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Keywords: prediction
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Proceedings Papers

Paper presented at the SPE Reservoir Simulation Conference, March 28–30, 2023
Paper Number: SPE-212204-MS
... Abstract Integrated reservoir studies for performance prediction and decision-making processes are computationally expensive. In this paper, we develop a novel linearization approach to reduce the computational burden of intensive reservoir simulation execution. We achieve this by introducing...
Proceedings Papers

Paper presented at the SPE Reservoir Simulation Conference, October 26, 2021
Paper Number: SPE-203917-MS
... prediction for no-flow boundary conditions. However, it provides acceptable predictions for constant pressure boundary conditions. We also assessed the capability of the PIML method in handling fractures. The results indicate that the PIML can provide accurate predictions for parallel fractures subjected...
Proceedings Papers

Paper presented at the SPE Reservoir Simulation Conference, October 26, 2021
Paper Number: SPE-203965-MS
... network. After training, the model is tested over large variations of well control settings. Accurate pressure and saturation solutions are predicted along with the injection and production well quantities using the proposed approach. Errors in the predicted quantities of interest are reduced...
Proceedings Papers

Paper presented at the SPE Reservoir Simulation Conference, October 26, 2021
Paper Number: SPE-203924-MS
... those considered in this work. machine learning reservoir simulation fluid dynamics artificial intelligence deep learning geomodel flow in porous media history matching es-mda procedure realization prediction application production well neural network upstream oil & gas time...
Proceedings Papers

Paper presented at the SPE Reservoir Simulation Conference, October 26, 2021
Paper Number: SPE-203953-MS
... Simulators for the prediction of gas production from hydrate accumulations are inevitably complicated because of the need to fully consider the coupled flow, thermal, thermo-dynamic and geochemical processes associated with the hydrate dissociation and formation. A direct result of the complexity...
Proceedings Papers

Paper presented at the SPE Reservoir Simulation Conference, October 26, 2021
Paper Number: SPE-203955-MS
... are presented that illustrate homogeneous and drift-flux flow model differences for various well scenarios. thermal method reservoir simulation well model sagd circulation steam holdup light blue circle steam-assisted gravity drainage prediction well trajectory fraction inclination gas holdup...
Proceedings Papers

Paper presented at the SPE Reservoir Simulation Conference, October 26, 2021
Paper Number: SPE-203962-MS
... simulation simulation dpdp model upstream oil & gas prediction shape factor model closure fracture geometry loss function dataset permeability deep learning training dataset lägerdorf dataset upscaled parameter fine-scale simulation neural network accuracy random linear fracture...
Proceedings Papers

Paper presented at the SPE Reservoir Simulation Conference, October 26, 2021
Paper Number: SPE-204002-MS
... learning sagd upstream oil & gas training data workflow ml time-step predictor prediction static workflow solution state Introduction The prediction of oil and gas recovery from hydrocarbon reservoirs is a challenging modelling activity and requires the use of numerical methods...
Proceedings Papers

Paper presented at the SPE Reservoir Simulation Conference, October 26, 2021
Paper Number: SPE-203987-MS
... and convergence behavior. flow in porous media reservoir simulation hydraulic fracturing upstream oil & gas modeling & simulation complex reservoir average ratio timestep case 2 locality equation of state fluid dynamics prediction convergence behavior fracture network iteration...
Proceedings Papers

Paper presented at the SPE Reservoir Simulation Conference, October 26, 2021
Paper Number: SPE-203976-MS
... successfully captured the physics in the high-fidelity model. The Bayesian-LSTM MCMC produces an accurate prediction with narrow uncertainties. The posterior prediction through the high-fidelity model ensures the robustness and precision of the workflow. This approach provides an efficient and high-quality...
Proceedings Papers

Paper presented at the SPE Reservoir Simulation Conference, April 10–11, 2019
Paper Number: SPE-193855-MS
...-driven model Upstream Oil & Gas network model commercial simulator geo-cellular model history matching Artificial Intelligence prediction producer gpsnet model reservoir simulation observation data well case reservoir management simulator well point historical data society...
Proceedings Papers

Paper presented at the SPE Reservoir Simulation Conference, April 10–11, 2019
Paper Number: SPE-193912-MS
... projection-based model reduction with machine learning techniques to predict multi-phase flow dynamics using considering solutions. In particular, we use POD-DEIM as a global-local model reduction technique and RNN as the machine learning approach. POD performs Galerkin projection on specified spaces, which...
Proceedings Papers

Paper presented at the SPE Reservoir Simulation Conference, April 10–11, 2019
Paper Number: SPE-193904-MS
.... Given relatively moderate data requirements, we show that it is possible to attain a high level of predictability from hidden field state variables and well production data. As the main conclusion of this work, EDMD stands as a promising data- driven choice for efficiently reconstructing flow/fracture...
Proceedings Papers

Paper presented at the SPE Reservoir Simulation Conference, April 10–11, 2019
Paper Number: SPE-193896-MS
... simulations. For the phase stability tests, an ANN model is built to predict the saturation pressures at given temperature and compositions, and consequently the stability can be obtained by comparing the saturation pressure with the system pressure. The prediction accuracy is more than 99% according to our...
Proceedings Papers

Paper presented at the SPE Reservoir Simulation Conference, April 10–11, 2019
Paper Number: SPE-193918-MS
...   . The sensitivity matrix G( m ) is a N d h × N m matrix in which the entry of the ℓ th row and j th column is represented by the partial derivative of the ℓ th predicted datum ( ℓ th entry of the vector of reservoir predictions for the history-matching period, d h ) with respect...
Proceedings Papers

Paper presented at the SPE Reservoir Simulation Conference, April 10–11, 2019
Paper Number: SPE-193838-MS
... parameterization of the error model is needed in order to obtain good estimate of physical model parameters and to provide better predictions. In this study, the last three approaches (i.e. 4, 5, 6) outperform the others in terms of the quality of the estimated parameters and the prediction accuracy (reliability...
Proceedings Papers

Paper presented at the SPE Reservoir Simulation Conference, February 20–22, 2017
Paper Number: SPE-182637-MS
... and production forecasts. The bandwidth and computational throughput provided by GPUs allow such simulations to be performed extremely fast using only a modest amount of hardware. Through this case study, we show that by coupling an advanced history matching, prediction and optimization tool with a fast GPU...
Proceedings Papers

Paper presented at the SPE Reservoir Simulation Conference, February 20–22, 2017
Paper Number: SPE-182696-MS
...Future Directions This simple method seems to predict a weak downward trend at the site, but there is quite a bit of room to improve its predictive capabilities. A significant weakness of this method is that it treats each point in time as an independent variable. One very simple way...
Proceedings Papers

Paper presented at the SPE Reservoir Simulation Conference, February 20–22, 2017
Paper Number: SPE-182660-MS
... identify large-scale geological features such as faults. INSIM-FT remedies this INSIM deficiency. The reliability of INSIM-FT for history-matching, future reservoir performance prediction and reservoir characterization is validated with two synthetic models, and its performance is compared...
Proceedings Papers

Paper presented at the SPE Reservoir Simulation Symposium, February 23–25, 2015
Paper Number: SPE-173206-MS
... model as the additive combination of a growth model and a data-driven model. Numerical results are oriented to illustrate surrogate capabilities for performing a diverse set of SAGD forecasts under uncertainty, for predicting production for a variable number of fractures and for inferring inflow...

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