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Keywords: machine learning
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Proceedings Papers
Publisher: Society of Petroleum Engineers (SPE)
Paper presented at the SPE Conference at Oman Petroleum & Energy Show, April 22–24, 2024
Paper Number: SPE-218506-MS
... on the feedback from downhole sensors and other monitoring devices. Machine Learning: Applying machine learning algorithms to continuously learn and adapt to changing reservoir conditions, improving the accuracy of decision-making during the fracturing process. The integration of digital engineered...
Proceedings Papers
Publisher: Society of Petroleum Engineers (SPE)
Paper presented at the SPE Conference at Oman Petroleum & Energy Show, April 22–24, 2024
Paper Number: SPE-218537-MS
... geologist drilling operation mudrock sandstone well logging log analysis neural network reservoir characterization mahmoud artificial intelligence dataset information journal coefficient limitation structural geology rock type elkatatny machine learning functional neural network model...
Proceedings Papers
Publisher: Society of Petroleum Engineers (SPE)
Paper presented at the SPE Conference at Oman Petroleum & Energy Show, April 22–24, 2024
Paper Number: SPE-218557-MS
... the measurements are carried out. We will also discuss a number of research questions on the need to extend the utility of mud gas data beyond the traditional reservoir fluid typing. A physics-based workflow that follows the machine learning modeling approach will be presented and discussed. Example results of two...
Proceedings Papers
Publisher: Society of Petroleum Engineers (SPE)
Paper presented at the SPE Conference at Oman Petroleum & Energy Show, April 22–24, 2024
Paper Number: SPE-218548-MS
... in terms of existing physics principles becomes very significant undertaking. Production data modeling with machine learning By leveraging the vast amounts of data being acquired at well sites and production facilities, management teams may be able to fine tune strategies by "deciphering...
Proceedings Papers
Publisher: Society of Petroleum Engineers (SPE)
Paper presented at the SPE Conference at Oman Petroleum & Energy Show, April 22–24, 2024
Paper Number: SPE-218562-MS
... (1) σ 1 = ( μ 2 + 1 + μ ) 2 σ 3 Abstract The growth of machine learning (ML) approaches has sparked innovations in many applications including hydraulic fracturing design. The crucial drawback in these models is the subjectivity...
Proceedings Papers
Publisher: Society of Petroleum Engineers (SPE)
Paper presented at the SPE Conference at Oman Petroleum & Energy Show, April 22–24, 2024
Paper Number: SPE-218564-MS
...’ increasing complexity and demands. Emerging technologies like artificial intelligence (AI) and machine learning (ML) present hopeful solutions to tackle these obstacles. ML algorithms can analyze large volumes of pipeline data, identify patterns, and uncover valuable insights to optimize pipeline...
Proceedings Papers
M. S. Khan, A. Barooah, H. Ferroudji, M. A. Rahman, I. Hassan, R. Hasan, A. K. Sleiti, S. R. Gomari, M. Hamilton, Q. Marashdeh
Publisher: Society of Petroleum Engineers (SPE)
Paper presented at the SPE Conference at Oman Petroleum & Energy Show, April 22–24, 2024
Paper Number: SPE-218536-MS
... intelligence reservoir surveillance flow metering scenario hassan machine learning ert production monitoring fraction pipeline production logging production control electrical resistance tomography engineering journal concentration rahman khan experimental investigation leak scenario...
Proceedings Papers
Amr Gharieb, Mohamed Adel Gabry, Mohamed Elsawy, Tamer Edries, Walid Mahmoud, Ahmed Algarhy, Nihal Darraj
Publisher: Society of Petroleum Engineers (SPE)
Paper presented at the SPE Conference at Oman Petroleum & Energy Show, April 22–24, 2024
Paper Number: SPE-218560-MS
... machine learning technologies. The evaluation methodology focuses on systematically centralizing, collecting, and structuring data from diverse sources. This includes a spectrum from Excel files and SQL databases to extensive big data, such as videos, hard files etc., spanning various departments...
Proceedings Papers
Mobeen Murtaza, Mujtaba Allowaim, Azeem Rana, Muhammad Shahzad Kamal, Sulaiman Alarifi, Shirish Patel, Mohamed Mahmoud
Publisher: Society of Petroleum Engineers (SPE)
Paper presented at the SPE Conference at Oman Petroleum & Energy Show, April 22–24, 2024
Paper Number: SPE-218563-MS
... fluids and materials artificial intelligence formation damage machine learning inhibitor drilling fluid formulation mineral completion installation and operations drilling fluid selection and formulation reservoir characterization na-ben nacl comprehensive assessment cacl 2 particle...
