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Abstract Scoping studies using data from three mature fields suggest that simple workflows that use only essential stratigraphic and facies constraints are as good in capturing overall reservoir fluid flow response as complex, highly constrained workflows that use detailed stratigraphic and facies constraints. Thus, considerable time and cost saving may be realized during initial model building and updating if simple, but appropriate, workflows are used. The reservoirs studied include a Permian-age carbonate reservoir in New Mexico, an Upper Miocene deepwater clastic reservoir in California, and an Eocene-age shallow water clastic reservoir in Venezuela. Two dimensional cross section models of the deepwater clastic reservoir showed that cumulative production and water breakthrough times were essentially the same for models using the two major stratigraphic picks as for models constrained by 12 detailed stratigraphic picks. Three dimensional streamline simulation was used to demonstrate that adding facies and rock type constraints had little impact on recovery factors for a carbonate reservoir scoping project area consisting of 25, 5-spot waterflood patterns. Likewise, a very complex workflow for the shallow water clastic data set from Venezuela constrained by eight facies and 16 detailed stratigraphic picks yielded the same reservoir response as a simple, two facies, and four major stratigraphic picks constrained workflow. These studies suggest that for reservoirs with moderate to high net to gross (>30–40%) or with small differences in the porosity vs. permeability trends of facies/rock types that simple geological modeling workflows are adequate for subsequent fluid flow simulation. Models generated using the shallow water clastic data sets and evaluated using three dimensional streamline simulation showed that varying the semivariogram range parameters by factors between 0.25 and 2 times the data driven range value also had little effect on reservoir response. An important issue surrounds the impact of up-scaling on fluid flow response. Vertical up-scaling by factors commonly used for full field simulation models has little impact on fluid flow response based on studies of the New Mexico carbonate reservoir and the shallow water clastic reservoir in Venezuela. However, areal up-scaling of models generated using a very fine 50 foot areal grid significantly alters the fluid flow characteristics and warrants additional study. Introduction This paper presents the results of several small studies done over the past six years or so that provide insight into how to efficiently build static models for mature fields that preserve those geological features (e.g. heterogeneity) critical to fluid flow. Numerous recent papers have addressed issues critical to mature field characterization, static and dynamic modeling, and management.[1–5] A variety of papers have been published that address specific aspects of how best to capture critical geological heterogeneities in earth models prior to and during upscaling for dynamic simulation.6–14 The primary focus of this paper is to compare the fluid flow response of dynamic models derived from static models generated using stochastic workflows that utilize differing amounts of geological complexity (constraints) using data from a carbonate and two clastic reservoirs. Although not the primary focus of this paper, results from a study of vertical and areal upscaling of a carbonate reservoir are also presented. Carbonate Reservoir Study A scoping study was done in order to assess the effect of incorporating varying amounts of geological detail or constraints using a data-rich portion of the Eunice Monument South Unit (EMSU) reservoir is located in Lea County, New Mexico about 25 miles south of the city of Hobbs (Fig. 1). The field was discovered in 1929 and has produced about 15% of the estimated 1000 MMSTB OOIP from over 250 wells as of early 2001, when this study was completed.
- South America (1.00)
- North America > United States > Texas (1.00)
- North America > United States > California > Kern County (0.28)
- North America > United States > New Mexico > Lea County (0.24)
- Research Report > New Finding (0.86)
- Research Report > Experimental Study (0.86)
- Phanerozoic > Paleozoic > Permian (0.48)
- Phanerozoic > Cenozoic > Neogene > Miocene > Upper Miocene (0.34)
- Geology > Sedimentary Geology > Depositional Environment > Marine Environment > Deep Water Marine Environment (1.00)
- Geology > Rock Type > Sedimentary Rock > Clastic Rock (1.00)
- Geology > Geological Subdiscipline > Stratigraphy (1.00)
- South America > Venezuela > Zulia > Maracaibo Basin > Ayacucho Blocks > Lagunillas Field (0.99)
- North America > United States > Texas > Permian Basin > Yeso Formation (0.99)
- North America > United States > Texas > Permian Basin > Yates Formation (0.99)
- (49 more...)
