A Monte Carlo Simulation-based algorithm for updating Combined Variance cost function in optimally locating additional drillholes

Soltani-Mohammadi S., Sohrabian B., Safa M., TERCAN A. E.

INTERNATIONAL JOURNAL OF MINING RECLAMATION AND ENVIRONMENT, cilt.36, ss.305-322, 2022 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 36
  • Basım Tarihi: 2022
  • Doi Numarası: 10.1080/17480930.2022.2036558
  • Dergi Adı: INTERNATIONAL JOURNAL OF MINING RECLAMATION AND ENVIRONMENT
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, Agricultural & Environmental Science Database, Applied Science & Technology Source, Compendex, Computer & Applied Sciences, Environment Index, Geobase, Greenfile, INSPEC, Pollution Abstracts
  • Sayfa Sayıları: ss.305-322
  • Anahtar Kelimeler: Particle swarm optimisation, uncertainty, boreholes, combined variance, cokriging, PARTICLE SWARM OPTIMIZATION, GENETIC ALGORITHM
  • Hacettepe Üniversitesi Adresli: Evet

Özet

Optimally locating additional boreholes in the boundaries of ore deposits is an important problem in mining projects. To solve this problem, combined variance has been proposed as a cost function to be minimized. An issue about combined variance is its dependence on the value of variable at unknown location. This value is achieved through a round-based algorithm that estimates the probability of occurrence of ore and rounds it to the nearest integer without considering all scenarios. This study aims to consider all scenarios using a Monte Carlo simulation-based algorithm. This approach uses ordinary cokriging to estimate the probability of occurrence of ore at unknown locations. Then, the estimated probabilities are entered into a Monte Carlo simulation procedure to generate various realizations. The method was applied in the Chadormalu ore deposit to propose ten additional boreholes. The round-based algorithm proposed additional drill holes in the middle of ore-intersected and non-intersected initial drill holes. However, the Monte Carlo-based algorithm is sensitive to the thickness such that in boundaries with thicker ore, the additional boreholes are suggested farther away from the ore-intersected drill holes and closer to the non-intersected ones and vice versa.