hydrothermal alteration

The younger granites of Gabal Gattar area, Northern Eastern Desert of Egypt, host hydrothermal uranium mineralization at the northern segment of Gattar batholith and along its contacts with the oldest Hammamat sediments. The host rocks display many features of hydrothermal overprint results in changing their basic engineering characteristics as a function of variations of the degree of alteration. Progression from less altered to altered and mineralized rocks as the result of the alteration processes was assessed by the chemical index of alteration (CIA). The CIA numerical values were calculated by   the molecular proportion of Al to the cations Ca, Na, and K. The studied rocks were divided into five grades according to degree of alteration and strength properties including: fresh (AG-I), slightly altered (AG-II), moderately altered (AG-III), highly altered (AG-IV) and very highly altered (AG-V). The strength properties of the studied rock units correlated well with the alteration grades assigned to them. That is, as the grade increased from AG-I to AG-V, abrasion resistance and crushability index increased, whereas compressive strength, slake durability and impact strength decreased.

The Dehaj area, located in the southern part of the Urumieh-Dokhtar magmatic belt, is a well-endowed terrain hosting a number of world-class porphyry copper deposits. These deposits are all hosted in an acidic to intermediate volcano-plutonic sequence greatly affected by various types of the hydrothermal alterations, whether argillic, phyllic or propylitic. Although there are a handful of hitherto-discovered porphyry copper deposits in the area, the geological setting of the area suggests the possibility of finding further deposits. The recognition and delineation of the hydrothermal alterations can pave the way for the discovery of further potential zones that possibly host the porphyry copper deposits. The current work proposes a hybrid methodology applied to the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) imagery by combining the application of dimension reduction and fractal techniques to delineate the hydrothermally-altered zones In order to reduce the dimensionality of multi-band ASTER data, Robust Principal Component Analysis (RPCA) was employed to elicit the traces of hydrothermally-related mineral assemblages including illite, sericite, quartz, kaolinite, epidote, and chlorite. Highlighting the existence of the aforementioned minerals, the extracted components require interpretation, i.e. a boundary is required to constraint the hydrothermally affected zones from the rest of the geological units. In order to tackle such a challenge, the authors introduce the concept of value-pixel fractal technique for the extracted principal components. The Prediction-Area (P-A) plot is used for the validation, which shows that the identified alterations correlate with the mineralization. The results obtained are verified by a geological survey, where a number of samples are collected from the delineated zones. The samples are analyzed by the XRD techniques, finding that this work is successful in classifying the hydrothermally-altered zones.

This work applies support vector machine (SVM) algorithms in two versions of singular and general SVM classifiers to map hydrothermal alteration zones in the northwestern part of the Kerman Cenozoic Magmatic Arc (KCMA). Three visible bands and six SWIR bands of ASTER images were applied as inputs for SVM classifiers. The develosped algorithms were able to classify ASTER images into hydrothermal alteration or non-hydrothermal alteration classes. In singular SVM, nine classifiers were able to vote individually for every pixel in the image. Then, they were combined through integration rules to present a final decision about every pixel. The general SVM classifier integrated nine ASTER bands at the signal level to produce the final decision. The classification error rate showed that the general Gaussian RBF kernel-based SVM classifier had higher accuracy for the classification of hydrothermal alteration zones. The SVM results were then compared with other classified images based on band ratio and SAM methods. The main problem associated with these methods was that vegetation covering was highlighted as alteration zones while the SVM algorithm could solve this issue. Also, the verification of results, based on field and laboratory investigations, showed the SVM method to produce a more accurate map of alteration than that obtained from the band ratio and SAM.