Chapter 7: Structural Analysis of Drill Core for Mineral Exploration and Mining: Review and Workflow Toward Domain-Based 3-D Interpretation

2020 ◽  
pp. 215-245
Author(s):  
Julia Kramer Bernhard ◽  
Wayne Barnett ◽  
Ron Uken ◽  
Russell Myers
Keyword(s):  
Structural Analysis ◽  
Mineral Exploration ◽  
Drill Core

scholarly journals Mineral Mapping and Vein Detection in Hyperspectral Drill-Core Scans: Application to Porphyry-Type Mineralization

Minerals ◽  
2019 ◽  
Vol 9 (2) ◽  
pp. 122 ◽  
Author(s):  
Laura Tusa ◽  
Louis Andreani ◽  
Mahdi Khodadadzadeh ◽  
Cecilia Contreras ◽  
Paul Ivascanu ◽  
...  
Keyword(s):  
Mineral Exploration ◽  
Mining Industry ◽  
Structural Data ◽  
Short Wave ◽  
Variable Density ◽  
Drill Core ◽  
Distribution Maps ◽  
Mineral Mapping ◽  
Core Logging ◽  
Core Mapping

The rapid mapping and characterization of specific porphyry vein types in geological samples represent a challenge for the mineral exploration and mining industry. In this paper, a methodology to integrate mineralogical and structural data extracted from hyperspectral drill-core scans is proposed. The workflow allows for the identification of vein types based on minerals having significant absorption features in the short-wave infrared. The method not only targets alteration halos of known compositions but also allows for the identification of any vein-like structure. The results consist of vein distribution maps, quantified vein abundances, and their azimuths. Three drill-cores from the Bolcana porphyry system hosting veins of variable density, composition, orientation, and thickness are analysed for this purpose. The results are validated using high-resolution scanning electron microscopy-based mineral mapping techniques. We demonstrate that the use of hyperspectral scanning allows for faster, non-invasive and more efficient drill-core mapping, providing a useful tool for complementing core-logging performed by on-site geologists.

Hyperspectral drill-core imaging for ore characterization

2020 ◽  
Author(s):  
Laura Tusa ◽  
Mahdi Khodadadzadeh ◽  
Margret Fuchs ◽  
Richard Gloaguen ◽  
Jens Gutzmer
Keyword(s):  
Machine Learning ◽  
Remote Sensing ◽  
High Resolution ◽  
Hyperspectral Imaging ◽  
Mineral Exploration ◽  
Electromagnetic Spectrum ◽  
Drill Core ◽  
Ore Characterization ◽  
Ore Types ◽  
Drill Cores

<p>Mineral exploration campaigns represent an essential step in the discovery and evaluation of ore deposits required to fulfil the global demand for raw materials. Thousands of meters of drill-cores are extracted in order to characterize a specific exploration target. Hyperspectral imaging is recently being explored in the mining industry as a tool to complement traditional logging techniques and to provide a rapid and non-invasive analytical method for mineralogical characterization. The method relies on the fact that minerals have different spectral responses in specific portions of the electromagnetic spectrum. Sensors covering the visible to near-infrared (VNIR) and short-wave infrared (SWIR) are commonly used to identify and estimate the relative abundance of minerals such as phyllosilicates, amphiboles, carbonates, iron oxides and hydroxides as well as sulphates (Clark, 1999). The distribution of these mineral phases can frequently be used as a proxy for the distribution of ore minerals such as sulphides. Typical core imaging systems can acquire hyperspectral data from a whole drill-core tray in a matter of seconds. Available sensors record data in several hundreds of contiguous spectral bands at spatial resolutions around 1 mm/pixel.</p><p>​​In this work, we apply a local high-resolution mineralogical analysis, such as SEM-MLA (Kern et al., 2018), for a precise and exhaustive mineral mapping of some selected small samples. We then upscale these mineralogical data acquired from thin sections to drill-core scale by integrating hyperspectral imaging and machine learning techniques. Our proposed method is composed of two main steps. In the first step, after initially co-registering the hyperspectral and high-resolution mineralogical data and making a training set, a machine learning model is trained. In the second step, we apply the learned model to obtain mineral abundance and association maps over entire drill-cores.</p><p>​​The mapping is further used for the calculation of other mineralogical parameters essential to exploration and further mining stages such as modal mineralogy, mineral association, alteration indices, metal grade estimates and hardness. The proposed methodological framework is illustrated on samples collected from a porphyry type deposit, but the procedure is easily adaptable to other ore types. Therefore, this approach can be integrated in the standard core-logging routine, complementing the on-site geologists and can serve as background for the geometallurgical analysis of numerous ore types.  </p><p>​​</p><p>​​Clark, R. N., 1999, “Spectroscopy of rocks and minerals, and principles of spectroscopy,” in Remote sensing for the earth sciences: Manual of remote sensing, vol. 3, John Wiley & Sons, Inc, pp. 3–58.</p><p>​​Gandhi, S. M. and Sarkar, B. C., 2016, “Drilling,” in Essentials of Mineral Exploration and Evaluation, pp. 199–234.</p><p>​​Kern, M., Möckel, R., Krause, J., Teichmann, J., Gutzmer, J., 2018. Calculating the deportment of a fine-grained and compositionally complex Sn skarn with a modified approach for automated mineralogy. Miner. Eng. 116, 213–225.</p>

