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By Edward Holloway

The basis for the selection of the ultimate pit for an open-pit mining operation is generally opaque. Some form of value-based analysis will generally guide the final decision; however, the value will often gradually plateau while the ultimate pit size continues to increase. There is no established framework to guide specialists in the selection of the ultimate pit, with such decisions regularly made on a somewhat arbitrary basis. The key component that is missing from the analyses typically used to select the size of the ultimate pit is risk. Once risk is quantified within the analysis framework, the decision-mak-ing range is significantly reduced and the process for select-ing the ultimate pit becomes more consistent, replicable and defensible. The technique outlined in this paper provides an approach to including risk in the process used to select the ultimate pit.

Jun 1, 2024

By Don Opacic

The disposal of sludges and other similar industrial wastes is a major problem. Liquid wastes from industrial operations, when treated, produce significant volumes of sludge which are difficult to dispose of, because of the chemical and physical properties of the sludge. In the mining industry sludge is produced from various water treatment operations, in particular mine drainage neutralization. Waste water from coal preparation plants also produces a sludge however the sludge is in fact a slurry containing clays, coal fines and coal impurities. In many areas the disposal of these sludges is producing a serious problem. Mine drainage sludge consists of a variety of hydrous iron oxides, usually ferric oxides, contaminated with other neutralization products such as calcium sulfate. The volume of sludge from mine water or mine

Jan 1, 1973

By P. Huttagosol

The use of computer models to design ultimate pit limits during feasibility study and long range mine planning is becoming a significant practice in open pit mining. One of the problems in determining optimal ultimate pit limits using true optimization techniques has been they require a great deal of computer memory and execution time. In this paper, the maximum closure of a graph, which is a true optimizing model developed by Lerchs and Grossmann, is modified for solving ultimate pit limit problems. By using some properties of the original L&G graph algorithm, the tree configuration can be reduced to only connections between positive ore nodes. The modified algorithm is shown to require less memory and processing time while still yielding an optimal solution.

Jan 1, 1989

By Ernest Baafi, David Drew

Microsoft Excel based ultimate pit limit (UPL) optimiser has been developed to determine the greatest economic value of an orebody. UPL manipulates a given geological block model to define an ultimate pit limit using either the moving cone, method or Korobov algorithm or Lerchs-Grossman technique. UPL is designed to be an adjunct to MS Excel; the cells in Excel are excellent analogue to the blocks in a geological model, providing X-Y dimensions in an easily viewable and editable state. The use of individual worksheets within an Excel workbook provides the necessary depth to a 3-D block model.

Jan 1, 2002

By Y. C. Kim

To generate a most profitable, ultimate pit limit is generally the first step in mine design. This paper presents a new graph theory oriented, optimum ultimate pit limit design algorithm which will maximize the total undiscounted net profit. This algorithm performs much better than the well known Lerchs-Grossmann algorithm, in terms of the reduction in computation time and computer memory requirements. This algorithm operates on many directed trees in a graph, where each vertex in a tree represents a block in the mine model. The formation of each directed tree is based more on the ore-waste support concept than the geometry constraints alone. The general procedures of the algorithm, programming considerations and two case study results are discussed in the paper.

Jan 1, 1992

By Randal J. Barnes

Computer based techniques for solving the Ultimate Pit Limit Problem have appeared in mining literature since the early 1960's. The majority of papers pertaining to this subject can be partitioned into one of two categories: discussion of the pros and cons of a particular algorithm, or a case study presenting specific applications of an algorithm. Subsequently, there has a1 so been considerable debate concerning the best techniques between, essentially, two camps: those favoring the moving cones techniques, and those favoring the techniques which yield true optimal pit designs. The purpose of this paper is not to add to this debate, but rather to present a few new ideas (partially a new look at an old idea), which can be easily implemented to noticeably improve any ultimate pit limit approach independent of the particular algorithm used. These ideas fall under the heading of "bounding the optimum" (Barnes and Johnson, 1980).

Jan 1, 1982

By P. Muduli, Y. Xi, T. M. Yegulalp, A. J. Arias

A short review of current practices and recent developments is followed by a description of a newly developed approach for solution of the optimum, ultimate pit limit problem. The new approach utilizes network modeling of the problem for solution by maximum flow algorithm. The latest developments in the implementation of maximum flow algorithm present significant time and memory savings as compared to initial development due to Ford and Fulkerson (1956). Results of a series of computational tests are presented to demonstrate how this approach performs as compared to the well-known Lerchs Grossman algorithm. It is also shown that the solution by the new method automatically includes several optimal solutions based on a predetermined number of benches to be included in the analysis.

