Mahyar Yousefi; R. Gholami; A. Kamkarr-Ruhani; A. Moradzade
Abstract
In the systematic exploration plan for prospecting the mineral deposit, we can design an exploration algorithm using the modeling of known mineral occurrences. Such an algorithm is a key to recognize the area where is high probability of mineralization, reduce the risk of exploration and increases the ...
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In the systematic exploration plan for prospecting the mineral deposit, we can design an exploration algorithm using the modeling of known mineral occurrences. Such an algorithm is a key to recognize the area where is high probability of mineralization, reduce the risk of exploration and increases the probability of exploration success. In this paper, we introduce an algorithm for optimizing mineral potential model and target generation in the exploration operation with focus on the gold exploration. In this way, after descriptive and conceptual modeling of gold deposit, all of the characteristics that can be used as an exploration criterion have been identified and assembled as a target model. Then, various data layers have been used to generate significant evidential maps. Then all of the evidential maps should be combined to generate mineral potential model (map) of the mineralization type sought. Recent map shows the probability location of gold mineralization as target area. Finally an algorithm has been introduced in which all of the exploration stage and methods have been identified base on priority.
A.R. Arab-Amiri; A. Moradzadeh; D. Rajabi; B. Siemon; N. Fathianpour
Abstract
It is about 30 years that Helicopter electromagnetic (HEM) surveys are being used for rapid mineral and ground water exploration, environmental investigations and also geological mapping in extensive areas. Despite this, one of the most important problems in using obtained data from the surveys is accurate ...
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It is about 30 years that Helicopter electromagnetic (HEM) surveys are being used for rapid mineral and ground water exploration, environmental investigations and also geological mapping in extensive areas. Despite this, one of the most important problems in using obtained data from the surveys is accurate interpretation of the data. Otherwise, there will be no beneficial results while spending high costs. Thus the interpretation of the data is as old as the surveys. Several experts have tried to improve the interpretation of HEM data and they have achieved great successes. Almost the results of all these surveys are presented as resistivity (or conductivity)-depth sections. To reach this target, the first step is to solve the electromagnetic induction integral equation. As solving this integral is not possible using analytical methods, several numerical methods such as Laplace transformation, Hankel transformation and Jacobi-Matrix methods have been suggested for the solution of the integral, and different approaches have been presented with each method by various authorities. One of the most important solution methods is fast Hankel transformation. In this paper, it is attempted to use this method for finally obtaining resistivity-depth sections. For solving the induction equation by this method, we need the kernel function of the integral and weighting coefficients that replace the Bessel function in the integral. For this, first we use the Guptasarma-Singh method. Then results of this method are corrected and evaluated. Then, these results will be analyzed and tested with two synthetic models in addition to presenting the results of inverse modeling. Finally, by adding new parameter named α0 to induction equation, we will clearly see an improvement in the results of inverse modeling. Meanwhile, the problem of singularity that occurs at high frequencies is almost removed.
A.R. Arab-Amiri; A. Moradzadeh; D. Rajabi; N. Fathianpour; B. Siemon
Abstract
Today Helicopter-borne electromagnetic (HEM) data survey play important role for high resolution and fast 3D mapping of resistivity structures within the vast area. The standard method of interpretation of these data is to inverse them frequently. As surveying system is not fixed during the survey, hence ...
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Today Helicopter-borne electromagnetic (HEM) data survey play important role for high resolution and fast 3D mapping of resistivity structures within the vast area. The standard method of interpretation of these data is to inverse them frequently. As surveying system is not fixed during the survey, hence noise is accompanying the measured data. To process the measured noisy data they are fed into the several filters to get better data to be used for modeling. During the filtering stage some of signals are also lost. Therefore, it is required to choose modeling techniques that has minimum error and provide accurate subsurface model. In this paper, first the response of the three synthetic layered earth models were calculated by using three different Hankel transform forward modeling methods. Then with adding different percents of random noise to the synthetic data, they were modeled inversely by different methods. The obtained results indicate that the so-called improved Guptasarma-Singh inverse modeling method could provide better responses for all three synthetic models.
H. Aghajani; A. Moradzadeh; H. Zeng
Abstract
Estimation of depth and horizontal location of anomalous bodies plays an important role for selecting exploration wells location. There are many methods for depth estimating, and most of them use high-pass filters. The Normalized Full Gradient (NFG) method is one of these methods that use Fourier series ...
