Permeability Upscaling Techniques for Reservoir Simulation

Salazar, M. Uzcategui; Piamo, Jose Villa

doi:10.2523/106679-ms

Cited by 3 publications

(3 citation statements)

References 7 publications

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“…: pore volume of sample , cm 3 : bulk volume of sample , cm 3 ∅: effective porosity , fraction The permeability was measured for the all core plug samples using the conventional steady state method with injecting of nitrogen gas through the plug samples with known viscosity of the applied gas, Figure ( The gas permeability for all samples were run with five points of mean pore pressure including (150,175,200, 225,250) psi respectively. The results of gas apparent permeabilities of each sample were plotted with the inverse of applied pore pressure for each permeability measurement, as shown in Figure (5). A straight line is interconnected all points and intersects the y-axis (apparent) permeability where inverse of pore pressure equal to zero presents the mean pore pressure tends to infinity [29].…”

Section: Methodsmentioning

confidence: 99%

“…Permeability is an essential parameter for the evaluation of reservoir potentiality and production rate estimation of a specific field. In addition, this parameter can be used in reservoir simulation of particular rock type [1,2,3,4,5]. The liquid permeability only measure for a specific rock interval and from a limited number of core samples.…”

Section: Introductionmentioning

confidence: 99%

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Liquid and Gas Corrected Permeability Correlation for Heterogeneous Carbonate Reservoir Rocks

Mustafa¹,

Rashid²,

Ismail³

2020

KJAR

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Permeability is considered as an efficient parameter for reservoir modelling and simulation in different types of rocks. The performance of a dynamic model for estimation of reservoir properties based on liquid permeability has been widely established for reservoir rocks. Consequently, the validated module can be applied into another reservoir type with examination of the validity and applicability of the outcomes. In this study the heterogeneous carbonate reservoir rock samples of the Tertiary Baba Formation have been collected to create a new module for estimation of the brine permeability from the corrected gas permeability. In addition, three previously published equations of different reservoir rock types were evaluated using the heterogenous carbonate samples. The porosity and permeability relationships, permeability distribution, pore system and rock microstructures are the dominant factors that influenced on the limitation of these modules for calculating absolute liquid permeability from the klinkenberg-corrected permeability. The most accurate equation throughout the selected samples in this study was the heterogenous module and the lowest quality permeability estimation was derived from the sandstone module.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Liquid and Gas Corrected Permeability Correlation for Heterogeneous Carbonate Reservoir Rocks

Mustafa¹,

Rashid²,

Ismail³

2020

KJAR

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“…For example, a high permeability streak channel in a reservoir region often leads to early water breakthrough, computing effective absolute permeability together with original rock relative permeabilities cannot capture this behaviour, unless a multi-phase upscaling is performed. Salazar et al (2007) in their studies concluded that the two-phase upscaling generated better flow behaviour than the single-phase upscaling. They further stated that the most important aspect in upscaling is the upscaling ratio, which determines the accuracy of production predictability.…”