scholarly journals Development of Rapid Synchrotron 2D X-ray Mapping and XANES of Rock Slabs and Drill Core as a Tool for the Mineral Exploration and Mining Industries

2018 ◽  
Vol 24 (S2) ◽  
pp. 510-511 ◽  
Author(s):  
Neil R. Banerjee ◽  
Lisa L. Van Loon ◽  
Trevor J. Flynn ◽  
David Muir
Keyword(s):  
Mineral Exploration ◽  
Drill Core ◽  
X Ray

scholarly journals The Rocklea Dome 3D Mineral Mapping Test Data Set

2020 ◽  
Author(s):  
Carsten Laukamp ◽  
Maarten Haest ◽  
Thomas Cudahy
Keyword(s):  
Remote Sensing ◽  
Case Studies ◽  
Test Data ◽  
Mineral Exploration ◽  
Hyperspectral Data ◽  
Mineral Deposits ◽  
Drill Core ◽  
Data Set ◽  
Mineral Mapping ◽  
Barren Ground

Abstract. The integration of surface and subsurface geoscience data is critical for efficient and effective mineral exploration and mining. Publicly accessible datasets to evaluate the various geoscience analytical tools and their effectiveness for characterisation of mineral assemblages and lithologies or discrimination of ore from waste are however scarce. The open access Rocklea Dome 3D Mineral Mapping Test Data Set (Laukamp, 2020; https://doi.org/10.25919/5ed83bf55be6a) provides an opportunity for evaluating proximal and remote sensing data, validated and calibrated by independent geochemical and mineralogical analyses, for exploration of channel-iron deposits (CID) through cover. We present hyperspectral airborne, surface and drill core reflectance spectra collected in the visible-near infrared and shortwave infrared wavelength ranges (VNIR-SWIR; 350 to 2500 nm), as well as whole rock geochemistry obtained by means of X-Ray fluorescence analysis and loss on ignition measurements of drill core samples. The integration of surface with subsurface hyperspectral data collected in the frame of previously published Rocklea Dome 3D Mineral Mapping case studies demonstrated that about 30 % of exploration drill holes were sunk into barren ground and could have been of better use, located elsewhere, if airborne hyperspectral imagery had been consulted for drill hole planning. The remote mapping of transported Tertiary detritals (i.e. potential hosts of channel iron ore resources) versus weathered in situ Archaean geology (i.e. barren ground) has significant implications for other areas where cover (i.e. regolith and/or sediments covering bedrock hosting mineral deposits) hinders mineral exploration. Hyperspectral remote sensing represents a cost-effective method for regolith landform mapping required for planning drilling programs. In the Rocklea Dome area, vegetation unmixing methods applied to airborne hyperspectral data, integrated with subsurface data, resulted in seamless mapping of ore zones from the weathered surface to the base of the CID – a concept that can be applied to other mineral exploration and mineral deposit studies. Furthermore, the associated, independent calibration data allowed to quantify iron oxide phases and associated mineralogy from hyperspectral data. Using the Rocklea Dome data set, novel geostatistical clustering methods were applied to the drill core data sets for ore body domaining that introduced scientific rigour to a traditionally subjective procedure, resulting in reproducible objective domains that are critical for the mining process. Beyond the already published case studies, the Rocklea Dome 3D Mineral Mapping Test Data Set has the potential to develop new methods for advanced resource characterisation and develop new applications that aid exploration for mineral deposits through cover. The here newly presented white mica and chlorite abundance maps derived from airborne hyperspectral highlight the additional applications of remote sensing for geological mapping and could help to evaluate newly launched hyper- and multispectral spaceborne systems for geoscience and mineral exploration.

