Geosteering in deep water wells: A theoretical review of challenges and solutions
1 Shell Deep water, Gulf of Mexico. USA.
2 Sheval Engineering Services Limited, Nigeria.
Review
World Journal of Engineering and Technology Research, 2024, 03(01), 046–054.
Article DOI: 10.53346/wjetr.2024.3.1.0054
Publication history:
Received on 01 July 2024; revised on 10 August 2024; accepted on 13 August 2024
Abstract:
Geosteering in deep water wells presents unique challenges and opportunities within the oil and gas industry. This paper comprehensively reviews these challenges, including geological uncertainties, technological limitations, operational constraints, and economic and safety risks. Advanced geosteering tools and techniques, such as : Real time borehole image, resistivity inversion, anisotropy measurements, are discussed alongside the integration and the application of machine learning (ML) and artificial intelligence (AI) to enhance decision-making processes. Predictive modeling and uncertainty quantification are explored as essential components for optimizing wellbore placement and managing risks. Furthermore, the paper highlights emerging trends in geosteering technology, including augmented reality (AR), virtual reality (VR), and high-resolution sensors, which promise to improve the accuracy and efficiency of drilling operations. Sustainability considerations are also addressed, emphasizing the need for environmentally friendly drilling practices and reducing the industry's environmental footprint. This theoretical review underscores the importance of continuous technological advancements and the adoption of best practices to overcome the complexities of deepwater drilling. By leveraging innovative solutions and prioritizing sustainability, the oil and gas industry can enhance the success and safety of drilling operations, ensuring long-term viability and environmental stewardship.
Keywords:
Geosteering; Deep Water Wells; Machine Learning; Predictive Modeling; Sustainability
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Copyright © 2024 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0