Section: Single-phase or Multi-phase Upscaling?mentioning

confidence: 99%

Upscaling for Thermal Recovery

Abubakar¹,

Muggeridge²,

King³

2014

SPE International Heavy Oil Conference and Exhibition

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Thermal recovery is one of the most widely applied EOR methods worldwide. It is used mainly to improve the recovery of more viscous oils. Heat is used primarily to reduce the viscosity of oil but may also improve recovery by other mechanisms such as oil expansion, steam distillation and reduction in capillary forces. As a result, the prediction of thermal recovery performance requires more complex and computationally demanding numerical simulations than is the case when evaluating a waterflood. The simulator has to evaluate the impact of both heat transfer and compositional behaviour on the fluid flows.In most cases the engineer will have to use coarser grids in the simulation models than would be needed for a waterflood in order to keep simulation times within acceptable limits. However, it has been shown in the modelling of other EOR processes that in fact much finer grids may be needed to capture the frontal dynamics of the displacement than would be the case in waterflooding. As a result, the simulation of steamflooding on the field scale is unlikely to capture the impact of small scale heterogeneity on flow, as well as being severely affected by numerical dispersion. The ideal solution is to use homogenization to capture the effects of sub-grid-block heterogeneity combined with advanced numerical techniques such as dynamic/adaptive gridding or higher order schemes to reduce the impact of numerical diffusion and dispersion. However, such methods are not currently available in the commercial simulators available to most engineers.The alternative is to use upscaling, but as yet there are no upscaling methodologies suitable for thermal oil recovery methods. Upscaling is a way of altering the inputs to numerical flow models so that simulations run on a coarse grid. These will a) predict the impacts on flow of sub-grid heterogeneity (homogenization) and b) will be less affected by numerical dispersion. For waterflooding this is typically achieved by calculating the effective absolute permeability for each coarse grid cell. In many cases, it is also necessary to upscale the well index and the transmissibilities of the well blocks. Upscaling the absolute permeability, the well index and the well block transmissibilities, ensures that the overall pressure drop for single phase flow between wells is correctly predicted in the coarse grid, whilst upscaling the relative permeabilities ensures that the two-phase flow effects (pressure drop, breakthrough time and water cut development) are correctly modelled. Although there is a significant literature on single-phase upscaling and the development of pseudo relative permeabilities for waterflooding applications, these methods do not capture the heat transport or the impact of temperature on the oil mobility. ivIn this research, a combination of pseudoisation procedures (by making reasonable assumptions) with the Buckley-Leverett solution approximated for thermal EOR processes is used to derive analytical pseudo-relative permeabilities for both hot water and steam ...

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Quantification of Simulation Model Grid Size Impact on Polymer Flooding Application in Heavy Oil Heterogeneous Reservoir

et al. 2016

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Polymer flooding can be a viable alternative to enhance oil recovery of heavy oil fields. The comparison of water and polymer flooding requires a reliable reservoir numerical model to safely ensure the decision analysis including uncertainties and involving a significant amount of simulation runs. Reservoir engineers usually work-around this problem using fast models to reduce computational time; however, it is important to maintain the reliability of heterogeneous reservoir models. Therefore, the proposed work demonstrates how the grid size impacts on accuracy of results and both the time and computational resources. In addition, it is performed an analysis to establish how the typical physical phenomena related to the polymer flooding impact the applicability of the proposed methodology. A highly heterogeneous heavy oil field is used in our proposed studies. The application is conducted to assist pilot test wells. Initially, the definition of the reference strategy (OTM) is presented. In this case study, the OTM strategy is based on the optimization of location and number of wells. Secondly, the effect of grid size on the process is evaluated through two procedures: (1) DA method: a selection of grid size defined by drainage area of the selected wells; and (2) UP method: upscaling is performed in the simulation model. Then, production parameters resulting from models of both procedures (DA and UP) are compared with OTM results. The definition of which procedure is better to represent the wells of interest is performed. Finally, the impact of three polymer flooding physical phenomena (degradation, adsorption and Non-Newtonian effect) on production results is presented, in order to verify the accuracy of the generated fast models in maintained considering these effects. The DA method present good accuracy for reservoir response compared to the reference OTM results. Differently, UP models are not as accurate as DA models for production results indicators. In conclusion, the application of the methodology allows choosing the DA over the UP technique to support our decision in the investigated recovery methods, showing a reliable and fast procedure. Finally, this procedure shows excellent applicability and robustness when a typical polymer flooding study is carried out: the evaluation of physical phenomena impact on production results based on wells of interest.

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Permeability Upscaling Techniques for Reservoir Simulation

Cited by 3 publications

References 7 publications

Liquid and Gas Corrected Permeability Correlation for Heterogeneous Carbonate Reservoir Rocks

Liquid and Gas Corrected Permeability Correlation for Heterogeneous Carbonate Reservoir Rocks

Upscaling for Thermal Recovery

Quantification of Simulation Model Grid Size Impact on Polymer Flooding Application in Heavy Oil Heterogeneous Reservoir

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