IDEAS home Printed from https://ideas.repec.org/a/hin/complx/9404567.html
   My bibliography  Save this article

Fractal Assessment of the Disturbances of Phosphate Series Using Lacunarity and Succolarity Analysis on Geoelectrical Images (Sidi Chennane, Morocco)

Author

Listed:
  • Abderrahim Ayad
  • Saad Bakkali

Abstract

In Sidi Chennane phosphate deposit, the disturbances cause serious challenges for the OCP mining engineers during both exploration and the exploitation stages. They are qualified as worst rocky hard to be quantified since they interfere with phosphates series. In this paper, we propose the fractal analysis as a simple efficient tool to quantify the rate of the disturbances by two different methods, namely, the Lacunarity and the Succolarity. The analysis was carried out on eight geoelectrical images of a disturbed area of 50 hectares located in the northern part of Sidi Chennane. The results proved that there is a strong correlation between the disturbances rate and the corresponding fractal value indexes. It appears that the distinction between two disturbed areas is the difference between their corresponding fractal values. This has an important implication to discriminate between the phosphate deposit at high risk of disturbances and the deposit at low risk. The fractal analysis can be thus used as a crucial concept in ranking the prospective zones of phosphate as well as improving the phosphate reserve estimation.

Suggested Citation

  • Abderrahim Ayad & Saad Bakkali, 2019. "Fractal Assessment of the Disturbances of Phosphate Series Using Lacunarity and Succolarity Analysis on Geoelectrical Images (Sidi Chennane, Morocco)," Complexity, Hindawi, vol. 2019, pages 1-12, July.
    • Handle: RePEc:hin:complx:9404567
    DOI: 10.1155/2019/9404567
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/8503/2019/9404567.pdf
    Download Restriction: no
    File URL: http://downloads.hindawi.com/journals/8503/2019/9404567.xml
    Download Restriction: no
    File URL: https://libkey.io/10.1155/2019/9404567?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Lior Shamir & John D Delaney & Nikita Orlov & D Mark Eckley & Ilya G Goldberg, 2010. "Pattern Recognition Software and Techniques for Biological Image Analysis," PLOS Computational Biology, Public Library of Science, vol. 6(11), pages 1-10, November.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Louis-François Handfield & Yolanda T Chong & Jibril Simmons & Brenda J Andrews & Alan M Moses, 2013. "Unsupervised Clustering of Subcellular Protein Expression Patterns in High-Throughput Microscopy Images Reveals Protein Complexes and Functional Relationships between Proteins," PLOS Computational Biology, Public Library of Science, vol. 9(6), pages 1-19, June.
    2. Assaf Zaritsky & Sari Natan & Judith Horev & Inbal Hecht & Lior Wolf & Eshel Ben-Jacob & Ilan Tsarfaty, 2011. "Cell Motility Dynamics: A Novel Segmentation Algorithm to Quantify Multi-Cellular Bright Field Microscopy Images," PLOS ONE, Public Library of Science, vol. 6(11), pages 1-10, November.
    3. Philipp Mergenthaler & Santosh Hariharan & James M Pemberton & Corey Lourenco & Linda Z Penn & David W Andrews, 2021. "Rapid 3D phenotypic analysis of neurons and organoids using data-driven cell segmentation-free machine learning," PLOS Computational Biology, Public Library of Science, vol. 17(2), pages 1-33, February.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:hin:complx:9404567. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Mohamed Abdelhakeem (email available below). General contact details of provider: https://www.hindawi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.