Abstract
The automated classification of acid rock drainage (ARD) potential developed in this study is based on a manual ARD Index (ARDI) logging code. Several components of the ARDI require accurate identification of sulfide minerals that hyperspectral drill core scanning technologies cannot yet report. To overcome this, a new methodology was developed that uses red–green–blue (RGB) true color images generated by Corescan® to determine the presence or absence of sulfides using supervised classification. The output images were then recombined with Corescan® visible to near infrared-shortwave infrared (VNIR-SWIR) mineral classifications to obtain information that allowed an automated ARDI (A-ARDI) assessment to be performed. To test this, A-ARDI estimations and the resulting acid-forming potential classifications for 22 drill core samples obtained from a porphyry Cu–Au deposit were compared to ARDI classifications made from manual observations and geochemical and mineralogical analyses. Results indicated overall agreement between automated and manual ARD potential classifications and those from geochemical and mineralogical analyses. Major differences between manual and automated ARDI results were a function of differences in estimates of sulfide and neutralizer mineral concentrations, likely due to the subjective nature of manual estimates of mineral content and automated classification image resolution limitations. The automated approach presented here for the classification of ARD potential offers rapid and repeatable outcomes that complement manual and analyses derived classifications. Methods for automated ARD classification from digital drill core data represent a step-change for geoenvironmental management practices in the mining industry.
Highlights
Accurate classification of the acid forming potential of waste rock is vital to ensure the appropriate management of potential environmental hazards associated with mining operations [1]
One potential hazard is the generation of acid rock drainage (ARD), which forms when iron-sulfide minerals contained in mine waste materials are exposed to oxygen and water and aided by bacterial catalysis (e.g., Acidithiobacillus ferrooxidans, Acidithiobacillus thiooxidans, Leptospirillum ferrooxidans), undergo oxidation to produce acid, metals and sulfate as shown in Equations (1)–(3) [1,2]: FeS2 + 7/2O2 + H2 O → Fe2+ + 2SO4 2− + 2H+
These were chosen as they represent a range of mineralization, texture and alteration characteristics allowing for robust assessment of A-ARD Index (ARDI)-based classifications
Summary
Accurate classification of the acid forming potential of waste rock is vital to ensure the appropriate management of potential environmental hazards associated with mining operations [1]. Whilst other minerals (e.g., sulfates) can produce acid in a mine waste environment (e.g., Equation (4) where M is Al3+ or Fe3+ for alunite and jarosite, respectively), the traditional focus in a mine waste characterization program is on iron-sulfides. This is because there is a shorter lag-time to acid generation and they typically dominate the acid forming mineralogy. Australia [6], Iron Mountain mine, United States [7,8,9]).
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
