The Fine Grid Model: GF3

2013 ◽  
pp. 115-128
Author(s):  
P.B. Crean ◽  
T.S. Murty ◽  
J.A. Stronach
Keyword(s):  
Fine Grid ◽  
Grid Model

The Overall Fine Grid Model: GF7

2013 ◽  
pp. 137-166
Author(s):  
P.B. Crean ◽  
T.S. Murty ◽  
J.A. Stronach
Keyword(s):  
Fine Grid ◽  
Grid Model

Evaluation of Singular Value Decomposition (SVD) Enhanced Upscaling in Reservoir Simulation

2020 ◽  
Author(s):  
Xu Zhou ◽  
Mayank Tyagi
Keyword(s):  
Reservoir Simulation ◽  
Homogeneous Model ◽  
Flow Simulation ◽  
Reservoir Modeling ◽  
Base Case ◽  
Fine Grid ◽  
Heterogeneous Model ◽  
Grid Model ◽  
Simulation Results ◽  
Simulation Time

Abstract Reservoir upscaling is an important step in reservoir modeling for converting highly detailed geological models to simulation grids. It substitutes a heterogeneous model that consists of high-resolution fine grid cells with a lower resolution reduced-dimension homogeneous model using averaging schemes. Its objective is to use a coarse grid model to represent a fine grid model, thus to reduce simulation time. The benefit of upscaling in reservoir simulation is that it efficiently saves simulation time, and effectively preserves key features of data for flow simulation. Singular Vector Decomposition (SVD) is a matrix decomposition method. It has been used for image processing and compressing. It has been proved to be capable of providing a good compression ratio, and effectively saves digital image storage space. SVD also has been used in noise suppression and signal enhancement. It has been shown to be effective in reducing noise components arising from both the sound sampling and delivery system. This study evaluates the effect of SVD in parameterization and upscaling for reservoir simulation. A two-phase flow reservoir model was created using data from the SPE tenth comparative solution project [1]. Simulation results show that SVD is valid in the parameterization of permeability values. The reconstructed permeability matrices using certain amount of singular values are good approximations of the original permeability values. Simulation results from SVD processed permeability values are similar to that using the original values. SVD is then applied on the upscaled permeability value to evaluate the effectiveness on upscaling. Simulation results were compared between the base case, upscaled case, and SVD upscaled case. The simulation results did not show a significant improvement in the accuracy of predicting oil production by applying SVD on the upscaled permeability values. It could be because the reconstructed permeability matrix has the same dimension before and after the SVD processing, thus the model accuracy and efficiency are not significantly improved. Future work includes adding more cases to further explore the effect of SVD on upscaling. The number of grid blocks may be increased, and more layers can be added to investigate whether SVD enhance upscaling for larger scale reservoir simulation models.

A Nested-Grid Hydrodynamic/Pollutant Transport Model for Nearshore Areas in Hamilton Harbour

1995 ◽  
Vol 30 (2) ◽  
pp. 205-230 ◽  
Author(s):  
Ioannis K. Tsanis ◽  
Jian Wu
Keyword(s):  
Transport Model ◽  
Pollutant Transport ◽  
Coarse Grid ◽  
Fine Grid ◽  
Flushing Time ◽  
Grid Model ◽  
Hamilton Harbour ◽  
Nested Grid ◽  
Water Elevations ◽  
The Impact

Abstract A nested-grid depth-averaged circulation model was developed and applied to three nearshore areas in Hamilton Harbour: the western basin, LaSalle Park waterfront and the northeastern shoreline. The grid sizes used were 100 m for the whole harbour, and 25 m for the three nearshore areas. General features of current circulation and horizontal mixing times under various wind directions and speeds were obtained for the whole harbour using the coarse-grid model. The fine-grid model (water elevations and current information on the open boundaries were obtained from the whole harbour model) then provided current patterns which were used to drive the pollutant transport model. Simulation results reveal that the current in the fine-grid model is close to the current from the coarse-grid model, while more detailed current structures are explored. The water elevations from the fine-grid model agree well with the elevations from the coarse-grid one. The impact of artificial islands was examined by studying changes in current patterns, pollutant peaks, exposure and flushing time in different locations of concern. The design proposed provides: (i) minimum change in the existing current patterns; (ii) avoidance of pollutant hot spots; and (iii) minimum changes in the flushing time of pollutants.

