Seismics in Mineral Exploration

A special issue of Minerals (ISSN 2075-163X). This special issue belongs to the section "Mineral Exploration Methods and Applications".

Deadline for manuscript submissions: 31 December 2024 | Viewed by 7844

Special Issue Editors


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Guest Editor
‘Multi-Wave & Multi-component’ (MWMC) Seismic Group, State Key Laboratory of Geological Processes and Mineral Resources, School of Geophysics and Information Technology, China University of Geosciences, Beijing 100083, China
Interests: seismic anisotropy; multi-component seismic; multi-wave seismic; rotational seismology; deep underground geophysical observation; ocean geophysics; mineral seismic

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Guest Editor
Institutions of Earth Science, Chinese Academy of Sciences, Beijing 100029, China
Interests: artificial intelligence geophysics; compressive sensing seismic exploration; seismic while drilling; numerical simulation and FWI

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Guest Editor
School of Geophysics and Information Technology, China University of Geosciences (Beijing), Beijing 100083, China
Interests: seismic exploration; mineral exploration; passive reflection seismic; seismic imaging; seismic migration; GPU
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
School of Geosciences and Info-Physics, Central South University, Changsha 410083, China
Interests: geo-electromagnetic induction methods for mineral exploration; joint inversions for minerals
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The main problem encountered by mineral seismic exploration is accurately imaging concealed rock mass, faults and ore bodies with limited investment. Therefore, how to decrease the seismic acquisition cost is the most important point of concern. Promoted by rapid development of modern information science and technology, artificial intelligence, multi-component seismometers or nodes, and remote sensing techniques are widely applied in exploration seismology. However, mineral seismic is not a simple duplication of oil and gas seismics or engineering seismics. In recent years, much progress involving compressive sensing, multi-component seismics, active and passive source techniques, joint geophysical inversion and field cases has been achieved. For this Special Issue, submitted papers should be focused on a feasible, cost-effective seismic solution for mineral exploration to further improve the seismic precision, resolution and reliability. At least one of the following four topics should be covered:

(1) New theories, methods and techniques about active and passive source seismic and geo-electromagnetic induction methods, including significant or defeated cases. It should be noted that research on active reflection seismics, scattering seismics and geo-electromagnetic induction prospecting is not welcomed here, while joint active and passive seismic, natural and artificial source of geo-electromagnetic methods are favored topics.

(2) Seismic acquisition techniques assisted with artificial intelligence aimed at characterizing the complex topography and underground structures of mineral deposits, spare and non-regular grid seismic sampling, and active and passive seismics with multi-component sensors, especially methods about wave field construction with compressive sensing, and methods about separation of hybrid source and denoising. If there is no real mineral application, fossil energy models or cases can be supplemented.

(3) Multi-component seismics. Whether the source is active or passive, multi-component geophones and data processing methods, especially methods about vector denoising, multi-wave imaging, joint imaging with body and surface waves, should be given enough emphases; wide-frequency seismic migration joined with active and passive sources, and relatively new inversion methods and applications are particularly welcomed.

(4) Integrated geophysics. Seismic constrained geophysical interpretation and inversion, such as gravity-seismic, electro-seismic, and magnetic-seismic inversion, including joint imaging and inversion with surface and vertical logging are worth considering.

Prof. Dr. Yun Wang
Dr. Shoudong Huo
Prof. Dr. Guofeng Liu
Prof. Dr. Zhengyong Ren
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

  • mineral seismic
  • compressive sensing
  • artificial intelligence
  • multi-component seismic
  • active seismic
  • passive seismic
  • joint imaging and inversion
  • integrated geophysics

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Published Papers (5 papers)

