
TY  - JOUR
A1  - Hope, Matthew 
A1  - Bourne, Barry 
A1  - Crosato, Simon 
A1  - Howe, Brendan 
A1  - Holden, Eun-Jung 
A1  - Ching Fu, Shih 
A1  - Kovesi, Peter 
T1  - Application of automated detection techniques in magnetic data for identification of Cu-Au porphyries
JF  - ASEG Extended Abstracts
JO  - ASEG Extended Abstracts
Y1  - 2010
VL  - 2010
IS  - 1
SP  - 1
EP  - 6
KW  - 
UR  - https://doi.org/10.1071/ASEG2010AB137 
N2  - Automated shape recognition technology has been developed for application to porphyry exploration, through a joint research initiative between Barrick Gold and the Centre of Exploration Targeting at the University of Western Australia, commencing in 2009. The result is the Development of the Porphyry Texture Filter for application to magnetic datasets. Many mineralised porphyries display concentric zonation in their magnetic character as a by-product of extensive hydrothermal alteration systems and secondary magnetite development/destruction. This characteristic magnetic signature can be exploited by image processing techniques enabling the enhancement, identification and quantification of features. Features must agree with a user-defined set of criteria for size, shape and magnetic contrast. Development of the technique was carried out on the world class Reko Diq porphyry system resulting in successful identification of all major known mineralised porphyry centres and additional targets within the camp. User control over filter parameters has resulted in the successful application of the filter on projects in a range of geological and erosional environments. The ability to rapidly characterise porphyry-like signatures using mathematical principles and geometries results in an unbiased geophysical target layer. When integrated with other geoscientific data, the filter has consistently supported target generation activities. Examples of the Porphyry Texture Filter application and results from Reko Diq, Grasberg and active exploration projects are shown. 
ER  -

