Books by Roussos Dimitrakopoulos
- Addresses core aspects of the sustainable, responsible, and optimal development and utilization... more - Addresses core aspects of the sustainable, responsible, and optimal development and utilization of Earth’s mineral resources
- Presents both state-of-the art methods and major applications in the global mineral resources industry
- Includes contributions from international experts in the field
This book presents a collection of papers on topics in the field of strategic mine planning, including orebody modeling, mine-planning optimization and the optimization of mining complexes. Elaborating on the state of the art in the field, it describes the latest technologies and related research as well as the pplications of a range of related technologies in diverse industrial contexts.
Papers by Roussos Dimitrakopoulos
Resources Policy, 2016
Complex polymetallic mining projects with multiple processing streams tend to require tight blend... more Complex polymetallic mining projects with multiple processing streams tend to require tight blending constraints, with different operational and processing targets. These blending requirements are generally not focused solely on metal grade, but rather on a set of geometallurgical variables that affect the performance of the operation and its ability to meet targets and maximize project value. Because of this, a multivariate destination policy is developed here, based on coalition formation clustering (a line of study of cooperative game theory), which avoids the use of cutoff grades and defines where material is sent by accounting for the value and relation of groups of blocks being processed together. This allows improving investment decisions as a result of optimizing project performance, because the variables that affect blending and processing requirements are actively accounted for in the optimization process. A case study on a copper-gold mine with six destinations is presented, where the method proposed shows significant improvements in meeting processing requirements and increases the expected net present value by 5.6% when compared to a traditional method. This shows that complex processing requirements can be accounted for and respected without any loss of project value.
Stochastic simulation-based risk assessment for drilling optimisation
Taylor & Francis eBooks, Mar 15, 2005
Geological uncertainty is recognised as the critical factor in the estimation, categorisation and... more Geological uncertainty is recognised as the critical factor in the estimation, categorisation and economic assessment of coal resources. Resource classifications are often defined by fixed drillhole spacings, leading to resource classifications that reflect neither the in situ variability of the deposit nor the risk associated with it. In addition, there is significant expenditure associated with drilling to warrant considering methods that may reduce the amount of metres drilled. A state-of-the-art quantitative approach to optimising drillhole spacings and patterns, and minimise risk in coal resource estimation and classification is presented here. It is based on the quantification of geological uncertainty using modern stochastic simulation technologies that integrate the (a) in-situ variability of coal geologic attributes and (b) level of available information. This approach aims to assist coal mining companies by identifying cost-savings for drilling programs and 'competent persons' to help to comply with regulations and reporting codes such as the JORC Code in Australia. The case study from an Australian coal seam demonstrates the characteristics and effectiveness of the proposed drilling optimisation approach.
High-order Statistics of Spatial Random Fields: Exploring Spatial Cumulants for Modeling Complex Non-Gaussian and Non-linear Phenomena
Mathematical geosciences, Dec 11, 2009
Abstract The spatial distributions of earth science and engineering phenomena un-der study are cu... more Abstract The spatial distributions of earth science and engineering phenomena un-der study are currently predicted from finite measurements and second-order geosta-tistical models. The latter models can be limiting, as geological systems are highly complex, non-Gaussian, ...
Jōhō chishitsu, 1991
This paper deals with the technological transfer of geostatistical knowledge and expertise
Artificially intelligent geostatistics: A framework accommodating qualitative knowledge-information
Mathematical Geosciences, Apr 1, 1993
The purpose of this paper is to stress the need to examine Al-based models and techniques in deal... more The purpose of this paper is to stress the need to examine Al-based models and techniques in dealing with qualitative knowledge, information, and expertise in geostatisties. A model of artificially in-telligent geostatistics is proposed as a general framework. The model ...
Geostatistical Modeling of Gridblock Permeabilities for 3D Reservoir Simulators
SPE reservoir engineering, Feb 1, 1993
Summary A geostatistical method is presented to determine the absolute horizontal and vertical ef... more Summary A geostatistical method is presented to determine the absolute horizontal and vertical effective permeabilities at the reservoir block scale from core support-scale values required for 3D reservoir flow simulations. The key element of the geostatistical model is the definition of block support-scale permeabilities as the spatial power average of core-support values over the volume of a reservoir gridblock. Block support-scale permeabilities are then found to be a function of the permeability variogram, the averaging volume, and a power-averaging constant, which is derived separately for horizontal and vertical flow with a numerical approach. The application of the proposed method requires that core-support values be available within each reservoir block. These values are generated with the technique of conditional simulation. This technique provides simulated values reproducing the actual core data at sampled locations and their statistical properties. The approach developed for the determination of permeability input to full-field simulators is demonstrated by an application to the Crystal Viking field "H" pool in Alberta.
