Synthetic Analysis Of Multivariate Geological Information And Ore Prediction Of Southern Region Of Peru

Along with the progress of geology as well as the increase of prospecting difficulties, the traditional prospecting methods have been replaced by high-tech methods. Meanwhile, the latest prospecting theory and modern information systems are playing a more and more important role in prospecting works. Taking the mineral resource reconnaissance and the prospecting forecast as goals, modern prospecting methods can use the data of mineral resources, remote sensing, geophysical and geochemical exploration to perform information extraction, integration and analysis, in order to pick out the zones with best anomalies and thereon define the prospective mineralized area.In this paper, southern Peru is taken as the research area where the exploration data have been collected. These data include that of geological minerals, remote sensing, the stream sediments and aeromagnetic survying, and so on. Information extraction, integration and analysis are carried out on the data, and an effective method is provided for informational searching and forecasting mineral deposits. Specific research works include:Multivariate geological data's information extraction technique, format transformation and conformity, data fusion processing, GIS spatial analysis technology and comprehensive information quota forecast of conditional probability model of the amount of information, etc.The following are the primary achievements in this paper:1. Remote sensing images of southern Peru were processed by means of principal components analysis and ratio transformation, so as to extract the alteration information related to metalliferous mineralization. Various data processing methods were employed to process the system sediments data to delineate geochemical anomalies. By carrying out extremely, analytic continuation processing on the aeromagnetic data, aeromagnetic anomaly information was extracted, then, according to the anomaly information, lithological character, rock mass were defined and faulted structure of the research area was inferred.2. Based on origin and spatial relevance of the multivariate geological information, fusion processing of the remote sensing data, geochemical anomaly data, and the aeromagnetic anomaly data were carried out using the multivariate geological data fusion method, and different multivariate geological data fusion processing methods were summarized.3. Using GIS spatial analysis techniques, the correlation among regional stratum, mineral type, intrusive rock, faulted structure, remote sensed alteration anomaly, geochemical anomaly and aeromagnetic anomaly was analyzed, and the connection of metalliferous mineralization and the above variables was concluded.4. Through the analysis of ore prospecting advantage of multivariate geological information, the geologic variables favorable for comprehensive assessment was screened out to build information content conditional probability synthesis forecast quantification model, using the overall analysis results in this paper, mineral forecasting were performed in southern region of Peru. By drawing up the information content chronogram, prospecting targets were delineated, which laid a solid foundation for further ore prospecting in the region.