Citas bibligráficas
Vargas, O., (2017). Implementación del modelamiento en 3D y estimación de los recursos con métodos geoestadísticos mina Chipmo U.E.A. Orcopampa - CMBSAA [Tesis, Universidad Nacional de Ingeniería]. http://hdl.handle.net/20.500.14076/10129
Vargas, O., Implementación del modelamiento en 3D y estimación de los recursos con métodos geoestadísticos mina Chipmo U.E.A. Orcopampa - CMBSAA [Tesis]. : Universidad Nacional de Ingeniería; 2017. http://hdl.handle.net/20.500.14076/10129
@misc{sunedu/3922910,
title = "Implementación del modelamiento en 3D y estimación de los recursos con métodos geoestadísticos mina Chipmo U.E.A. Orcopampa - CMBSAA",
author = "Vargas Machuca Bueno, Octavio Benigno",
publisher = "Universidad Nacional de Ingeniería",
year = "2017"
}
The Chipmo ore deposit is located in the District of Orcopampa, 350 km from the city of Arequipa. It is an intermediate sulfidation vein-hosted gold deposit, dating approximately to 18Ma (Noble, 1998). The mineralization is hosted within andesitic and rhyolitic rocks belonging to the Sarpane Volcanic rocks dating to 19 Ma (Swanson, 2002), which is correlated with the Tacaza Group in Southern Peru. The work has been developed and divided into three stages: 1) database, 2) modelling by Leapfrog 3D geological software, and 3) resource estimation by Vulcan mining software. Compañia de Minas Buenaventura S.A.A. stays at the forefront of technological innovations. If we look back to the '80s and early' 90s, resources calculations were made manually and with the help of calculators. In the mid- 1990s, the Lotus123 software were begun to be used to calculate resources. At the end of the decade of the '90s, resources calculation was made by Autocad and Excel softwares. At the beginning of the new millennium, the software Gemcom (later Gems and now Geovia) was used by Compañia de Minas Buenaventura S.A.A to calculate the ore grade average, which is an inaccurate and very geometric method, which neither takes into consideration the phenomenon of mineralized structure, nor provides the error associated with the estimation. In general terms, these methods have an infamous problem known as conditional bias of geostatistical simulation for estimation of recoverable reserves, which in practice means an overestimation of high ore grades and underestimation of low ore grades; therefore Compañia de Minas Buenaventura S.A.A. makes the decision to implement 3D modeling and resources estimation by geostatistical methods used for mineral evaluation. Geological modeling applied in currrent mining is defined by various geological controls, such as geomodels, which are currently used for explorating new mineralized zones, interpretating the mineralization and fluid flow, resource estimation, reserve estimation and short-, medium- and long-terms mine planning. These geomodels are constructed based on mining sampling, geological sections as a result of geological logging interpretation, geological mapping of levels, sublevels and ore passes, and other geological controls. The modeling of geological structures was made by using the Leapfrog software implicit modeling tools. The database modeling considers the chemical analysis (assays) of mining channels and diamond drilling. In addition, core samples logging, geological mapping of underground mine, underground mine topography, as well as plants and geological sections interpreted by those people responsible for each zone, were used. The block model is designed by zones (Nazareno and Prometida) and the block dimensions are 3 m (azimuth) x 1.5 m (vein width) x 3 m (height) and the composite width is 1.5 m. The estimation of the elements such as Gold (Au) (ppm), Silver (Ag) (ppm) was made. The estimation domains were generated for each element according to the stationarity conditions. Each element and each domain: Outlier / Capping were evaluated in order to define a high ore grade domain, variogram, estimation parameter studies, visual validation, global validation and local validation or Swath Plot. Vulcan © software - Version 10.0, Snowden Supervisor - © Version 8.4 and SGeMS software was used for resource estimation. The ore reserve estimation methods are Ordinary Kriging (OK), Inverse Distance (ID) and Nearest Neighbor (NN), the first two methods will be used to report resources and categorize them, and the NN by its characteristics will be used to validate the interpolation of the OK and ID methods. In mining there are different criteria being used for categorization of geological resources, some are more effective than others, but they all are based on the information reliability. Some companies consider that in order to resources to be categorized as measured, one minimum composite should be within the block; while other companies consider composites and mining development should be included, among other alternatives. For this first stage of the implementation the anisotropic distance as well as the amount of composites are being considered to denominate each type of resource as Measured, Indicated and Inferred. The final result will allow obtaining a better geological interpretation and a greater degree of certainty for planning mining operations.
Este ítem está sujeto a una licencia Creative Commons Licencia Creative Commons