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A new mine planning optimisation software tool called Blasor has been developed and implemented at BHP Billiton’s Yandi Joint Venture operation in the Pilbara. Blasor is specifically configured for designing and optimising the long-term pit development plan for the multi-pit blended-ore operation at Yandi. It is used for optimal design of the ultimate pits and the mining phases contained within those pits. In designing the mining phases, Blasor ensures that all market tonnage, grade and impurity constraints are observed whilst maximising the nett discounted cash flow (DCF) of the joint venture operation.

The value of a mining project is based upon a quantitative model of material of value in the ground, a block model of the deposit, and a schedule for extracting this material including relevant revenues and costs. The schedule usually attempts to maximise the net present value (NPV) of the project over the life of the mine. Frequently, a block model is the result of a smooth interpolation, such as kriging, of data collected from holes drilled throughout the orebody. More drill holes will lead to greater certainty in the contents of block models and from these ‘more accurate’ block models, schedules of greater ultimate value may be realised. We discuss how conditional simulations can assist with rigorously valuing the trade-off between the cost of extra drilling and the schedules of greater value that may be constructed from the resultant block models of greater accuracy.

BHP Billiton commenced exploration surveying with the world's first fully operational, airborne gravity gradiometer in October 1999. This gradiometer (called Einstein), together with a later one called Newton, was developed in conjunction with Lockheed Martin by BHP Billiton's FALCON project. FALCON data are acquired by Sander Geophysics Ltd., flying a Cessna Grand Caravan to survey specifications typical of aeromagnetic surveys. The first FALCON survey was flown over a portion of the Bathurst mining camp in New Brunswick, Canada in order to compare system performance with existing extensive and detailed ground-gravity data. The ground-gravity data, supplied courtesy of Noranda Minerals Exploration Ltd., were upward continued to the flying height and vertically differentiated to provide vertical gravity gradient data suitable for comparison with the airborne data. The two data sets compare very well and the results demonstrate that the FALCON airborne gravity gradiometer is capable of detecting sources with a vertical gravity gradient signal of greater than 10 Eo and a full-width at half-maximum amplitude of 500 m.

In processing and interpreting the data collected during FALCON airborne gravity gradiometry surveys it is necessary to carefully compensate for topographic features. So that surveys may be performed even in areas where accurate DEMs (Digital Elevation Maps) are unavailable, the FALCON aircraft have been fitted with laser scanners, providing ground return data across a sufficiently wide swathe so that very adequate DEMs over the whole survey area can be produced. Additionally, in one aircraft, a laser profilometer has been fitted adjacent to the scanner, providing independent data to monitor the scanner integrity throughout a survey. This paper briefly describes the scanner features and details the post processing of the scanner ground returns through to gridded DEM format. The intrinsic accuracy of the scanner at low scan angles is demonstrated to be very good, accounting for a ground height error of less than 0.1m standard deviation. Taking into account that DGPS height errors are about 0.15m, the resulting ground height error is estimated as 0.2m standard deviation, which is confirmed by the analysis of height differences in the overlapping areas between adjacent lines. This estimate is characteristic of a lightly vegetated terrain. This level of topographic error will have a negligible impact on our ability to identify target anomalies arising from geological variations.

In this paper we show that the problem of optimal mine planning can be cast in the framework of receding horizon control. Traditional formulations of this problem have cast it in the framework of mixed integer linear programming. In this paper, we present an alternative formulation of the mine planning problem using the ''language'' of control engineering. We show that this alternative formulation gives rise to new insights which have the potential to lead to improved computational procedures. The advantages are illustrated by an example incorporating many practical features of an actual mine planning problem.

Traditionally the process of mine development, pit design and long-term scheduling is based on a single deterministic orebody model built by the interpolation of drill hole data using some form of spatial interpolation procedure, e.g. kriging. Typical steps in mine design would include the determination of the ultimate pit, the development of a number of mining phases (pushbacks) and then the development of a life-of-mine schedule. All of these steps would have the aim of maximising the mine’s net present value (NPV), along with meeting numerous other business and physical constraints. There are a number of software packages commercially available and widely used in the mining industry that deal with some or all of these issues. The methods employed by all of these packages treat the process described above in a strictly deterministic way. In reality, given the sparse drill hole data, there is usually significant and variable uncertainty associated with a single or unique deterministic block model. This uncertainty is not captured or used in the planning process. This paper describes work undertaken by the Exploration and Mining Technology Group within BHP Billiton to develop a new mathematical algorithm for mine optimisation under orebody uncertainty. This uncertainty is expressed as a number of conditionally simulated orebody models. This optimisation algorithm is implemented in a new software package. The software uses a number of proprietary algorithms along with the commercially available mixed integer-programming package ILOG CPLEX. The development targets all phases of mine optimisation, including the NPV optimal block extraction sequence, pushback design, and simultaneous cut-off grade and mining schedule optimisation.