Exploration
Samaneh Barak; Ali Imamalipour; Maysam Abedi
Abstract
The Sonajil area is located in the east Azerbaijan province of Iran. According to studies on the geological structure, the region has experienced intrusive, subvolcanic, and extrusive magmatic activities, as well as subduction processes. As a result, the region is recognized for its high potential for ...
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The Sonajil area is located in the east Azerbaijan province of Iran. According to studies on the geological structure, the region has experienced intrusive, subvolcanic, and extrusive magmatic activities, as well as subduction processes. As a result, the region is recognized for its high potential for mineralization, particularly for Cu-Au porphyry types. The main objective of this research work is to utilize the fuzzy gamma operator integration approach to identify the areas with high potential for porphyry deposits. To carry out this exploratory approach, it is necessary to investigate several indicator layers including geological, remote sensing, geochemical, and geo-physical data. The analysis reveals that the northeastern and southwestern parts of the Sonajil region exhibit a greater potential for porphyry deposits. The accuracy of the resulting Mineral Potential Map (MPM) in the Sonajil region was evaluated based on data from 20 drilled boreholes, which showed an agreement percentage of 83.33%. Due to the high level of agreement, certain locations identified in the generated MPM were recommended for further exploration studies and drilling.
M. Azadi; M. Abedi; Gh. H. Norouzi Baghkameh
Abstract
< p>Attenuation of the signal received from sources causing anomalies and reduction of data resolution are the negative features of airborne measurements. Using a stable downward continuation method is a practical way to address these shortcomings. In this study, we investigated the efficiency ...
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< p>Attenuation of the signal received from sources causing anomalies and reduction of data resolution are the negative features of airborne measurements. Using a stable downward continuation method is a practical way to address these shortcomings. In this study, we investigated the efficiency of various stabilizers in achieving stable downward continued data. The purpose of this study is to select the most appropriate stabilizer(s) for this operation. We examined the various stabilizing functions by introducing them into the Tikhonov regularization problem. The results of research on synthetic airborne gravity and magnetic data showed that βL1 (the other definition of L1 norm) and SM (the smoothest model) stabilizers have the potential to be used in the stable implementation of the downward continuation method. These stabilizers performed better than the other in the three comparisons, including visual, quantitative (RMS error), and graphical comparisons. Also, by examining the airborne magnetic data related to the Esfordi district in Yazd province (Iran), it was found that in general the βL1 stabilizer is more suitable than the other stabilizing functions studied in this research.
S. Talesh Hosseini; O. Asghari; Seyed A. Torabi; M. Abedi
Abstract
An accurate modeling of sophisticated geological units has a substantial impact on designing a mine extraction plan. Geostatistical simulation approaches, via defining a variogram model or incorporating a training image (TI), can tackle the construction of various geological units when a sparse pattern ...
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An accurate modeling of sophisticated geological units has a substantial impact on designing a mine extraction plan. Geostatistical simulation approaches, via defining a variogram model or incorporating a training image (TI), can tackle the construction of various geological units when a sparse pattern of drilling is available. The variogram-based techniques (derived from two-point geostatistics) usually suffer from reproducing complex and non-linear geological units as dyke. However, multipoint geostatistics (MPS) resolves this issue by incorporating a training image from a prior geological information. This work deals with the multi-step Single Normal Equation Simulation (SNESIM) algorithm of dyke structures in the Sungun Porphyry-Cu system, NW Iran. In order to perform a multi-step SNESIM algorithm, the multi-criteria decision-making and MPS approaches are used in a combined form. To this end, two TIs are considered, one for simulating dyke structures in the shallow depth, and two for simulating dyke structures in a deeper depth. In the first step, a TI is produced using geological map, which has been mined out during the previous exploration operations. After producing TI, the 35 realizations are simulated for the shallow depth of deposit in the area under study. To select the best realization (as a TI for the next step) of the simulation results, several statistical criteria are used and the results obtained are compared. To this end, a hybrid multi-criteria decision-making is designed on the basis of a group of statistical criteria. In the next step, the dyke structures in the deeper depth are also simulated by the new TI.
