Journal of Engineering Geology

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In present research, landslide hazard zonation of Latian dam watershed area has been carried out using Analytic Hierarchy Process (AHP), Valuing area accumulation, Factor overlay and Information value methods. At first, different maps comprising slope, aspect, altitude, faults, drainage network, access roads, lithology, land use and friction angle maps were prepared digitally using GIS. Afterward affecting factors were evaluated using old landslides. The results of evaluation show that seven parameters are important effective factors on sliding in this area. These parameters were leaded to landslide zonation maps. These maps show that potentially high risk zones point of view landslides are located near the central and western boundaries of the reservoir. Performance of four used classification methods were evaluated and compared. The evaluation results show that Valuing area accumulation and Factor overlay are precise methods for evaluating landslide potential in the study area respectively

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Ground-Penetrating Radar (GPR) is a non-destructive and high-resolution geophysical method which uses high-frequency electromagnetic (EM) wave reflection off buried objects to detect them. In current research this method has been used to identify geometrical parameters of buried cylindrical targets such as tunnel structures. To achieve this aim, relationships between the geometrical parameters of cylindrical targets with the parameters of GPR hyperbolic response have been determined using two intelligent pattern recognition methods known as artificial neural network and template matching. To this goal GPR responses of synthetic cylindrical objects produced by 2D finite-difference method have been used as templates in the neural network and template matching algorithms. The structure of applied neural network has been designed based on extracting discriminant and unique features (eigenvalues and the norm of eigenvalues) from the GPR images and predicting all geometrical parameters of the targets, simultaneously. Also the template matching operation carried out using two diverse similarity approaches, spatial domain convolution and normalized cross correlation in 2D wave number domain. The results of the research show that both two employed intelligent methods can be applied for in situ, real-time, accurate and automatic interpretation of real GPR radargrams, however in general the neural network method has led to less error and better estimation than template matching to predict the geometrical parameters of the cylindrical tar

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Extended Abstract
Introduction
Dimension stones market is considered as an important and profitable sector of mineral deposit business due to their share in national economic performance. There exist a number of technical reports highlighting a lack of rock quality control in the sequence of quarrying and dimension stones production procedures, which has lowered the production efficiency and consequently the profitability of this strategic mineral industry in Iran. The quality of dimension stones depends on several factors which fractures, joints, voids and fine beddings are the most important factors that down-grade the quality. Therefore, foremost the quality and desirability of the building stone must be precisely determined by sampling, compressive strength testing and preparing microscopic sections. All of the mentioned evaluation methods are destructive. Moreover, sampling and performing multiple tests on all parts of a quarry or on all quarried stone blocks, is not possible. Detection of fractures hidden into the dimension stone blocks is achievable using fast, low-cost, accurate and non-destructive ground-penetrating radar (GPR) method. GPR is a high-resolution geophysical method which uses electromagnetic waves with high-frequency in order to map structures and detect buried objects in subsurface without coring or any destruction of the medium.
 
 
Materials and methods
In current research, GPR method has been applied to evaluate the quality of quarried travertine blocks at Haji-Abad quarry complex in Mahallat district, Markazi province, before starting any processing operation. To achieve this goal, the 2-D GPR responses of synthetic models resembling cubic dimension stone blocks containing fine layering and discontinuities, were primarily simulated using a modified 2-D finite-difference forward modeling program in the frequency-domain coded in MATLAB. Among the variety of available numerical methods, the finite-difference time-domain (FDTD) method has paid more attention due to having the simple understanding of the concepts, flexibility, simulation and modeling of complex environments and the acceptability of its responses in the applied cases. In this research, the simulation has been implemented for both calcareous and dolomitic rocks (including travertine and marbles) and granites. In the study area, the GPR data acquisition was carried out using a GPR system equipped with shielded 250 MHz central frequency antenna, 0.5 m antenna distance and 2 cm sampling intervals by monostatic common-offset reflection profiling method. In order to process, analyze and interpretation of data, Ground Vision and Radexplorer software were employed. The most important pre-processing and processing operations applied to the data to provide the final sections, comprising time-zero correction, dewowing (removing very low frequency components from the data), DC shift removal, Butterworth filtering, running average, background removal and types of amplitude gain.
Results and Conclusion
The results of the forward modeling show that the GPR response of fine beddings interfaces and major discontinuities hidden in the volume of dimension stone blocks are clearly detectable. Interpretation of the actual radargrams taken from a real GPR case study (Haji-Abad quarry complex) after employing various B-scan pre-processing and filtering procedures, indicates that GPR method is highly capable to detect fine beddings and discontinuities in order to evaluate the quality of dimension stone before starting any quarrying process. Validation of the obtained results of the present research was carried out on one of the blocks with a predicted large oblique joint while the existence of the large joint was proven under the cutting saw in the stone processing plant. However, it should be noted that due to the existence of inherent heterogeneity encompassing fine beddings, in addition to noises from different sources and their associated multiple reflections in real radargrams, the response of shallow major discontinuities may mask the response of minor ones located underneath or deeper, so as a result may not be detectable with routing GPR radargrams../files/site1/files/121/Ahmadi_Abstract.pdf
 