- Reservoir Description and Dynamics > Reservoir Simulation > Scaling methods (1.00)
- Reservoir Description and Dynamics > Reservoir Fluid Dynamics > Flow in porous media (1.00)
- Reservoir Description and Dynamics > Reservoir Characterization > Geologic modeling (1.00)
- Reservoir Description and Dynamics > Reservoir Characterization > Exploration, development, structural geology (1.00)
Abstract Steady-state upscaling techniques are attractive because they are quick and simple to implement; unlike dynamic methods, there is no need for fine grid simulation and the upscaled properties are not case dependant. They are based on the assumption that either capillary forces (capillary equilibrium limit, CL) or viscous forces (viscous limit, VL) dominate flow. However, the reservoir conditions for which these assumptions are valid have not been clearly defined. It is generally supposed that the CL method is valid at ‘low’ flow rates over ‘small’ lengthscales, while the VL method is valid at ‘high’ flow rates over ‘large’ lengthscales. These qualitative criteria are difficult to properly apply and can be easily violated, yielding significant errors in predicted reservoir performance. We have identified a comprehensive suite of dimensionless groups which can be used to define the validity of steady-state methods. The groups account for the effect of heterogeneity, as well as the other parameters which control the balance between capillary and viscous forces. Numerical simulations have been used to identify the range of values for these groups over which steady-state methods are valid. Our results yield a practical set of quantitative criteria which can be used to determine the validity of steady-state upscaling methods for a wide range of geological models. They capture the effects of capillary trapping and are valid regardless of fluid mobility, wettability or end-point saturation. We test our criteria against three realistic models of small-to intermediate-scale geological heterogeneity. We find that the criteria do a good job of predicting the range of validity for each method, and are conservative in all cases, suggesting that if they are met then steady-state upscaling techniques can be applied with confidence, and may still be valid for slightly less restrictive conditions. However, in the models investigated, we find that the validity of the CL method is restricted to very low flow rates which are unlikely to be encountered in most production scenarios. This is because the CL method overestimates the amount of capillary trapping. In general, VL upscaling is valid over a much more reasonable range of reservoir flow rates. Introduction Steady-state multi-phase upscaling has become increasingly popular because it is fast, robust and computationally cheap (e.g [1–8]). Unlike their dynamic counterparts, steady-state techniques do not need a full fine-grid simulation prior to generating the pseudo (upscaled) rock properties. However, steady-state upscaling is limited to areas in the reservoir where either capillary (capillary limit, CL) or viscous (viscous limit, VL) forces dominate flow. Using steady-state upscaling methods outside their validity range can yield significant errors in predicted recovery (e.g. [6]).
- Europe > Norway > North Sea (0.28)
- North America > United States > Texas (0.28)
- Overview (0.46)
- Research Report > New Finding (0.34)
- Geology > Geological Subdiscipline (0.34)
- Geology > Rock Type > Sedimentary Rock (0.33)
- Europe > Norway > North Sea > Northern North Sea > South Viking Graben > NOAKA Project > Krafla North Prospect > Etive Formation (0.99)
- Europe > Norway > North Sea > Northern North Sea > North Viking Graben > Block 30/6 > Veslefrikk Field > Statfjord Group Formation (0.99)
- Europe > Norway > North Sea > Northern North Sea > North Viking Graben > Block 30/6 > Veslefrikk Field > Dunlin Group Formation (0.99)
- (4 more...)
Abstract A comprehensive reservoir model that provides excellent turnaround time for history match and evaluation of different development scenarios had been developed through careful application of upscaling methods for the large carbonate reservoir of Umm Gudair field located in Kuwait and partitioned neutral zone. The model was built maintaining integrity of the geological model. The detailed geologic model, built using the latest techniques, was very large (157 layers, 10 million cells) and it was necessary to upscale the model into a reasonably sized simulation model that runs smoothly with a good turnaround time to make multiple runs to match 42 years oil/water production and pressure history of about 200 wells. The vertical upscaling were to be done maintaining the integrity of the fine-scale geological model, preserving physics of the displacement process and providing provisions for water shut off jobs implemented through squeezing off bottom perforations. Although the flux-based upscaling techniques provided guidance, it alone was not sufficient to optimize the layering scheme for the simulation model. A hybrid approach combining the elements of the methods of minimizing variation and flux, manual judgment and streamline simulation was applied to generate a vertically upscaled model with 42 layers that effectively replicated the fine-scale fluid flow behavior. Two simulation models were generated with different areal dimensions - a coarse model with 200×200 mt (to accelerate the history match process) and a fine-scale model with 100×100 mt (983,000 active cells) for infill drilling studies. Excellent history match has been achieved and the model has been demonstrated as an effective reservoir management tool for further field development. This paper discusses the steps applied towards effectively converting the geologic model to simulation model through upscaling, the systematic approach towards building the history match model highlighting the critical steps and an overview of the quality of history match. Introduction The Umm Gudair field, located in Kuwait and the Partitioned Neutral Zone, as illustrated in Figure-1 is a large carbonate reservoir spread over an area of about 200 sq.kms. The field consists of two anticlines separated by a gentle dipping saddle area. The primary producing horizon is the Lower Cretaceous carbonate rock located at an average depth of 8200' subsea. The reservoir is approximately 600' thick with maximum oil column of about 400 ft. The field was discovered in 1962 and was put on commercial production by 1968. However, it had been produced at a low rate till 1995 with about 50 wells. Accelerated production plan was implemented later to enhance the production to about three fold with drilling of additional 150 wells and implementing artificial lift in all these wells.
