Investigation and Use of Remote Sensing and Geophysical Methods to Potential Iron Ore- Northeast of Deh Chah-Fars

Document Type : Original Article

Author

Surveying Group, University of Bojnourd, Bojnourd, Iran

Abstract

Introduction: The Gravimetric method is an early exploration tool for minerals. In other areas, the use of this method has been developed from common applications such as mapping the bedrock structure to a wider range of applications, including the location of faults in the environment Sedimentary deposits, revealing hidden semiconductor associations, determining the position of salt domes in sedimentary environments with weak Gravity response, and finally, modeling the structures by means of a three-dimensional return of Gravimetric data.
Material and Methods: In this study, using first-order data from an ASTER sensor of type-1A, which was used in 2007, was first used by using remote sensing methods including spectral analysis of color combinations and band ratio with software The ENVI, which carried out the ASTER data, the alteration zones associated with iron Fe mineralization were identified in the region. In the next step, the geomorphic data of ground Gravimetric measurement in the study area has been used and has been applied to the processing and analysis of ground Gravity complete bougure data using Oasis Montaj software. Finally, with the simultaneous use of three major exploratory data, significant areas of iron ore mineralization have been identified and investigated within the study area.
Results and Discussion: The important iron ore reserves in this zone can be noted that the Gol-Gohar iron ore geological units Gol-Gohar iron ore schists, metamorphic sandstone, quartzite, and metamorphic masses are diabasic. The RGB color combination (123) has been processed on ASTER sensor data, and the interpretation of the studied area with respect to field geological information in the region is such that iron-metallurgical units are observed in dark blue. The color Composition (468) RGB was processed on ASTER sensor data, and the interpretation of the studied area is due to the field geological information in the region. Band Ratio is the image processing method that involves dividing a band into another band. The ratio (Band 5 + Band 7) / Band 6 was applied to the ASTER sensor data, as presented in the figure, bright pixels showing sericite, muscovite, Illite, and smectite minerals. As seen in all processed ASTER data, the anomalies of numbers A, B, C, and D differ from other geological units in the study region. Using methods of ground gravimetric processing, many methods were used to identify the sources. We were able to identify five anomalies under the ground that it is very important. Anomalies B’ related to two geological dikes with a lower depth than other anomalies. Anomalies A’, C’, D’ and E’ are much larger and longer. And they have an important source at high depths.
Conclusion: In this study, according to remote sensing studies and ground gravimetric studies, five anomalies have been discovered. In both methods, the results are consistent with each other. In fact, the anomalies A, B, C and D in the remote sensing method overlap with the anomalies A', B', C’, D' and E’ in the method of ground gravimetric. The most stable changes in the gravity field in all gravimetric analyzes are related to the A’ and C’ anomalies. The bonding method with a mathematical ratio of Band 3 / Band 1 and Band 5 / Band 4 ratio was also applied to ASTER sensor data. The ratio (Band 5 + Band 7) / Band 6 was applied to the ASTER sensor data, as presented in the figure, bright pixels showing sericite, muscovite, Illite, and smectite minerals. As seen in all processed ASTER data, the anomalies of numbers A, B, C, and D differ from other geological units in the study region. In the study area, we were able to identify four anomalies under the ground that it is very important. The geological structure of these anomalies is Northwest-South East. Anomalies A and anomalies B are related to two geological dikes with a lower depth than other anomalies. Anomalies C and anomalies D are much larger and longer. And they have an important source at high depths. According to the results of method Analytic Signal and method Vertical Derivative, we were able to identify the edges of these anomalies. In fact, the anomalies A, B, C and D in the remote sensing method overlap with the anomalies.

Keywords

References

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