Jan 1, 1994

To generate a most profitable ultimate pit limit is generally the first step in mine design. This paper presents a new graph theory oriented, optimum ultimate pit limit design algorithm which will maximize the total undiscounted net profit. This algorithm performs much better than the well known Lerchs-Grossmann algorithm, in terms of the reduction in computation time and computer memory requirements. This algorithm operates on many directed trees in a graph, where each vertex in a tree represents a block in the mine model. The formation of each directed tree is based more on the ore-waste support concept than the geometry constraints alone. The general procedures of the algorithm, programming considerations and two case study results are discussed in the paper.

Jan 1, 1990

By Tuncel M. Yegulalp

In this paper we revisit the well known "Ultimate Pit Limit Problem" and suggest an alternative approach for fast and efficient solution. We follow the approach originally proposed by Johnson and Barnes (1988), but utilize the "Excess Scaling Algorithm" in solving the equivalent maximum flow problem. This algorithm provides significant increases in speed and reduction in memory requirements over the well known Labeling Algorithm of Ford and Fulkerson (1956), enabling one to solve large problems with relatively small computers. We present results of a series: of benchmark tests using this approach against the well known Lerchs Grossman algorithm as well as a brief description of the new algorithm.

Jan 1, 1992

By H. Burton

"The selection of the ultimate pit shell has a major impact on the overall value of a mining project. The size and shape of this pit drives the selection of pushbacks, equipment, and project strategy, each of which are significant in their own right. Optimization of the ultimate pit shape is typically done using the Lerchs-Grossman algorithm with inputs of production costs, commodity prices, and pit slope constraints. This method ensures that every tonne mined is profitable but does not take into consideration the timing of material release. This timing is essential when calculating the Net Present Value (NPV) of the project, which is one of the most popular metrics for valuing deposits. Often, when the mining schedule and discounting are applied, material that was considered profitable before discounting becomes sterilized. The objective of this paper is to show the methodology for improving ultimate pit selection by considering the production schedule. Application of this technique will generally produce a smaller and higher-value pit than using the Lerchs-Grossman algorithm alone. INTRODUCTION The Lerchs-Grossman Algorithm was developed in the 1960s and exists to produce a mathematically optimum shape for open pit mines (1). This algorithm is now an industry leading technique for producing the theoretical optimum shape for open pits and is used in many popular pit optimization and strategic planning software packages, such as GEOVIA’s Whittle. The Lerchs-Grossman (LG) Algorithm is based on graph theory and optimizes on the assumption of non-discounted cash flows. This produces a mathematically optimum shape, but does not consider the timing with which the material will be removed from the ground. This is an important consideration, given that one of the most popular metrics for evaluating mining projects is Net Present Value (NPV) (2), which relies on the timing of cash flows as a major differentiator between options. This paper will discuss issues inherent in the use of ultimate pit selection based on undiscounted economic factors and illustrate a simple technique in Whittle, a leading software package, which can be used to improve the NPV of projects."

Jan 1, 2015

By J. Philip Bromberg

Any effectuation of a viable program of air pollution control will' require a basic understanding of the chemistry of atmospheric processes, the fate and migration of SO2, and the ultimate health effects of the sulfur oxides themselves. The migration and ultimate fate of Sop discharged into the atmosphere will be discussed with particular emphasis on the various conflicting views and how these relate to our present emission control regulations. Our present lack of knowledge is a severe detriment, and consideration will be given to those particular areas where future research may best be directed to provide the answers to a number of perplexing questions.

Jan 1, 1976

By Panlop Huttagosol

The use of computer models to design ultimate pit limit of an open pit mine during its feasibility study has become an emphasized procedure in mining. It is a normal practice in open pit mine design to generate the most profitable final pit limit. The limitations of designing this optimal pit limit have been the requirement of significant computing efforts as well as the use of complicated operations research techniques. In an attempt to describe a computer method that has an easy conceptualization and is able to provide a precise and desirable solution, a new technique is developed. The ultimate pit limit problem is formulated as a large scale transportation problem. The formulation is based on the use of a three dimensional block model to represent an ore body and surrounding materials. The solution technique is developed through solving the dual system of the formulated problem by using the adapted simplex algorithm of linear programming. The implementation on given case studies demonstrates that the new method is capable of providing an optimum pit value. The computing effort required by the algorithm is still the main constraint in solving a large scale problem. The technique provides open pit mine planners with an alternative tool in using a commercial linear programming software which is capable of solving a general transportation problem. The selected software must be able to handle a large scale problem, and it needs an additional effort td formulate the problem and transform a result into the ultimate pit limit solution.

