Application of intelligent models in reservoir and production engineering

Utilizing Artificial Intelligence Techniques for Modeling Minimum Miscibility Pressure in Carbon Capture and Utilization Processes: A Comprehensive Review and Applications

“…71−73 The modeling of MMP of the systems CO 2 − oil is among the successful examples where AI and ML methods have shown great importance and contribution by delivering many simple-to-use paradigms which can predict this vital parameter easily and with high accuracy. 74 This topic has attracted many researchers and gained noticeable popularity in the petroleum industry since the publication of the earliest paper on the application of AI for predicting MMP of CO 2 − oil systems, namely the study of Huang et al 75 published in 2003. Since then, the academic and industrial communities provided considerable numbers of valuable papers on modeling the MMP of CO 2 − oil systems using a broad panoply of AI methods.…”

“…Examples of this category include the studies published by Dehaghani and Soleimani, 76 Alatefi et al, 77 Olofinnika et al, 78 and Al-Khafaji et al 79 Among the prior papers, the recent paper of Alatefi et al 77 is the richest one as it summarizes many , 80 Ng et al, 70 Song et al, 81 and Mao and Jahanbani Ghahfarokhi. 82 • A part of a chapter in books devoted to the application of AI techniques in the petroleum industry or gas injection methods, such chapter four 74 of the book published by Hemmati-Sarapardeh et al 71 and the chapter written by Hadavimoghaddam et al 83 Due to the limited number of reviewed papers in the prior works, our current study provides a comprehensive examination of the application of AI techniques for modeling the MMP of CO 2 -oil systems. By reviewing approximately 80 studies in this area, we shed light on many previously unexplored aspects.…”

“…During the last decades, AI has been one of the most commonly used techniques for estimating the MMP of the CO 2 − oil systems. 71,74 Based on the published papers about the use of AI methods for modeling MMP of the CO 2 − oil systems, four families of AI-based approaches can be distinguished:…”

“…Examples of this category include the review papers published by Du et al, Ng et al, Song et al, and Mao and Jahanbani Ghahfarokhi A part of a chapter in books devoted to the application of AI techniques in the petroleum industry or gas injection methods, such chapter four of the book published by Hemmati-Sarapardeh et al and the chapter written by Hadavimoghaddam et al …”

“…During the last two decades, artificial intelligence (AI) techniques such as machine learning (ML) have emerged as a powerful tool in studying and modeling the behavior of many complicated phenomena in the oil and gas industry. , This family of technique has gained this attention thanks to its various advantages, including the ability to predict the investigated outputs with a satisfactory accuracy, the flexibility to adapt to different complex systems, the possibility to capture the nonlinearity and the complexity of different phenomena, and the simplicity, the low-cost and the good generalization of the resulted paradigms based on the knowledge and learning process. − The modeling of MMP of the systems CO 2 – oil is among the successful examples where AI and ML methods have shown great importance and contribution by delivering many simple-to-use paradigms which can predict this vital parameter easily and with high accuracy . This topic has attracted many researchers and gained noticeable popularity in the petroleum industry since the publication of the earliest paper on the application of AI for predicting MMP of CO 2 – oil systems, namely the study of Huang et al published in 2003.…”