Field Scale Production Decline Characteristics During Gravity Drainage

Understanding scaling of enhanced oil/bitumen recovery processes is essential in moving laboratory scale experimental results to field scale. Scaling theory for thermal processes is well understood and has been applied to steam processes. However, scaling of hybrid steam (thermal) /solvent (mass transfer) processes is still not well defined nor well understood. This paper investigates the scaling behavior of hybrid steam/butane gravity drainage processes using reservoir simulation (commercial thermal compositional simulator CMG STARSTM). Previous research has used reservoir simulation to confirm scaling groups for waterflooding. A similar strategy was used in this study whereby the scaling of a hybrid (steam) solvent oil recovery process was examined using reservoir simulations at three different reservoir scales: lab scale, semi-field scale and field scale to examine the influence of the mass transfer mechanisms of diffusion and dispersion on the scalability of the process. In particular, the influence of butane solvent concentration on scaling a steam/butane gravity drainage process was investigated by considering several butane mole fraction concentrations injected with steam (1%, 2%, 5%, 7%, 10%, 15%, 21%, 25% and 50%). Temperature contours, and mole fraction contours of butane in both the oil and gas phases were examined for various solvent injection concentrations to examine scalability. Numerical results are provided with no diffusion and dispersion, diffusion only, dispersion only and with both diffusion and dispersion added to the simulations. Results confirmed scalability of the process with no capillary effects when the simulation results were non-dimensionalized, although there were some issues with material balance errors in some of the simulation results particularly at high solvent concentrations. For low injection concentrations, the contours were almost identical (indicating scalability) for the three scales for the operating condition studied. In addition, capillary effects were also studied, and similar to scaling thermal processes, the capillarity effects influenced scalability of the process under the conditions studied particularly at higher injection concentrations. Scalability using reservoir simulation was generally preserved with low injection concentrations, but unusual behavior was observed at higher injection concentrations (>5%). Oil recovery curves were non-dimensionalized to make comparisons amongst the three scales. The oil recovery curves displayed an unusual S-shaped behavior at higher injection concentrations when capillary effects were included especially for the lab and semi-field scales. In all cases when all of the mechanisms are included (diffusion, dispersion and capillary effects), Scale 1 shows a much faster recovery than Scale 3 which suggests that the lab scale might temporally overestimate the field scale recovery for this particular process scenario.

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Integrated Field-scale Production and Economic Evaluation under Subsurface Uncertainty for the Pattern-driven Development of Unconventional Resources

10.2118/173247-ms ◽

2015 ◽

Cited By ~ 1

Author(s):

Guohua Gao ◽

Jeroen C. Vink ◽

Faruk O. Alpak

Keyword(s):

Economic Evaluation ◽

Scale Production ◽

Field Scale ◽

Unconventional Resources

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Integrated Field-Scale Production and Economic Evaluation Under Subsurface Uncertainty for the Pattern-Driven Development of Unconventional Resources With Analytical Superposition

SPE Reservoir Evaluation & Engineering ◽

10.2118/173247-pa ◽

2015 ◽

Vol 19 (01) ◽

pp. 118-129 ◽

Cited By ~ 1

Author(s):

Guohua Gao ◽

Jeroen C. Vink ◽

Faruk O. Alpak

Keyword(s):

Time Delay ◽

Work Flow ◽

Scale Production ◽

Field Scale ◽

Full Field ◽

Unconventional Resources ◽

Single Pattern ◽

Pattern Development ◽

The Impact

Summary The in-situ upgrading process (IUP) is a thermal-recovery technique that relies on a pattern-based development process, a complicated physical process that involves thermal and mass transfer in porous media, which renders full field-scale reservoir simulations impractical. Although it is feasible to quantify the impact of subsurface uncertainties on recovery for small-scale sector models with experimental design (ED), it is still a very challenging problem to quantify their impact on field-scale quantities. Straightforward upscaling to field scale does not work because such conventional superposition-based methods do not capture the effects of spatial variability in rock and fluid properties and the time delay in sequential pattern development. In this paper, we show that, under certain mild assumptions, an analytical superposition formulation can be developed that propagates the uncertainties of production forecasts and economic evaluations generated from a sector model to full field-scale quantities. One can simplify this formulation further so that the variance of a field-scale quantity is analytically expressed as the variance of the same single-pattern quantity multiplied by a (computable) scaleup factor. This makes it possible to implement a practical uncertainty quantification work flow in which single-pattern results are upscaled to accurate full field results with reliable uncertainty ranges, without the need for full field-scale simulations. We apply the proposed novel superposition and uncertainty-propagation method to a multipattern IUP development, and demonstrate that this work flow produces reliable results for field-scale production and economics as well as realistic uncertainty ranges. Moreover, these results indicate that the scaleup factor for single-pattern results can accurately capture the impact of spatial correlations of subsurface uncertainties, the size of the field-scale model, the time-delay in pattern development, and the discount rate. Uncertainty quantification of field-scale production and economics is a key factor for the successful development of unconventional resources such as extraheavy oil and oil shale with significant rewards in terms of risk management and project profitability. With minor modifications, the proposed method can also be applied to other pattern-driven processes such as the in-situ conversion process (ICP) and steam-assisted gravity drainage.

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