Soil attributes, including those in mine spoil heaps, critically affect plant growth during land ... more Soil attributes, including those in mine spoil heaps, critically affect plant growth during land rehabilitation. Their characterization through a limited number of samples requires quantification of spatial variability, which is then used at various stages throughout the rehabilitation process and assists risk analysis and rehabilitation decision making. Stochastic simulation is a tool used for the quantification of uncertainty. This paper presents the suitability of stochastic simulation for the joint simulation of soil attributes and introduces a new computationally efficient method. The method is based on: (i) the Minimum/Maximum Autocorrelation Factors (MAF), involving the de-correlation of pertinent variables into spatially noncorrelated factors, and (ii) the simulation of MAF and back transformation to the conditional simulations of the correlated variables. MAF factors in point (ii) are simulated using the new Generalised Sequential Gaussian Simulation (GSGS) technique which ...
Electromagnetic full-waveform tomography is computer intensive and requires good knowledge of ant... more Electromagnetic full-waveform tomography is computer intensive and requires good knowledge of antenna characteristics and ground coupling. As a result, ground-penetratingradar tomography usually uses only the first wavelet’s arrival time and amplitude data. We propose to improve the classical approach by inverting multiple slowness and attenuation fields using stochastic tomography. To do so, we model the slowness and attenuation covariance functions to generate geostatistical simulations that are conditional to the arrival times, amplitudes, slowness, and attenuation observed along boreholes. We combine slowness and attenuation fields to compute conductivity and permittivity fields from which we model synthetic radar traces using a finite-difference timedomain full-waveform algorithm. Modeled traces that best match the measured ones correspond to the computed conductivity and permittivity fields that correlate best with the true physical properties of the ground. We apply the metho...
The classical maximum closure problem is of particular importance to the mining industry because ... more The classical maximum closure problem is of particular importance to the mining industry because it is the underlying formulation related to mine design and production scheduling; this problem can be easily solved by a polynomial time max-flow/min-cut algorithm. However, if a single capacity constraint is added to the maximum closure formulation, the classical structure is destroyed and is classified in a category of NP-hard problems. Using classical integer programming techniques to solve these formulations with capacity constraints, it can take several days to solve linear programming (LP) relaxation of the real instances. This phenomenon has hindered the development of exact optimization approaches for open pit mine design and production scheduling of realistic sized problems. In this paper, we develop an algorithm to solve the LP relaxation of the maximal closure problem with a single constraint, which is often referred to as the precedence constrained knapsack problem. The prop...
Geostability modeling of transmissibility for 2D reservoir studies
Spe Formation Evaluation, 1990
Journal of Mining Science, 2014
An integral part of open pit optimization is deciding which section of the ultimate pit to mine d... more An integral part of open pit optimization is deciding which section of the ultimate pit to mine during a specific period. For a given period there are often operational and marketing constraints that restrict what can be removed or processed. The operational constraints arise from a number of different limitations such as safe slope of internal mining walls, mill and mining capacity. Traditional methods for pushback (phase) design that incorporate these constraints are ad-hoc and can lead to suboptimal solutions. Another important optimization decision that must be made is the cut-off grade to be used for a specific period. In this paper, a new method is presented that generates near maximal expected profit and dynamically defines the optimal cut-off grade for each mining period or pushback over the life-of-mine, thus deciding whether a block is ore or waste during the optimization process. More specifically, a method for converting a fractional linear program solution into an integral solution known as pipage rounding is applied to an integer program formulation of a pushback design optimization problem. The proposed method aims to produce a set of pushbacks in a way that the total discounted profit to be generated through production scheduling is maximized. Two case studies demonstrate the applied aspects of the proposed method.
Resources Policy, 2013
ABSTRACT Cutoff grade specifies the available supply of metallic ore from an open pit mine to the... more ABSTRACT Cutoff grade specifies the available supply of metallic ore from an open pit mine to the multiple processing streams of an open pit mining complex. An optimal cutoff grade strategy maximizes the net present value (NPV) of an open pit mining operation subject to the mining, processing, and marketing/refining capacity constraints. Even though, the quantities of material flowing from the mine to the market are influenced by the expected variation in the available metal content or inherent uncertainty in the supply of ore, the majority of cutoff grade optimization models not only disregard this aspect and may lead to unrealistic cash flows, but also they are limited in application to an open pit mining operation with single processing facility. The model proposed herein determines the optimal cutoff grade policy based on a stochastic framework that accounts for uncertainty in supply of ore to the multiple ore processing streams. An application on a large-scale open pit mining operation develops a unique cutoff grade policy along with a portfolio of mining, processing, and marketing/refining rates. Owing to the geological uncertainty, the approach addresses risk by showing a difference of 14% between the minimum and maximum production rates, cash flows and NPV.
