International Research Journal of Innovations in Engineering and Technology - IRJIET International Open Access, Monthly, Peer Reviewed, Reputed Journal ISSN (online): 2581-3048

Impact Factor (2025): 6.9

DOI Prefix: 10.47001/IRJIET

Investigating the Frontiers of Deep Learning and Machine Learning: A Comprehensive Overview of Key Challenges in Missing Well Log Estimation

Abstract

Well logging is a significant method of geological formation description and resource assessment in the exploration and development of oil, natural gas, minerals, groundwater, and sub-surface thermal energy, as well as geotechnical engineering and environmental research. However, the challenging problem of estimating well logging data always exists because well logs can only be measured through a drilling process involving costly and time-consuming field trials. This study provides a brief overview of Deep Learning (DL) models and examines the well-logging issues in estimating missing well-log data. In addition, it discusses a literature review focusing on the application of DL models for well-log estimation. The outcome of this exploratory work necessitates suitable requirements for the design and implementation.

Country : Nigeria

1 Nwankwo C.G2 Alade S.M3 Agbakwuru O.A4 Amanze B.C5 Akawuku G.I

  1. Department of Computer Science, Chukwuemeka Odumegwu Ojukwu University Uli, Nigeria
  2. Department of Computer Science, Nnamdi Azikiwe University Awka, Nigeria
  3. Department of Computer Science, Nigeria Imo State University Owerri, Nigeria
  4. Department of Computer Science, Nigeria Imo State University Owerri, Nigeria
  5. Department of Computer Science, Nnamdi Azikiwe University Awka, Nigeria

IRJIET, Volume 8, Issue 7, July 2024 pp. 1-15

doi.org/10.47001/IRJIET/2024.807001

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