M. Babaei; M. Abedi; Gh. H. Norouzi; S. Kazem Alilou
Abstract
This work presents the application of a geostatistical-based modeling approach for building up electrical properties acquired from a geophysical electrical tomography survey deployed for the purpose of porphyry Cu exploration at the Takht-e-Gonbad deposit, in the central domain of Iran. Electrical data ...
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This work presents the application of a geostatistical-based modeling approach for building up electrical properties acquired from a geophysical electrical tomography survey deployed for the purpose of porphyry Cu exploration at the Takht-e-Gonbad deposit, in the central domain of Iran. Electrical data were inverted in 2D along several profiles across the main favorable zones of Cu-bearing mineralization to image electrical resistivity and chargeability properties. Upon tight spatial correlation of these geophysical properties and Cu mineralization (i.e. Cu grade), electrical models were constructed in 3D through geostatistical interpolation of 2D inverted data to provide insights into the geometry of probable ore mineralization. Anomalous geophysical zone that was coincident simultaneously with higher values of electrical chargeability and resistivity, was in accordance with the main body of high Cu grades generated from exploratory drillings. It reveals that the porphyry-type Cu mineralization system in this area has strong geophysical footprints controlled mainly by rock types and alterations. Note that these physical models supply valuable pieces of information for designing the layout of further exploratory drillings, constructing geological characteristics, separating non-mineralized form mineralized zones, and resource modeling.
Exploitation
S. Salarian; O. Asghari; M. Abedi; S. K. Alilou
Abstract
This work aims at figuring out the spatial relationships between the geophysical and geological models in a case study pertaining to copper-sulfide mineralization through an integrated 3D analysis of favorable target. The Ghalandar Skarn-Porphyry Cu Deposit, which is located in NW Iran, is selected for ...
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This work aims at figuring out the spatial relationships between the geophysical and geological models in a case study pertaining to copper-sulfide mineralization through an integrated 3D analysis of favorable target. The Ghalandar Skarn-Porphyry Cu Deposit, which is located in NW Iran, is selected for this research work. Three geophysical surveys of direct current electrical resistivity and induced polarization tomography along with magnetometry are performed to construct the physical properties of electrical resistivity, chargeability, and magnetic susceptibility, respectively. Inverse modeling and geostatistical interpolation are utilized to generate the physical 3D models. A 3D model of Cu grade is generated using ordinary kriging; however, the indicator kriging method is run to design a 3D model of rock types through incorporating the drilling results. Block models of geophysical and geological characteristics are cast in a similar 3D mesh to investigate their relationships in copper mineralization. A concentration-volume multi-fractal method is utilized to divide each model into its sub-sets, where the most productive portions in association with Cu-bearing mineralization are distinguished. Note that sub-sets of geophysical models are spatially matched with geological models of Cu grade and rock types. The zones with low electrical resistivity, high chargeability, and low magnetic susceptibility correspond to the main source of Cu mineralization in a dominated skarn rock type setting.
Maysam Abedi; Kiomars Mosazadeh; Hamid Dehghani; Ahmad MadanchiZare
Abstract
We have applied an automatic interpretation method of potential data called AN-EUL in unexploded ordnance (UXO) prospective which is indeed a combination of the analytic signal and the Euler deconvolution approaches. The method can be applied for both magnetic and gravity data as well for gradient surveys ...