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Estimation of depth and horizontal location of anomalous bodies plays an important role for selecting exploration wells location. There are many methods for depth estimating, and most of them use high-pass filters. The Normalized Full Gradient (NFG) method is one of these methods that use Fourier series to remove deficiencies and eliminate the oscillations which appear on the downward continuation when passing through center of an anomalous body. In this paper, the main goals is calculation of NFG and present a new method for determining optimum number of Fourier terms and use them for synthetic and real two and three dimensional field data. The obtained results on synthetic data indicate that the estimated location and depth of the model is in 10 percent error with the real. The NFG method has also applied on two sets of real field gravity data to determine the location and estimate depth of Humble salt dome (USA) and massive sulfide mineralization of Mobrun (Canada). For the first field data set the NFG has provided a depth to the centre equal to 4.8 km and for the second case the depth to the top section of mineralized body has been estimated 17 meters and its continuation to a depth more than 70 meters has also been confirmed. The obtained results of the NFG method on real field data in each case are in good agreement to those provided by other independent information arises from drilling and other geophysical methods. The above matter clearly illustrates that the NFG method is able enough to locate anomalous bodies and estimate their burial depth precisely.
A. Moradzadeh; F. Doulati Ardejani; B. Tayebi
Abstract
There are a few iron deposits in the north and northeastern part of Semnan city that none of them has a systematic exploration background. Ojat_Abad deposit is one of them located in 63 km of north-east of Semnan at the southern side of Semnan - Damghan main road. A magnetic survey including 1200 ...
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There are a few iron deposits in the north and northeastern part of Semnan city that none of them has a systematic exploration background. Ojat_Abad deposit is one of them located in 63 km of north-east of Semnan at the southern side of Semnan - Damghan main road. A magnetic survey including 1200 measuring points has been recently performed to explore the deposit within an area of 89 acres. The prepared total and residual magnetic field maps clearly demonstrate the existence of iron anomaly at seven locations in a zone with northeast - southwest trend. In this paper, attempt has been made to obtain more qualitative and quantitative information for the recognized anomalies by performing two and three dimensional (2D, 3D) numerical modeling. To achieve the goal, the residual anomaly map, obtained by professional software called Modelvison Pro is used. It was found that the results of 2D and 3D modeling confirm each other in the most cases and in addition are in quite good agreement with the results of existing mining excavations. The obtained results also demonstrate the explored anomalies locate separately, and except one of them, all are located at a depth less than 35 meters.
A. Moradzadeh; F. Tahmasbi; M. Fateh
Abstract
The magnetotelluric (MT) method is a natural source electromagnetic geophysical technique, which is used mainly in petroleum, mineral and geothermal exploration. As in this method, the quantity of the measured data is bulky and have a complex structure, their modeling, ...
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The magnetotelluric (MT) method is a natural source electromagnetic geophysical technique, which is used mainly in petroleum, mineral and geothermal exploration. As in this method, the quantity of the measured data is bulky and have a complex structure, their modeling, compared with the modeling of the other electrical data, is a very complex task or even impossible in some instances.
The main objective of this paper is to use the ability of the artificial neural networks (ANN) to find a solution for two-dimensional (2D) joint TE (transverse electric) and TM (transverse magnetic) modes inverse modeling of MT data. To achieve the goal, a multilayer perceptron (MLP) network with back propagation (BP) learning algorithm is used. In order to learn the designed network, many synthetic 2D models with the same category, have been created and their responses have been calculated for each polarization mode by forward modeling. Synthetic data include apparent resistivity and impedance phase in 9 stations and 11 frequencies in two polarization modes. After a comprehensive study, a perceptron with 3 layers and architecture of 396-9-9 has been designed and used to model the data.
This study show that the designed network is capable enough to produce an acceptable 2D underground model so that the correspondence mean relative modeling error is 3.9% and 6.9 % respectively for noise free data and 5 percent randomly added noisy data. This indicates that if ANN is designed and trained properly, then it would be capable enough to perform 2D inverse modeling of MT data. It has also shown that once the designed network has been trained properly it is able to perform the inverse modeling precisely in a short time. At the end, the performance of the designed network has been evaluated by a set of field MT data and its results has been compared with those produced by a common smooth rapid relaxation inversion (RRI) method. The comparison indicates that the results of these two different procedures are in close agreement.
