The Value of Automated Mineralogy
Over many years, the easy-to-find ores, oil and gas have been recovered. Today, mining and oil & gas companies spend substantial time and money analyzing rocks to predict the location, amount and
recoverability of the harder-to-find resources.
Return on investment hinges upon the accuracy of these predictions. Resource recovery is a high-risk/high-return endeavor based in large part on understanding rocks and their mineral chemistry, crystal structure, physical and optical properties, and the processes of their origin, formation, and geographical distribution.
Mining companies study ore to predict the feasibility of mining in a given area and to optimize grinding processes at existing mines—some encapsulating minerals require far more grinding to liberate the value mineral. The grinding costs can make mining economically infeasible at locations with high concentrations of these minerals. At other locations with different encapsulating minerals, too much grinding can waste large amounts of the value mineral.
Oil & gas companies analyze organic-rich rocks as possible sources of hydrocarbons that expel into reservoirs in porous and permeable rock. Analyzing porosity indicates the potential volume, while permeability indicates how easily the hydrocarbons can flow out of the reservoir. Further analyses of seal and trap formations determine if the hydrocarbons will remain in the subsurface or escape and be lost. In addition, understanding the thermal history of the source rock can point to the amount and timing of hydrocarbon generation and expulsion, and analyzing how hydrocarbons move from source to reservoir can help quantify the source of hydrocarbons in a particular area.
Mineralogy methods used by mining and oil & gas companies often depend upon subjective interpretations by highly-trained specialists. For example, optical microscopists examine ore particles and oil drill cuttings for color and texture variations. These variations can reveal chemical and mineral properties that indicate the location, amount and recoverability of the resource. But the subjectivity of the analysis impacts the accuracy of the predictions, contributing to the risks of the resource recovery business.
Automated mineralogy solutions improve return on investment with objective, quantitative answers. Direct calculations from the rock—chemical, mineral, textural and physical properties—eliminate guesswork. More sampling points improve texture definition, leading to digital images that are geologically accurate for both simple and highly complex rock textures. The images are reliable and amenable to extraction of key mineral, textural, chemical, and physical parameters, without manual intervention.