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Estudio geoeconómico de formaciones yesíferas de la España peninsular con potencial de explotación minera para aplicaciones industriales

dc.contributor.advisorHerrero Fernández, María Josefa
dc.contributor.advisorBustillo Revuelta, Manuel
dc.contributor.authorEscavy Fernández, José Ignacio
dc.date.accessioned2023-06-19T16:46:27Z
dc.date.available2023-06-19T16:46:27Z
dc.date.defense2013-09-19
dc.date.issued2013-12-13
dc.descriptionTesis inédita presentada en la Universidad Complutense de Madrid, Facultad de Ciencias Geológicas, Departamento de Petrología y Geoquímica, leída el 19-09-2013.
dc.description.abstractThe spatial competition between industrial companies, both extractive and manufacturing, is one of the major research topics in both Industrial Organization and Regional Science. In general, the spatial competition models focus on location decisions, pricing and production levels, that one or more companies have to perform when they want to enter or are operating in a given geographic market. The main objective of these companies is to maximize profits by being more competitive on price and location than other companies operating in the market. Therefore, one of the decisions that recurrently appear in the daily life of an industrial company is whether to increase production and, if so, how to reach such an increase: increasing production of existing plants, building new factories, acquiring competitors, etc. If the chosen option is to increase production via the construction of new factories, automatically arises a question: which are the best geographical areas to locate the new facility or facilities?. Location of the facilities is a very important decision because it will define, in many cases, the profitability of the sites, which is primarily controlled by its relative position with respect to raw materials, clients and competitors. If the installation to be built is dependent on natural raw materials that lose a relevant portion of their weight during processing, such in the manufacture of cement, plaster, ceramic, etc. the optimal position of the system is affected by the existence of such mineral resource in the area. In such a case, it is required the combined analysis from different disciplines to obtain the best locations: geology, economics, operations research, marketing, etc. From a mining perspective, the selection of the area to explore is the essential step to carry out at any exploration project. Prospectivity studies are a useful tool for the selection and prioritization of areas to investigate. Carranza (2009) defines prospectivity as the possibility or probability of certain mineral deposits of the desired type to be present in a given area. Normally, this probability is calculated by modeling the prospectivity, which seeks, through the implementation of predictive maps, to outline the areas with the greatest potential to host the mineralized zones. The use of this tool helps to reduce costs and minimize risks, both technical and financial, associated with decision making in the mining industry (Porwal and Kreuzer, 2010). This technique is usually applied in prioritizing the areas to explore both at regional and local scales...
dc.description.departmentDepto. de Mineralogía y Petrología
dc.description.facultyFac. de Ciencias Geológicas
dc.description.refereedTRUE
dc.description.statusunpub
dc.eprint.idhttps://eprints.ucm.es/id/eprint/23926
dc.identifier.urihttps://hdl.handle.net/20.500.14352/38023
dc.language.isospa
dc.page.total201
dc.publication.placeMadrid
dc.publisherUniversidad Complutense de Madrid
dc.rights.accessRightsopen access
dc.subject.cdu553.635(460)(043.2)
dc.subject.keywordYeso
dc.subject.keywordyacimientos
dc.subject.ucmGeología
dc.subject.unesco2506 Geología
dc.titleEstudio geoeconómico de formaciones yesíferas de la España peninsular con potencial de explotación minera para aplicaciones industriales
dc.typedoctoral thesis
dspace.entity.typePublication
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relation.isAdvisorOfPublication1df6fcdd-8f4e-485a-a759-2f9e008d9db8
relation.isAdvisorOfPublication.latestForDiscoveryb75de162-8f05-4978-b0da-5d187dafd6d0

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