Regional Structural Analysis by Remote Sensing for Mineral Exploration, Paraiba State, Northeast Brazil

2000 ◽  
Vol 15 (1) ◽  
pp. 70-77 ◽  
Author(s):  
Chan Chiang Liu ◽  
Manoel de Araújo Sousa ◽  
Tumkur Rajarao Gopinath
Keyword(s):  
Remote Sensing ◽  
Structural Analysis ◽  
Mineral Exploration ◽  
Northeast Brazil

scholarly journals Resolution Enhancement for Drill-Core Hyperspectral Mineral Mapping

2021 ◽  
Vol 13 (12) ◽  
pp. 2296
Author(s):  
Isabel Cecilia Contreras Acosta ◽  
Mahdi Khodadadzadeh ◽  
Richard Gloaguen
Keyword(s):  
Mineral Exploration ◽  
Resolution Enhancement ◽  
Hyperspectral Data ◽  
Spatial Sampling ◽  
Machine Learning Techniques ◽  
Drill Core ◽  
Accurate Analysis ◽  
Operational Conditions ◽  
Mineral Mapping ◽  
Supervised Learning Algorithms

Drill-core samples are a key component in mineral exploration campaigns, and their rapid and objective analysis is becoming increasingly important. Hyperspectral imaging of drill-cores is a non-destructive technique that allows for non-invasive and fast mapping of mineral phases and alteration patterns. The use of adapted machine learning techniques such as supervised learning algorithms allows for a robust and accurate analysis of drill-core hyperspectral data. One of the remaining challenge is the spatial sampling of hyperspectral sensors in operational conditions, which does not allow us to render the textural and mineral diversity that is required to map minerals with low abundances and fine structures such as veins and faults. In this work, we propose a methodology in which we implement a resolution enhancement technique, a coupled non-negative matrix factorization, using hyperspectral, RGB images and high-resolution mineralogical data to produce mineral maps at higher spatial resolutions and to improve the mapping of minerals. The results demonstrate that the enhanced maps not only provide better details in the alteration patterns such as veins but also allow for mapping minerals that were previously hidden in the hyperspectral data due to its low spatial sampling.

scholarly journals The Geometry and Structural Analysis of the Gold Deposits of Chirano Mine

2016 ◽  
Vol 16 (2) ◽  
pp. 10-19
Author(s):  
K. Ackon-Wood ◽  
J. S. Y. Kuma ◽  
J. A. Yendaw
Keyword(s):  
Structural Analysis ◽  
Gold Deposit ◽  
Shear Zone ◽  
Gold Deposits ◽  
Drill Core ◽  
The South ◽  
Complex Interplay ◽  
The North ◽  
Structural Deformations

The Chirano Mine gold deposit is a typical example of a structurally controlled deposit developed along the Kumasi Basin and the Sefwi Belt margin structure. The area has undergone various regimes of structural deformations. Consequently, all the Chirano deposits are intimately associated with shears and faults along a single continuous structural corridor known as the Chirano Shear Zone (CSZ). The CSZ geometry has been categorised into three major zones namely: (i) Laminated veins in shears, (ii) Breccia and (iii) Ductile to brittle ductile zones. The shear veins trend NE-SW and N-S, are laminated and occur in the sheared fabric close to the footwall. Penetrative foliated zones varying from a few centimeters to several meters constitute the ductile to brittle-ductile structures. Gold grades are much higher within this zone. Analysis of cataclasis intensity recorded in drill core confirms a semi brittle form of deformation within the mineralised domain. The CSZ has different orientations in dip and strike from the south of the mining lease to the north. The subtle changes in orientation are deposit dependent. The structure has a sinuous shape and tends to pinch and swell. The current geometry and the distribution of stratigraphy and orebodies at Chirano is a manifestation of the complex interplay of magmatic and hydrothermal events in the area.  Keywords: Ductile, Brittle-Ductile, Breccia, Chirano Shear Zone, Chirano Lode Horizon

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