A recently developed method, on the bases of “multifractal spectrum” filters for mineral exploration, is introduced in this paper. The “multifractal spectrum” filters, a group of irregularly shaped filters that a...A recently developed method, on the bases of “multifractal spectrum” filters for mineral exploration, is introduced in this paper. The “multifractal spectrum” filters, a group of irregularly shaped filters that are constructed on each processed datum, can be used to separate various types of geochemical and geophysical anomalies. The basic model, with an emphasis on the GIS based implementation and the application to the geochemical and geophysical data processing for mineral exploration in southern Nova Scotia, Canada, indicates its advantage in the separation of multiple anomalies from the background.展开更多
Observations made in different superlarge\|large gold deposits in Ailaoshan gold metallogenic belts, Yunnan Province, China, on the eastern margin of the Qingzang (Himalayas—Karakoram—Tibet) were investigated. Geote...Observations made in different superlarge\|large gold deposits in Ailaoshan gold metallogenic belts, Yunnan Province, China, on the eastern margin of the Qingzang (Himalayas—Karakoram—Tibet) were investigated. Geotectonically, the study area is situated in the conjoint between the Tethys and Himalayas tectonic domain, characterized by very complex geological structure, with strongly influenced by the Himalayas in late development.1\ Regional geology and gold deposits\;Ailaoshan gold metallogenic belts is localized between Ailaoshan super lithospheric faults and Jiujia—Anding brittle\|ductile shear zone, with NNW\|trending about 250km long. To southward, Zhenyuan supergiant gold deposits, Mojiang large gold deposits, and Daping giant gold deposits hosted in low metamorphic volcanic\|sedimentary rocks (D—C). Ore types include gold\|bearing quartz veins, gold\|bearing altered rocks, and the mixing of the two types. Most of gold orebodies took their positions in the substructures of the brittle\|ductile shear zone.展开更多
Constructing a statistical model that best fits the background is a key step in geochemical anomaly identification. But the model is hard to be constructed in situations where the sample population has unknown and/or ...Constructing a statistical model that best fits the background is a key step in geochemical anomaly identification. But the model is hard to be constructed in situations where the sample population has unknown and/or complex distribution. Isolation forest is an outlier detection approach that explicitly isolates anomaly samples rather than models the population distribution. It can extract multivariate anomalies from huge-sized high-dimensional data with unknown population distribution. For this reason,we tentatively applied the method to identify multivariate anomalies from the stream sediment survey data of the Lalingzaohuo district,an area with a complex geological setting,in Qinghai Province in China. The performance of the isolation forest algorithm in anomaly identification was compared with that of a continuous restricted Boltzmann machine. The results show that the isolation forest model performs superiorly to the continuous restricted Boltzmann machine in multivariate anomaly identification in terms of receiver operating characteristic curve,area under the curve,and data-processing efficiency. The anomalies identified by the isolation forest model occupy 19% of the study area and contain 82% of the known mineral deposits,whereas the anomalies identified by the continuous restricted Boltzmann machine occupy 35% of the study area and contain 88% of the known mineral deposits. It takes 4. 07 and 279. 36 seconds respectively handling the dataset using the two models. Therefore,isolation forest is a useful anomaly detection method that can quickly extract multivariate anomalies from geochemical exploration data.展开更多
文摘A recently developed method, on the bases of “multifractal spectrum” filters for mineral exploration, is introduced in this paper. The “multifractal spectrum” filters, a group of irregularly shaped filters that are constructed on each processed datum, can be used to separate various types of geochemical and geophysical anomalies. The basic model, with an emphasis on the GIS based implementation and the application to the geochemical and geophysical data processing for mineral exploration in southern Nova Scotia, Canada, indicates its advantage in the separation of multiple anomalies from the background.
文摘Observations made in different superlarge\|large gold deposits in Ailaoshan gold metallogenic belts, Yunnan Province, China, on the eastern margin of the Qingzang (Himalayas—Karakoram—Tibet) were investigated. Geotectonically, the study area is situated in the conjoint between the Tethys and Himalayas tectonic domain, characterized by very complex geological structure, with strongly influenced by the Himalayas in late development.1\ Regional geology and gold deposits\;Ailaoshan gold metallogenic belts is localized between Ailaoshan super lithospheric faults and Jiujia—Anding brittle\|ductile shear zone, with NNW\|trending about 250km long. To southward, Zhenyuan supergiant gold deposits, Mojiang large gold deposits, and Daping giant gold deposits hosted in low metamorphic volcanic\|sedimentary rocks (D—C). Ore types include gold\|bearing quartz veins, gold\|bearing altered rocks, and the mixing of the two types. Most of gold orebodies took their positions in the substructures of the brittle\|ductile shear zone.
基金Supported by projects of the National Natural Science Foundation of China(Nos.41272360,41472299,41672322)
文摘Constructing a statistical model that best fits the background is a key step in geochemical anomaly identification. But the model is hard to be constructed in situations where the sample population has unknown and/or complex distribution. Isolation forest is an outlier detection approach that explicitly isolates anomaly samples rather than models the population distribution. It can extract multivariate anomalies from huge-sized high-dimensional data with unknown population distribution. For this reason,we tentatively applied the method to identify multivariate anomalies from the stream sediment survey data of the Lalingzaohuo district,an area with a complex geological setting,in Qinghai Province in China. The performance of the isolation forest algorithm in anomaly identification was compared with that of a continuous restricted Boltzmann machine. The results show that the isolation forest model performs superiorly to the continuous restricted Boltzmann machine in multivariate anomaly identification in terms of receiver operating characteristic curve,area under the curve,and data-processing efficiency. The anomalies identified by the isolation forest model occupy 19% of the study area and contain 82% of the known mineral deposits,whereas the anomalies identified by the continuous restricted Boltzmann machine occupy 35% of the study area and contain 88% of the known mineral deposits. It takes 4. 07 and 279. 36 seconds respectively handling the dataset using the two models. Therefore,isolation forest is a useful anomaly detection method that can quickly extract multivariate anomalies from geochemical exploration data.
