Geological and trace element evidence for a marine sedimentary environment of deposition and biogenicity of 3.45 Ga stromatolitic carbonates in the Pilbara Craton, and support for a reducing Archaean ocean

Bedded carbonate rocks from the 3.45 Ga Warrawoona Group, Pilbara Craton, contain structures that have been regarded either as the oldest known stromatolites or as abiotic hydrothermal deposits. We present new field and petrological observations and high-precision REE + Y data from the carbonates in order to test the origin of the deposits. Trace element geochemistry from a number of laminated stromatolitic dolomite samples of the c. 3.40 Ga Strelley Pool Chert conclusively shows that they precipitated from anoxic seawater, probably in a very shallow environment consistent with previous sedimentological observations. Edge-wise conglomerates in troughs between stromatolites and widespread cross-stratification provide additional evidence of stromatolite construction, at least partly, from layers of particulate sediment, rather than solely from rigid crusts. Accumulation of particulate sediment on steep stromatolite sides in a high-energy environment suggests organic binding of the surface. Relative and absolute REE + Y contents are exactly comparable with Late Archaean microbial carbonates of widely agreed biological origin. Ankerite from a unit of bedded ankerite–chert couplets from near the top of the stratigraphically older (3.49 Ga) Dresser Formation, which immediately underlies wrinkly stromatolites with small, broad, low-amplitude domes, also precipitated from anoxic seawater. The REE + Y data of carbonates from the Strelley Pool Chert and Dresser Formation contrast strongly with those from siderite layers in a jasper–siderite–Fe-chlorite banded iron-formation from the base of the Panorama Formation (3.45 Ga), which is clearly hydrothermal in origin. The geochemical results, together with sedimentological data, strongly support: (1) deposition of Dresser Formation and Strelley Pool Chert carbonates from Archaean seawater, in part as particulate carbonate sediment; (2) biogenicity of the stromatolitic carbonates; (3) a reducing Archaean atmosphere; (4) ongoing extensive terrestrial erosion prior to ∼3.45 Ga.

Quantification of geological uncertainty and risk using stochastic simulation and applications in the coal mining industry

Stochastic simulation is a recognised tool for quantifying the spatial distribution of geological uncertainty and risk in earth science and engineering. Metals mining is an area where simulation technologies are extensively used; however, applications in the coal mining industry have been limited. This is particularly due to the lack of a systematic demonstration illustrating the capabilities these techniques have in problem solving in coal mining. This paper presents two broad and technically distinct areas of applications in coal mining. The first deals with the use of simulation in the quantification of uncertainty in coal seam attributes and risk assessment to assist coal resource classification, and drillhole spacing optimisation to meet pre-specified risk levels at a required confidence. The second application presents the use of stochastic simulation in the quantification of fault risk, an area of particular interest to underground coal mining, and documents the performance of the approach. The examples presented demonstrate the advantages and positive contribution stochastic simulation approaches bring to the coal mining industry

The effective management of geological risk in long-term production scheduling of open pit mines

Investment in mining projects, like most business investment, is susceptible to risk and uncertainty. The ability to effectively identify, assess and manage risk may enable strategic investments to be sheltered and operations to perform closer to their potential. In mining, geological uncertainty is seen as the major contributor to not meeting project expectations. The need to assess and manage geological risk for project valuation and decision-making translates to the need to assess and manage risk in any pertinent parameter of open pit design and production scheduling. This is achieved by taking geological uncertainty into account in the mine optimisation process. This thesis develops methods that enable geological uncertainty to be effectively modelled and the resulting risk in long-term production scheduling to be quantified and managed. One of the main accomplishments of this thesis is the development of a new, risk-based method for the optimisation of long-term production scheduling. In addition to maximising economic returns, the new method minimises the risk of deviating from production forecasts, given the understanding of the orebody. This ability represents a major advance in the risk management of open pit mining.