environment to identify when sensors start to stray, rather than wait for errors to grow. The carbon stripping (gold) circuit in the Pogo Mine of Alaska was selected for this project. Maintaining strip vessel temperatures at optimum levels is crucial for maximizing gold recoveries at Pogo, and hence the focus was on the temperature sensors of the two strip vessels. An automated algorithm to detect errors in strip vessel temperature sensors was developed that exploited data from multiple sensors in the strip circuit. This algorithm was able to detect with a high success rate when bias errors of magnitude as low as ± 2% were artificially induced into strip vessel temperature data streams. The detection times of about 1 month were much less than the industry average calibration frequency of 1 year. Thus, the algorithm helps detect errors early, without stopping the circuit. The algorithm alarms can serve as triggers when calibrations are done. Experimental methodology along with results, limitations of algorithms, and future research are also presented in this paper.

By W. G. Pariseau

"The Crandall Canyon Mine (CCM) is located in the Wasatch coal field in central Utah. Extensive longwall mining at CCM preceded a decision to recover coal left in barrier pillars on each side of a set of main entries extending far into the mine. During mining in March 2007, a major bump occurred that led to cessation of mining in the barrier pillar on the north side of the mains and to the start of mining in the south barrier pillar. Subsequent loss of ground control in August 2007, through coal pillar bursts had tragic consequences with loss of six miners and shortly afterward three rescue team members. A U.S. Mine Safety and Health Administration (MSHA)report describes the events in detail (MSHA, 2008).An important lesson to be learned from CCM is the need to select a computer program suitable for pillar design. Computer programs are engineering tools and selecting the right tool for the job is essential. In this regard, minimum program requirements include capability for computing stress distribution within a pillar and adjacent roof and floor strata. The reason is simple: strength of rock is stress dependent; both vary from point to point in pillars and adjacent strata. Preferably, one should follow the evolution of stress as the mining plan is executed from start to finish to assure safety or to warn of a potentially hazardous situation developing as mining progresses.The approach to the problem posed by barrier pillar mining at CCM is conventional in the sense of applying well known finite element modeling techniques to analysis of a proposed mining plan. The engineering purpose is to evaluate the mining plan with respect to ground control questions including roof, floor and pillar safety. Results of previous two-dimensional finite element analysis indicated pillar safety was by no means assured (MSHA, 2008; Pariseau, 2008; Pariseau, 2011). Geometry of barrier pillar mining is limited in two dimensions for example, crosscuts are not seen in vertical cross sections. While three-dimensional analyses are preferred, even moderately sized regions often lead to very large problem sizes that exceed computer capabilities. However, a recent development in finite element modeling of tabular deposits allows for whole mine analysis in three dimensions. This technique involves a dual node - dual mesh concept. Both have been used separately in much earlier work, but are only now used in combination. It is possible to have an estimation of subsidence at a kilometer scale and details of stress, strain and displacement about barrier pillars, main entries and pillars, and so on at a meter scale (Pariseau, 2014). No compromise involving empirical formulas or similar guess work is required. Indeed, all calculations are based on first principles: physical laws, kinematics, and material laws. Effects of joints and in situ variability or uncertainty in strata properties, elastic moduli and strengths, may be included for greater realism. An important objective of the present study is to assess the role of three-dimensional pillar geometry in arriving at conclusions regarding barrier pillar mining versus two-dimensional results."

Jan 1, 2014

By J. F. T. Agapito

OCI Wyoming mines two flat-lying trona seams that are 3- to 3.5-m- (10- to 11.5-ft-) thick, about10 m (33 ft) apart and 250-m- (820-ft-) deep at its Big Island Mine in Wyoming. Continuous miners and a yielding-pillar system have contributed to improvements in resource recovery and productivity. The use of yield pillars minimizes the stresses transmitted from the upper to the lower seam. However, yielding must not impact the good, long-term stability needed to prevent subsidence for a large portion of the mine beneath the Green River channel.

Jan 1, 2000

Mining is big business in Ontario. The province is Canada?s leading mining region. It consistently ranks among the top 10 jurisdictions worldwide for exploration spending, reaching about C$1 billion in 2011. More than 26 percent of all exploration and appraisal dollars spent in Canada are invested in Ontario. Minerals produced include nickel, copper, platinum group elements (PGE), cobalt, zinc, diamonds, gold and silver. It was reported that there are more than 600 mining exploration projects in the province. And, recent discoveries of chromite in northern Ontario?s Ring of Fire will add to the province?s mineral production in the coming years.

