The Calculation of Oil-water Relative Permeability From Capillary Pressure Data in an Oil-wet Porous Media: Case Study in a Dolomite Reservoir

2013 ◽  
Vol 32 (1) ◽  
pp. 38-50 ◽  
Author(s):  
B. Shabani ◽  
E. Kazemzadeh ◽  
A. Entezari ◽  
J. Aladaghloo ◽  
S. Mohammadi
2015 ◽  
Vol 137 (3) ◽  
Author(s):  
Dong Ma ◽  
Changwei Liu ◽  
Changhui Cheng

Relative permeability as an important petrophysical parameter is often measured directly in the laboratory or obtained indirectly from the capillary pressure data. However, the literature on relationship between relative permeability and resistivity is lacking. To this end, a new model of inferring two-phase relative permeability from resistivity index data was derived on the basis of Poiseuille's law and Darcy's law. The wetting phase tortuosity ratio was included in the proposed model. The relative permeabilities computed from the capillary pressure data, as well as the experimental data measured in gas–water and oil–water flow condition, were compared with the proposed model. Both results demonstrated that the two-phase permeability obtained by proposed model were generally in good agreement with the data computed from capillary pressure and measured in the laboratory. The comparison also showed that our model was much better than Li model at matching the relative permeability data.


SPE Journal ◽  
2021 ◽  
pp. 1-23
Author(s):  
Abdulrauf Rasheed Adebayo

Summary The limiting capillary pressure of foam (Pc*) and foam trapping in porous media are pore-scale foam properties that affect foam transport in porous media. They are strongly influenced by the characteristics of rock pores and throats. Because of experimental limitations, these foam properties are difficult to measure at core scale. As a result, our understanding of their relationship with different pore characteristics is limited. In this paper, novel coreflood and graphical analysis techniques were used to measure Pc* and the foam-trapping coefficient (FTC) at core scale. FTC is a new parameter synonymous to Land’s (1968) trapping coefficient, which describes foam-trapping behavior across an entire range of saturation as opposed to a single endpoint trapped saturation. The scalability of these two foam properties with permeability and other pore characteristics [average pore size (PS), average throat size (TS), average aspect ratio (AR), coordination number (CN), surface area/volume ratio, and reservoir-quality index (RQI)] were also investigated. Pore characteristics of 12 different rock samples were measured from 3D pore-network models generated from high-resolution X-raycomputed-microtomography images. The heterogeneity of the rock samples were quantified by the Dykstra-Parsons index (Dysktra and Parsons 1950), while the RQI and J-function methods were used to classify them according to their storage and flow properties. Each of the measured pore characteristics and their combination [combined pore character (CPC)] were then correlated with Pc* and FTC to understand their respective roles. Furthermore, the data points obtained from the graphical analysis of the coreflood data provided the required input data for a mechanistic foam model for relative permeability of foamed gas (Kovscek and Radke 1994). The estimated relative permeability of foamed gas was then used to study foam mobility in the different pore geometries. The overall results showed the following: P c * has strong negative correlations with all pore characteristics except AR, which has a weak positive correlation. P c * has the strongest correlation with RQI, CPC, and permeability; a moderate correlation with CN and TS; and a very weak correlation with PS. Foam trapping has positive correlations with all pore characteristics except AR, which has a negative correlation. Low AR appears to be responsible for significant trapping of foam in high-permeabilityrocks. Low AR favors more foam trapping, while high AR favors trapping of oil and gas during water imbibition in water-wetrocks. Foam trapping appears to have the dominant control on foam mobility.


Fractals ◽  
2020 ◽  
Vol 28 (03) ◽  
pp. 2050055
Author(s):  
HAIBO SU ◽  
SHIMING ZHANG ◽  
YEHENG SUN ◽  
XIAOHONG WANG ◽  
BOMING YU ◽  
...  

