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Low salinity relative permeability curves are required to estimate the benefit of low salinity waterflooding at the field-level. Low salinity benefit is measured from corefloods (i.e., at the plug scale) and the same benefit is often assumed in full field models to generate low salinity curves from high salinity curves (often pseudo curves). The validity of this assumption is investigated. We present how uncertainty distribution of low salinity benefit can be propagated through an ensemble of full field models in which each simulation case could have a set of distinctive high salinity pseudos. A 0.5-ft vertical resolution sector and its 10-ft upscaled counterpart are used. Low salinity benefit from corefloods is used to generate low salinity relative permeabilities for the high-resolution sector. Rock curves (relative permeability curves from corefloods) are used in the high-resolution sector to create "truth" profiles. Pseudo high and low salinity curves are generated for the upscaled sector by history matching high salinity and incremental low salinity truth case profiles. Low salinity benefit from the upscaled model is compared against that of high-resolution sector ("truth" model). It is crucial to include capillary pressure in high resolution models. In the case studied, analogue and published data are used to produce low salinity capillary pressure curves. Our results show that generating low salinity curves for high salinity pseudos using low salinity benefit from corefloods slightly underestimates the true low salinity benefit at field-scale (i.e., low salinity benefit estimated from high-resolution models). This conclusion is consistent for two extreme relative-permeability scenarios tested (i.e., a high total mobility-unfavorable fractional flow and low total mobility-favorable fractional flow). We demonstrate how a set of high salinity relative-permeability data obtained from corefloods, which encompasses a range for fractional flow and total mobility, can be included in ensemble modeling appropriately, and how low salinity benefit could be estimated for such an ensemble. It is adequate to generate low salinity curves for bounding high salinity sets of curves. The bounding low salinity curves can then be used to estimate low salinity curve for any interpolated high salinity curve. This significantly simplifies the process of generating a probability distribution function (pdf) of low salinity benefit for an ensemble of models, where each model has a different high salinity relative permeability. We explain the pseudoization process and how to generate a counterpart low salinity curve for a high salinity relative permeability that honors an estimated low salinity benefit from corefloods. We present how a pdf of low salinity benefit can be built for an ensemble of models with distinctive high salinity curves that each honors the low salinity benefit. The workflow simplifies the process of describing the uncertainty in the benefit of low salinity waterflooding.
Low salinity relative permeability curves are required to estimate the benefit of low salinity waterflooding at the field-level. Low salinity benefit is measured from corefloods (i.e., at the plug scale) and the same benefit is often assumed in full field models to generate low salinity curves from high salinity curves (often pseudo curves). The validity of this assumption is investigated. We present how uncertainty distribution of low salinity benefit can be propagated through an ensemble of full field models in which each simulation case could have a set of distinctive high salinity pseudos. A 0.5-ft vertical resolution sector and its 10-ft upscaled counterpart are used. Low salinity benefit from corefloods is used to generate low salinity relative permeabilities for the high-resolution sector. Rock curves (relative permeability curves from corefloods) are used in the high-resolution sector to create "truth" profiles. Pseudo high and low salinity curves are generated for the upscaled sector by history matching high salinity and incremental low salinity truth case profiles. Low salinity benefit from the upscaled model is compared against that of high-resolution sector ("truth" model). It is crucial to include capillary pressure in high resolution models. In the case studied, analogue and published data are used to produce low salinity capillary pressure curves. Our results show that generating low salinity curves for high salinity pseudos using low salinity benefit from corefloods slightly underestimates the true low salinity benefit at field-scale (i.e., low salinity benefit estimated from high-resolution models). This conclusion is consistent for two extreme relative-permeability scenarios tested (i.e., a high total mobility-unfavorable fractional flow and low total mobility-favorable fractional flow). We demonstrate how a set of high salinity relative-permeability data obtained from corefloods, which encompasses a range for fractional flow and total mobility, can be included in ensemble modeling appropriately, and how low salinity benefit could be estimated for such an ensemble. It is adequate to generate low salinity curves for bounding high salinity sets of curves. The bounding low salinity curves can then be used to estimate low salinity curve for any interpolated high salinity curve. This significantly simplifies the process of generating a probability distribution function (pdf) of low salinity benefit for an ensemble of models, where each model has a different high salinity relative permeability. We explain the pseudoization process and how to generate a counterpart low salinity curve for a high salinity relative permeability that honors an estimated low salinity benefit from corefloods. We present how a pdf of low salinity benefit can be built for an ensemble of models with distinctive high salinity curves that each honors the low salinity benefit. The workflow simplifies the process of describing the uncertainty in the benefit of low salinity waterflooding.
Summary The distribution of low-salinity benefit for an ensemble of models is required to evaluate low-salinity enhanced oil recovery (OREC) projects. To enable this, low-salinity pseudorelative permeability curves are required to estimate the benefit of low-salinity waterflooding at the field level. We present how the low-salinity benefit can be propagated through an ensemble of full-field models in which each simulation case could have a set of distinctive high-salinity pseudos. A 0.5-ft vertical resolution sector and its 10-ft upscaled counterpart are used. Relative permeability curves and the low-salinity benefit from corefloods are used in the high-resolution sector to create profiles. Pseudohigh- and low-salinity curves are generated for the upscaled sector by history matching high-salinity and incremental low-salinity profiles. Low-salinity benefit is typically measured from corefloods and the same benefit is often assumed at the field scale. Our results show that generating low-salinity curves for high-salinity pseudos using low-salinity benefit from corefloods slightly underestimates the true low-salinity benefit at field scale estimated from high-resolution models. This conclusion is consistent for two extreme relative permeability scenarios tested (i.e., a high-total-mobility unfavorable fractional flow and low-total-mobility favorable fractional flow). Including capillary pressure in high-resolution models was crucial. We would have come to another conclusion if we had not used capillary pressure in fine-grid simulation as approximately one-third of the benefit of low-salinity waterflooding was attributable to more favorable capillary pressure under low-salinity injection. We demonstrate how a set of high-salinity relative permeability data obtained from corefloods, which encompasses a range for fractional flow and total mobility, can be included in ensemble modeling appropriately and how low-salinity benefit could be estimated for such an ensemble. It is adequate to generate low-salinity curves for bounding high-salinity sets of curves. The bounding low-salinity curves can then be used to estimate low-salinity curve for any interpolated high-salinity curve. This workflow significantly simplifies the process of generating the distribution of low-salinity benefit corresponding to an ensemble of models which may be calibrated to limited history.
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