Keywords: Dimension stone Blocks (cubes); dimension stones production; Ground Penetrating Radar (GPR); Forward modeling; Quality control; Haji-Abad mining complex in Mahallat
 

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Introduction
     Ground-penetrating radar (GPR) method is a pretty new, non-destructive and high-resolution geophysical method that is widely used to identify the thickness of snow and ice layers and glaciers bed, because snow and ice are transparent for electromagnetic (EM) waves. Therefore, this method has been used to determine the thickness and basement topography of Alam-kooh glacier. In this research, only the GPR acquired data using unshielded antenna with central frequency of 25 MHz along one line in Alam-kuh glacier, Kelardasht- Mazandaran, have been processed and interpreted. The GPR data acquisition has been done by using common offset method, and transmitter-receiver separation of 6 meters. The final real radargram related to one of the surveyed GPR profiles in this region has been prepared after applying various processing operations containing signal saturation correction, amplitude gain, f-k migration filtering and static (topography) correction on the raw data. After applying processing sequences on the acquired data, the EM waves reflection off the interfaces of different layers including the reflections from the glacier basement have been detected, and by assigning a suitable EM wave velocity in the ice (0.16 m/ns), the thickness of 50 m for the ice layer laid under the survey line has been estimated. Also, in present research, forward and inverse modeling of GPR data have been performed to employ for snow, ice and glaciological investigations in the AlamKooh region of Mazandaran. To achieve this goal, GPR response of synthetic model corresponding to the real radargram was simulated first, by 2-D finite-difference time domain (FDTD) method. Afterward the inversion method by solving an optimization problem was employed to validate the interpretation of real GPR data.
Methodology and Approaches
     Based on the nature, physical and geometric properties of the subsurface target in the field data, their synthetic model have been built and their two-dimensional GPR responses forward modeling using ReflexW software and finite difference algorithms improved in the frequency domain, have been obtained. Also, it has been used an effective algorithm, coded in GUI environment of MATLAB programming software and as a result, a reliable and accurate inverse modeling has been carried out. In the present study, to simulate the behavior of the propagation of EM waves in GPR method, two-dimensional finite difference method has been used. The main advantage of this method is its comparative simplicity of the concept, high accuracy and simple implementation for complex and arbitrary models as well as easily adjusting the antenna when applied. In this study, acquisition of GPR field data and synthetic data modeling have been carried out in TM mode. The radargrams of the GPR data have been demonstrated using ReflexW software after performing necessary processing sequences.
Results and Conclusions
     The obtained results reveal that moraine materials covering the surface of the area are mainly fine-grained granite. The bed-rock or basement in the area is also granite. The polarity representing ice-bed rock is clearly seen on the GPR profiles. The topography of the glacier basement has successfully been detectable using just by GPR method. The electrical resistive nature of the glacier has caused large penetration depth of GPR pulses in this research. Furthermore, the results of the research for presented profiles on the basis of forward and inverse modeling output of GPR data in comparison with real GPR radargrams in the region validated the accuracy of GPR investigations in the area. Although with a quick glance, the error obtained by the inverse modeling for real GPR data seems unexpected and unacceptable, absolutely the high rate of error depends on many factors influencing on the real earth models containing various limitations existing in all forward modeling algorithms and software packages, impossibility of making forward modeling exactly according to the real models (due to the complex nature of the ground), taking into account the homogeneity and uniform host environment and targets in the modeling process unlike the diversity, the presence of different types of noises and so on. Therefore, making a controlled geophysical test site and trying performance of inverse modeling algorithm for field GPR data in this site, as well as determining the important physical parameters such as dielectric permittivity and electrical conductivity by experimental method through sampling from different depths for complex geological environments are suggested../files/site1/files/124/1ahmadpur%DA%86%DA%A9%DB%8C%D8%AF%D9%87.pdf

