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Keywords: neural network
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Proceedings Papers

Paper presented at the SPE Annual Technical Conference and Exhibition, September 23–25, 2024
Paper Number: SPE-220754-MS
... neural network (NN), creating a map from well-location parameters to the objective function. We utilize the analytical gradient of the NN, resulting in an effective search direction while saving the computational cost associated with stochastic-gradient perturbations. Our method features a novel NN...
Proceedings Papers

Paper presented at the SPE Annual Technical Conference and Exhibition, September 23–25, 2024
Paper Number: SPE-220857-MS
... and generalizability. The developed model performs robust smoke detection with high precision alerting and minimizing false positives from steam images. This application has been deployed in the plant within an end-to-end solution, creating a positive impact on operations. neural network operation detection...
Proceedings Papers

Paper presented at the SPE Annual Technical Conference and Exhibition, September 23–25, 2024
Paper Number: SPE-220921-MS
.... machine learning classification neural network triplet artificial intelligence cnn classifier dataset inspection workflow vector nearest neighbor accuracy similarity damage classification gas equipment component validation backbone Introduction Oil and gas companies across the globe...
Proceedings Papers

Paper presented at the SPE Annual Technical Conference and Exhibition, September 23–25, 2024
Paper Number: SPE-220840-MS
... the decision of whether to run a wireline image log. To achieve this goal, it is necessary to efficiently analyze multiple criteria that would ordinarily be dependent on the speed and subjectivity of human interpretation. The chosen solution involves the combination of convolutional neural networks with feed...
Proceedings Papers

Paper presented at the SPE Annual Technical Conference and Exhibition, September 23–25, 2024
Paper Number: SPE-220917-MS
... reservoir simulation enhanced recovery prediction equation geology evolution multi-step embed journal neural network machine learning arxiv preprint arxiv application latent representation chen Introduction Reservoir simulation is a computational process used to model multi-physics...
Proceedings Papers

Paper presented at the SPE Annual Technical Conference and Exhibition, September 23–25, 2024
Paper Number: SPE-220838-MS
... learning flow in porous media reservoir simulation artificial intelligence neural network scaling method geology rock type machine learning upscaling pcu-dl module accuracy architecture physics-constrained upscaling permeability value reservoir characterization pore segmentation equation...
Proceedings Papers

Paper presented at the SPE Annual Technical Conference and Exhibition, September 23–25, 2024
Paper Number: SPE-220876-MS
... of uncertain model parameters. To tackle these issues, we resort to cutting-edge deep learning (DL) technologies for their universal approximation capability in forward and inverse modeling based on automatic differentiation. In this study, we develop a Deep Neural Network-based History-Matching (DNN-HM...
Proceedings Papers

Paper presented at the SPE Annual Technical Conference and Exhibition, September 23–25, 2024
Paper Number: SPE-220978-MS
..., physical mechanism and constraints are embedded into the data-driven model to make the prediction results satisfy the prior domain knowledge. The transfer learning method based on physics-guided neural network (TL-PG) integrates the seepage theory with sparse spatial data to improve the prediction accuracy...
Proceedings Papers

Paper presented at the SPE Annual Technical Conference and Exhibition, September 23–25, 2024
Paper Number: SPE-221000-MS
..., establishing a new state-of-the-art in the field, offering enhanced accuracy and robustness in seismic data processing. diffusion posterior sampling deep learning neural network artificial intelligence reservoir characterization copaint refined diffusion posterior sampling gaussian noise...
Proceedings Papers

Paper presented at the SPE Annual Technical Conference and Exhibition, September 23–25, 2024
Paper Number: SPE-220991-MS
... fluids and materials drilling fluid management & disposal tripping borehole prediction well planning drillstring design node beijing gat neural network wellbore integrity artificial intelligence pipe machine learning wellbore tripping wellbore geometry mechanism engineering china...
Proceedings Papers

Paper presented at the SPE Annual Technical Conference and Exhibition, September 23–25, 2024
Paper Number: SPE-220954-MS
...) architecture to augment engineering datasets, particularly those related to solid particle erosion ( Ramiro et al., 2018 , Mansi et al., 2020 ). The framework consists of two main components: a generator and a discriminator. These neural networks compete against each other in a process known as adversarial...
Proceedings Papers

Paper presented at the SPE Annual Technical Conference and Exhibition, September 23–25, 2024
Paper Number: SPE-221057-MS
... such as injection rate and pressure data as input and multiphase production rates as output. We combine reduced physics models into a neural network architecture by utilizing two different approaches. In the first approach, the reduced physics model is used for pre-processing to obtain approximate solutions...
Proceedings Papers

Paper presented at the SPE Annual Technical Conference and Exhibition, September 23–25, 2024
Paper Number: SPE-220790-MS
...-decoder structure to do production forecasting. The findings demonstrate that ST-GFE significantly improves prediction accuracy for newly developed wells compared to the purely temporal models, such as recurrent neural network (RNN)-based and Transformer models. ST-GFE adapts to production changes...

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