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Keywords: neural network
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Proceedings Papers
Publisher: Society of Petroleum Engineers (SPE)
Paper presented at the SPE Annual Technical Conference and Exhibition, October 3–5, 2022
Paper Number: SPE-210235-MS
... vector machines, and neural network models were explored in this study and their performances were evaluated by several regression error metrics. Analysis of model results showed the potential of machine learning approach for predicting the FBHP especially in multiphase flow regime. The model results...
Proceedings Papers
Publisher: Society of Petroleum Engineers (SPE)
Paper presented at the SPE Annual Technical Conference and Exhibition, October 3–5, 2022
Paper Number: SPE-210220-MS
... of oil and gas equipment. alert buildup workflow neural network operation auto-encoder upstream oil & gas artificial intelligence predictive maintenance tool threshold deep learning machine learning offshore annulus well a-annulus hyperparameter sequential probability ratio test...
Proceedings Papers
Publisher: Society of Petroleum Engineers (SPE)
Paper presented at the SPE Annual Technical Conference and Exhibition, October 3–5, 2022
Paper Number: SPE-210295-MS
.... upstream oil & gas complex reservoir machine learning reservoir optimization problem taranaki basin neural network reservoir characterization architecture deep learning artificial intelligence co2 storage fracture co2 injection geothermal energy production new zealand co2 storage...
Proceedings Papers
Publisher: Society of Petroleum Engineers (SPE)
Paper presented at the SPE Annual Technical Conference and Exhibition, October 3–5, 2022
Paper Number: SPE-210296-MS
... equipment installation time, decreasing unplanned downtime, and reducing the potential for human error. It also provides operators and field service teams with greater confidence that the wellhead equipment has been properly installed. neural network wellhead installation completion installation...
Proceedings Papers
Publisher: Society of Petroleum Engineers (SPE)
Paper presented at the SPE Annual Technical Conference and Exhibition, October 3–5, 2022
Paper Number: SPE-210369-MS
.... Computer vision applied at the shaker will increase overall ROP, greatly improve the speed and accuracy of wellbore instability detection, reduce the exposure in a hazardous zone and improve the detection of pending downhole problems. neural network upstream oil & gas annular pressure drilling...
Proceedings Papers
Publisher: Society of Petroleum Engineers (SPE)
Paper presented at the SPE Annual Technical Conference and Exhibition, October 3–5, 2022
Paper Number: SPE-210303-MS
... iris knowledge assessment expert system representation neural network safeguard application scenario computational knowledge graph knowledge-based artificial intelligence approach operation information knowledge representation hazardous scenario knowledge graph risk management...
Proceedings Papers
Tarek M. Mostafa, Guang Ooi, Moutazbellah Khater, Mehmet Ozakin, Mohamed Larbi Zeghlache, Hakan Bagci, Shehab Ahmed
Publisher: Society of Petroleum Engineers (SPE)
Paper presented at the SPE Annual Technical Conference and Exhibition, October 3–5, 2022
Paper Number: SPE-210318-MS
.... A framework for artificial neural networks (ANN) is designed to assess the eight outputs and generate a two-dimensional map of the pipe cross-section. The ANN is trained using a finite-difference time-domain electromagnetic forward solver. The designed prototype is tested and validated through simulations...
Proceedings Papers
Publisher: Society of Petroleum Engineers (SPE)
Paper presented at the SPE Annual Technical Conference and Exhibition, October 3–5, 2022
Paper Number: SPE-210309-MS
... intelligence production control prediction neural network co 2 workflow dataset upstream oil & gas north america government production monitoring akhil datta-gupta saturation field-scale application validation dataset realization plume migration application optimization multiplier 0...
Proceedings Papers
Publisher: Society of Petroleum Engineers (SPE)
Paper presented at the SPE Annual Technical Conference and Exhibition, October 3–5, 2022
Paper Number: SPE-209959-MS
... using a hybrid neural network for detecting CO 2 leakage based on bottom-hole pressure measurements. The proposed workflow includes the generation of train-validation samples, the coupling process of training-validating, and the model evaluation. This work solves the diffusivity equation for pressure...
Proceedings Papers
Publisher: Society of Petroleum Engineers (SPE)
Paper presented at the SPE Annual Technical Conference and Exhibition, October 3–5, 2022
Paper Number: SPE-210061-MS
... for pipeline design and operation with corrosion mitigation and management. midstream oil & gas subsurface corrosion upstream oil & gas well integrity corrosion neural network riser corrosion machine learning modeling tsai spe annual technical conference pipeline corrosion application...