Proceedings Papers
Wei Chen, Nguyen Tien Hiep, Zhengxin Zhang, Yuelin Shen, Franklin Linares Scarioni, Daniel Cardozo Vasquez, Luis Felipe Gonzalez, Greg Skoff, Yezid Arevalo, Julien Converset
Publisher: Society of Petroleum Engineers (SPE)
Paper presented at the SPE Conference at Oman Petroleum & Energy Show, April 22–24, 2024
Paper Number: SPE-218613-MS
...). This is addressed by domain experts by selecting optimum drilling parameters based on their knowledge and offset performance. A hybrid approach was developed that blended machine-learning algorithms and domain knowledge to automate and improve the design of an optimum operating window for the best drilling...
Proceedings Papers
Publisher: Society of Petroleum Engineers (SPE)
Paper presented at the SPE Conference at Oman Petroleum & Energy Show, April 22–24, 2024
Paper Number: SPE-218631-MS
... different supervised regression machine learning algorithms (Random Forest, Support vector machine, CatBoost, Extra Tree, and Gradient Boosting) were utilized to develop a settling velocity model. In addition, the best-performing model is compared to two existing mechanistic models. The feature variable...
Proceedings Papers
Publisher: Society of Petroleum Engineers (SPE)
Paper presented at the SPE Conference at Oman Petroleum & Energy Show, April 22–24, 2024
Paper Number: SPE-218601-MS
... Abstract The Electrical Submersible Pump (ESP) is the most effective and consistent artificial lift method for medium to high production rates. Although the capital cost of ESP is high, it pales in comparison to the production losses resulting from its failure. Recently, Machine Learning (ML...
Proceedings Papers
Using a Genetic Algorithm to Estimate Bingham Equation Parameters for Rate of Penetration Prediction
Publisher: Society of Petroleum Engineers (SPE)
Paper presented at the SPE Conference at Oman Petroleum & Energy Show, April 22–24, 2024
Paper Number: SPE-218644-MS
... equation artificial intelligence sedimentary rock geology clastic rock evolutionary algorithm bingham dataset wallace modification genetic algorithm bingham equation rop penetration prediction estimate bingham equation parameter western desert machine learning accuracy ftsec...
Proceedings Papers
Publisher: Society of Petroleum Engineers (SPE)
Paper presented at the SPE Conference at Oman Petroleum & Energy Show, April 22–24, 2024
Paper Number: SPE-218620-MS
... lock predictive classification dataset machine learning prediction sery classification novel time sery approach Introduction Artificial lift devices are used in more than 90% of oil wells and account for over 20% of pumps used. Pumps are used to raise production fluids and are required...
Proceedings Papers
Publisher: Society of Petroleum Engineers (SPE)
Paper presented at the SPE Conference at Oman Petroleum & Energy Show, April 22–24, 2024
Paper Number: SPE-218621-MS
... and compared with the base case. geology enhanced recovery modeling & simulation geologist artificial intelligence displacement efficiency spe annual technical conference efficiency exhibition optimization problem chemical flooding methods paper experiment injection machine learning...
Proceedings Papers
Publisher: Society of Petroleum Engineers (SPE)
Paper presented at the SPE Conference at Oman Petroleum & Energy Show, April 22–24, 2024
Paper Number: SPE-218596-MS
... for different producing wells from different reservoirs. unconventional resource economics complex reservoir production logging geologist pressure transient testing flow in porous media fluid dynamics geology production forecasting reservoir surveillance machine learning history blf regime...
Proceedings Papers
Publisher: Society of Petroleum Engineers (SPE)
Paper presented at the SPE Conference at Oman Petroleum & Energy Show, April 22–24, 2024
Paper Number: SPE-218646-MS
..., curing conditions as well as conditions downhole in the wellbore. Using limited data available from experimental evaluations, it is possible to evaluate these properties longer term using machine learning approaches, as well as identify possible patterns in the dataset. This paper tests...
Proceedings Papers
Publisher: Society of Petroleum Engineers (SPE)
Paper presented at the SPE Conference at Oman Petroleum & Energy Show, April 22–24, 2024
Paper Number: SPE-218658-MS
... and provide automatic gas lift control. Flow meters is integrated with machine learning models to ensure measurement accuracy. Machine learning (ML) is used to build the AI agent which embedded in the wellhead edge after fine tuning. Real time data from sensors and meters are sent to the AI agent...
Proceedings Papers
Publisher: Society of Petroleum Engineers (SPE)
Paper presented at the SPE Conference at Oman Petroleum & Energy Show, April 22–24, 2024
Paper Number: SPE-218663-MS
... workflow for power line inspection that leverages machine learning algorithms to automate the process. The proposed workflow for vision inspection of power lines involves capturing high-resolution images of power lines using drones or other unmanned vehicles. These images are then processed using a deep...
Proceedings Papers
Publisher: Society of Petroleum Engineers (SPE)
Paper presented at the SPE Conference at Oman Petroleum & Energy Show, April 22–24, 2024
Paper Number: SPE-218774-MS
... Abstract Objective Risk reduction and increased Fabric Maintenance efficiency using Artificial Intelligence and Machine Learning algorithms to analyze full-facility imagery for atmospheric corrosion detection and classification. Following imagery capture and processing, deficiencies...
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