Applied Geophysical Imaging and Data Processing

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Earth Sciences".

Deadline for manuscript submissions: 30 June 2024 | Viewed by 607

Special Issue Editor


E-Mail Website
Guest Editor
Institute of Methodologies for Environmental Analysis, National Research Council of Italy (CNR-IMAA), C. da S. Loja, I-85050 Tito, PZ, Italy
Interests: applied geophysics; electromagnetic methods; natural hazards

Special Issue Information

Dear Colleagues,

Recently, increasing attention has been paid to novel applications of geophysical imaging and data processing for investigating unknown/poorly studied geophysical processes and complex geological environments of the Earth’s near subsurface. The exploration of the “Earth Thin Skin” (0-10 km of depth) is vital for human life and has an extraordinary social and economic impact (e.g., natural hazards, sustainable geo-energy and geo-resources, extreme events related to climate change, and environmental protection, etc.), in alignment with the UN’s Sustainable Development Goals.

The main objective of this Special Issue is to promote and platform relevant studies that focus on the following key topics: (1) novel approaches for the analysis and interpretation of geophysical imaging; (2) the development of innovative algorithms for geophysical data processing, with emphasis on novel AI-based methods (e.g., machine learning); (3) new methods for the analysis of time-lapse sequences of 4D geophysical images; (4) the development of innovative methods for the 3D and 4D visualization of geophysical tomographic images. Papers on recent research achievements obtained in the framework of different applicative domains (natural hazards, environmental monitoring, hydrogeology, geo-resources, engineering geology, urban geophysics, archaeology, etc.) are strongly welcomed and encouraged.

Dr. Vincenzo Lapenna
Guest Editor

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. Applied Sciences is an international peer-reviewed open access semimonthly 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

  • applied geophysics
  • geophysical imaging
  • tomography
  • signal processing
  • machine learning

Published Papers (1 paper)

Order results
Result details
Select all
Export citation of selected articles as:

Research

18 pages, 10258 KiB  
Article
Segmental Regularized Constrained Inversion of Transient Electromagnetism Based on the Improved Sparrow Search Algorithm
by Chao Tan, Xingzuo Ou, Jiwei Tan, Xinyu Min and Qihao Sun
Appl. Sci. 2024, 14(4), 1360; https://doi.org/10.3390/app14041360 - 7 Feb 2024
Viewed by 469
Abstract
The initial inversion model is typically established in a transient electromagnetic nonlinear inversion, assuming the accurate capture of the number of layers in the geoelectric model; however, this assumption leads to significantly poorer inversion results for complex models when obtaining the exact number [...] Read more.
The initial inversion model is typically established in a transient electromagnetic nonlinear inversion, assuming the accurate capture of the number of layers in the geoelectric model; however, this assumption leads to significantly poorer inversion results for complex models when obtaining the exact number of layers from available a priori information, which is challenging. This study proposes a segmented regularized inversion method to enhance inversion accuracy and stability under varying conditions. The process involves two key steps: Firstly, a segmented initial model is established based on preliminary information. The layering criteria and layer thickness threshold for each segment are set during inversion to reduce dependence on the accuracy of the preliminary information. Secondly, a segmented regularization constraint is added to the objective function to improve the efficiency and stability of the inversion, as numerous parameters can exacerbate the problem of inversion ambiguity. Subsequently, an improved sparrow search algorithm (ISSA) is utilized to optimize the inversion objective function. This enhances the efficiency of searching for the objective function and the algorithm’s ability to escape local optimal solutions. The proposed method is evaluated using one-dimensional and two-dimensional models with different initial models and inversion algorithms and applied to the inversion of on-site exploration data in a coal mining area in Chongqing. Comparative results demonstrate that the proposed segmented regularization method, based on the improved sparrow search algorithm, exhibits superior practicality and a higher fitting accuracy. Full article
(This article belongs to the Special Issue Applied Geophysical Imaging and Data Processing)
Show Figures

Figure 1

Back to TopTop