Jan 1, 2013

By Tyler Acorn, Brandon Wilson, Jeff Boisvert

Scenario-level uncertainty is a representation of large-scale differences encountered when considering ultimate mining pits optimized over various subsets of stochastic realizations. Accounting for scenario-level uncertainty allows mine plans to be assessed against several probabilistic subsurface interpretations. Scenario-level uncertainty is found through clustering stochastic geostatistical realizations and optimizing final pits across the realizations in each cluster. Where these pits are geometrically different, plans for each scenario differ. Knowing these differences allows the value of each planning alternative to be assessed based on the value and relative probability of each scenario. These results also facilitate the use of formal decision-making frameworks for planning, leading to optimization that better represents the full statistical characterization of the deposit. An example utilizing this approach evaluates both infrastructure placement and drilling program requirements. In both cases, scenario-level uncertainty improves initial plans by limiting opportunity costs and identifying additional potential.

By Tyler Acorn, Brandon Wilson, Jeff Boisvert

Scenario-level uncertainty is a representation of large-scale differences encountered when considering ultimate mining pits optimized over various subsets of stochastic realizations. Accounting for scenario-level uncertainty allows mine plans to be assessed against several probabilistic subsurface interpretations. Scenario-level uncertainty is found through clustering stochastic geostatistical realizations and optimizing final pits across the realizations in each cluster. Where these pits are geometrically different, plans for each scenario differ. Knowing these differences allows the value of each planning alternative to be assessed based on the value and relative probability of each scenario. These results also facilitate the use of formal decision-making frameworks for planning, leading to optimization that better represents the full statistical characterization of the deposit. An example utilizing this approach evaluates both infrastructure placement and drilling program requirements. In both cases, scenario-level uncertainty improves initial plans by limiting opportunity costs and identifying additional potential.

By K. Saikiran, A. R. Nalla

Longwall management, regular shield maintenance, and evaluation of ground control problems can be performed using real-time shield monitoring program. Based on real-time shield pressure data, evaluation of intensity and interval of periodic weighting, estimation of time-dependent pressure increase and the effects of geologic anomalies can be obtained. In this study, full-face shield pressure data of over 457 m (1,500 feet) of face advancement is analyzed to evaluate shield response in the presence of surface lineaments, floor undulations, and multiple main roofs. Shield pressure increase due to web cutting is also correlated with setting pressure during periodic weighting and normal time. In addition, time-dependent pressure increase rate on Sundays and holidays is also correlated with time average pressure and the location of previous periodic weighting.

Jan 1, 2000

By F. Mielli

Ranging between 20% and 40% of the typical mining operational costs, energy in mining operations is a growing concern for the industry. However, this concern is a complex, multi-faceted variable that involves government regulations, societal pressures, cost and competitiveness. A mining company successful in energy efficiency is becoming the standard of a successful company. The suggested energy strategy in mining and mineral processing operations has to follow a well structured approach that entails the following: ? Understanding where energy is being used and why, ? Recommending and implement energy conservation measures, ? Driving visibility to targets and results, ? Leveraging the energy spend across the enterprise, ? Developing a robust energy and sustainability strategy.

Jan 1, 2012

By W. Scheetz

The Brewer Gold Mine is an open-pit, heap leach operation that processes about 122 kt/m (135,000 stpm). The mine is operated by Brewer Gold Inc., a subsidiary of Westmont Mining Inc., and is located near Jefferson, SC, about 80 km (50 miles) southeast of Charlotte, NC and 80 km (50 miles) northeast of Columbia, SC (Fig. 1). All of the ore to date has been produced from a breccia body of hydrothermal origin and a related smaller body of fault-controlled ore, known as the B-6. Reserves at the time the mine commenced production were 4.6 Mt (5.1 million st) grading 1.4 g/t (0.042 oz per st) gold. History Although some reports of a pre-Revolution War shaft at the Brewer are in the literature (Lieber, 1856, Nitze and Wilkens, 1897), gold was first produced in earnest from the Brewer Mine in 1828. Production occurred primarily from placer deposits south of the present mine workings. Lieber noted in 1856 that “every branch, gulch, ravine or even declivity of the main hill has been washed and rewashed.”

