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Minerals
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Advanced Technologies in Quantitative Mineralogy and Elemental Mapping
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Advanced Technologies in Quantitative Mineralogy and Elemental Mapping

A special issue of Minerals (ISSN 2075-163X).

Deadline for manuscript submissions: closed (17 March 2023) | Viewed by 7113

Special Issue Editors

Dr. François R. Doucet

E-Mail Website
Guest Editor
ELEMISSION Inc., 3410, Thimens blvd., Montreal, QC H4R 1V6, Canada
Interests: LIBS; hyperspectral imaging; drill core digitation; quantitative automated mineralogy; multi-elemental assays
Prof. Dr. Marc Constantin

E-Mail Website
Guest Editor
Departement de geologie et de genie geologique, Faculte des sciences et de genie, Universite Laval, Quebec, QC G1V 0A6, Canada
Interests: LIBS; igneous petrology
Dr. Christophe Germay

E-Mail Website
Guest Editor
EPSLOG SA, Rue Hocheporte, 76, 4000 Liege, Belgium
Interests: core logging and digitalization

Special Issue Information

Dear Colleagues,

The last two decades have been marked by the development of several innovative ways to automate core logging by bringing spectroscopy as a hyperspectral tool to observe the core using systematic physicochemical–mineralogical signals acquired with electronic-based sensors. Core logging consists in recording and visually measuring information to determine the lithology, mineralogy, geological structures, and alteration zones through cylindrical rock samples drilled and recovered from a potential mineral deposit, the drill core. It is the first in a series of actions aimed at determining the grade, size, and economic viability of a mineral deposit. Historically, this important task was executed by geologists using their naked eyes and a hand lens. Innovative spectroscopic-based approaches have the advantage to minimize human interpretation errors. Since human judgement can be altered by the surrounding environmental conditions and the level of tiredness, to name a few distraction sources, these sensors can be seen as new “cameras” to observe and to characterize the drill core, therefore facilitating the work of core logging done by the geologist/geometallurgist/mineralogist/petrologist.

This Minerals Special Issue is aiming to publish state-of-the-art geological core imaging research, gathering the latest progress in the field of core logging. This Special Issue of Minerals invites papers dealing with the use of hyperspectral imaging and multisensor-based imaging technologies for drill core, cuttings, grab samples, metallurgical samples, etc.

Dr. François R. Doucet
Prof. Dr. Marc Constantin
Dr. Christophe Germay
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Minerals is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • rock imaging
  • hyperspectral imaging
  • LIBS, LA-ICP-MS, SWIR, LWIR, NIR, XRF
  • quantitative automated mineralogy
  • multielemental assays
  • core logging

Published Papers (4 papers)

