Design in Mineral Resources exploitation with computer usage

PART A: Introduction- Historical development and contribution of computers in the mining industry. Financial cost calculations - income. Stages open-air farm design. Maps, drilling, geological information. Ad - processed drilling data, calculation of complex samples. Calculation of basic statistical figures, calculation variogrammatos. Geometrical inventory calculation methods. Development of digital models of the deposit and honors by the method of inverse distance (ID) with the method Krigging. Geometric elements of outdoor farms. Defining the limits of an operation with financial benchmarks Method mobile cone-Method Lerch Grossman. Production planning. Apply to deposit Cu disseminated mineralization. PART B: Methodology evaluation elements layered exploration drilling, drilling strata evaluation rules calculation of the qualitative characteristics of recoverable layers, modeling ore reserves calculation and quality. PART C: Application of artificial neural networks to stock assessment and quality deposits.

Objectives

Engineer studying digital models for the estimation of the deposit through the statistical analysis of data derived from sampling, as well as is in contact with computer models and algorithms that developed to optimize the exploitation in economic net present value terms.

Prerequisites

Geostatistics

Syllabus

1. Introduction  2. Financial information  2.1 Economic indicators  2.2 costing data - revenues 3. open-air farm design stage  3.1 Introduction  3.2 Maps, drilling, geological information  3.3 Ad - processed drilling data  3.4 Calculation of complex samples  3.5 Geometrical inventory calculation methods  3.6 Development of digital models of the deposit  3.6.1. Yield values ​​with the method of inverse Distance (ID)  3.6.2. Method Krigging  3.6.2.1 Calculation of basic statistical figures  3.6.2.2 Calculation variogrammatos 4. Geometric outdoor elements holdings  5. Determining the limits of a exploitation by financial criteria  5.1. Method mobile cone  6. Production planning  6.1. Generally  6.2. Prepare production schedule PART B:  8. Methodology drilling data evaluation lignite deposits  8.1 Basic definitions and concepts: Natural lignite, technical recoverable lignite, lignite exploitation, lignite Power  8.2 Methodology evaluation lignite deposits  8.2.1 Valuation rules lignite layers drilling  8.2.2 Calculation of qualitative characteristics recoverable lignite layer  8.2.3 deposit modeling PART C: Application of artificial neural networks to solving problems related to outdoor design holdings  1. Introduction  2. Neural networks  3. Development of neural network for calculating parameters farm  3.1 Presentation-analysis of the problem  3.2 Developing neural network  3.3 Training of the neural network  3.4 Assurance Testing  4. Application of neural network to calculate operating parameters-compared to other methods  5. Conclusions