Proceedings Papers
Habib Ouadi, Ilyes Mellal, Abderraouf Chemmakh, Sofiane Djezzar, Aldjia Boualam, Ahmed Merzoug, Aimen Laalam, Nadia Mouedden, Youcef Khetib, Vamegh Rasouli, Olusegun Tomomewo
Publisher: Society of Petroleum Engineers (SPE)
Paper presented at the SPE Annual Technical Conference and Exhibition, October 3–5, 2022
Paper Number: SPE-210104-MS
... Regression, Random Forest Regression, XGB Regression, and Artificial Neural Network as well as Grey Wolf Genetic Algorithm, to study the permeability and porosity stress dependency for Bakken Formation in Williston Basin, those methods were compared based on their performance by applying the statistical...
Proceedings Papers
Publisher: Society of Petroleum Engineers (SPE)
Paper presented at the SPE Annual Technical Conference and Exhibition, October 3–5, 2022
Paper Number: SPE-210372-MS
... structural geology air emission history matching pressure transient testing fluid dynamics sustainability waterflooding reservoir simulation gas injection method flow in porous media neural network subsurface storage drillstem testing social responsibility upstream oil & gas united states...
Proceedings Papers
Publisher: Society of Petroleum Engineers (SPE)
Paper presented at the SPE Annual Technical Conference and Exhibition, October 3–5, 2022
Paper Number: SPE-210031-MS
... Analysis (MRA), ANN, and SVM to two case studies. Wang et al. (2020) predicted production at ultra-high water cut stage by means of Recurrent Neural Network (RNN) using existing oil field production data. They conducted experimental verification and application effect analysis to compare the RNN...
Proceedings Papers
Ruben Rodriguez-Torrado, Alberto Pumar-Jimenez, Pablo Ruiz-Mataran, Mohammad Sarabian, Julian Togelius, Leonardo Toro Agudelo, Alexander Rueda, Enrique Gallardo, Ana Maria Naranjo, Sandro Arango, Jose Alberto Villasmil
Publisher: Society of Petroleum Engineers (SPE)
Paper presented at the SPE Annual Technical Conference and Exhibition, October 3–5, 2022
Paper Number: SPE-210133-MS
... dynamics in porous media. An optimization process that exploits Geo-Net speed and finds solutions that minimize the error between observed measurement in the reservoir and the obtained by the simulator. Geological Neural Networks (GEO-NET) and petrophysical characterization The architecture...
Proceedings Papers
Publisher: Society of Petroleum Engineers (SPE)
Paper presented at the SPE Annual Technical Conference and Exhibition, October 3–5, 2022
Paper Number: SPE-210131-MS
..., and the ratio of minimum to mean apertures. We then construct hydraulic aperture surrogates using an Artificial Neural Network (ANN). At the field scale, we deploy Long Short-Term Memory (LSTM) to capture the recovery factor at field-scale. The final results are the time-varying recovery factor and its...
Proceedings Papers
Publisher: Society of Petroleum Engineers (SPE)
Paper presented at the SPE Annual Technical Conference and Exhibition, October 3–5, 2022
Paper Number: SPE-210177-MS
...://doi.org/10.2118/201459-MS Yu , Y. , Si , X. , Hu , C. , and Zhang , J. 2019 . A review of recurrent neural networks: LSTM cells and network architectures . Neural computation , 31 ( 7 ), 1235 – 1270 . Zhu , J. , Forrest , J. , Xiong , H. , and Kianinejad...
Proceedings Papers
Publisher: Society of Petroleum Engineers (SPE)
Paper presented at the SPE Annual Technical Conference and Exhibition, October 3–5, 2022
Paper Number: SPE-210160-MS
... cluster efficiency issue led by the current geometric completion design. Last, using the newly proposed smart sampling algorithm, a 200-critical-case database was built and fed into the Neural Network algorithm for training proxy models. After running the proxy models in a random-search algorithm...
Proceedings Papers
Publisher: Society of Petroleum Engineers (SPE)
Paper presented at the SPE Annual Technical Conference and Exhibition, October 3–5, 2022
Paper Number: SPE-210191-MS
... artificial neural network (ANN) was used as a machine learning approach. To train the neural network, the well data were divided into two sections where the ANN model was optimized on the upper well data interval and tested in the lower interval. During the rock physics analysis, the lower interval...
Proceedings Papers
Publisher: Society of Petroleum Engineers (SPE)
Paper presented at the SPE Annual Technical Conference and Exhibition, September 21–23, 2021
Paper Number: SPE-205985-MS
...’ may be highly subjective, thus, prone to inconsistencies. In our work, we propose to automate the well correlation workflow by using a Soft- Attention Convolutional Neural Network to predict well markers. The machine learning algorithm is supervised by examples of manual marker picks...
Proceedings Papers
Publisher: Society of Petroleum Engineers (SPE)
Paper presented at the SPE Annual Technical Conference and Exhibition, September 21–23, 2021
Paper Number: SPE-205997-MS
... artificial intelligence psia machine learning regressor predictor prediction neural network lightgbm algorithm coefficient artificial proxy feature dew point pressure reservoir temperature relative error dataset upstream oil & gas correlation elsharkawy pseudocritical...