Reservoir Models for Input into Flow Simulators

1999 ◽  
pp. 177-222
Author(s):  
F. Jerry Lucia
Keyword(s):  
Reservoir Models

Integration of production data into reservoir models

2001 ◽  
Vol 7 (S) ◽  
pp. S65-S73 ◽  
Author(s):  
Dean S. Oliver ◽  
Albert C. Reynolds ◽  
Zhuoxin Bi ◽  
Yafes Abacioglu
Keyword(s):  
Production Data ◽  
Reservoir Models

Impacts of Petrophysical Cut-Offs in Reservoir Models

2004 ◽  
Author(s):  
Bruno J.P. Lalanne ◽  
Gerard J. Massonnat
Keyword(s):  
Reservoir Models

History matching reservoir models simulated from the pluri-Gaussian method

2005 ◽  
Author(s):  
Paul Thomas ◽  
Mickaele Le Ravalec-Dupin ◽  
Frederic Roggero
Keyword(s):  
History Matching ◽  
Reservoir Models ◽  
Gaussian Method

Differences in the Upscaling Procedure for Compositional Reservoir Simulations of Immiscible and Miscible Gas Flooding

2021 ◽  
Author(s):  
Victor de Souza Rios ◽  
Arne Skauge ◽  
Ken Sorbie ◽  
Gang Wang ◽  
Denis José Schiozer ◽  
...  
Keyword(s):  
Computational Cost ◽  
Specific Treatment ◽  
Dynamic Responses ◽  
Scale Model ◽  
Small Scale ◽  
Coarse Scale ◽  
Reservoir Models ◽  
Permeability Upscaling ◽  
Gas Flooding ◽  
Grid Block

Abstract Compositional reservoir simulation is essential to represent the complex interactions associated with gas flooding processes. Generally, an improved description of such small-scale phenomena requires the use of very detailed reservoir models, which impact the computational cost. We provide a practical and general upscaling procedure to guide a robust selection of the upscaling approaches considering the nature and limitations of each reservoir model, exploring the differences between the upscaling of immiscible and miscible gas injection problems. We highlight the different challenges to achieve improved upscaled models for immiscible and miscible gas displacement conditions with a stepwise workflow. We first identify the need for a special permeability upscaling technique to improve the representation of the main reservoir heterogeneities and sub-grid features, smoothed during the upscaling process. Then, we verify if the use of pseudo-functions is necessary to correct the multiphase flow dynamic behavior. At this stage, different pseudoization approaches are recommended according to the miscibility conditions of the problem. This study evaluates highly heterogeneous reservoir models submitted to immiscible and miscible gas flooding. The fine models represent a small part of a reservoir with a highly refined set of grid-block cells, with 5 × 5 cm2 area. The upscaled coarse models present grid-block cells of 8 × 10 m2 area, which is compatible with a refined geological model in reservoir engineering studies. This process results in a challenging upscaling ratio of 32 000. We show a consistent procedure to achieve reliable results with the coarse-scale model under the different miscibility conditions. For immiscible displacement situations, accurate results can be obtained with the coarse models after a proper permeability upscaling procedure and the use of pseudo-relative permeability curves to improve the dynamic responses. Miscible displacements, however, requires a specific treatment of the fluid modeling process to overcome the limitations arising from the thermodynamic equilibrium assumption. For all the situations, the workflow can lead to a robust choice of techniques to satisfactorily improve the coarse-scale simulation results. Our approach works on two fronts. (1) We apply a dual-porosity/dual-permeability upscaling process, developed by Rios et al. (2020a), to enable the representation of sub-grid heterogeneities in the coarse-scale model, providing consistent improvements on the upscaling results. (2) We generate specific pseudo-functions according to the miscibility conditions of the gas flooding process. We developed a stepwise procedure to deal with the upscaling problems consistently and to enable a better understanding of the coarsening process.

Controlling the sedimentological realism of deltaic reservoir models by the use of intelligent sedimentological prior information

First Break ◽  
2014 ◽  
Vol 32 (10) ◽  
Author(s):  
S. Rojas ◽  
V. Demyanov ◽  
M. Christie ◽  
Dan Arnold
Keyword(s):  
Prior Information ◽  
Reservoir Models
Sign in / Sign up

Export Citation Format

Share Document