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Research

20 pages, 10206 KiB  
Article
Region Expansion of a Hyperspectral-Based Mineral Map Using Random Forest Classification with Multispectral Data
by Hideki Tsubomatsu and Hideyuki Tonooka
Minerals 2023, 13(6), 754; https://doi.org/10.3390/min13060754 - 31 May 2023
Cited by 1 | Viewed by 1383
Abstract
Observation images from hyperspectral (HS) sensors on satellites and aircraft can be used to map minerals in greater detail than those from multispectral (MS) sensors. However, the coverage of HS images is much less than that of MS images, so there are often [...] Read more.
Observation images from hyperspectral (HS) sensors on satellites and aircraft can be used to map minerals in greater detail than those from multispectral (MS) sensors. However, the coverage of HS images is much less than that of MS images, so there are often cases where MS images cover the entire area of interest while HS images cover only a part of it. In this study, we propose a new method to more reasonably expand the mineral map of an HS image with an MS image in such cases. The method uses various mineral indices from the MS image and MS sensor’s band values as the input and HS image-based mineral classes as the output. Random forest (RF) two-class classification is then applied iteratively to determine the distribution of each mineral in turn, starting with the minerals that are most consistent with the HS image-based mineral map. The method also involves the correction of misalignment between HS and MS images and the selection of input variables by RF multiclass classification. The method was evaluated in comparison with other methods in the Cuprite area, Nevada, using the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and Hyperspectral Imager Suite (HISUI) as HS sensors and the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) as MS sensors. As a result, all of the evaluated region-expansion methods with an HS–MS image pair, including the proposed method, showed better performance than the method using only an MS image. The proposed method had the highest performance, and the inter-mineral averages of the F1-scores for the overlap and non-overlap areas were 85.98% and 46.46% for the AVIRIS–ASTER image pair and 82.78% and 42.60% for the HISUI–ASTER image pair, respectively. Although the performance in the non-overlap region was lower than in the overlap region, the method showed high precision and high accuracy for almost all minerals, including minerals with only a few pixels. Misalignment between the HS–MS images is a factor that degrades accuracy and requires precise alignment, but the misalignment correction in the proposed method could suppress the effect of misalignment. Validation studies using different regions and different sensors will be carried out in the future. Full article
(This article belongs to the Special Issue Advanced Technologies in Quantitative Mineralogy and Elemental Mapping)
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13 pages, 7675 KiB  
Article
Chemical and Mineralogical Analysis of Samples Using Combined LIBS, Raman Spectroscopy and µ-EDXRF
by Virginia Merk, Khulan Berkh, Dieter Rammlmair and Lutz Pfeifer
Minerals 2023, 13(6), 729; https://doi.org/10.3390/min13060729 - 26 May 2023
Cited by 1 | Viewed by 1527
Abstract
Energy-dispersive X-ray fluorescence (EDXRF) analysis is one of the standard techniques for the evaluation of mineral deposits. The advantage of EDXRF is the fast delivery of information about the bulk elemental composition as well as the elemental composition of each mineral class. With [...] Read more.
Energy-dispersive X-ray fluorescence (EDXRF) analysis is one of the standard techniques for the evaluation of mineral deposits. The advantage of EDXRF is the fast delivery of information about the bulk elemental composition as well as the elemental composition of each mineral class. With micro energy-dispersive X-ray fluorescence (µ-EDXRF) analysis, information can be obtained with a micrometer resolution. However, it has some limitations. With EDXRF, light elements (e.g., lithium) cannot be detected, and the count rates for carbon, fluorine and sodium are very low. This might lead to a misinterpretation of the mineral classes and the worth of the deposit. Furthermore, the identification of the alteration phases of primary minerals is ambiguous. Here, we will present an approach to overcome the limitations of µ-EDXRF by complementing it with combined laser-induced breakdown spectroscopy (LIBS) and Raman spectroscopy. In contrast to EDXRF, LIBS is able to detect all elements, including light elements. Raman spectroscopy can identify mineral phases and eventually provide additional information on their alterations and modifications. In the present paper, we show results for two different samples covering a certain chemical and mineralogical range that demonstrate the potential of the proposed combination of methods for the chemical and mineralogical analysis of geological samples. Full article
(This article belongs to the Special Issue Advanced Technologies in Quantitative Mineralogy and Elemental Mapping)
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16 pages, 4576 KiB  
Article
A Novel Method for Evaluation of Ore Minerals Based on Optical Microscopy and Image Analysis: Preliminary Results
by Licia Santoro, Marco Lezzerini, Andrea Aquino, Giulia Domenighini and Stefano Pagnotta
Minerals 2022, 12(11), 1348; https://doi.org/10.3390/min12111348 - 25 Oct 2022
Cited by 1 | Viewed by 2158
Abstract
Natural or artificial light allows us to see and analyze matter with our eyes, which are the first tools used in several experiments. In geosciences, particularly in mineralogy, light is used for optical microscopy observations. Reflected and transmitted light applied to the study [...] Read more.
Natural or artificial light allows us to see and analyze matter with our eyes, which are the first tools used in several experiments. In geosciences, particularly in mineralogy, light is used for optical microscopy observations. Reflected and transmitted light applied to the study of ore deposits can be useful to discriminate between gangue from precious phases. Knowledge of the structural and morphological characteristics, combined with the quantitative evaluation of mineral abundance, is fundamental for determining the grade of ore deposits. The accuracy and reliability of the information are closely linked to the ability of the mineralogist, who more and more often uses Scanning Electron technology and automated mineralogy systems to validate the observations or solve complex mineralogy. While highly accurate, these methods are often prohibitively expensive. The use of image analysis using standard algorithms and artificial intelligence, available as open source, and commercial packages (such as ImageJ, Fiji or MATLAB), can provide advantages in fast, cost-effective, and robust mineral analysis. Recently, the application of neural networks provided increasingly effective image analysis and, among the different types of neural networks available today, the self-organizing maps of Kohonen (SOM) seem to be among the most promising, given their capacity to receive many images as inputs and reduce them to a low number of neuronal outputs that represent all the input characteristics in a lower-dimensional space. In this work, we will show the preliminary results of a new method based on SOM and the combined use of images acquired in transmitted and reflected light to reconstruct false 3D surfaces, which were able to show the presence of intergrow between gangue phases and precious minerals. Full article
(This article belongs to the Special Issue Advanced Technologies in Quantitative Mineralogy and Elemental Mapping)
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21 pages, 14464 KiB  
Article
A New Image Processing Workflow for the Detection of Quartz Types in Shales: Implications for Shale Gas Reservoir Quality Prediction
by Sen Guo, David Misch, Reinhard F. Sachsenhofer, Yanming Zhu, Xin Tang and Weichen Bai
Minerals 2022, 12(8), 1027; https://doi.org/10.3390/min12081027 - 16 Aug 2022
Viewed by 1281
Abstract
A shale lithofacies scheme is commonly used to characterize source rock reservoirs of the Lower Cambrian Niutitang Formation. However, this classification ignores that individual components such as quartz may have different origins, potentially affecting reservoir quality. The main objective of this article is, [...] Read more.
A shale lithofacies scheme is commonly used to characterize source rock reservoirs of the Lower Cambrian Niutitang Formation. However, this classification ignores that individual components such as quartz may have different origins, potentially affecting reservoir quality. The main objective of this article is, therefore, to present a refined scheme for lithofacies and an image processing workflow for the detection of quartz types in the Niutitang Formation shales from the Jiumen outcrop in the Guizhou Province (Upper Yangtze Basin, SW China). In order to do so, a combination of bulk density, optical and scanning electron microscopy and image analysis was used. The shale lithology was macroscopically classified into seven major categories and nineteen subcategories. Subsequently, the shales were investigated at the microscopic level, mainly focusing on quartz types and microstructural variations. Afterwards, the workflow to calculate the weight per unit volume (1 cm3) of the quartz types was presented, i.e., firstly, by calculating the weight of mineral matter by subtraction of the measured weight of organic matter from the bulk shale; secondly, by calculating the weight of total quartz in bulk shale from the weight of mineral matter and its proportion calculated from X-ray diffraction data; thirdly, by calculating the weight of detrital quartz and non-detrital quartz with energy dispersive X-ray mapping, image processing and quartz density; finally, by calculating the weight of clay-sized quartz by subtracting of the weight of detrital and non-detrital quartz from the weight of the total quartz. The bulk quartz content was found to be dominated by clay-sized quartz, which may mainly control the mesopore volume available for gas storage and, hence, the shale gas reservoir development. Full article
(This article belongs to the Special Issue Advanced Technologies in Quantitative Mineralogy and Elemental Mapping)
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