Jan 1, 1992

By M. K. Mohanty

A modified coal flotation characterization procedure, referred to as the Advanced Flotation Washability (AFW) technique, has been developed which, compared to traditional procedures, provides a more accurate prediction of the optimum separation performance achievable by a froth flotation process. The AFW procedure uses a vertically-baffled flotation column which provides enhanced selectivity among particles of varying degrees of hydrophobicity due to a plug-flow environment and an improved carrying-capacity environment. In fact, the separation performance of the traditional procedures was enhanced by increasing the possibility of operating under improved selectivity conditions. The separation performance provided by the AFW procedure was superior to that obtained from multiple cleaning stages using commercially-available flotation columns under both kinetic and carrying-capacity limiting conditions.

Jan 1, 1997

By Serkan Saydam, Ercument Yalcin

This paper presents the results of Caldagi Nickel-Cobalt Ore Deposit's, located in Turkey, reserve and ultimate pit limit design analysis. Reserve analysis of any deposit requires two steps. First one is to constitute of block model of the deposit and second step is to generate ultimate pit limit. The block model of the Caldagi ore deposit has been created by means of geostatistics. The reserves of nickel and cobalt in this block model are defined as resource, approximately 12 million tons of nickel and 1 million tons of cobalt with average grades of 0.9% Ni and 0.03% Co, respectively. Ultimate pit limit analysis has been performed by considering economic, technical and legal factors. In this paper, the ultimate pit limits are generated by Lerchs & Grossmann (L&G) algorithm. As a consequence of ultimate pit limit design, total amount of tonnage to be excavated is 1.4 billions of tons, 700 million of which contains ore and 747 million of which is the tonnage of waste.

Jan 1, 2002

By M. Deutsch, E. González, M. Williams

"There is uncertainty in ultimate pit limits due to geologic variation and unpredictable economic landscapes. In this work we show how this uncertainty affects the ultimate pit and how it can be analyzed to improve the mine planning process. A stochastic framework using geostatistical simulation and parametric analysis is used to model the effects of geologic and economic variation on ultimate pit limits and overall project economics. This analysis is made possible by a new, highly efficient pit optimization implementation which can be automated and set up to calculate ultimate pits for hundreds of different scenarios in a matter of hours. Quantifying ultimate pit uncertainty early in the mine planning process allows mining engineers to make informed decisions regarding infrastructure placement, and to mitigate the possibility of incurring substantial costs relocating critical mine facilities. INTRODUCTION The mining industry is increasingly concerned with the effects of risk and uncertainty. Uncertain prices, unpredictable global markets, and unknown foreign exchange rates can alter the economic viability of a mining project in substantial ways. This economic uncertainty is compounded by geologic uncertainty. The extent and quality of any given deposit cannot be fully measured and is not known before consequential decisions must be made. These two sources of uncertainty are responsible for the majority of deviation between what happens during operation and what was initially planned. Understanding and explicitly quantifying this uncertainty will lead to better decision making and allow mining engineers and investors to be aware of what may occur. It is unrealistic to believe that one model, estimated from sparse measurements, is enough to capture both geologic and economic uncertainty and allow for optimal decisions. The entire breadth of uncertainty should be considered, as both upside and downside risks have large impacts on the investment potential and operational efficiency of mining projects. The workflow presented here uses Monte Carlo simulation and parametric analysis together to explicitly analyze the breadth of geologic and economic uncertainty as it applies to ultimate pit calculation and long range mine planning."

Jan 1, 2015

By W. R. Boehme

The test work was done in two parts. In Part I, five 6 x 16 mesh activated coconut shell carbon samples made by four different manufacturers were evaluated as to their gold loading rate and total gold loading. The five carbon samples tested are not identified by manufacturer and are simply designated as Types A through E. Then from the carbons tested, a suitable highly active carbon was selected for subsequent studies on impurity effects upon loading, Part II. Test Procedures The procedures and tests descriptions are given for the ultimate gold carbon loading tests and the dynamic gold carbon loading tests.

Jan 1, 1983

Open pit optimization and mine design depend upon a realistic estimate of the grade-tonnage dis¬tribution. The estimate should reflect what can be reasonably recovered and processed. The McCoy/Cove operation in central Nevada is a gold and silver mine. Recoverable reserve estimations of gold and silver were made using indicator kriging and the indirect log normal variance correction to construct the grade- tonnage distribution. Optimal pits were generated using this distribution, and the results were compared to the pits generated by ordinary kriging and indicator kriging block mean methods. The results indicate that the proposed method for multimetal recoverable reserve estimation shows an improvement in terms of predicting the recoverable tons and grades. The optimal pits generated from the recoverable resource model are larger than those generated by the ordinary kriging and indicator kriging block mean methods. This model maximizes the overall recovery of the mineral resource.

