In Liberia, Mano has interests in 3 mineral licences with gold exploration activity. To date most exploration has focused on the 100,000 hectare license known as the Bea Mountain Mineral Development Agreement (BEA-MDA) in western Liberia. Mano has a 100% interest in the BEA-MDA license subject to a 10% free carried interest and a 3% royalty in favour of the Republic of Liberia. The MCA reconnaissance license (1,500,000 hectares) is held under a Mineral Cooperation Agreement (MCA) with the Republic of Liberia.

В Методических рекомендациях изложены общие положения, основные принципы, цели, задачи и методы геолого-экономической оценки и обоснования кондиций для подсчета запасов предварительно подетально разведуемых рудных месторождений.

The Cajon Borate Deposit lies within Bacanora Minerals Ltd’s Magdalena Basin Project area in the state of Sonora, Northern Mexico. The Magdalena project consists of 2 concession blocks covering a total of 15,508 hectares. The concessions are 100% owned by Bacanora’s Mexican subsidiary: Minera Sonora Borax S.A. de C.V., subject to a 3% royalty to a Rio Tinto subsidiary and a 3% gross over-riding royalty to Colin Orr-Ewing. The property is road accessible and located 17 kilometres east of the town of Magdalena de Kino and has excellent access from that centre, either by rail or truck, to local markets for borate or to overseas markets from the port at Guaymas. <...>

This report (the “Report”) was prepared for Lithium Americas Corp. (the “Company” or “LAC”) to document the methods and results of a Measured, Indicated and Inferred Resource Estimate on mineral claims held by the Company. The estimate applies to lithium and potassium contained in brine within the basin of the Olaroz and Cauchari Salars, two adjacent salt lakes in the Jujuy Province of northwestern Argentina. <...>

Mineral Resources and their subsequent conversion to Ore Reserves are of key importance to mining companies. Their reliable estimation is critical to both the confidence in a feasibility study, and also to the day-to-day operation of a mine. Together with sampling, assaying, geological and other errors introduced during interpretation and estimation, additional errors are likely to be introduced during the application of technical and economic parameters used for conversion of resources to reserves. There is thus a requirement for high-quality interpretation and estimation to be supported by high-quality data.

There are two main issues stemming from Vallée’s (2002) comments on Dominy et al. (2001b). First, he raises the importance of quality assurance/quality control (QA/QC) during resource estimation programs, and second, he indicates that the resolution and understanding of continuity (grade and geological) issues are paramount in the classification of resources. In particular, continuity is critical at the boundary between the Inferred and Indicated Mineral Resource categories.

The often complex, erratic, and localized nature of gold is a common feature of many vein-style gold deposits. This style of mineralization is often referred to as being nuggety or possessing a high-nugget effect. As a result of these complexities resource estimation is difficult and in general, only Exploration Results can be provided or an Inferred Mineral Resource estimated from surface drilling data alone. Underground development, further drilling, and probably bulk sampling will be required to delineate Indicated and Measured Resources.

Resource modelling is a complex process involving different specialists with relevant experience using a multi-disciplinary approach and the best available technology and reviews by independent auditors. The reliability of the final resource estimate is highly dependent on the quality control exercised at each stage of the process. At each step in the resource modelling process it is necessary to define the specific objectives, the methodology proposed to achieve those objectives and to establish a set of checks and validation tools to assess the effectiveness of the proposed methodology. Designation of responsibility and authority for meeting these objectives must also be clearly identified. External audits must also be incorporated to review and validate the implementation of new procedures.

Resource modelling is the basis for any economic appraisal of a mining project and includes a number of steps from data acquisition and validation to resource reporting, classification, and risk analysis

Техногенные месторождения - это скопления минеральных веществ, образовавшиеся в результате складирования отходов добычи полезных ископаемых (некондиционные руды, вскрышные и вмещающие породы), обогатительного (хвосты, шламы), металлургического (шлаки, золы, кеки) и других производств, качество и количество которых позволяет осуществлять их добычу и переработку на реальной экономической основе <...>