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Maximum surface settlement (MSS) is an important parameter for the design and operation of earth pressure balance (EPB) shields that should determine before operate tunneling. Artificial intelligence (AI) methods are accepted as a technology that offers an alternative way to tackle highly complex problems that can’t be modeled in mathematics. They can learn from examples and they are able to handle incomplete data and noisy. The adaptive network–based fuzzy inference system (ANFIS) and hybrid artificial neural network (ANN) with biogeography-based optimization algorithm (ANN-BBO) are kinds of AI systems that were used in this study to build a prediction model for the MSS caused by EPB shield tunneling. Two ANFIS models were implemented, ANFIS-subtractive clustering method (ANFIS-SCM) and ANFIS-fuzzy c–means clustering method (ANFIS-FCM). The estimation abilities offered using three models were presented by using field data of achieved from Bangkok Subway Project in Thailand. In these models, depth, distance from shaft, ground water level from tunnel invert, average face pressure, average penetrate rate, pitching angle, tail void grouting pressure and percent tail void grout filling were utilized as the input parameters, while the MSS was the output parameter. To compare the performance of models for MSS prediction, the coefficient of correlation (R²) and mean square error (MSE) of the models were calculated, indicating the good performance of the ANFIS-SCM model.

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Introduction
Ground-penetrating radar (GPR) is a high-resolution geophysical method which uses electromagnetic waves with high-frequency in order to map structures and objects buried in subsurface without any destruction of the medium. In present research, choice of optimum parameters of real data acquisition for this method has been studied. The governed behavior on the GPR fields can be simulated by solving the Maxwell’s equations and the appropriate boundary conditions that form the basis of electromagnetic theory. Among the variety of available numerical methods, the finite-difference time-domain (FDTD) method has paid more attention due to having the simple understanding of the concepts, flexibility, simulation and modeling of complex environments and the acceptability of its responses in the applied cases. The purpose of this study is to identify what reasonable information can be obtained from field data under different environmental conditions and different survey parameters.
 
Materials and methods
To achieve the goal, first forward modeling of GPR data has been carried out for several synthetic models corresponding to common targets in subsurface installations, using 2-D finite-difference time-domain method by means of GPRMAX, ReflexW and Radexplorer softwares. The main purpose of the simulations is investigation of the effect of survey parameters such as spatial sampling intervals (trace interspacing) and temporal sampling frequency on the GPR response of targets with various physical and geometrical parameters. Also to select and design the most appropriate conditions and survey parameters for real GPR data, numerous field traverses were performed in Isfahan University of Technology campus over the pre-known buried cylindrical targets containing power cable, petro-gas pipe, water pipeline and waste water pipeline with diverse host media. In this operation due to having one monostatic GPR system equipped by shielded antenna with central frequency of 250 MHz, some of the survey parameters containing central frequency, antenna separation and antenna directivity are invariant. The most important investigated survey parameters are temporal sampling frequency, spatial sampling distance (trace intervals), time window and number of stacked traces.
 