Jan 1, 1999

By T. M. Yegulalp

A short review of the current practice and recent developments is followed by a description of a newly developed approach for the solution of the optimum ultimate pit limit problem. The new approach utilizes the network modeling of the problem for solution by maximum flow algorithm. The latest developments in the implementation of maximum flow algorithm present significant time and memory savings as compared to initial development due to Ford and Fulkerson. Results of a series of computational tests are presented to demonstrate how this approach performs as compared to the well-known Lerchs Grossman algorithm. It is also shown that the solution by the new method will automatically include several optimal solutions based on predetermined number of benches to be included in the analysis.

Jan 1, 1993

By C. Garcia, H. Arias, J. D. Miller, C. L. Lin

The question of ultimate recovery in heap leaching operations is always of particular concern with respect to economic considerations. Of course the particle size distribution is a critical factor which determines ultimate recovery and which must be established based on a balance between the extent of mineral exposure and transport phenomena. Now it seems that the ultimate recovery for a given particle size distribution can be established from mineral exposure analysis by x-ray microtomography (XMT). Using recently developed software, micro-CT data can be used to determine the fraction of mineral exposed and thus the ultimate recovery. Examples of mineral exposure analysis are given for the copper heap leaching operation at Zaldivar, Chile.

Jan 1, 2002

By Z. Jin, D. DePaoli, P. Zhang

"Phosphate beneficiation in Florida generates more than one tonne of phosphatic clay, or slime, per tonne of phosphate rock produced. Since the start of the practice of large-scale washing and desliming for phosphate beneficiation, more than 2 Gt of slime has accumulated, containing approximately 600 Mt of phosphate rock, 600 kt of rare earth elements (REEs) and 80 million kilograms of uranium. The recovery of these valuable elements from the phosphatic clay is one of the most challenging endeavors in mineral processing, because the clay is extremely dilute, with an average solids concentration of 3 percent, and fine in size, with more than 50 percent having particle size smaller than 2 µm, and it contains nearly 50 percent clay minerals as well as large amounts of magnesium, iron and aluminum. With industry support and under funding from the Critical Materials Institute, the Florida Industrial and Phosphate Research Institute in conjunction with the Oak Ridge National Laboratory undertook the task to recover phosphorus, rare earths and uranium from Florida phosphatic clay. This paper presents the results from the preliminary testing of two approaches. The first approach involves three-stage cycloning using cyclones with diameters of 12.4 cm (5 in.), 5.08 cm (2 in.) and 2.54 cm (1 in.), respectively, to remove clay minerals followed by flotation and leaching. The second approach is a two-step leaching process. In the first step, selective leaching was conducted to remove magnesium, thus allowing the production of phosphoric acid suitable for the manufacture of diammonium phosphate (DAP) in the second leaching step. The results showed that multistage cycloning with small cyclones is necessary to remove clay minerals. Selective leaching at about pH 3.2 using sulfuric acid was found to be effective for removing more than 80 percent of magnesium from the feed with minimal loss of phosphorus.IntroductionFlorida phosphate ore, or “matrix,” as it is called locally, contains three different mineral groups that have to be separated from each other: (1) phosphate minerals, (2) clay minerals and (3) quartz, or sand. As mined, the phosphate and sand particles are embedded in compacted mud, or clay-balls. Before separation can begin, all of the particles must be liberated from the matrix of mud. The very first unit operation in the beneficiation process is to disaggregate the various particles. This actually starts while the matrix is flowing through the multimile pipeline from the mine to the beneficiation plant. While in the pipeline, the matrix is exposed to shear forces as it passes through the various centrifugal pumps along the pipeline. These intense shear forces cause a significant percentage of the sand and phosphate particles to be liberated from the clay-balls by the time they arrive at the plant. Once they reach the plant, the first goal is to finish disaggregating the clay, and follow that by making a size separation at 1 mm. This processing is conducted in the washer, consisting of a large rotating trammel screen and a few stages of log washer, screens and hydrocyclones. In all of the currently operating beneficiation plants, the washer is a large structure that receives the matrix, screens it and then discharges a pebble phosphate product sized larger than 1.0 mm and a slurry of liberated clay, sand and phosphate particles that are smaller than 1.0 mm."

Jan 1, 2017