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Research

30 pages, 11844 KiB  
Article
Enhancing Thin Coal Seam Detection in Eastern Indian Coalfields Using ICWT-Decon-Based Seismic Attributes and Acoustic Impedance Inversion
by Naresh Kumar Seelam, Thinesh Kumar, Santosh Dhubia, Gangumalla Srinivasa Rao and Sanjit Kumar Pal
Minerals 2024, 14(9), 920; https://doi.org/10.3390/min14090920 - 7 Sep 2024
Viewed by 697
Abstract
A high-resolution seismic survey (HRSS) is often used in coal exploration to bridge the data gap between two consecutive boreholes and avoid ambiguity in geological interpretation. The application of high-resolution seismic surveys in the Indian context is challenging as the delineation of thin [...] Read more.
A high-resolution seismic survey (HRSS) is often used in coal exploration to bridge the data gap between two consecutive boreholes and avoid ambiguity in geological interpretation. The application of high-resolution seismic surveys in the Indian context is challenging as the delineation of thin non-coal layers within the coal layer requires a very high seismic data resolution. However, conventional seismic processing techniques fail to resolve thin coal/non-coal layers and faults, which is crucial for the precise estimation of coal resources and mine economics. To address these issues, we applied the inverse continuous wavelet transform deconvolution (ICWT-Decon) technique to post-stack depth-migrated seismic sections. We examined the feasibility of the ICWT-Decon technique in both a synthetic post-stack depth-migrated model and 2D/3D seismic data from the North Karanpura and Talcher Coalfields in Eastern India. The results offered enhanced seismic sections, attributes (similarity and sweetness), and acoustic inversion that aided in the precise positioning of faults and the delineation of a thin non-coal layer of 4.68 m within a 16.7 m coal seam at an approximate depth of 450 m to 550 m. This helped in the refinement of the resource estimation from 74.96 MT before applying ICWT-Decon to 55.92 MT afterward. Overall, the results of the study showed enhancements in the seismic data resolution, the better output of seismic attributes, and acoustic inversion, which could enable more precise lithological and structural interpretation. Full article
(This article belongs to the Special Issue Seismics in Mineral Exploration)
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22 pages, 24009 KiB  
Article
What Extra Information Can Be Provided by Multi-Component Seismic Data: A Case Study of 2D3C Prospecting of a Copper–Molybdenum Mine in Inner Mongolia, China
by Yingda Li, Yutian Gu, Yi Zhang, Yun Wang, Guangming Yu and Mingcai Xu
Minerals 2024, 14(7), 689; https://doi.org/10.3390/min14070689 - 30 Jun 2024
Viewed by 933
Abstract
With the decrease in shallow mineral reserves, deep mineral resources have become the focus of exploration. Seismic exploration, renowned for its deep penetration and high spatial resolution and precision, stands as a primary technique in geophysical exploration. In comparison to traditional P-wave seismic [...] Read more.
With the decrease in shallow mineral reserves, deep mineral resources have become the focus of exploration. Seismic exploration, renowned for its deep penetration and high spatial resolution and precision, stands as a primary technique in geophysical exploration. In comparison to traditional P-wave seismic exploration, multi-component seismic techniques offer the advantage of simultaneously acquiring P-wave and S-wave data, overcoming the limitations of single P-wave impedance in predicting lithology and enabling high-precision imaging of subsurface structures. Constrained by field survey costs, the reflection seismic illumination is lower and results in a poor signal-to-noise ratio of multi-component seismic data in metallic ore exploration, which poses great challenges in imaging converted S-waves. Based on the seismic and geological characteristics of metallic ores, this study conducts imaging research on metallic ore models through synthetic data and field multi-component seismic data from a copper–molybdenum mine in Inner Mongolia, China. The emphasis is given to PS-wave pre-stack time migration based on precisely sorting the commonly converted point so as to explore the feasibility and technical advantages of multi-component seismic exploration in metal mines. Synthetic data and field data testing demonstrate that PS-wave imaging contains more abundant structural and lithological information compared to PP-waves, indicating promising prospects for the application of multi-component seismic data in metallic ore exploration. Full article
(This article belongs to the Special Issue Seismics in Mineral Exploration)
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23 pages, 12616 KiB  
Article
Full-Waveform Modeling of Complex Media Seismic Waves for Irregular Topography and Its Application in Metal Ore Exploration
by Wenchao Su, Shoudong Huo and Xuhui Zhou
Minerals 2024, 14(7), 664; https://doi.org/10.3390/min14070664 - 27 Jun 2024
Viewed by 578
Abstract
Seismic exploration has caught widespread attention in metal ore exploration due to its higher resolution. However, the presence of topography and complex underground structures in metal ore exploration complicates seismic records. Therefore, it is essential to apply a numerical simulation method suitable for [...] Read more.
