Geomechanics in Reservoir Simulation: Overview of Coupling Methods and Field Case Study

The paper addresses the modeling of geomechanical effects induced by reservoir production and their influence on fluid flow in the reservoir. Geomechanical effects induced by reservoir production can be particularly pronounced in stress sensitive reservoirs, such as poorly compacted reservoirs and fractured reservoirs. The authors review the main coupled mechanisms associated with the production of these reservoirs, and describe the different approaches that can be used to solve the coupling between fluid flow and geomechanical problems. A field case study is then presented. A stress dependent reservoir simulator-ATH2VIS-was used to quantify effects associated with the production of a highly heterogeneous and compartmentalized limestone reservoir. This simulator relies on a partial coupling approach with different time steps for reservoir and geomechanical simulations and manages data exchanges at given time intervals between the ATHOSTM reservoir simulator developed at IFP and the VISAGETM geomechanical simulator (VIPS Ltd. , 2001). The results of the coupled reservoir geomechanical simulations indicate that perturbation of the reservoir mechanical equilibrium specifically leads to progressive strain localization on a limited number of faults. Only specific parts of these faults are critically stressed, depending on pore pressure variations in their vicinity, temperature variations, and fault strikes compared with stress orientation. The normal strains resulting from geomechanical computations are interpreted in terms of permeability variations using a fracture and fault permeability model to improve the dynamic description of fluid flow and history matching

Statistical Reservoir Model: calibrating faults and fractures, and predicting reservoir response to water flood

Abstract: This paper describes the new concept of a ‘Statistical Reservoir Model ’ to determine significant well-pair correlations. We solve this conceptual problem using a predictive error filter, combined with Bayesian methods that identify those well pairs that are related to each other with statistical significance, for the Gullfaks reservoir in the North Sea. Significant, long-range, corre-lations in the whole field are found at an optimal time lag of one month. The correlation function for significantly-correlated well pairs, after normalization for the distribution of available wells, shows a long-range power-law decay that is consistent with a critical-point response at the reser-voir scale. A principal component analysis shows a strong correlation with the location and orien-tation of faults that intersect the main producing horizon. A predictive experiment shows that the model performs very well both in history matching and predictive mode on a time scale of about one month. Hydrocarbon reservoirs comprise subsurface bodies of rock of suitable porosity and permeability to allow the storage and transmittal of oil and gas. Producer wells are sunk into a reservoir to allo