Impact of grade distribution on the final pit limit definition

Abstract

Geologic modeling is an important step in determining the benefits and final pit dimensions for mining operations. Geostatistical models and distance-based functions are the main methods used to estimate the grade behavior. However, these two methods, despite their similar mean values, differ in spatial variability. The objective of this article is to prove, by comparing the two methodologies, that models with different spatial variability using the Lerchs-Grossmann algorithm will output subtly different final pit dimensions and scheduling. Furthermore, with the direct block schedule (DBS), these differences can be considerable. The tests compared the methodologies using the following three models: inverse distance (ID), ordinary kriging (OK) and turning bands simulation (TBS). The results demonstrate that the Lerchs-Grossmann algorithm is only slightly sensitive to the spatial variability of the grade; however, DBS requires the model populations to be better defined because of its greater sensitivity to spatial variability.

Fuel consumption efficiency regarding the road quality in the coal mine: a case study

“…Observation and data collection was carried out using a speedometer to determine the speed of the production unit operating on the road with grade criteria> 8% to obtain the time and distance travelled by the production unit in the road area [17]. The mine road design affects the pit limit conditions, so the grade determines the pit depth [18]. There is a relationship between the grade slope and the fuel consumption based on the number of 30 sample units operating in the area where the road slope exceeds the standard (Table 5).…”

“…With the unit condition with a maximum load of 166 tons and the effect of gravity, the resistance grade is 15.45% with a rolling resistance of 0.57%, so that the total resistance is 16.02%. In the Caterpillar Edition 46 Handbook, the total unit resistance specification of 16.02 is included in the high category [18].…”

Analysis of the impacts of slope angle variation on slope stability and NPV via two different final pit definition techniques

“…Treating uncertainties is one of the mainstream paths in recent mine planning studies. There are numerous research studies with different approaches to different sources of uncertainties, such as Burgarelli et al (2018), Carvalho et al (2018) and Ramazan and Dimitrakopoulos (2018). The first study presented the impact of market uncertainty by evaluating the influence of iron ore price simulation on mining sequencing using the DBS methodology; the second, compared models in terms of sensitivity to the spatial variability of the ore grades using both the LG algorithm and the DBS; and the later, integrated deposit variability and uncertainty directly in the production scheduling optimization process.…”