Results and discussion
Regarding carried out investigations through field data acquisition, in only one case the GPR system failed to detect any understated targets which this mode is related to choice a sampling distance of 1 cm and a sampling frequency of 504 MHz. The sampling frequency of 504 MHz is just capable to detect the surface water pipeline (due to its low burial depth). Also only in three cases the GPR system is capable to detect all subsurface targets so that the first mode of the trace interval is 2 cm and the sampling frequency is 1954 MHz, whereas in the latter two, the trace interval is 1 cm and the sampling frequencies have been selected 1563 and 1954 MHz. At the end success or failure of the targets detection was investigated on the basis of selected survey parameters and the probability of successful target detection was determined depending on the temporal and spatial sampling frequency so that the maximum probability of target detection is regarding to temporal sampling frequency of 1954 MHz and trace interval of 1 cm. Regarding GPR field data acquisition, considering the relations between the central frequency of GPR measurement systems, the depth of penetration and resolution, the diversity of materials and various components of the host media of targets and their surface overburdens a range of dierse equipments with a variety of frequencies is needed, which all of them are not generally available.
 
Conclusion
As a general conclusion of this study, in order to reduce the risk in GPR data acquisition operation, optimal survey parameters are suggested as follows:
The sampling frequency should be about 7 to 8 times the central frequency of the employed system (should not be less than this value in order to avoid aliasing and on the other hand, due to reduction in the amount of data and thus the memory needed for storage and processing), trace interspacing equal to 1 cm (in order to detect all buried targets especially targets with small size), the number of stacked traces equal to 16 (to reduce the amount of computer memory required for processing and storing data) and time window according to the computational-empirical relation (1).
                                                                                                                                                                (1)
Where W is time window, D is the maximum depth and V is the minimum velocity.
The results of this research are not restricted to the investigated case, but in practice are applicable for cases with similar host environments, especially in urban areas (which application of non-destructive methods such as GPR is necessary)../files/site1/files/131/6Extended_Abstract(1).pdf

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Introduction
This work intends to apply ASTER images to discriminate hydrothermal alteration zones in Kerman Cenozoiic Magmatic Belt (KCMB). Band ratio, principal component analysis, Crosta and color composite images are important methods to analyze satellite images. Previous researches showed that these techniques are not able to discriminate hydrothermal alteration zones and they usually detect vegetation covering as alteration zones. The reason is found in the spectral signature of vegetation and alteration minerals. It means that they present the same interaction when face with electromagnetic energy in different wavelengths. Hydroxyl-bearing minerals are the important products of hydrothermal alteration. Clays, which contain Al-OH- and Mg-OH-bearing minerals and hydroxides in alteration zones, are distinguished by absorption bands in the 2.1–2.4 µm range of ASTER data. Solving these problems is difficult when using standard image-processing techniques such as band rationing, principal component analysis, or spectral angle mapper. In recent years, several attempts were made to extract altered regions in the areas covered with vegetation. To overcome this problem, this research uses ASTER data by applying support vector machine (SVM) algorithmn. SVM is a new technique for data classification in remote sensing application. This paper aims to investigate the potential of SVM algorithm in mapping of hydrothermally altered areas. In many applications, SVM has been shown to provide higher performance than traditional learning machines and has been introduced as powerful tools for solving classification problems. The adopted dataset contains three ASTER scenes using SWIR and VNIR bands, covering the Meiduk porphyry copper deposit, Kader, Abdar and Iju occurrences located in Kerman Province, southeast Iran.
Material and methods
This work has been prepared on three ASTER level 1B scenes. Two scenes were acquired on 18^th April 2000 and another scenes on 15^th June 2007. These scenes were georeferenced by using an orthorectified ETM ⁺  image,  in  UTM projection and WGS-84 ellipsoid as a datum.  The first two data sets were corrected for Crosstalk. Atmospheric corrections were also performed by using Fast Line of Sight Atmospheric Analysis of Spectral Hypercubes (FLAASH). The data sets were then mosaicked.­­ Internal Average Relative Reflectance (IARR) correction was also applied. In this part, the training and test samples of the ASTER data are presented. The adopted image is a multispectral satellite image that contains 2204 training pixels which 516 pixels are related to arjillic zone, 1278 pixels are related to phyllic zone and 500 pixels are pertinent to propylitic zone (Fig. 1).