Mining Technology, 2002
The quantification of uncertainty and risk has major implications for open-pit design and product... more The quantification of uncertainty and risk has major implications for open-pit design and production scheduling as it relates to the management of cash flows in the order of millions of dollars. Optimization in mine planning has been accepted as a set of techniques that introduce analytical mathematical methods into planning. The most common approach in open-pit design and planning is based on the Lerchs-Grossmann three-dimensional graph theory, implemented in industry applications as the nested Lerchs-Grossmann algorithm. A key concern when dealing with risk and uncertainty, particularly considering the financial implications of decisions made on the basis of optimization studies, may be expressed by the statement: 'I would rather be approximately right than precisely wrong'. This statement hints at a way to address the uncertainty present in any mine design and plan. To deal with, manage and benefit from risk requires further development of quantitative methods used in planning that can minimize the chances of a single, precisely wrong expectation. As a result, strategic investments can be sheltered and operations perform closer to their potential. Traditional evaluation of mining projects includes drilling and sampling, generating a representative orebody model, deciding mining and processing methods, assessing capital and operating costs and developing a technical and financial life-of-mine plan. In addition, to assess the worth of a project, summary indicators, which include total project size, capital requirements and net present value, are developed and used
International Journal of Surface Mining, Reclamation and Environment, 1990
ABSTRACT OILSAND is a computer software system designed to perform all steps required for the geo... more ABSTRACT OILSAND is a computer software system designed to perform all steps required for the geostatistical modelling, display, and preliminary evaluation of the in-situ reserves of an oil sand deposit. The system allows the integration of geological control descriptions with the techniques of ordinary kriging and conditional simulation. In addition, it permits the consideration of the mining method in the calculation of reserves and associated estimation variance. OILSAND consists of five main and three display programs in standard FORTRAN code. The main programs (a) calculate statistics of the input data; (b) generate two and/or three dimensional grids of kriged and/or conditionally simulated variates; and (c) perform volumetric calculations. Display programs are used to display data statistics and cross-sectional representations of grided three-dimensional block models of a deposit.
International Journal of Surface Mining, Reclamation and Environment, 1990
Abstract Geostatistical techniques have been successfully employed in ore reserve estimation for ... more Abstract Geostatistical techniques have been successfully employed in ore reserve estimation for more than two decades. It remains however, that the application of these techniques is not straightforward. To provide the means for the transferring of the knowledge and expertise involved, expert system technologies may be integrated with geostatistics. As a result intelligent geostatistical systems may be build to assist the industry in ore reserve estimation. Two experimental geostatistical expert systems developed, demonstrate that such systems are technically feasible, compatible to geostatisticians, simple to use, expandable, and educative for the user.
Engineering Optimization, 2013
ABSTRACT In a mining complex, the mine is a source of supply of valuable material (ore) to a numb... more ABSTRACT In a mining complex, the mine is a source of supply of valuable material (ore) to a number of processes that convert the raw ore to a saleable product or a metal concentrate for production of the refined metal. In this context, expected variation in metal content throughout the extent of the orebody defines the inherent uncertainty in the supply of ore, which impacts the subsequent ore and metal production targets. Traditional optimization methods for designing production phases and ultimate pit limit of an open pit mine not only ignore the uncertainty in metal content, but, in addition, commonly assume that the mine delivers ore to a single processing facility. A stochastic network flow approach is proposed that jointly integrates uncertainty in supply of ore and multiple ore destinations into the development of production phase design and ultimate pit limit. An application at a copper mine demonstrates the intricacies of the new approach. The case study shows a 14% higher discounted cash flow when compared to the traditional approach.
Journal of the Japanese Association for Petroleum Technology, 1996
Stochastic models of petroleum reservoir geological attributes are used in reservoir studies to: ... more Stochastic models of petroleum reservoir geological attributes are used in reservoir studies to: (i) generate effective reservoir properties at the reservoir gridblock scale; and (ii) assess uncertainty in reservoir performance forecasting. The present paper formalizes the methodology in terms of transfer functions and introduces an alternative implementation of the sequential indicator simulation algorithm based on relative indicator variables. In addition, the determination of effective block permeabilities from stochastic images of point support-scale permeability fields is presented in the context of generalized power averages. Applications of the above are demonstrated in the simulation of reservoir lithofacies and gridblock permeabilities. The effects of stochastic imaging and reservoir characterization in assessing reservoir forecasting are illustrated.
Mining technology, Feb 12, 2019
As more and more data about mining complex operations are collected and stored, it becomes increa... more As more and more data about mining complex operations are collected and stored, it becomes increasingly important for computer systems to help human operators make better, more informed decisions. This can be done indirectly, through improved visualization or prediction, or directly by suggesting decisions that respond to new information. This paper contributes to the direct approach by showing how state-of-the-art data-driven decision making can be used for optimizing material flows in a large mining complex. To this end, a combination of neural networks and policy gradient reinforcement learning is used for computing material destination decisions that automatically respond to new information. Results using a computational model of a large copper mining complex show that the proposed method significantly outperforms an optimized cut-off grade policy similar to the one currently used at the mine.
Mathematical geosciences, Apr 1, 2017
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Books by Roussos Dimitrakopoulos
- Presents both state-of-the art methods and major applications in the global mineral resources industry
- Includes contributions from international experts in the field
This book presents a collection of papers on topics in the field of strategic mine planning, including orebody modeling, mine-planning optimization and the optimization of mining complexes. Elaborating on the state of the art in the field, it describes the latest technologies and related research as well as the pplications of a range of related technologies in diverse industrial contexts.
Papers by Roussos Dimitrakopoulos