Oil–water relative permeability curve is an important parameter for analyzing the characters of oil and water seepages in low-permeability reservoirs. The fluid flow in low-permeability reservoirs exhibits distinct nonlinear seepage characteristics with starting pressure gradient. However, the existing theoretical model of oil–water relative permeability only considered few nonlinear seepage characteristics such as capillary pressure and fluid properties. Studying the influences of reservoir pore structures, capillary pressure, driving pressure and boundary layer effect on the morphology of relative permeability curves is of great significance for understanding the seepage properties of low-permeability reservoirs. Based on the fractal theory for porous media, an analytically comprehensive model for the relative permeabilities of oil and water in a low-permeability reservoir is established in this work. The analytical model for oil–water relative permeabilities obtained in this paper is found to be a function of water saturation, fractal dimension for pores, fractal dimension for tortuosity of capillaries, driving pressure gradient and capillary pressure between oil and water phases as well as boundary layer thickness. The present results show that the relative permeabilities of oil and water decrease with the increase of the fractal dimension for tortuosity, whereas the relative permeabilities of oil and water increase with the increase of pore fractal dimension. The nonlinear properties of low-permeability reservoirs have the prominent significances on the relative permeability of the oil phase. With the increase of the seepage resistance coefficient, the relative permeability of oil phase decreases. The proposed theoretical model has been verified by experimental data on oil–water relative permeability and compared with other conventional oil–water relative permeability models. The present results verify the reliability of the oil–water relative permeability model established in this paper.


2012 ◽  
Vol 616-618 ◽  
pp. 964-969 ◽  
Author(s):  
Yue Yang ◽  
Xiang Fang Li ◽  
Ke Liu Wu ◽  
Meng Lu Lin ◽  
Jun Tai Shi

Oil and water relative permeabilities are main coefficients in describing the fluid flow in porous media; however, oil and water relative permeability for low - ultra low perm oil reservoir can not be obtained from present correlations. Based on the characteristics of oil and water flow in porous media, the model for calculating the oil and water relative permeability of low and ultra-low perm oil reservoirs, which considering effects of threshold pressure gradient and capillary pressure, has been established. Through conducting the non-steady oil and water relative permeability experiments, oil and water relative permeability curves influenced by different factors have been calculated. Results show that: the threshold pressure gradient more prominently affects the oil and water relative permeability; capillary pressure cannot influence the water relative permeability but only the oil relative permeability. Considering effects of threshold pressure gradient and capillary pressure yields the best development result, and more accordant with the flow process of oil and water in low – ultra low perm oil reservoirs.


SPE Journal ◽  
2017 ◽  
Vol 22 (03) ◽  
pp. 940-949 ◽  
Author(s):  
Edo S. Boek ◽  
Ioannis Zacharoudiou ◽  
Farrel Gray ◽  
Saurabh M. Shah ◽  
John P. Crawshaw ◽  
...  

Summary We describe the recent development of lattice Boltzmann (LB) and particle-tracing computer simulations to study flow and reactive transport in porous media. First, we measure both flow and solute transport directly on pore-space images obtained from micro-computed-tomography (CT) scanning. We consider rocks with increasing degree of heterogeneity: a bead pack, Bentheimer sandstone, and Portland carbonate. We predict probability distributions for molecular displacements and find excellent agreement with pulsed-field-gradient (PFG) -nuclear-magnetic-resonance (NMR) experiments. Second, we validate our LB model for multiphase flow by calculating capillary filling and capillary pressure in model porous media. Then, we extend our models to realistic 3D pore-space images and observe the calculated capillary pressure curve in Bentheimer sandstone to be in agreement with the experiment. A process-based algorithm is introduced to determine the distribution of wetting and nonwetting phases in the pore space, as a starting point for relative permeability calculations. The Bentheimer relative permeability curves for both drainage and imbibition are found to be in good agreement with experimental data. Third, we show the speedup of a graphics-processing-unit (GPU) algorithm for large-scale LB calculations, offering greatly enhanced computing performance in comparison with central-processing-unit (CPU) calculations. Finally, we propose a hybrid method to calculate reactive transport on pore-space images by use of the GPU code. We calculate the dissolution of a porous medium and observe agreement with the experiment. The LB method is a powerful tool for calculating flow and reactive transport directly on pore-space images of rock.


AIChE Journal ◽  
2003 ◽  
Vol 49 (10) ◽  
pp. 2472-2486 ◽  
Author(s):  
C. D. Tsakiroglou ◽  
M. A. Theodoropoulou ◽  
V. Karoutsos

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