1409
Mineralogy as a Key Indicator for Coal Processing
Anelda van Staden
Teck Metals Ltd.—Technical Services, Trail, BC, Canada
Ievgenii Redka, Zijiang Yang, Maria Holuszko
Mining Engineering, University of British Columbia (UBC), Vancouver, BC, Canada
ABSTRACT: Steelmaking coal is used in about 72% of global steel production. Steel has an important role in
today’s society including building infrastructure but also contributes to clean energy projects and transportation
alternatives that are important building blocks as the world transitions to a low carbon economy A more detailed
understanding of steelmaking coal properties from operations located in south-eastern British Columbia (BC) is
important as these impact the final product and have a direct effect on the quality of the coke available for the
primary steelmaking process.
It is well known that ash content drives coal washability characteristics and this has historically been applied
in the calculations of a Washability Number, a parameter that represents the washing/cleaning characteristic of
coal. From the current study, it was found that this washability proxy does not always explain the less optimal
wash plant performance of some coal seams. This study explored this relationship to understand the factors
affecting coal washability and thus the quality of the processed coal.
A variety of techniques were used to characterize the coals including a Mineral Liberation Analyzer (MLA), an
X-ray Powder Diffractometer (XRPD), and a Micro-Fourier Transform Infra-Red (FTIR) spectrometer. Results
were compared against washability tests conducted on small samples and mineralogical data sets available for
a baseline seam that historically showed good plant performance. Findings demonstrated that the texture of a
coal in terms of the size and distribution of mineral matter (ash content) and macerals (coal content and lib-
eration) plays a fundamental role in producing a clean product from the raw coal and thereby its washability
performance. The mineral matter (ash) composition, primarily the presence of liberated clay minerals, impacts
the performance of the gravity separation units and flotation circuits. It was concluded that Micro-FTIR or a
machine-learning approach applied to XRD data sets can be used as a proxy for the identification of problematic
mineral phases at the exploration phase and could provide a predictive characterization of material ultimately
fed to the plant. Automated mineralogy techniques can be applied to a smaller subset of samples to gain textural
information and liberation potential.
Mineralogy as a Key Indicator for Coal Processing
Anelda van Staden
Teck Metals Ltd.—Technical Services, Trail, BC, Canada
Ievgenii Redka, Zijiang Yang, Maria Holuszko
Mining Engineering, University of British Columbia (UBC), Vancouver, BC, Canada
ABSTRACT: Steelmaking coal is used in about 72% of global steel production. Steel has an important role in
today’s society including building infrastructure but also contributes to clean energy projects and transportation
alternatives that are important building blocks as the world transitions to a low carbon economy A more detailed
understanding of steelmaking coal properties from operations located in south-eastern British Columbia (BC) is
important as these impact the final product and have a direct effect on the quality of the coke available for the
primary steelmaking process.
It is well known that ash content drives coal washability characteristics and this has historically been applied
in the calculations of a Washability Number, a parameter that represents the washing/cleaning characteristic of
coal. From the current study, it was found that this washability proxy does not always explain the less optimal
wash plant performance of some coal seams. This study explored this relationship to understand the factors
affecting coal washability and thus the quality of the processed coal.
A variety of techniques were used to characterize the coals including a Mineral Liberation Analyzer (MLA), an
X-ray Powder Diffractometer (XRPD), and a Micro-Fourier Transform Infra-Red (FTIR) spectrometer. Results
were compared against washability tests conducted on small samples and mineralogical data sets available for
a baseline seam that historically showed good plant performance. Findings demonstrated that the texture of a
coal in terms of the size and distribution of mineral matter (ash content) and macerals (coal content and lib-
eration) plays a fundamental role in producing a clean product from the raw coal and thereby its washability
performance. The mineral matter (ash) composition, primarily the presence of liberated clay minerals, impacts
the performance of the gravity separation units and flotation circuits. It was concluded that Micro-FTIR or a
machine-learning approach applied to XRD data sets can be used as a proxy for the identification of problematic
mineral phases at the exploration phase and could provide a predictive characterization of material ultimately
fed to the plant. Automated mineralogy techniques can be applied to a smaller subset of samples to gain textural
information and liberation potential.