- Asia > Middle East > Kuwait > Ahmadi Governorate > Arabian Basin > Widyan Basin > Umm Gudair Field > Marrat Formation > Sargelu Formation (0.99)
- Asia > Middle East > Kuwait > Ahmadi Governorate > Arabian Basin > Widyan Basin > Umm Gudair Field > Marrat Formation > Najmah Formation (0.99)
- Asia > Middle East > Kuwait > Ahmadi Governorate > Arabian Basin > Widyan Basin > Umm Gudair Field > Marrat Formation > Marrat "C" Formation (0.99)
- (11 more...)
Abstract Any quantitative workflow, designed to constrain reservoir models to 3D/4D seismic data, must rely on petro-elastic modelling (or PEM), which relates fluid and rock properties to elastic ones. Various scales must be accounted for: laboratory cores and well logs, geological and seismic grids, fluid flow simulator models. The petro-elastic model is generally a fine-scale model ("pem"), defined and calibrated for each specific case against core and logs data. Aiming a 4D history matching workflow at the flow model scale, we then need to validate the use of the logs-scale calibrated "pem" at a larger scale, vertically and laterally. In this paper we proposed a methodology to define an upscaled "PEM" (new set of relationships valid at reservoir-scale), by tuning a fine-scale existing "pem", adjusting the most sensitive and relevant parameters, by an optimisation procedure. Some previous studies already addressed downscaling problems (from reservoir to geological/seismic scale), but no previous work has proposed any solution for an upscaled PEM. The main results of this study, using real field data, are the following:upscaling is necessary, depending on the degree of static and dynamic heterogeneity; the optimisation procedure is successful in calibrating a fine-scale "pem" to get a reservoir-scale "PEM"; the procedure is sensitive to the Backus averaging parameters, which must be defined carefully; this workflow is performed at wells in this study, but could be extended to reservoir scale, when a fine-scale geological model is available Introduction This study was motivated by the use of 4D seismic data, in particular in History-Matching. One possible approach, consists of applying the matching loop at the elastic domain level and at the reservoir scale, making use of a petro-elastic model to convert fluid properties and static rock properties into simulated elastic properties. This was developed during the HUTS project [Ref. 1, 2, 3)]. Coupling such a rock physics module, or petro-elastic model (PEM) with fluid flow modelling, the simulated elastic parameters (impedances) can be predicted before and during production. This can then enable the changes in rock and fluid properties to be compared with the changes inferred from the seismic surveys, thus providing additional information for computer-aided history matching. Other studies [Ref. 4, 5] also propose similar quantitative work, each applying a different approach in terms of the objective function used to minimising the mismatch between ‘observed’ seismic and computed impedances (PEM), and/or domain scale. There are indeed various scales to be considered and accounted for within the above mentioned 4D history matching workflow, or any quantitative approach: laboratory cores and well logs, geological and seismic grids, fluid flow simulator models. Since the PEM is to be used for seismic modelling and history matching of reservoir models, it can be applied at any of these above-mentioned scales. Other authors [Ref. 6] propose the geological scale as the domain for the history matching, thereby simulating the PEM at the same scale as the geostatistical simulation grid, i.e. generating synthetic saturation/pressure with the fluid flow simulator, downscaling to the fine geological model scale and then computing the elastic properties.