TY - JOUR
T1 - Integrated GIS-based modelling for the quantitative prediction of magmatic Ti-V-Fe deposits
T2 - A case study in the Panzhihua-Xichang area of southwest China
AU - Cong, Yuan
AU - Dong, Qingji
AU - Bagas, Leon
AU - Xiao, Keyan
AU - Wang, Kun
PY - 2017/12/1
Y1 - 2017/12/1
N2 - The estimation of undiscovered mineral resources is an important part in the potential value of a mineral field and its long-term use. This manuscript documents six procedures for estimating the volume of potential mineral resources in an area that is based on integrated geological information forming part of a metallogenic model. The technique for this methodology includes: (1) the development a metallogenic model or models for mineral deposits in the study area; (2) the integration of the characteristics of known mineral anomalies with geology, geochemistry and geophysics to establish a predictive model for mineralization; (3) the definition of possible mineral resources incorporating predictive models with characteristic analyses, the knowledge-driven Delphi method, and magnetic anomalies; (4) calculate the parameters for the quantitative prediction, areas of known mineral deposits and their estimated dip extension, ore‐bearing coefficients, and their similarity coefficients based on explored ore-deposits in the area studied; (5) complete quantitative predictions using an synthetic volumetric equation; and (6) assess zones that are considered prospective for mineral resources. The procedure is tested for magmatic Ti-V-Fe resources in a known mineralized zone in the Sichuan Province of China.
AB - The estimation of undiscovered mineral resources is an important part in the potential value of a mineral field and its long-term use. This manuscript documents six procedures for estimating the volume of potential mineral resources in an area that is based on integrated geological information forming part of a metallogenic model. The technique for this methodology includes: (1) the development a metallogenic model or models for mineral deposits in the study area; (2) the integration of the characteristics of known mineral anomalies with geology, geochemistry and geophysics to establish a predictive model for mineralization; (3) the definition of possible mineral resources incorporating predictive models with characteristic analyses, the knowledge-driven Delphi method, and magnetic anomalies; (4) calculate the parameters for the quantitative prediction, areas of known mineral deposits and their estimated dip extension, ore‐bearing coefficients, and their similarity coefficients based on explored ore-deposits in the area studied; (5) complete quantitative predictions using an synthetic volumetric equation; and (6) assess zones that are considered prospective for mineral resources. The procedure is tested for magmatic Ti-V-Fe resources in a known mineralized zone in the Sichuan Province of China.
KW - Geo-information integration modelling
KW - Magmatic deposits
KW - Ore-bearing geological body
KW - Quantitative prediction
KW - Synthetic volume method
UR - http://www.scopus.com/inward/record.url?scp=85031420903&partnerID=8YFLogxK
U2 - 10.1016/j.oregeorev.2017.09.016
DO - 10.1016/j.oregeorev.2017.09.016
M3 - Article
AN - SCOPUS:85031420903
SN - 0169-1368
VL - 91
SP - 1102
EP - 1118
JO - Ore Geology Reviews
JF - Ore Geology Reviews
ER -