JOURNAL OF ANALYTICAL AND NUMERICAL METHODS IN MINING ENGINEERING
Year:2016 | Volume:5 | Issue:10 |Papers Count:9

Summary: One of the most important problems in the interpretation of gravity or magnetic data is to obtain information about the sources position (geometry and depth). Potential field automatic interpretation techniques can significantly decrease the interpretation workload of a geophysicist and are widely used. Automatic interpretation methods can be classified into two major groups: modeling and analytical. Euler Deconvolution, Werenr Deconvolution and recently, Tilt-Depth method are the commonly used (practical goals) analytical methods. The basic idea in Tilt-Depth method is simultaneous application of tilt angle for edge and depth estimation of magnetic contact model. In this method, the vertical and horizontal gradients of magnetic contact substituted in tilt equation lead to an equation for depth estimation. This paper generalizes the tilt-depth method to gravity data using the horizontal cylinder and the buried sphere models.Introduction: Salem et al, (2007) introduced the tilt-depth method for the magnetic anomaly over a contact. Previously Miller and Singh had developed the tilt angle as a method of enhancing images of the vertical derivative of potential field data. The tilt-depth method only depends on mapping specific contours of the magnetic tilt angles. The zero contours delineate the spatial location of the magnetic source edges whilst the depth to the source is the distance between the zero and either the –45° or the +45° contour or their average. The tilt-depth method adds to the arsenal of geophysical methods currently in use to estimate magnetic source depths, many of which use second- and/or third-order derivatives. These include methods based on Euler’s equation and the local wavenumber, both of which calculate the source depths for a range of source-body geometries, and, more recently, for the simultaneous estimation of both source depth and source type. Methodology and Approaches: In this paper, the tilt-depth method will be both generalized (by applying it to gravity models) and extended (by using all values of the ratio of the field gradients, not just a single value). The gravity models used are 2D horizontal cylinder and buried sphere. In this regard we developed a MATLAB code for applying the proposed method to synthetic and real data. In this code the selection of the ratio of the vertical to horizontal derivatives are done on the basis of the signal to noise ratio of the dataset. Also for the consistency of result the vertical derivative is calculated using Hilbert transform. The final equation was solved by Newton method. Results and Conclusions: The efficiency of the proposed method tested using various synthetic gravity models. The sensitivity of methods to noise and interface was tested using synthetic data. On the basis of observations the method is sensitive to noise, but if the data continued upward before applying the algorithm or using of the stable derivative operator the inconsistency of the result decreases seriously. For overcome in body overlapping phenomena we suggest anomaly windowing or insulating by means of Bott (1966) algorithm. This method applied on 2 gravity profiles from Shavaz Iron ore in Yazd province. Then the results compared with power spectrum depth analysis. Accordance to this comparison the proposed method could produce the same result as power spectrum. In this case w upward gravity data to 2m in order to decrease noise content.

Summary: In geological sciences, especially geochemistry, multivariate statistical methods have many applications. So that, they were employed as a new application for recognition main alterations in Cu-Mo porphyry system such as argillic, potassic, and propylitic alterations. For determination of alteration areas, results of 607 lithogeochemical samples were utilized in Hararan area, which appears to possess the potentiality for porphyry mineralization and locates in Baft sheet (1:100,000 series) in the southeast of Iran. 607 rock samples were analyzed by ICP-MS in Amdel laboratory for 45 elements. However, it used just the results of Ca, Na, Al, Fe, S, K, Rb, Mg elements for this paper.  Results of hierarchical cluster and k- means Cluster methods showed two different clusters: K, Rb, S elements and Mg, Ca, Na, Al, Fe elements have been in cluster 1 and cluster 2, respectively. Cluster1 and cluster2 introduced as potassic and argillic alterations and propylitic alteration, respectively. The results of factor analysis not only confirmed the above results but also the first factor map depicted small areas of argillic and potassic alterations in the southern parts of the region, so that these areas did not identify by k-means cluster method. Introduction: Hydrothermal Alteration plays a key role in types of mineralization. For recognition of alteration zones, there are common techniques such as mineralogical, lithological studies and field surveys. Researchers used different methods for identifying alteration zones. Therefore, in this study, it was utilized multivariate analysis techniques as a new application for mentioned objective. Methodology and Approaches: In regional geochemistry an advantage would be that instead of presenting maps for 40-50 (or more) elements only maps of 4-6 factors may have to be presented, containing a high percentage of the information of the single element maps. It is even more informative if factor analysis can be used to reveal unrecognized multivariate structures in the data that may be indicative of certain geochemical processes, or, in exploration geochemistry, of hidden mineral deposits. Cluster analysis is used to delineate the relationships between elements and shows which elements tend to have similar variations in concentrations. Results and Conclusions: In this study, 607 lithogeochemical samples were analyzed for 44 elements. But Ca, Na, Al, Fe, S, K, Rb, Mg were selected to recognize alteration zones in Hararan area. Before performing multivariate analysis, the preprocessing of geochemical data was performed including the replacement of censored and outlier data. The results of factor and cluster analysis showed that Fe, Ca, Al, Na, Mg elements and K, Rb, S elements represented Propylitic and argilic alteration, respectively.

