Download PDFOpen PDF in browserAI-Driven Approaches to Enhancing Reservoir Management: Predictive Modeling Techniques for Long-Term Production ForecastingEasyChair Preprint 144698 pages•Date: August 15, 2024AbstractThe advent of artificial intelligence (AI) has brought significant advancements in various industries, including the oil and gas sector. This paper explores the potential of AI-driven approaches in enhancing reservoir management, focusing on predictive modeling techniques for long-term production forecasting. By leveraging AI algorithms, such as machine learning and deep learning, operators can gain deeper insights into reservoir behavior, optimize production strategies, and improve decision-making processes. The paper also discusses the challenges associated with implementing AI in reservoir management, including data quality, model interpretability, and computational requirements. Through a comprehensive analysis, this study aims to provide a detailed understanding of how AI can revolutionize reservoir management for long-term production forecasting. Keyphrases: : AI in Reservoir Management, Data Quality in AI, High Performance Computing, Long-Term Production Forecasting, Model Interpretability, deep learning, machine learning, neural networks, oil and gas industry, predictive modeling
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