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المؤلفRahaman, Md Shokor A.
المؤلفIslam, Jahedul
المؤلفWatada, Junzo
المؤلفVasant, Pandian
المؤلفAlhitmi, Hitmi Khalifa
المؤلفHossain, Touhid Mohammad
تاريخ الإتاحة2024-04-16T12:54:42Z
تاريخ النشر2021
اسم المنشورInternational Journal of Innovative Computing, Information and Control
المصدرScopus
الرقم المعياري الدولي للكتاب13494198
معرّف المصادر الموحدhttp://dx.doi.org/10.24507/ijicic.17.02.539
معرّف المصادر الموحدhttp://hdl.handle.net/10576/53908
الملخصThe most important element for the exploration and development of oil and oil shale is total organic carbon (TOC). TOC estimation is considered a challenge for geologists since laboratory methods are expensive and time-consuming. Therefore, due to the complex and nonlinear relationship between well logs and TOC, researchers have begun to use artificial intelligence (AI) techniques. Hence, the purpose of this research is to explore new paradigms and methods for AI techniques. First, this article provides a recent overview of selected AI technologies and their applications, including artificial neural networks (ANNs), convolutional neural networks (CNNs), hybrid intelligent systems (HISs), and support vector machines (SVMs) as well as fuzzy logic (FL), particle swarm optimization (PSO). Second, this article explores and discusses the benefits and pitfalls of each type of AI technology. The study found that hybrid intelligence technology was the most successful and independent AI model with the highest probability of infer-ring properties of oil shale oil and gas fields (such as TOC) from wireline logs. Finally, some possible combinations are proposed that have not yet been investigated.
راعي المشروعAcknowledgments. The authors would like to thank and highly appreciate Petroleum Research Fund (PRF), Cost Center 0153AB-A33 and the project leader Dr. Eswaran Padmanabhan for supporting the research. The authors also would like to thank Universiti Teknologi PETRONAS (UTP) for Graduate Research Assistantship (GRA) scheme.
اللغةen
الناشرICIC International
الموضوعArtificial intelligence
Organic shale
Pattern recognition
Total organic carbon (TOC)
Well logs
العنوانArtificial intelligence approach to total organic carbon content prediction in shale gas reservoir using well logs: A review
النوعArticle
الصفحات539-563
رقم العدد2
رقم المجلد17
dc.accessType Abstract Only


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