SPE Middle East Oil and Gas Show and Conference 2019
DOI: 10.2118/195072-ms
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Applications of Artificial Neural Networks in the Petroleum Industry: A Review

Abstract: Oil/gas exploration, drilling, production, and reservoir management are challenging these days since most oil and gas conventional sources are already discovered and have been producing for many years. That is why petroleum engineers are trying to use advanced tools such as artificial neural networks (ANNs) to help to make the decision to reduce non-productive time and cost. A good number of papers about the applications of ANNs in the petroleum literature were reviewed and summarized in tables.… Show more

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Cited by 70 publications
(20 citation statements)
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“…The applications of deep learning (DL) and machine learning (ML) in the petroleum industry have gained more concern [19], particularly in forecasting oil production [20,21], forecasting of pressure-volume-temperature (PVT) properties [22,23], optimizing well placement and oil production [24,25], the prediction of reservoir petrophysical properties, including porosity and permeability [26,27], and oil spill detection [28]. Deep learning has been incorporated into the petroleum industry with the remarkable development of deep learning algorithms, enabling overcoming troublesome concerns in oilfields [21].…”
Section: Introductionmentioning
confidence: 99%
“…The applications of deep learning (DL) and machine learning (ML) in the petroleum industry have gained more concern [19], particularly in forecasting oil production [20,21], forecasting of pressure-volume-temperature (PVT) properties [22,23], optimizing well placement and oil production [24,25], the prediction of reservoir petrophysical properties, including porosity and permeability [26,27], and oil spill detection [28]. Deep learning has been incorporated into the petroleum industry with the remarkable development of deep learning algorithms, enabling overcoming troublesome concerns in oilfields [21].…”
Section: Introductionmentioning
confidence: 99%
“…Deep learning approaches and their implementation have recently grown in the petroleum industry, particularly in reservoir engineering applications (Alkinani et al 2019), including predicting porosity and permeability (Erofeev et al 2019;Ahmadi and Chen 2019), Pressure-Volume, Temperature (PVT) (Goda et al 2003;Alkinani et al 2019), sensitive analysis and history matching, and forecasting oil production (Ahmadi and Bahadori 2015;Montgomery and O'sullivan 2017;Guo et al 2018).…”
Section: Introductionmentioning
confidence: 99%
“…Artificial Neural Networks (ANN) are increasingly used in a wide range of engineering applications [1][2][3][4][5][6][7]. ANN have proven their excellent pattern recognition capability [8], whether optical [9], acoustical [10] or in other multi-feature datasets [11].…”
Section: Introduction-neural Network In Engineering Just a Modern Buzzword?mentioning
confidence: 99%