Fig. 1. Training pixels for learning SVM algorithm; Red pixels: arjillic; Green pixels: phyllic; Blue pixels: propylitic
Results and discussion
ASTER bands 4, 6, 7 and 8 were applied for determination of phyllic and arjilic zones and 9 bands of ASTER for propylitic alteration. In order to evaluate the developed algorirhm, confusion matrix was used and validation showed that discrimination of phylic and arjilic is not possible but propylitic zone could be identified by SVM. Also, the present research introduced a new error function, so called blind error, which is calculated using confusion matrix. Based on blind error, SVM did not classify 73.6 percent of the alteration pixels. But the remained pixels were classified with accuracy of 66.06%. Honarmand et al. (2011) and Mojedifar et al. (2013) studied the field samples of the present study area. Their studies showed that sericitization is the most widespread form of hydrothermal alteration at the Iju, Serenu, Chahfiroozeh, Meiduk, Parkam, Kader and Abdar porphyry copper deposits. Two types of phyllic alteration could be found in the study area including ferric-iron-rich and iron-oxide poor phyllic alteration. ASTER images were also analyzed by band rationing and principal component analysis (PCA) in order to compare their results with the SVM classified image. A comparison of the field data with altered areas mapped by PCA reveals errors in the classified map. Vegetation cover and sedimentary rocks are enhanced, which are erroneously identified as areas of alteration. The band ratio approach yields similar errors to those produced by the PCA method. These problems are less evident in the classified image obtained by SVM. The qualitative assessment of the accuracy of these methods indicates that SVM algorithm could be a reliable technique for alteration mapping, provided that the nature of the training areas is well known.
Conclusion
A comparison of the results obtained from traditional classification methods and support vector machine algorithm was performed in order to map hydrothermal alteration. Since the known occurrence of mineralization in the study area is consistent with the mapped distribution of hydrothermal alteration using SVM, this method is suggested to apply in exploring for hydrothermal alteration in other parts of the Iranian Cenozoic magmatic belt../files/site1/files/132/6Extended_Abstracts.pdf
 