Summary: The instruments locating has influence on cost-utility and mining operations. Monitoring rock deformations is important in assessing the stability of rock structures. The instrumentation system enables high precision assessment of strains and displacements. Nowadays, stability of slope in advanced countries is controled by high-resolution tools and methods for monitoring data evaluation assist in the continuous interpretation of the behavior of ground and support interaction. Instruments can provide early warning of impending failures, allowing time for safe evacuation of the area and time to implement remedial action. Safety monitoring requires quick retrieval, processing, and presentation of data, so that decisions can be made promptly. Introduction: Sarcheshmeh copper mine with the area of about 3.6 square kilometers, now the stability of western wall is currently an important problem. From the reasons mentioned above, the authors proposed that monitoring is the best applicable method to monitor stability of western wall of Sarcheshmeh copper mine. Monitor of the stability of western wall, can detect shear zones and help determine whether shear is planar or circular. It is possible to determine whether movement is constant, accelerating, or slowing. Methodology and Approaches: For the stability control of western wall, according to the wall geometry, rock type, geology conditions and the strength properties of rock masses and discontinuities, installing the instruments is the most appropriate way to control stability of this slope. Such technologies improve our ability to solve many problems in geo-science and geo-engineering. In this paper, In order to locate a suitable location for installing the instrument, the geographic information system (GIS) was used. For selection of the useful location for instrument, the geological conditions, the structural and hydrogeological properties of the rock masses are collected and then converted in to photo maps. Then, the analytical hierarchy process (AHP) and fuzzy logic methods were used. Important geological and geomechanical parameters such as lithology, alteration, piezometer level, faults, discontinuities condition, spacing, geological strength index, rock mass rating the quality of rock, uniaxial compressive strength, elevation, dip and dip direction of slope at different level of mine were evaluated and then the GIS photo maps of each parameter prepared. Results and Conclusions: Each layer for every parameter was georeferenced. Using the rating considered for each parameter by AHP method the reclassification of layers by ArcGIS9.3 software was done. The data layers were integrated using fuzzy method. An appropriate photo map for installation of the instrument in west wall of mine was produced. Finally, after field survey, several areas were identified and proposed for further investigation.

Summary: The aim of this paper is to present a new numerical method to solve the wave equation with a good accuracy and high stability using the Leapfrog symplectic integrator and rapid expansion method (REM). It can be used for seismic modeling and reverse time migration (RTM). Using the REM with Fourier transform method for spatial derivative, the Leapfrog-rapid expansion method (L-REM) can be even used for larger time steps. The L-REM provides the solution of the wave equation and its first time derivative at the current time step. In addition to the very low error for the small time steps, increasing the time step also lead to more accurate results and high stability in comparison with the similar methods such as Stormer-Verlet, Leapfrog and Stormer-Verlet-rapid expansion method which will also be discussed in this paper. Introduction: Wave-field extrapolation is implemented by solving the wave equation through various mathematical methods. The finite difference method is a well-known and popular numerical tool to discretize the wave equation, and its use has been common in the approximation of the spatial and time derivatives for a wave-field. Originally, the time operator was approximated by a second-order scheme, whereas the spatial derivatives were approximated by a fourth-order scheme. Approximating the time derivative in this way may introduce numerical error, leading to distortion of the pulse and numerical dispersion, which can be avoided with small time steps at the expense of increasing the computational time. Also some other methods such as Stormer-Verlet (SV), Leapfrog (L) and Stormer-Verlet-rapid expansion method (SV-REM) have been presented to improve the solution of wave equation. In the current study, a symplectic scheme based on Leapfrog integrator and rapid expansion method (L-REM) is proposed to extrapolate the wave-field and its first derivatives in time for the same time step which can be used to calculate Poynting vectors for wave-field separation and to calculate the reflection angles. Methodology and Approaches: In order to verify the numerical accuracy and behaviour of the error associated with Leapfrog-REM scheme a numerical example has been presented to be solved using different time sampling values. For implementation, an explosive source used in the centre of the computational domain having a Ricker wavelet with a maximum frequency of 25 Hz. Results and Conclusions: The presented L-REM scheme provides the solution of the wave equation and its first time derivative for different time steps. In addition to the very low error for the small time steps, increasing the time step also lead in the more accurate results and high stability in comparison with the similar methods.

