A Review of Reservoir Simulation Techniques and Considerations on Future Developments

Jensen, Ole Krogh

doi:10.3997/2214-4609.201411303

Cited by 2 publications

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

Numerical simulation of interfacial coupling phenomena in two-phase flow through porous media

Ayodele¹,

Bentsen²

2004

Computational Mechanics

View full text Add to dashboard Cite

This paper provides details of the numerical simulation process for the interfacial coupling effect in multiphase flow through porous media. It covers the theoretical background, description of mathematical formulations, basic assumptions in the models, normalization and transformation between Lagrangian and Eulerian formulations, specification of boundary conditions, discretization and grid system, and solution methods. The main advantage of the Lagrangian formalism is that it eliminates the need for space discretization thereby reducing computation time and error. The numerical simulation process was codified into a stand-alone numerical simulator using the Java TM Programming language. Numerical examples obtained from the numerical simulator are presented to show the applicability of the computational technique and to investigate the effects of interfacial coupling and hydrodynamic effects. Numerical results show that interfacial coupling (viscous and capillary) and hydrodynamic effects are insignificant in twophase, cocurrent, horizontal, porous media flow. Sensitivity analyses studies carried out with the simulator show that if the viscous factor in the parameter that control the amount of viscous coupling is taken as the theoretically established value of 2 or below, then the viscous coupling effect is insignificant. Otherwise, the viscous coupling effect would have a greater effect on the physics of flow and might lead to unreasonable results.

show abstract

Numerical simulation of interfacial coupling phenomena in two-phase flow through porous media

Ayodele¹,

Bentsen²

2004

Computational Mechanics

View full text Add to dashboard Cite

show abstract

Deep Learning Based Hydraulic-mechanical Simulation of Petroleum Reservoirs

Wang

Liang

Zhang

et al. 2020

Day 4 Thu, October 29, 2020

View full text Add to dashboard Cite

Knowing that accurate yet time-efficient multihpysical reservoir simulation is a major challenge, we have developed a deep neural network (DNN) based multiphysical simulator to acceletate the geomechanical calculation. We first generated 20,000 pressure -stress pairs by conducting regious multiphysical simulation with various mechanical properties using a full physics reservoir simulator. All data pairs are simulated by 128 *128 grid blocks. We then developed a U-Net network, a proven structure in image segmentation based on convolutional neural network (CNN), and trained the network with the generated data using Tensorflow. The U-Net network takes the pressure field as the input and regresses the stress field in a pixel-to-pixel manner. The model is trained with 100 epochs using Adam optimizer with a learning rate of 0.001 on GPU. The trained network is thereafter deployed in the reservoir simulator to predict the stress field from numerically solved pressure field at time step level. Hence the geomechanical simulation is replaced by the DNN proxy. Our results show that the accuracy of the U-Net network is above 97%, in the metric of mean square error. Moreover, the U-Net network possesses excellent capability for dimension generalization. With the implementation of the proxy DNN simulator, the simulation time spent in the geomechanical module has been reduced by more than 95% on a 256*256 case study. The novelty of our work lies in the pioneering application of DNN method to train and predict the time-dependent stress field, avoiding the curse of dimensionality. Our trained model can be conveniently connected with an existing reservoir simulator, which greatly saves the efforts of code development.

show abstract

A Review of Reservoir Simulation Techniques and Considerations on Future Developments

Cited by 2 publications

References 0 publications

Numerical simulation of interfacial coupling phenomena in two-phase flow through porous media

Numerical simulation of interfacial coupling phenomena in two-phase flow through porous media

Deep Learning Based Hydraulic-mechanical Simulation of Petroleum Reservoirs

Contact Info

Product

Resources

About