Conventional mine planning approaches use an estimated orebody model as input to generate optimal production schedules. The smoothing effect of some geostatistical estimation methods cause most of the mine plans and production forecasts to be unrealistic and incomplete. With the development of simulation methods, the risks from grade uncertainty in ore reserves can be measured and managed through a set of equally probable orebody realizations. In order to incorporate grade uncertainty into the strategic mine plan, a stochastic mixed integer programming (SMIP) formulation is presented to optimize an underground cut-and-fill mining production schedule. The objective function of the SMIP model is to maximize the net present value (NPV) of the mining project and minimize the risk of deviation from the production targets. To demonstrate the applicability of the SMIP model, a case study on a cut-and-fill underground gold mining operation is implemented.

It is important that the strategic mine plan makes optimum use of available resources and provides continuous quality ore to drive sustainable mining and profitability. This requires the development of a well-integrated strategy of mining options for surface and/or underground mining and their interactions. Understanding the current tools and methodologies used in the mining industry for surface and underground mining options and transitions planning are essential to dealing with complex and deep-seated deposits that are amenable to both open pit and underground mining. In this study, extensive literature review and a gap analysis matrix are used to identify the limitations and opportunities for further research in surface-underground mining options and transitions optimization for comprehensive resource development planning.

The decision to exploit a mineral deposit that can be extracted by open pit and/or underground mining involves consideration of the following options: (a) independent open pit extraction; (b) independent underground extraction; (c) simultaneous open pit and underground (OPUG) extraction; (d) sequential OPUG extraction; and (e) combinations of (c) and (d). This paper investigates the extraction strategy for deposits using Mixed Integer Linear Programming (MILP) optimisation framework to maximise the net present value and determine the schedules for mining, processing, underground capital and operational developments, and 3D crown pillar position. The MILP framework is implemented for a gold deposit. The results showed a combined sequential and simultaneous open pit and underground (OPUG) mining with crown pillar as the optimal extraction option generating NPV that is 11% and 13% better than independent OP or UG mining, respectively.

A review of general optimization studies that have been proposed for underground mining shows that previous works lack flexibility, operability and practicality in relation to cut-and-fill mining production scheduling. This paper presents a robust mixed integer linear programming (MILP) formulation for underground cut-and-fill mining. The objective function of the model is to maximize the net present value (NPV) of the operation while meeting all mining and processing operational and technical constraints. The MILP model features stope development and extraction sequencing constraints, mining and processing tonnage fluctuation constraints, and extraction duration and active levels control constraints. These features make the model more practical and expandable. The MILP model is verified and validated with two case studies from an existing mine and the results are compared with the actual mining strategy. The comparison shows a 9% to 17% improved NPV in both case studies resulting from mining higher grades and processing less tonnes thereby generating a better cash flow.

The Birim River, one of the main tributaries of the Pra River is among the important freshwater bodies in Ghana which serves as a rich source for gold and diamond production in the country. Artisanal mining activities along river bodies promote continual introduction of wide range of contaminants (heavy metals) into these water bodies, and their toxicity poses great threat to the ecology as well as the environment. This study assesses the level of heavy metals (Cr, Fe, Ni, Zn, As, Cd, Hg and Pb) in the Birim River of Ghana. The concentrations of the heavy metals were determined by Atomic Absorption Spectrophotometer (AAS) and Inductively Coupled Plasma – Mass Spectrometer (ICP-MS). Heavy metals concentration were analysed in the dissolved, suspended mineral fractions, and sediment phases of the River. The result obtained showed that the Birim River is heavily polluted with heavy metals. Samples [Apapam (KB2), Ahwenease (KB3), Adadeatem (KB4), Adukrom (KB5), Akim (KA2), Abodom (KA3), Kade (KA4), Anweaso (KA10) and Kusi (KA11)] with high heavy metals concentrations are located in areas where small scale mining is dominant, indicating that the major contamination source in the water body is resulting from small scale mining activities. Heavy metals concentration measured as dissolved were lower than WHO standards with the exception of Fe. There are high accumulations of heavy metals in the suspended mineral fractions of the river. The sediments were also greatly polluted with heavy metal sinks.