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Keywords: machine learning
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Proceedings Papers

Paper presented at the SPE Reservoir Characterisation and Simulation Conference and Exhibition, January 24–26, 2023
Paper Number: SPE-212594-MS
... a machine-learning (ML) proxy model, which reproduces the behavior of a reservoir simulator and results in significant speedup compared to running the numerical simulator. Initially, we generate an ensemble of realizations via the reservoir simulator to train the different ML algorithms. The data set...
Proceedings Papers

Paper presented at the SPE Reservoir Characterisation and Simulation Conference and Exhibition, January 24–26, 2023
Paper Number: SPE-212614-MS
... artificial intelligence deep learning modeling & simulation optimization problem upstream oil & gas neural network australia government matrix scenario prod enhanced geothermal system porous media machine learning fracture inj simulator equation adam prediction operator...
Proceedings Papers

Paper presented at the SPE Reservoir Characterisation and Simulation Conference and Exhibition, January 24–26, 2023
Paper Number: SPE-212600-MS
... specific gravity, viscosity, composition etc. The challenge is to develop a new approach which overcomes the current shortcomings. In this paper a new machine learning based model has been developed using Interactive Multivariate Linear Regression (I-MLR) method by integrating a large number of datasets...
Proceedings Papers

Paper presented at the SPE Reservoir Characterisation and Simulation Conference and Exhibition, January 24–26, 2023
Paper Number: SPE-212669-MS
... fusion geologist big data reservoir characterization uae government upstream oil & gas artificial intelligence machine learning interpretation application drilling well-to-well correlation correlation artificial intelligence assisted operation geology asia government data mining real...
Proceedings Papers

Paper presented at the SPE Reservoir Characterisation and Simulation Conference and Exhibition, January 24–26, 2023
Paper Number: SPE-212592-MS
... in porous media machine learning coefficient correlation toolkit figure algorithm gaussian process regression model watershed segmentation extraction Introduction Permeability is one of essential parameters for characterization of the rock property, and highly relevant to a wide range...
Proceedings Papers

Paper presented at the SPE Reservoir Characterisation and Simulation Conference and Exhibition, January 24–26, 2023
Paper Number: SPE-212620-MS
... uncertainty, where an ensemble of large-scale models is to be considered and the number of required reservoir simulations tends to be even larger. asset and portfolio management machine learning optimization problem uae government upstream oil & gas artificial intelligence reservoir asia...
Proceedings Papers

Paper presented at the SPE Reservoir Characterisation and Simulation Conference and Exhibition, January 24–26, 2023
Paper Number: SPE-212593-MS
... clustering method middle east classification fluid dynamics united states government well logging machine learning reservoir novel semi-supervised clustering method emd carbonate pore size distribution artificial intelligence aa reservoir reservoir characterization histogram carbonate...
Proceedings Papers

Paper presented at the SPE Reservoir Characterisation and Simulation Conference and Exhibition, January 24–26, 2023
Paper Number: SPE-212663-MS
... & simulation chemical flooding methods interaction experiment engineering reservoir simulation optimization problem netherlands government machine learning swaf flooding concentration foam scenario Introduction The production stages of a traditional crude oil project are normally...
Proceedings Papers

Paper presented at the SPE Reservoir Characterisation and Simulation Conference and Exhibition, January 24–26, 2023
Paper Number: SPE-212639-MS
... & gas machine learning darcy generalized correlation spe-212639-ms Introduction Overview Permeability is one of the critical flow properties that need to be determined for most injection and production processes. It impacts as well the resvoir development and mangament plans. Depending...
Proceedings Papers

Paper presented at the SPE Reservoir Characterisation and Simulation Conference and Exhibition, January 24–26, 2023
Paper Number: SPE-212658-MS
... machine learning permeability upstream oil & gas reservoir simulation europe government reservoir storage saline aquifer proceedings carbonate reservoir saturation dataset prediction ssim fractured reservoir equation porosity Introduction A carbonate reservoir is defined...
Proceedings Papers

Paper presented at the SPE Reservoir Characterisation and Simulation Conference and Exhibition, January 24–26, 2023
Paper Number: SPE-212659-MS
... machine learning resolution nanoprobe algorithm transformation temporal resolution tracer breakthrough united states government artificial intelligence breakthrough presented chem-probe tracer analyte nanoprobe tracer spe annual technical conference exhibition producer Introduction...
Proceedings Papers

Paper presented at the SPE Reservoir Characterisation and Simulation Conference and Exhibition, January 24–26, 2023
Paper Number: SPE-212597-MS
.... asia government upstream oil & gas reservoir simulation subsurface storage united states government neural network climate change co 2 society permeability mole fraction tariq machine learning concentration fno deep learning artificial intelligence petroleum engineer mineral...
Proceedings Papers

Paper presented at the SPE Reservoir Characterisation and Simulation Conference and Exhibition, January 24–26, 2023
Paper Number: SPE-212641-MS
.... Nevertheless, a poor WAG design often results in unfavorable oil recovery. This study investigates WAG optimization in a sandstone field using a hybrid numerical-machine learning (ML) model. In this work, we present a hybrid neural approach for optimizing the WAG injection process that can be easily integrated...
Proceedings Papers

Paper presented at the SPE Reservoir Characterisation and Simulation Conference and Exhibition, January 24–26, 2023
Paper Number: SPE-212673-MS
.... Replacing iterative flash calculations partially or completely in obtaining the satisfactorily accurate number of phases and compositionswith machine learning (ML) models is proven to be an efficient strategy to accelerate flash calculation. In this study, support vector machine (SVM), artificial neural...
Proceedings Papers

Paper presented at the SPE Reservoir Characterisation and Simulation Conference and Exhibition, January 24–26, 2023
Paper Number: SPE-212612-MS
...’ efficiency and reduce the interpretation bias by automating the Pc-based pore network characterization and applying machine learning (ML) to capillary pressure modeling. We have also built advanced analytics dashboards to allow for QC and interactive adjustments by the user. The solution defines the pore...
Proceedings Papers

Paper presented at the SPE Reservoir Characterisation and Simulation Conference and Exhibition, January 24–26, 2023
Paper Number: SPE-212666-MS
... it is very expensive from aspects of computational time and investment in the model building process. In this work, the machine learning methods for accurate production forecast that honor the material balance constraints are presented. The presented hybrid model approach consists of several main components...
Proceedings Papers

Paper presented at the SPE Reservoir Characterisation and Simulation Conference and Exhibition, January 24–26, 2023
Paper Number: SPE-212611-MS
... machine learning methods, to obtain fine-scale flow behavior given flow behavior from a low-resolution simulation of an upscaled-reservoir model. We demonstrate our model on a two-phase, deal-oil, and heterogenous oil reservoir, and we reconstruct the oil saturation map of the reservoir. We also...
Proceedings Papers

Paper presented at the SPE Reservoir Characterisation and Simulation Conference and Exhibition, January 24–26, 2023
Paper Number: SPE-212690-MS
... into the accuracy and prediction performances of these machine learning-based proxy models for 3D oil-water systems as well as their efficiency in nonlinearly constrained production optimization for waterflooding applications. upstream oil & gas artificial intelligence gradient united states government...

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