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Introduction
Drilling has various methods that from different aspects such as crushing mechanism, type of used energy etc., is divided to several types containing hand held drilling, percussive drilling, cable-tool drilling, rotary (or circular) drilling, percussive-rotary drilling and core drilling. Unlike the direct circulation drilling system (DC) in the reverse circulation drilling system (RC), the drilling fluid moves the annulus between borehole wall and the drilling pipe and comes back with the drilled pieces along inside the drilling pipe. The exploratory drilling system of RC by conducting powder samples with high purity and fast drilling rate, is a great help to the velocity and accurate of exploration of ore deposits. Samples produced in this method are in the form of soil and rock powdered and rock fragments of the drilled part, which may be dry or with little moisture. The air flow inside the cycle causes the collected powder sample to be often dry but sometimes is wet due to groundwater or drilling mud. Drilling is one of the most costly mining processes. Therefore, the most important goal in drilling engineering is to reduce costs, and the best possible decision to optimize the cost of drilling is to choose the best possible drilling method. Based on the field data, cost of drilling for each meter of a soft rock (e.g. travertine) by core drilling and direct drilling methods are about 3.3 and 1.2 times of the RC method, respectively. Also the cost of drilling, for each meter of a hard rock (e.g. granite) by core drilling and direct drilling methods are about 2.6 and 1.3 times of the RC method, respectively.
Materials and methods
In the present research, reverse circulation drilling (RC) has been compared with other important, common and practical drilling methods, such as direct circulation and core drilling methods in terms of various criteria containing drilling (time) rate, price (cost), type and quality of acquired samples and performance efficiency of drilling. Also, as a field study in this research, deep drilled boreholes with RC and core drilling methods in the gold mine of Khomein-Akhtarchi located in the Markazi province, were investigated and compared from different aspects. At the end, the ability to select the most appropriate drilling method among the variety of methods was studied. The study region is located at 25 km northeast of Khomein city in the Markazi province. This region consists of two exploration areas of Zarmadan-Akhtaran1 with the area of 13.21 square kilometers and Zarmadan-Akhtaran2 with the area of 2.85 square kilometers. Access to the Akhtarchi gold region is possible through the Khomein-Shahabiyeh (Goldsat)-Mahallat road. In the mining region, the Permian rock complexes include dolomite, dolomitic limestone from brown to dark gray, black Irony sandstone and white to milky limestone known as p^ds, p^dl and p^l units in the geological maps.
In the studied region, several deep boreholes, most of them by RC and some of them by core drilling methods have been drilled. In general, by now in the Akhtarchi gold zone in the Zarmadan-Akhtaran2 area 54 powder boreholes have been drilled through RC method called by RC1 to RC54. Also, there are 25 core drilling boreholes, 18 boreholes called by BH1 to BH18 in the Zarmadan-Akhtaran1 area and 5 boreholes called by BH1 to BH5 in the Zarmadan-Akhtaran2 area. During drilling operations, Permian and Cretaceous rock units have been encountered. The details of drilling via RC method for 4 boreholes with numbers 50, 51, 53 and 54 have been accurately taken. The measured drilling times were obtained from drilling personnel of the mine through the questionnaire which they were weighted mean if needed.
Results and discussion
The average drilling time for each meter of rock in boreholes 53 and 54 is 2:12 and 2:54 minutes, respectively. In both cases, the time duration is very short and this feature is one of the advantages of the RC drilling method. The longer average duration of drilling for each meter of rock in the borehole 54 than 53, is due to the depth of the borehole 54 and the hammer problem of the drilling machine during the drilling this borehole. In Table 1, the average duration of drilling operation per meter of rock in the Akhtarchi gold mine is given according to the type of rock (lithology) at definite depth intervals, on the basis of field studies. According to this table data, the duration of the drilling for each meter of rock in the greater depths increases that the reasons for increasing the duration of drilling for each meter of rock in greater depths are the difficulty of drilling due to the increasing length of rig, the reduction of transient energy to the bit, the probability of greater borehole declination, compaction increasing and as a result increasing the strength of rocks and more hydrostatic and lithostatic pressures in the great depths meanwhile at a great depth, the probability of capturing the drilling rig is too high. Also the cost (the time price) of drilling per meter of rock in this mine based on the dip and depth of drilling is about 1300 to 2000 thousand Rials by the RC method, against 2620 to 4250 thousand Rials by the core drilling method.
The results of the present research indicate that the RC drilling in comparison with other drilling methods, especially conventional and applied ones in terms of drilling costs and drilling rate (time) is highly desirable while is desirable regarding depth of drilling, the type and quality of the acquired samples and the overall efficiency of drilling performance. Although the core drilling method with the ability to drill very deep boreholes obtaining cores in terms of the type and quality of the acquired samples, as well as the depth of the drilling is the most desirable, but for exploration drilling (especially in the detailed exploration stages), deposits with low-grade and very little mineral indices (like gold mine of Khomein-Akhtarchi), and hence the large sample sizes are needed, employing RC drilling method having comparative advantages is economic.
Conclusion
Regarding the use of RC drilling method in the case study, the gold mine of Khomein-Akhtarchi, it was found that the RC method compared to the core drilling method, in terms of the duration of drilling operations or the speed of advance (the rate of penetration in the rock), drilling costs and efficiency of performance is desirable. Also, according to the type of mineral deposit (gold type), which is low-grade and the indices of the mineral are very low, therefore the large sample sizes are needed, thus, in terms of the type of obtained samples, employing RC drilling method in this case, is accounted a very important advantage related to the DC method (in terms of accuracy) and core drilling method (in terms of cost). The results of this research are useful for all users of drilling operations, including drilling engineers and technicians, engineering geology and geotechnical practitioners, mineral exploration engineers, groundwater aquifers and hydrocarbon reserves (oil and gas) to choose the optimal drilling method under different environmental and economic conditions based on criteria such as the purpose of drilling operations, costs, progress rate, type and quality of the yielded samples and the efficiency of drilling operation. Also, the use of RC drilling method has the advantages over the other drilling methods to be suggested for exploration of low-grade deposits such as gold, silver and copper, especially in the final stages such as detailed and mining exploration.
 

