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Using Remote Sensing Investigation, Gis Application and Geostatistics Analysis for Geological Mapping and Mineral Prospecting Around Shulai Area, Red Sea State, Sudan

المؤلف الرئيسي: Elameen, Hassan Khogali (Author)
مؤلفين آخرين: Zeinelabdein, Khalid Abdelrahman Elsayed (Advisor)
التاريخ الميلادي: 2020
موقع: الخرطوم
الصفحات: 1 - 130
رقم MD: 1206987
نوع المحتوى: رسائل جامعية
اللغة: الإنجليزية
الدرجة العلمية: رسالة ماجستير
الجامعة: جامعة النيلين
الكلية: كلية النفط والمعادن
الدولة: السودان
قواعد المعلومات: Dissertations
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المستخلص: This study was carried out in the northeastern part of Block 11, Ariab mining company (AMC) concession, western part of Red Sea Hills in the Red Sea State of northeast Sudan. The study area is bounded by latitudes 18°59`47.798" -19°24`55.378"N and longitudes 36°31`6.311"- 36°01`3.895"E. The study aimed to conduct geological mapping at the scale of 1:100 000 and mineral prospecting using remote sensing and GIS authenticated by field work. The study revealed that the area under consideration consists of a multi-deformed and poly-metamorphosed basement complex terrain, which belongs to the Nubian shield. The oldest rock units of basement complex, consists of basic metavolcanics and meta-sediments, which were intruded by the syn to late unorogenic granitic intrusions. The basement complex units are overlain by alluvial, superficial deposits. Different digital image processing techniques were applied on the multispectral data of Landsat 8٠ The spectral enhancement of various color composite images help the visual interpretation in geological context. Image transformations through decorrelation stretching, principal component transformation (PCA) and Sultan Ratio image are the main techniques adopted for geological mapping. The color composite image of bands 7, 5 and 2 in RGB sharpened with the panchromatic band yielded an overall good lithologic discrimination than other images. Moreover, interpolation of the elements in stream samples has been taken place to see the distribution of these elements in the study area which help to identify the different geological units. The production of Geological map of Shulai area was based on Landsat 8 images processing, stream samples data and interpretation with limited field survey. The SRTM raster data was used for generating the streams. Lineaments has been digitized from PCI image after doing high-pass spatial filtering. The dominant lineament trends are the N-NW - S-SE (340٥) trend, which corresponds to Oko shear zone, the other trend is NE - sw (65٥) trend, which corresponds to Nakaseib suture zone.

Using Landsat 8 OLI images, band ratioing and the Feature Oriented Principal Components transformations (FOPCT) were applied to produce Sabin, Abram and Crosta colored composite images, respectively. These images are used to detect the presence of alteration zones related to the mineralization in the study area. The ASTER semi hyperspectral data have been treated by two methods, the first is to obtain the mineral indices images that revealed the wide distribution of indicator minerals in the study area as they are found in original rock or detected as alteration zones. The mineral indices images hardly defined alteration zone. The Spectral Angle Mapper (SAM) classifier of ASTER data gives better results than the Landsat ones in the context of delineating the alteration halos related to mineralization zones. SAM classifier images portrayed at least ten sites as highly probable alteration mineralization zones, in a belt of meta volcano-sedimentary and andesite rock in the south, central and north part of the study area. Also all these alteration zones are controlled by the two major structures in the study area which are Oko shear zone and Nakaseib suture zone. However, this study revealed that the results of mineral prospecting investigations obtained from ASTER data are more superior than those obtained from Landsat 8 OLI data, as the former is characterized by a higher spectral resolution and therefore, has good capability in distinguishing the spectral signatures of the indicator minerals and in the delineation of the alteration halos related to mineralization zones. Spatial analysis techniques have been applied for stream sediment samples, where cluster and outlier analysis and hot spot analysis have been used to verify the alteration zones. In the results of this analysis, gold shows hot spots clustering in the central part of the study area (Ribda and Hashai), south part (Shulai and Ayrite), west part (Bahadna), north west part (Amur) and north east part (Derbuykwan). These areas match well with the alteration zones that have been mapped by using remote sensing techniques. Eventually, 200 rock samples have been taken in the study area from different facies. The majority of the sample give a positive result which indicate that most of the alteration zones contain gold.