Summary: Underground and infrastructure projects are generally complex project with many variables including ground ‎and groundwater conditions are variable and uncertain. These ‎conditions infliction significant risks in all project components or parts that are indirectly related with the ‎project, and has led to the high costs and time delays to the project. Ranking by providing timely response to risk it all, helpful to the risk management process will be more ‎successful. In this paper,  prioritize risks are discussed in the mechanized tunneling to using Fuzzy Technique ‎for Order Preferences by Similarity to Ideal Solution (FTOPSIS) in rocky environments. The calculations ‎performed in 19 separate zone and ultimately three risk as the high risk (main) in each zone specified. The ‎analysis results show that leaks of toxic gases in rocks and water leaks and influx into the tunnel in this study ‎are respectively most important risks.‎ Introduction: Risk assessment is one of the fundamental elements of risk ‎management, and with respect to the uncertain nature of tunneling projects and the need to spend resources, is ‎important. Ranking of risks is a key part of this process, because with ‎ranking, priority each risk in front of other risks specified and in the result, decision maker can be plan about the ‎the amount of allocation existing resources for deal with each risk.‎ Methodology and Approaches: In order to risk assessment, different methods have been introduced. In this paper, the method is Fuzzy Technique ‎for Order Preferences by Similarity to Ideal Solution has been used to rank the risks. In this study, according to Hydrogeology of tunnel route, kilometer of 00+000 to 13+290 divided to 19 ‎zone. 9 risk as the most important of the geological risks and 4 factor as effective criteria’s is introduced for ranking ‎in mechanized tunneling in rocky environments. Results and Conclusions: The analysis results show that leaks of toxic gases in rocks and water leaks and influx into the tunnel are ‎respectively most important risks in the tunnel. Hence the should be by allocating more resources ‎seeking eliminate or reduce the damaging effects of these risks on project objectives. Therefore, the recommended, ‎strategies to counter risks listed to be determined before drilling operations, until in the event of, tunneling operations ‎to be performed without interruption.‎

Summary: During the last decade, stabilization of soil slopes using nailing has attracted a lot of attention. Optimization of nailing in excavation projects is a potential factor for significant cost savings. Such optimizations are typically performed using trial and error approaches, and thus in several cases the design is not optimal. Introduction: Soil nailing is a construction technique that can be used as a remedial measure to treat unstable natural soil slopes or as a construction technique that allows the safe over-steepening of new or existing soil slopes. The aim of this study is to analyze the stability of slopes using genetic algorithm considering various factors to achieve the optimum length of soil reinforcement elements. Methodology and Approaches: Four main points to be considered in determining if soil nailing would be an effective retention technique are as follows. First, the existing ground conditions should be examined. Next, the advantages and disadvantages for a soil nail wall should be assessed for the particular application being considered. Then other systems should be considered for the particular application. Finally, cost of the soil nail wall should be considered. In this study, a computer code has been developed which uses the genetic algorithm in MATLAB software to determine the percentage of allowable reduction on the length of reinforcement, considering soil shear strength parameters. The code has been developed in such a way that a user unfamiliar with the genetic algorithm concepts is able to easily complete the reinforcement optimization process. A case study has been performed using soil specifications for the central region of Mashhad, around the holy shrine of Imam Reza (AS). Results and Conclusions: The outcome of this research suggests that changing rebar size does not substantially affect the total length of reinforcements; however, a change in the diameter of the drill hole has a more significant influence on the reduction of the reinforcement length.

