TY - THES

T1 - Stochastic approach to address and measure grade uncertainty in mining operation for decision making in short term planning

AU - Saldana Larrea, Tony Sadah

N1 - no embargo

PY - 2022

Y1 - 2022

N2 - The grade uncertainty is one of the critical aspects that could determine the viability of a mining operation, especially in underground mines. The mining planning uses as input the geological block model usually estimated by the kriging technique, which is the most widely method used to develop the block model. Nevertheless, the smoothing effect generates deviations in ore grade reserves, which produce deviations between planned and executed ore grades. The present work will explain a suitable proposal to overcome the grade uncertainty in mining operations and define a short-term production planning using geostatistical simulation as well as a metaheuristic approach. The first chapter explains the main problems generated by geological uncertainty in an underground mine operation as well as the proposed solution. The second chapter defines the general concepts for the stochastic mine planning required to be able to understand the different theories used to estimate, simulate and optimize the block models. The third chapter exemplifies the methodology followed to be able to develop a method to generates a short-term production plan considering geological uncertainty. Furthermore, will be detailed the new heuristic approach developed to be able to define a mining extraction scheduling in a short time for the "room and pillar" mining method. The fourth chapter presents the implementation and execution of the project itself in a controlled environment, developing, assessing, valuating and classifying a set of different equiprobable block models, to subsequently develop the short-term production program. It was shown that the kriging estimate had a “high” geological risk and a “moderate” economic potential, so it was chosen among 50 realizations, to work with simulation 19, which had a “low” geological risk and a “high” economic potential. The fifth and sixth chapters refer to the discussion of the results obtained in each step and the conclusions achieved.

AB - The grade uncertainty is one of the critical aspects that could determine the viability of a mining operation, especially in underground mines. The mining planning uses as input the geological block model usually estimated by the kriging technique, which is the most widely method used to develop the block model. Nevertheless, the smoothing effect generates deviations in ore grade reserves, which produce deviations between planned and executed ore grades. The present work will explain a suitable proposal to overcome the grade uncertainty in mining operations and define a short-term production planning using geostatistical simulation as well as a metaheuristic approach. The first chapter explains the main problems generated by geological uncertainty in an underground mine operation as well as the proposed solution. The second chapter defines the general concepts for the stochastic mine planning required to be able to understand the different theories used to estimate, simulate and optimize the block models. The third chapter exemplifies the methodology followed to be able to develop a method to generates a short-term production plan considering geological uncertainty. Furthermore, will be detailed the new heuristic approach developed to be able to define a mining extraction scheduling in a short time for the "room and pillar" mining method. The fourth chapter presents the implementation and execution of the project itself in a controlled environment, developing, assessing, valuating and classifying a set of different equiprobable block models, to subsequently develop the short-term production program. It was shown that the kriging estimate had a “high” geological risk and a “moderate” economic potential, so it was chosen among 50 realizations, to work with simulation 19, which had a “low” geological risk and a “high” economic potential. The fifth and sixth chapters refer to the discussion of the results obtained in each step and the conclusions achieved.

KW - Erzgehalt Unsicherheit

KW - geostatistische Simulation

KW - kurzfristige Planung

KW - stochastische Planung

KW - metaheuristik

KW - grade uncertainty

KW - geostatistical simulation

KW - short term planning

KW - stochastic planning

KW - metaheuristic

M3 - Master's Thesis

ER -