1-20 of 101
Keywords: neural network
Close
Follow your search
Access your saved searches in your account

Would you like to receive an alert when new items match your search?
Close Modal
Sort by
Proceedings Papers

Paper presented at the Offshore Technology Conference, May 6–9, 2024
Paper Number: OTC-35108-MS
...Discussion The results presented provide an extensive comparison between the use of VDL and 2D Combined Signals technique to train a convolutional neural network model (CNN). The problem of searching for a log interpretation model using artificial intelligence that helps petrophysicists...
Proceedings Papers

Paper presented at the Offshore Technology Conference, May 6–9, 2024
Paper Number: OTC-35168-MS
... artificial intelligence in general and particularly generative AI could transform the human-machine interaction in the oil and gas industry, covering specific examples in the fields of artificial lift and power generation. neural network artificial lift system deep learning machine learning...
Proceedings Papers

Paper presented at the Offshore Technology Conference, May 6–9, 2024
Paper Number: OTC-35230-MS
... makes it possible to conduct more detailed and accurate forecasts, which can help to improve the safety and efficiency of CO 2 storage projects. geologist air emission neural network petroleum play type deep learning enhanced recovery subsurface storage reservoir surveillance chemical...
Proceedings Papers

Paper presented at the Offshore Technology Conference, May 6–9, 2024
Paper Number: OTC-35306-MS
...-parameter domain. Then, a Convolutional Neural Networks (CNN) architecture is designed to synthesize the outcomes of the clustering analysis with the extensive dataset obtained from Cone Penetration Testing (CPT). This network undergoes a training process using a combination of current program data...
Proceedings Papers

Paper presented at the Offshore Technology Conference, May 6–9, 2024
Paper Number: OTC-35325-MS
... to discrete variabilities in soil conditions. They also reveal potential applications for deep learning in reducing uncertainty in the characterization of areas with complex soils without drastically increasing the scope of a site investigation. geologist neural network mineral artificial...
Proceedings Papers

Paper presented at the Offshore Technology Conference, May 6–9, 2024
Paper Number: OTC-35313-MS
... numerical simulations and data-based models. The available data at a point in the Santos Basin, Brazil, was: 5 deterministic forecast models and 80 members from probabilistic forecast simulations and in-situ wave buoy measurement. Ensemble means and neural networks forecasts were calculated and compared...
Proceedings Papers

Paper presented at the Offshore Technology Conference, May 6–9, 2024
Paper Number: OTC-35364-MS
... the Borssele area. geology deep learning sustainability artificial intelligence geological subdiscipline conditioning cnn interpretation reservoir characterization workflow dataset geologist neural network sustainable development estimation seg technical program expanded abstract...
Proceedings Papers

Paper presented at the Offshore Technology Conference, May 6–9, 2024
Paper Number: OTC-35401-MS
... artifacts that are often observed using conventional imaging or inversion algorithms to deal with sparse gathers. The numerical experiments demonstrated the accuracy and efficiency of these deep learning algorithms on both synthetic data and field data. deep learning geologist neural network...
Proceedings Papers

Paper presented at the Offshore Technology Conference, May 6–9, 2024
Paper Number: OTC-35476-MS
.... geologist sedimentology neural network structural geology sedimentary geology reservoir simulation prediction machine learning variance linear regression crossline integration depositional environment interpolation resistance geological complexity workflow artificial intelligence reservoir...
Proceedings Papers

Paper presented at the Offshore Technology Conference, May 1–4, 2023
Paper Number: OTC-32211-MS
... tensions reasonably, with a reduced number of reliable measurements. Implementation of these techniques can help to extend the useful life of these TTMS. united states government sub-sea system tendon tension tendon tendon 3 neural network machine learning model input prediction mse bridge...
Proceedings Papers

Paper presented at the Offshore Technology Conference, May 1–4, 2023
Paper Number: OTC-32300-MS
... variables such as slug frequency, amplitude, slug volume, etc. The selected model outperformed traditional statistical models such as Non-Parametric Time Series (NPTS) and other deep neural network models such as DeepAR, and Simple Feed Forward. The model was able to match the flow behavior during slugging...
Proceedings Papers

Paper presented at the Offshore Technology Conference, May 1–4, 2023
Paper Number: OTC-32304-MS
... learning models were built and compared with the baseline, such as Gaussian process regressor, random forest, neural network, and natural gradient boosting, with the purpose of identifying the most accurate one. To solve the overfitting issue caused by the small size of the dataset, several strategies have...
Proceedings Papers

Paper presented at the Offshore Technology Conference, May 1–4, 2023
Paper Number: OTC-32427-MS
... (BAUV) equipped with video cameras and mobile edge computing devices. We deploy a deep neural network (DNN) specially trained for a variety of underwater image/video processing tasks. The intelligent computer vision processing unit allows us to navigate and track objects even when the visibility is poor...
Proceedings Papers

Paper presented at the Offshore Technology Conference, May 1–4, 2023
Paper Number: OTC-32428-MS
... of unknown duration between different drilling parameters, a properly designed time series analysis model may be able to capture their relationships and make reasonable predictions. Recurrent Neural Network with long short-term memory (RNN-LSTM) architecture is a deep learning algorithm capable of making...
Proceedings Papers

Paper presented at the Offshore Technology Conference, May 1–4, 2023
Paper Number: OTC-32447-MS
... ; Mahmoud et al., 2021 ) and extra parameters might be included as bite features and mud hydraulics. Through the literature, many techniques were implemented for such purposes as support vector (SVM) machine, artificial neural network (ANN), random forest (RF), gradient tree boosting, convolution neural...
Proceedings Papers

Paper presented at the Offshore Technology Conference, May 1–4, 2023
Paper Number: OTC-32505-MS
... of the calibration dataset with good accuracy. upstream oil & gas flow metering production monitoring deep learning artificial intelligence well aa neural network reservoir surveillance prediction united states government well test production control equation machine learning well test data...

Product(s) added to cart

Close Modal