Bitumen content estimation of Athabasca oil sand from broad band infrared reflectance spectra

Abstract

AbstractOil sand is a mixture of quartz grains, clay minerals, bitumen, water, and minor accessory minerals. There is a need in oil sands mining operations for a robust method to estimate total bitumen content in real time; and so modelling of the total bitumen content (TBC) in Athabasca oil sands of Western Canada was undertaken on the basis of hyperspectral reflectance spectra. A selection of different bitumen, water, and clay mineral spectral features (3.0–30.0 µm) was used to develop broad‐band TBC predictive models that have good accuracy, with less than 1.5% error with respect to laboratory methods of bitumen assay. These models are also robust, in that they are independent of mine location. Simple broad band models, based upon previously identified Gaussian features or wavelet features, provide an incremental improvement over the currently deployed industry two‐band ratio model. An improved two‐band model was also developed, which makes use of a combination of the same two bands but normalised to their mean. A wavelet‐based, broad‐band model comprised of indices and five bands, where the bands are normalised to the mean of the bands, adequately addresses the influence of water, clay, and textural variation on selected bitumen features. This five‐band model appears to produce the most robust estimator of TBC, with a dispersion of ∼1.1–1.5%, which can be applied to different sites within a mine and to different mines without additional tuning or calibration, as evidenced by regression slopes of 0.99–1.0 for modelling, validation, and blind data sets.