Summary: Khooni exploratory area is located at 270 kilometers of Esfahan, and belongs to Central Iran geological zone. According to some instances expressing gold mineral forming in this area, make reconnaissance of favorable area as an essential fact. A well-known algorithm of clustering is K-Means by which the data are divided into K clusters on the basis of distance. In this analysis, using the K-Means method to classify the sampling of khooni district for Gold, Arsenic and Antimony elements. The optimal K value was determined and then the data were clustered and the behavioral characteristics were analyzed, and at the end relationships and equations with correlation coefficients were identified and the grade of gold were estimated based on four parameters Arsenic, Antimony content; length and width of the sampling points. Introduction: There are many methods to estimate the grade because of mining projects have high dependency to determine the tonnage accurately. One of the new methods of estimating the grade is clustering. Thus, it is necessary to find information about the relationships and behavior elements of Gold, Arsenic and Antimony to each other. in this area to determine the extent of the geochemical halo and to identify favorable area as well as estimation. Methodology and Approaches: In this study fordetermination the behavior of the mentioned elements, the famous and efficient method of K-Means, which is one of the clustering methods, are used, that is based on minimizing total of Euclidean distance from the center each class. For this purpose, the quality function and silhouette criterion have been used to determine the optimal number of clusters. All data ranged the number of classes from k=3 to k=10 and afterwards the optimumnumber of clusters were selected by mentioned methods. At the end, according to the Center of clusters, the equation for estimating the grade of gold is provided. In this study, MATLAB and SPSS software are used to achieve results. Results and Conclusions: The relationship of gold, arsenic and antimony according to length and width of the sampling points were determined for estimation grade of gold, Results showed that clustering with k=5 in case of Au, As and Sb were better than other classes number in each case. Obtained equation for estimating grade of gold element based on four parameters Arsenic, Antimony content; length and width of the sampling points, is Au=1.995 As -14.892 Sb+ 0.221 x – 0.375 Y + 0.561 and the correlation coefficient 73% is reported. Also to evaluate the accuracy of the estimator, the results were validated. Estimated gold element values almost match with actual values of gold element that represents the accuracy of the used method.

Summary: Currently, the environmental protection has found an important role in most countries. The effluents of the Sungun Copper Mine Concentration Plant (SCMCP) have the destructive effects. The location of farms, especially around the mine, should be performed based on technical and economical topics. In the present study, in order to the consideration of the main aims of the Mine management, a multi-objective approach is used. The effluents of SCMCP have some destructive effects on the Arasbaran forests. Thus, determination of the proper locations to discharge the wastewaters of the SCMCP is one of the important issues which should be considered. The Data Envelopment Analysis (DEA) method is an appropriate method for measuring the efficiency. The development of uncertainty in the world, indicates the importance of DEA method and its applications. Introduction: Recently, various methods have been used to purify industrial and urban effluents also acidic mine drainages considering the importance of the environmental issues. In general, plants use several basic processes to do purification in the nature. In order to choose the best location of farm plants that are irrigated with wastewaters of the SCMCP, the management main goals should be considered. Methodology and Approaches: In the present study, the efficient locations have been determined in order to discharge the industrial wastewaters of the SCMCP using multi-objective approach based on developed DEA method that is the Simultaneous Data Envelopment Analysis (SDEA) which uses the interval data. The integration of quartet goals with the weighted global criterion method is used to solve the proposed multi-objective model. Results and Conclusions: How to use the model, the analysis process of the results, the description and the validation of the model for the Sungun Copper Mine have been studied as the case study. Due to the obtained results from solving the model and considering the different weight combinations, it can be said that the proposed model tries to provide a balance among different functions.

Summary: In the earth sciences, a great deal of uncertainty modeling depends on subsurface interpretation. The exploratory borehole is one of the best tools for subsurface exploration and data gathering. In the mineral exploration project, the layout of boreholes is designed based on the available information and engineering judgment, which may result in a lack of information or redundant information in decision making. This paper presents a new algorithm to compute the parameters of the optimal exploratory boreholes network. Introduction: There are three significant concepts in sampling design, including probabilistic geometry, geostatistical error management, and information theory. The probability of intersection between target and network was calculated as a function of the target geometry and its relative orientation with respect to the directional and dimensional properties of exploration network. Methodology and Approaches: Designing of the optimal drilling network contains two main strategies: (i) maximize the detection (exploration) probability, (ii) minimize the cost of drilling. These two principles, which are two opposite points of each other. The beginning optimization stage of drilling network is determining the strike direction of the network that depends on the main direction and shape ratio (length to width) of the ore. In the following phase, the efficiency model (gross drilling return) is defined as the difference of the detection probability and cost function (as the two principals of optimization model). The ore detection probability was the function of ore geometry (directional and dimensional parameters), the ratio of ore length to drilling network length, and the angle of the borehole. Three types of ore geometry are considered: 1D (Vein model), 2D (band or layer model) and 3D (mass model). Results and Conclusions: In this present study, the ore with three dimensional geometry was studied that were the primary model produced by geophysical investigations. The effective parameters of the drilling cost function are related to the length of the borehole, the type of drilling, and inclination of the borehole. To compute the optimal parameters, the partial derivative of efficiency model was solved based on the independent variables (the size of drilling network and the angle of borehole). Finally, according to local variety in the dip of deposit, the optimal orientation of boreholes was correct based on angle of surface effect.