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Introduction
Drill-bit selection is one of the most important aspects of well planning due to the bearing it can have on the overall cost of the well. Bit selection in conventional and slightly inclined wells is a very delicate and complex process. In high angle and horizontal wells it is even more difficult. Historically, drilling engineers have selected bits on the basis of what has been worked well in the area and what has been determined to have the lowest cost run from offset bit records. Often the best bit records were not available for evaluation, because the best bit may not yet have been run, may have been run by a competitor or the engineer was new to the area. As a result the bit program was generally developed by trial and error and at significant additional costs for a large number of wells. In most cases the optimum program was never reached because there was nothing to predict that a bit selection change could further reduce the cost of the well. In this study, an alternative solution approaches using the concept of the power of data mining algorithms to solve the optimum bit program for a given field is proposed.
Material and methods
It has been considered an offset well to be drilled outside the known boundaries of a known field. For this purpose, the seventh well (X-7) of the same field was used as a verification point. The data was trained using the well log and rock bit data of six wells located in the field and the real well log data of well 7 was input as unknown data. These depths are selected based on reported rock bit program. When compared to the real data, it could be observed that the models (adaptive neuro fuzzy inference system, K-nearest neighbors, decision tree, Bayesian classification theory and association rules) estimates the formation hardness accurately. This minor discrepancy was also present with the company’s suggested rock bit program, which was based on the previous wells’ rock bit data.
Results and discussion
In this paper, data mining algorithms for optimum rock bit program estimation is proposed. The accuracy and efficiency of the developed data mining algorithms (adaptive neuro fuzzy inference system, K-nearest neighbors, decision tree, Bayesian classification theory and association rules) that requires sonic and neutron log data input was tested for several real and synthetic cases. In the case of a development? well to be drilled outside the known boundaries of a field the model estimated rock bits with properties that consider the formation hardness correctly but slightly underestimated further rock bit details. The models also produced reasonable rock bit programs for an advance well to be drilled within the known boundaries of a field and a wildcat well drilled in a nearby field with similar rock properties to the training field. Thus it was concluded that the developed adaptive neuro fuzzy inference system is suitable as a front-end system for rock bit selection that could help engineers in decision-making analysis.
Conclusion
Optimum bit selection is one of the important issues in drilling engineering. Usually, optimum bit selection is determined by the lowest cost per foot and is a function of bit cost and performance as well as penetration rate. Conventional optimum rock bit selection program involves development of computer programs created from mathematical models along with information from previously drilled wells in the same area. Based on the data gathered on a daily basis for each well drilled, the optimum drilling program may be modified and revised as unexpected problems arose. The approaches in this study uses the power of data mining algorithms to solve the optimum bit selection problem. In order to achieve this goal, adaptive neuro fuzzy inference system, K-nearest neighbors, decision tree, Bayesian classification theory and association rules were developed by training the models using real rock bit data for several wells in a carbonated field. The training of the basic models involved use of both gamma ray and sonic log data. After that the models were tested using various drilling scenarios in different lithologic units. It was observed that the adaptive neuro fuzzy inference system model has provided satisfactory results.
 
 

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In Yazd Darreh-Zereshk copper deposit geophysical data containing magnetic, resistivity and induced polarization have been surveyed and 25 boreholes have been drilled in the area. In the present research, inversion and processing of geophysical data as well as their qualitative and quantitative accordance with boreholes assay data have been carried out. To achieve the goal first, total magnetic intensity map after applying necessary filters and processing, was mapped to identify surface and deep expansion of anomalies on it. Drawing the anomaly profile of magnetic stations surveyed along 4 geoelectric profiles shows that most of the magnetic anomaly zones have high chargeability and low resistivity that indicates the qualitative compatibility of magnetic and geoelectric data, as a result increasing the probability of mineralization in the area. Afterward  on the basis of qualitative interpretation of geoelectrical sections, optimal locations of drilling on the each profile were proposed. Plotting mineral deposit cross-section along the geoelectrical profiles using the boreholes assay data, revealed that drilling of some boreholes located on the geophysical profiles haven’t been based on the results of geophysical operation, carried out without any right logic, purpose and design. In general, the qualitative accordance of the results of geoelectrical operation with the boreholes assay data showed a pretty good qualitative accordance. Also investigation of linear correlation coefficient value between inverted geophysical data and borehole assay in a specific same range after a same definite gridding and interpolation of their values, overall indicated a relatively good quantitative accordance (between 0.4 and 0.7)../files/site1/files/151/1.pdf

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