Jan 1, 1991

By D. M. Ziebarth

"During the mid to late 1960s, the underground potash industry in Saskatchewan was born. For the next four decades the industry operated at a steady pace, supporting a large part of the world demand, until 2008 when the potash market heightened. Operators were motivated to capitalize on this increased demand, new mines were proposed while existing mines were planning upgrades. Potash Corp. of Saskatchewan (PCS) was one of the major producers planning upgrades to its production facilities quickly, including modifying the existing headframe and shaft at the PCS Cory Site to accommodate a new 1.5-kt/h (1,650-stph) hoisting plant. Upon completion of the project, the innovative operations group continuously reviewed methods to increase production and reduce operating costs, allowing PCS to continue being competitive on the world market.BackgroundPotash production is a major Saskatchewan industry and has played a significant role in the economy for more than 40 years. Production commenced in 1962 when water problems were overcome at the International Minerals and Chemical (IMC) Mine near Esterhazy, Saskatchewan. A surge of development by other companies resulted in 12 companies opening 10 mines by 1970. In 1975, Potash Corp. of Saskatchewan was created by the government of Saskatchewan, and shortly thereafter purchased several mines in Saskatchewan, including the Cory Mine, near Saskatoon.Cory has been in operation since 1968 and is located 12 km (7.5 miles) west of Saskatoon in central Saskatchewan. The mine is located in the center of the world’s largest potash deposit, 1,000 m (3,300 ft) below surface.PCS has embarked on sizable capital expansions of more than CDN$7 billion.The $1.6-billion Cory expansion was expected to raise operational capability of the site to 2.7 Mt/a (3 million stpy), an increase of 1.9 Mt/a (2.1 million stpy). To achieve 2.7 Mt/a (3 million stpy) of finished product and considering the 22.6 percent average production recovery (Potash Corp, 2013), 12 Mt/a (13.2 million stpy) of ore must be hoisted to the surface for processing. To deliver this rate required upgrading of the hoisting plant to 1.5 kt/h (1,650 stph). To accomplish this ambitious challenge, creative thinking, careful planning and a cohesive team was needed to work together to ensure the schedule, budget and most importantly that the work was completed safely (Potash Corp., 2013)."

Apr 1, 2017

By K. S. Liddell

Ultra fine grinding is becoming increasingly used in the mining industry over recent years. The development of large-scale units for high volume grinding of low value materials and concentrates has opened up new areas of economical metal extraction. The ability of stirred vertical mills to produce very fine particles with high surface areas, is providing mine operators with novel extraction possibilities within gold concentrate regrind for Biox or leach feed, Activox autoclave feed preparation and lime slaking operations. The paper will review design, operational and maintenance aspects of ANI-Metprotech stirred vertical mills, comparing these to tower mills, horizontal bead mills and attrition mills.

Jan 1, 2001

By G. Tiess, S. Mujiyanto

Indonesia is a fast growing democratic developing country comprising more than 17,000 islands, founding member of ASEAN and a member of the G-20 major economies. It is one of the most highly mineralised countries in the world, the mining sector playing a pivotal role in the country's economy. In 2001, the Decentralization Law No. 22/1999 came into force and caused a transfer of authority and responsibility from central to regional and local administrative governments. The new Mining Law of 2009 substituted its 40 year old predecessor, but lacked detailed regulations for its implementation. These were only issued in 2010, which lead to a period of great uncertainty for investors in the mining industry. The new legislation intends to foster domestic economic development, which may be interpreted as protectionist policy. For the development of a sustainable mineral resources policy, further endeavours will have to be made.

Jan 1, 2011

By Rodrigo Jerez

Advances in inexpensive computer automation led to the development and use of a computerized ore control system at the Cyprus Copperstone Gold Mine near Parker, AZ. These new ore control practices improved accuracy, performance and productivity of the ore control effort. An automated system for data collection, including bar coding of blasthole samples, laboratory analysis, data management, grade estimation, cut delineation and ore zone stake out, plays a major role in ore control practices. This is of particular interest because of the large amount of blasthole information being processed, analyzed and reported daily. Copperstone Gold management has been progressive toward new, efficient methods regarding ore reserve estimation, long-term mine planning, short-term mine planning, ore control and surveying. Technological advances, including powerful personal computers, applicable mine planning software and surveying instrumentation, have become readily available and affordable. The computerized ore control procedures used at Copperstone include sample data collection, laboratory automation and computerized data management. These have reduced the time to complete ore control on a blast pattern by 50% to 75%. The final product - ore control - is generated in a more timely and accurate manner.

Jan 1, 1991