A New Simulation Layer Optimization and Permeability Upscaling Method for Preserving Critical Reservoir Heterogeneity

2021 ◽  
Author(s):  
Dachang Li ◽  
Corneliu-Liviu Ionescu ◽  
Baurzhan Muftakhidinov ◽  
Byron Haynes ◽  
Bakyt Yergaliyeva
Keyword(s):  
History Matching ◽  
Cost Effective ◽  
Coarse Grid ◽  
Oil Field ◽  
Reservoir Properties ◽  
The Caspian Sea ◽  
Fine Grid ◽  
Grid Model ◽  
Compositional Model ◽  
Permeability Upscaling

Abstract Running a fine grid model with 107 - 109 of cells is possible using a supercomputer with 103 - 106 of CPUs but may not be always cost-effective. The most cost-effective way is to use a coarse grid model that is much smaller but with static/dynamic profiles very close to the fine grid model. This paper proposes a new layer optimization and upscaling method with the aim for creating a consistent coarse grid model. Unlike the industry's existing layer optimization and upscaling methods, the proposed method performs layer optimization and upscaling fully integrated with the Lorenz coefficient and curves (LCC). Coarse grid layers and their permeabilities are created by minimizing the difference between fine and coarse grid LCCs. The process consists of static and dynamic optimizations. The former is measured by LCC while the latter by pressure, GOR, and water-cut. A new LCC-based permeability upscaling method is developed to preserve the fine grid multiphase flow behaviors. A satisfactory coarse grid model is achieved when both static and dynamic criteria are met. The proposed method has been successfully applied to a giant carbonate oil field in the Caspian Sea that consists of a matrix dominated platform and a fracture/karst dominated rim. Due to the field's complex geology and high H2S content (15%), a dual porosity, dual permeability compositional model has been created to model compositional sour crude flow within and between the matrix and fracture/karst features. The reservoir drive mechanisms are fluid expansion, miscible gas injection and aquifer drive. The reservoir is undersaturated and has an abnormally high initial reservoir pressure. The fine-grid static model contains 104 million cells (370×225×625×2) and the optimized upscaled coarse-grid dynamic model has 8.3 million cells (370×225×50×2). The upscaled model can be run efficiently on the company's existing HPC infrastructure with a maximum of 64 CPUs. Excellent matches of the Lorenz coefficient maps for reservoir total/zones and Lorenz curves at all wells between the fine and coarse grid models have been achieved. Matches on the dynamic variables, e.g., pressure, gas breakthrough time, and GOR growth, in all producers are within the defined acceptable tolerances. The high quality of the static and dynamic matches between the coarse- and fine-grid models confirms that the reservoir properties of the coarse-grid model is very close to the fine-grid model and can be used a base model for history matching and uncertainty analysis.

scholarly journals CO$$_{2}$$ Convection in Hydrocarbon Under Flowing Conditions

2021 ◽  
Author(s):  
Trine S. Mykkeltvedt ◽  
Sarah E. Gasda ◽  
Tor Harald Sandve
Keyword(s):  
Enhanced Oil Recovery ◽  
Oil Recovery ◽  
Flow Behavior ◽  
Cost Effective ◽  
Fine Grid ◽  
Cost Effective Method ◽  
Gravity Effects ◽  
Petroleum Resources ◽  
Nearby Point ◽  
Diffusive Processes

AbstractCarbon-neutral oil production is one way to improve the sustainability of petroleum resources. The emissions from produced hydrocarbons can be offset by injecting capture CO$$_{2}$$ 2 from a nearby point source into a saline aquifer for storage or a producing oil reservoir. The latter is referred to as enhanced oil recovery (EOR) and would enhance the economic viability of CO$$_{2}$$ 2 sequestration. The injected CO$$_{2}$$ 2 will interact with the oil and cause it to flow more freely within the reservoir. Consequently, the overall recovery of oil from the reservoir will increase. This enhanced oil recovery (EOR) technique is perceived as the most cost-effective method for disposing captured CO$$_{2}$$ 2 emissions and has been performed for many decades with the focus on oil recovery. The interaction between existing oil and injected CO$$_{2}$$ 2 needs to be fully understood to effectively manage CO$$_{2}$$ 2 migration and storage efficiency. When CO$$_{2}$$ 2 and oil mix in a fully miscible setting, the density can change non-linearly and cause density instabilities. These instabilities involve complex convective-diffusive processes, which are hard to model and simulate. The interactions occur at the sub-centimeter scale, and it is important to understand its implications for the field scale migration of CO$$_{2}$$ 2 and oil. In this work, we simulate gravity effects, namely gravity override and convective mixing, during miscible displacement of CO$$_{2}$$ 2 and oil. The flow behavior due to the competition between viscous and gravity effects is complex, and can only be accurately simulated with a very fine grid. We demonstrate that convection occurs rapidly, and has a strong effect on breakthrough of CO$$_{2}$$ 2 at the outlet. This work for the first time quantifies these effects for a simple system under realistic conditions.

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