Intrinsic geological model generation for chromite pods in the Sabzevar ophiolite complex, NE Iran

Soleimani, Mehrdad; Shokri, Behshad Jodeiri

doi:10.1016/j.oregeorev.2016.03.013

Cited by 14 publications

(6 citation statements)

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“…Numerous podiform chromite resources are a high motivation for Iran country as a main chromite trader in the world [20]. These podiform chromite resources are mostly related to ophiolite complexes in northeast Iran or Zagros orogenic belt [21]. The Ni ore can be also extracted as "byproduct" from several Cr deposits.…”

Section: Region Of Interestmentioning

confidence: 99%

Multi-element geochemical anomaly recognition applying geologically-constrained convolutional deep learning algorithm with Butterworth filtering

Sabbaghi,

Tabatabaei,

fathianpour

2024

Preprint

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Deep learning networks have extensively been used to detect multi-element geochemical anomalies linked to different mineral deposits in recent decade. Efficient detection of multi-element geochemical anomalies is a significant issue that should be done through capable processing methods. The two-dimensional (2D) convolutional neural networks (CNN) are a powerful subset of machine learning algorithms which can present magnificent conclusions. Because those have the ability to extract high-level features of complex inputs. But, there are several shortcomings in applying 2D images as input of the CNNs for multi-element geochemical anomaly mapping. This challenge can be solved designing one-dimensional (1D) CNN to convolve geochemical data table yielding unbiased maps produced. Also, great feature extraction ability of the CNNs can increase defining geological constraints and training their frameworks with frequency domain data which is contained superlative information. In this regard, a novel geologically-constrained convolutional deep learning (GCDL) algorithm has been developed to classify multi-element geochemical data table. Accordingly, constructed GCDL with frequency domain training data of the Cr mineralization in the Robat Sefid district, NE Iran, could demonstrate impressive results. Based on success-rate curves, produced map of frequency domain geochemical data has plotted 86.22% Cr occurrences via 28% corresponding area while produced map of spatial domain geochemical data has plotted 79.91% Cr occurrences via same corresponding area.

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Section: Region Of Interestmentioning

confidence: 99%

Multi-element geochemical anomaly recognition applying geologically-constrained convolutional deep learning algorithm with Butterworth filtering

Sabbaghi,

Tabatabaei,

fathianpour

2024

Preprint

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“…The existing studies focus on the geological analysis using existing GIS approaches, plotting stratigraphic columns and statistical graphs for spatial data visualization (Koshnaw et al, 2020;Mouthereau et al, 2007), geologic modelling data using in-situ experiments Heidari et al (2021); Hosseini et al (2021); Lindh and Lemenkova (2022c); Soleimani and Jodeiri Shokri (2016), geochemical data analysis Afzal et al (2017); Lindh and Lemenkova (2022a); Mokhtari and Sadeghi (2021) and do not deal with a detailed explanation of scripting techniques of the geological mapping. As a consequence, they either lack detailed explanation of the techniques of cartographic data visualization (Tavani et al, 2018) or have limited use of scripting in geologic modelling (Lemenkov and Lemenkova, 2021).…”

Section: Related Workmentioning

confidence: 99%

A Script-Driven Approach to Mapping Satellite-Derived Topography and Gravity Data Over the Zagros Fold-and-Thrust Belt, Iran

Lemenkova

2022

Artificial Satellites

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Integrated geophysical mapping benefits from visualizing multi-source datasets including gravity and satellite altimetry data using 2D and 3D techniques. Applying scripting cartographic approach by R language and GMT supported by traditional mapping in QGIS is presented in this paper with a case study of Iranian geomorphology and a special focus on Zagros Fold-and-Thrust Belt, a unique landform of the country affected by complex geodynamic structure. Several modules of GMT and ’tmap’ and ’raster’ packages of R language were shown to illustrate the efficiency of the console-based mapping by scripts. Data sources included high-resolution raster grids of GEBCO/SRTM, EGM-2008, SRTM DEM and vector geologic layers of USGS. The cartographic objective was to visualize thematic maps of Iran: topography, geology, satellite-derived gravity anomalies, geoid undulations and geomorphology. Various cartographic techniques were applied to plot the geophysical and topographic field gradients and categorical variations in geological structures and relief along the Zagros Fold-and-Thrust Belt. The structures of Elburz, Zagros, Kopet Dag and Makran slopes, Dasht-e Kavir, Dasht-e Lut and Great Salt Desert were visualized using 3D-and 2D techniques. The geomorphometric properties (slope, aspect, hillshade, elevations) were modelled by R. The study presented a series of 11 new maps made using a combination of scripting techniques and GIS for comparative geological-geophysical analysis. Listings of R and GMT scripting are provided for repeatability.

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“…Iran is known as an oil land, but there are a variety of minerals in this country [24], chromite is one of them, which can be found almost everywhere in Iran [26]. Most of the deposits are alpine type chromite, which is distributed in several places like schlieren bands, massive lenses, and dissemination in serpentinized ultrabasic rocks [27]. Forumad mine and processing plant is located in Sabzevar district and has an alpine type deposit, with similar minerals and rock compositions (Figure 1).…”

Section: Locationmentioning

confidence: 99%

Evaluation of Chromite Recovery from Shaking Table Tailings by Magnetic Separation Method

Khakmardan¹,

Doodran²,

Shirazy³

et al. 2020

OJG

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Intrinsic geological model generation for chromite pods in the Sabzevar ophiolite complex, NE Iran

Cited by 14 publications

References 50 publications

Multi-element geochemical anomaly recognition applying geologically-constrained convolutional deep learning algorithm with Butterworth filtering

Multi-element geochemical anomaly recognition applying geologically-constrained convolutional deep learning algorithm with Butterworth filtering

A Script-Driven Approach to Mapping Satellite-Derived Topography and Gravity Data Over the Zagros Fold-and-Thrust Belt, Iran

Evaluation of Chromite Recovery from Shaking Table Tailings by Magnetic Separation Method

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