Seismic exploration has caught widespread attention in metal ore exploration due to its higher resolution. However, the presence of topography and complex underground structures in metal ore exploration complicates seismic records. Therefore, it is essential to apply a numerical simulation method suitable for metal ore exploration to study the propagation law of seismic waves in shallow and ore-forming zones, providing reliable theoretical support for multi-component seismic techniques. In particular, the presence of topography generates strong-amplitude surface waves, scattered waves, and converted waves, which consistently distort seismic records and affect the imaging accuracy of the metallogenic belts. Additionally, the propagation of seismic waves is also affected by the anisotropy and viscoelasticity of the underground medium. This paper proposes an elastic wave finite-difference numerical simulation method suitable for irregularly topographical and complex medium conditions, named the comprehensive parameter correction method, which implements a free-surface boundary condition based on the concept of medium averaging. It is algorithmically simple and implies no additional computational costs. Meanwhile, the results obtained by this method are highly consistent with those of the spectral element method, demonstrating its accuracy. By presenting several numerical simulation cases and illustrating the impact of topography and medium conditions on seismic records, this paper demonstrates the necessity of considering irregularly topographical and complex medium conditions in metal ore exploration. In conclusion, the numerical simulation method we propose provides a solid theoretical foundation for the application of seismic exploration methods in metal ore exploration. Full article
(This article belongs to the Special Issue Seismics in Mineral Exploration)
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15 pages, 12681 KiB  
Article
Real-Time Ambient Seismic Noise Tomography of the Hillside Iron Oxide–Copper–Gold Deposit
by Timothy Jones, Gerrit Olivier, Bronwyn Murphy, Lachlan Cole, Craig Went, Steven Olsen, Nicholas Smith, Martin Gal, Brooke North and Darren Burrows
Minerals 2024, 14(3), 254; https://doi.org/10.3390/min14030254 - 28 Feb 2024
Cited by 1 | Viewed by 3290
Abstract
We conduct an exploration-scale ambient noise tomography (ANT) survey over the Hillside Iron Oxide–Copper–Gold (IOCG) deposit in South Australia, leveraging Fleet’s direct-to-satellite technology for real-time data analysis. The acquisition array consisted of 100 sensors spaced 260 m apart which recorded continuous vertical-component seismic [...] Read more.
We conduct an exploration-scale ambient noise tomography (ANT) survey over the Hillside Iron Oxide–Copper–Gold (IOCG) deposit in South Australia, leveraging Fleet’s direct-to-satellite technology for real-time data analysis. The acquisition array consisted of 100 sensors spaced 260 m apart which recorded continuous vertical-component seismic ambient noise for 14 days. High quality Rayleigh wave signals, with a mean signal-to-noise ratio (SNR) of 40, were recovered in the frequency band 1–4 Hz after processing the recorded data between 0.1–9 Hz. Our modelling results capture aspects of the deposit’s known geology, including depth of cover, structures linked to mineralisation, and the mineralised host rock, down to approximately 1 km depth. We compare our velocity model with existing magnetic, gravity, induced polarisation and drilling data, showing strong correlation with each. We identify several new features of the local geology, including the behaviour of key structures down to 1 km, and highlight the significance of a Cambrian-age dolomite that cuts across the main structural corridor that hosts the Hillside deposit. An analysis of model convergence rates with respect to Rayleigh wave SNRs shows that real-time data analysis can reduce recording duration at the site by 65% compared to traditional deployment durations, from ∼14 days to ∼5 days. Finally, we conclude by commenting on the efficacy of the ANT technique for the exploration of IOCG systems more broadly. Full article
(This article belongs to the Special Issue Seismics in Mineral Exploration)
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25 pages, 20194 KiB  
Article
Prediction of Lithium Oilfield Brines Based on Seismic Data: A Case Study from L Area, Northeastern Sichuan Basin, China
by Yuxuan Zhou, Yuyong Yang, Zhengyang Wang, Bing Zhang, Huailai Zhou and Yuanjun Wang
Minerals 2024, 14(2), 159; https://doi.org/10.3390/min14020159 - 31 Jan 2024
Viewed by 1391
Abstract
Lithium is an important mineral resource and a critical element in the production of lithium batteries, which are currently in high demand. Oilfield brine has significant value as a raw material for lithium extraction. However, it is often considered a byproduct of oil [...] Read more.
Lithium is an important mineral resource and a critical element in the production of lithium batteries, which are currently in high demand. Oilfield brine has significant value as a raw material for lithium extraction. However, it is often considered a byproduct of oil and gas production and is either abandoned or reinjected underground. Exploration and development of oilfield brines can enhance the economic benefits of oilfields and avoid wasting resources. Current methods for predicting brine distribution rely on geological genetic analysis, which results in low accuracy and reliability. To address this issue, we propose a workflow for lithium brine prediction that uses seismic and logging data. We introduced waveform clustering control and used the mapping relationship between seismic waveforms and well-logging curves to predict high-quality reservoirs based on the electrical and physical properties of lithium brine reservoirs. In this workflow, the seismic waveforms were first clustered using singular value decomposition. The sample sets of well-logging properties were established for the target location. The target properties were divided into high- and low-frequency components and predicted separately. The predicted results of the high-quality reservoirs in the study area were verified using elemental content test results to demonstrate the effectiveness of the method. Our study indicates that well-logging property prediction constrained by waveform clustering can predict lithium brines in a carbonate reservoir. Full article
(This article belongs to the Special Issue Seismics in Mineral Exploration)
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