Project Info
Automated Core Scanning – Geochemical and Mineralogical Characterization and Visualization of the Subsurface
Katharina Pfaff
kpfaff@mines.edu
Thomas Monecke
tmonecke@mines.edu
Project Goals and Description:
Diamond drill core and drill cuttings represent the most important sources of subsurface geological information in the minerals and geothermal industries. Large amounts of drilling are typically conducted as projects advance from the early exploration to the production stage, with companies commonly expending several millions of dollars per year and project. Inconsistent or incorrect manual acquisition of information makes correlation between adjacent holes complicated or impossible. In many deposit types, intense hydrothermal alteration obliterates primary rock textures, adding significantly to uncertainty in manual logging by geologists. Many of the challenges in geological modeling can be overcome through the use of modern core scanning technology available at Mines (Center for Advanced Subsurface Earth Resource Models, CASERM). The CASERM member Minalyze AB is one of the world’s leading manufacturers of continuous X-ray fluorescence (XRF) core scanning technology. Their revolutionary core scanner allows rapid geochemical analysis of core in addition to imaging of the core and the measurement of the core topography. CASERM is currently developing a new hyperspectral core scanning system with the company Hyspex, a supplier for hyperspectral cameras. Hyperspectral sensing is a widely used and rapid technique to gain insights of the mineralogical composition of altered and unaltered rocks and is particularly useful in the identification of clay minerals. At present there has not been a single case study where geochemical and mineralogical scanning has been conducted on the same diamond drill core or rock cuttings. Devising a workflow that integrates geochemical and mineralogical data sets would be transformational in the mining and geothermal industry as it would allow rock and alteration type identification using machine learning techniques. The IMURF students (two are requested) will study drill core and drill cuttings from selected geothermal fields and scan the materials using the Minalyze core scanner to obtain images and topography data as well as co-registered geochemical information. The IMURF students will assist the research team in setting up the new Hyspex hyperspectral scanner and test hyperspectral imaging of the drill core and drill cuttings. This step will be supported by the hyperspectral experts at the U.S. Geological Survey. Once the new system is fully functional, the students will hyperspectrally image the same drill core and core cuttings previously investigated by XRF. This will allow the creation of two independent but co-registered geochemical and mineralogical data sets from the same core and drill cuttings. Subsequently, the student(s) will work with the measured data to provide co-registered data sets that can then be used for subsurface modeling and visualization endeavors. The deliverable at the end of the internship will be an optimized workflow and the availability of several co-registered data sets comprising geochemical, mineralogical, image, and topography data and the capability to visualize the subsurface.
The team (PIs Pfaff, Monecke, Duzgun, Tenorio and Li) has been working together through various stages of project development, preliminary data production and early proposal writing. The successful students will be mentored by faculty from Geology and Geological Engineering and Mining Engineering (PIs Pfaff, Monecke and Duzgun). PIs Pfaff and Monecke will introduce the students to mineral and materials characterization, including a background in XRF and hyperspectral methods and applications and will supervise the undergraduate research students in how to use the XRF and hyperspectral core scanners (including data acquisition, interpretation and exporting). PI Duzgun will supervise and guide students in remote sensing and hyperspectral data interpretation. PI Tenorio will guide the students in co-registration of heterogeneous datasets in preparation for full data integration and PI Li will help students interpret geophysical data obtained from the same drill core.
More Information:
Grand Challenge: Engineer the tools of scientific discovery.
Primary Contacts:
Katharina Pfaff, kpfaff@mines.edu
Thomas Monecke, tmonecke@mines.edu
Sebnem Duzgun, duzgun@mines.edu
Luis Tenorio, ltenorio@mines.edu
Yaoguo Li, ygli@mines.edu
Student Preparation
Qualifications
Students ideally would have a background in mining, geology and geological engineering, mathematics and statistics, or coding. Interest in the mining or geothermal industry would be preferable.
TIME COMMITMENT (HRS/WK)
5 hours per week
SKILLS/TECHNIQUES GAINED
The IMURF students will become familiar with state-of-the-art mineral and materials characterization methods and will learn how to visualize and model the subsurface in three dimensions. The laboratory facilities in the Department of Geology and Geological Engineering are equipped with a sample preparation facility, multiple microscopes, a field-emission scanning electron microscope, quantitative automated mineralogy systems, a mapping micro-XRF, hand-held XRF and hyperspectral systems, and XRF- and hyperspectral-core scanning systems. The students will be able to prepare and analyze sample materials and be involved in the data interpretation. XRF and hyperspectral methods techniques are widely used in a large variety of industries (geology, mining, food, environmental, disaster monitoring), given the successful students a clear advantage on the job market or graduate school applications over their peers.
- One student will take the lead on the mineralogy and geochemical characterization
- One student will take the lead subsurface modeling and visualization
MENTORING PLAN
The undergraduate research project (Fall 2022 and Spring 2023) will be subdivided into three general milestones with discrete goals:
- August through October 2022 - Learning:
- Working in a mineral and materials characterization laboratory, including but not limited to safety training.
- Sample preparation for (1) subsequent core scanning and analytical work.
- XRF and hyperspectral core scanning
- Organizational skills and preparatory work to ensure success and high-quality data generation and literature review.
- November 2022 through February 2023 – Learning/Analysis:
- Continued literature review and achievement of information literacy, data analysis and critical thinking.
- Training of effective communication skills.
- XRF and hyperspectral core scanning, data analysis and data co-registration
- March through May 2023 – Analysis/Synthesis/Presentation:
- Data interpretation, critical thinking during data analysis and quantitative reasoning skills.
- Data presentation – quantitative reasoning and scientific reasoning
- Effective communication skills
Preferred Student Status
Sophomore
Junior