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We have applied an automatic interpretation method of potential data called AN-EUL in unexploded ordnance (UXO) prospective which is indeed a combination of the analytic signal and the Euler deconvolution approaches. The method can be applied for both magnetic and gravity data as well for gradient surveys based upon the concept of the structural index (SI) of a potential anomaly which is related to the geometry of the anomaly sources. With AN-EUL method, both the depth and the approximate geometry (or SI) of the causative sources can be deduced. A realistic model for UXO to be simulated by a simple shape body is a prolate spheroid. The method is applied for both synthetic potential data assuming a collection of causative UXO sources replicating various sizes placed at different depths. In both cases, the estimated depth and the SI of the synthetic UXOs approximately correspond to the synthetic model parameters. The location detection of the causative sources is based upon the Blakely automatic picking algorithm. For both data sets, since the anomaly responses of the small UXOs are affected by noise, the estimated SI is a bit disturbed but the locations correspond to the real ones. The Blakely algorithm also identifies weak anomalies that are due to noise in data; thus, a post-processing of the estimated SI of the automatically detected sources may be needed to prevent false alarm sources in UXO exploration. Two field data sets have been provided to demonstrate the capability of the applied methods in UXO detection.
Maysam Abedi; Kiomars Mosazadeh; Hamid Dehghani; Ahmad MadanchiZare
Abstract
This paper describes an efficient edge-preserved regularization algorithm for downward continuation of magnetic data in detection of unexploded ordnance (UXO). The magnetic anomalies arising from multi-source UXO can overlap at a height over the ground surface, while causative sources may not be readily ...
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This paper describes an efficient edge-preserved regularization algorithm for downward continuation of magnetic data in detection of unexploded ordnance (UXO). The magnetic anomalies arising from multi-source UXO can overlap at a height over the ground surface, while causative sources may not be readily separated due to low level of signal-to-noise ratio of the observed data. To effectively the magnetic method work in the cleanup stage of contaminated area with UXO, the magnetic anomalies of UXO sources should be enhanced in order to separate the locations of different sources. The stable downward continuation of magnetic data can increase the signal-to-noise ratio which subsequently causes the separation of UXO sources by enhancing the signals. We formulate the downward continuation as a linear ill-posed deconvolution problem in this study. To obtain a reasonable downward continued field, it is stabilized in a Fourier domain to regularize the downward solution using the edge-preserved (or total-variation) algorithm. The L-curve method is used to choose the optimum value of the regularization parameter which is a trade-off between the misfit and the solution norms in the cost function of optimization problem. A synthetic magnetic field is constructed from isolated multi-source UXO anomalies, whose results show that the data can be stably downward continued by the proposed method. Likewise, a field data set has been provided to demonstrate the capability of the applied method in UXO detection.
Maysam Abedi; Gholam-Hossain Norouzi; Nader Fathianpour; Ali Gholami
Abstract
This paper describes the application of approximate methods to invert airborne magnetic data as well as helicopter-borne frequency domain electromagnetic data in order to retrieve a joint model of magnetic susceptibility and electrical resistivity. The study area located in Semnan province of Iran consists ...
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This paper describes the application of approximate methods to invert airborne magnetic data as well as helicopter-borne frequency domain electromagnetic data in order to retrieve a joint model of magnetic susceptibility and electrical resistivity. The study area located in Semnan province of Iran consists of an arc-shaped porphyry andesite covered by sedimentary units which may have potential of mineral occurrences, especially porphyry copper. Based on previous studies, which assume a homogenous half-space earth model, two approximate methods involving the Siemon and the Mundry approaches are used in this study to generate a resistivity-depth image of underground geologically plausible porphyry unit derived from airborne electromagnetic data. The 3D visualization of the 1D inverted resistivity models along all flight lines provides a resistive geological unit which corresponds to the desired porphyry andesite. To reduce uncertainty arising from single geophysical model, i.e., the resistivity model acquired from the frequency domain electromagnetic data, a fast implementable approach for 3D inversion of magnetic data called the Lanczos bidiagonalization method is also applied to the large scale airborne magnetic data in order to construct a 3D distribution model of magnetic susceptibility, by which the obtained model consequently confirms the extension of an arc-shaped porphyry andesite at depth. The susceptible-resistive porphyry andesite model provided by integrated geophysical data indicates a thicker structure than what is shown on the geological map while extends down at depth. As a result, considering simultaneous interpretation of airborne magnetic and frequency domain electromagnetic data certainly yield lower uncertainty in the modeling of andesite unit as a potential source of copper occurrences.
