• DocumentCode
    188508
  • Title

    An Ontology-Based Automatic Approach for Lithologic Correlation

  • Author

    Fonseca Garcia, Luan ; Carbonera, Joel ; Abel, Mara

  • Author_Institution
    Inst. of Inf., Univ. Fed. do Rio Grande do Sul, Porto Alegre, Brazil
  • fYear
    2014
  • fDate
    10-12 Nov. 2014
  • Firstpage
    130
  • Lastpage
    137
  • Abstract
    In this paper we present an automatic approach for the litho logic correlation task, which is a crucial task in the domain of Petroleum Geology. In our approach, we consider the litho logic correlation task as formally equivalent to the task of DNA sequence alignment, in the domain of Bioinformatics. This allows us to use well-known sequence alignment algorithms for dealing with this task. Moreover, our approach uses a domain ontology for representing the knowledge about the domain objects. This ensures an agreement regarding the formal vocabulary used for describing the geological objects, allowing us to deal with the data collected by different geologists in a homogeneous way. Finally, we also use clustering techniques for finding groups of geological objects that are sufficiently similar for being correlated by the sequence alignment algorithms. We discuss some results of the application of our approach to a real dataset.
  • Keywords
    geology; knowledge representation; ontologies (artificial intelligence); petroleum industry; DNA sequence alignment; bioinformatics; geological objects; knowledge representation; lithologic correlation; ontology-based automatic approach; petroleum geology; sequence alignment algorithms; Clustering algorithms; Correlation; DNA; Grain size; Ontologies; Rocks; Clustering; Data Mining; Ontology; Petroleum Geology; Sequence Alignment;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Tools with Artificial Intelligence (ICTAI), 2014 IEEE 26th International Conference on
  • Conference_Location
    Limassol
  • ISSN
    1082-3409
  • Type

    conf

  • DOI
    10.1109/ICTAI.2014.29
  • Filename
    6984465