scholarly journals Methodology for Concurrent Multi-Parametric Physical Modeling of a Target Natural Unfractured Homogeneous Sandstone

Processes ◽  
2020 ◽  
Vol 8 (11) ◽  
pp. 1448
Author(s):  
Joseph Y. Fu ◽  
Xiang’an Yue ◽  
Bo Zhang

In petroleum, geological and environmental science, flow through porous media is conventionally studied complementarily with numerical modeling/simulation and experimental corefloods. Despite advances in numerical modeling/simulation, experimental corefloods with actual samples are still desired for higher-specificity testing or more complex mechanistic studies. In these applications, the lack of advances in physical modeling is very apparent with the available options mostly unchanged for decades (e.g., sandpacks of unconsolidated packing materials, industry-accepted substitutes with fixed/mismatching petrophysical properties such as Berea sandstone). Renewable synthetic porous media with adjustable parameters are the most promising but have not advanced adequately. To address this, a methodology of advanced physical modeling of the fundamental parameters of dominant mineralogy, particle size distribution, packing, and cementation of a target natural porous media is introduced. Based upon the tight physical modeling of these four fundamental parameters, the other derived parameters of interests including wettability, porosity, pore throat size distribution, permeability, and capillary pressure can be concurrently modeled very close as well by further fine-tuning one of the fundamental parameters while holding the rest constant. Through this process, concurrent multi-parametric physical modeling of the primary petrophysical parameters including particle size distribution, wettability, porosity, pore throat size distribution, permeability, capillary pressure behavior in a target sandstone becomes possible.

2017 ◽  
Vol 140 ◽  
pp. 08013 ◽  
Author(s):  
Karsta Heinze ◽  
Xavier Frank ◽  
Valérie Lullien-Pellerin ◽  
Matthieu George ◽  
Farhang Radjai ◽  
...  

2021 ◽  
Author(s):  
Javad Bezaatpour ◽  
Esmaeil Fatehifar ◽  
Ali Rasoulzadeh

Abstract Knowledge of porous media structure is an essential part of the hydrodynamic investigation of fluid flow in porous media. To study soil behavior (as a granular porous media) and water and contaminant movement in the vadose zone, appropriate estimation of soil water retention curve (SWRC) and soil hydraulic conductivity curve (SHCC) has a pivotal role and is one of the most challenging topics for researchers and engineers in soil and water science. The SWCR can be approximated using an accurate particle size distribution (PSD) function. In this study by applying random close packing (RCP) method as an encouraging method for predicting and studying particle configuration, an optimal particle size distribution is developed for coarse-grained soils (0.025 mm < PSD < 3.35mm). The mentioned RCP is generated using heuristic algorithm with merging applicable equations of soil science. For porous media modeling, MATLAB software is used and the predicted results by the optimal model for the parameters of porosity, pressure drop, and saturated hydraulic conductivity are compared with laboratory measurements. Experimental design is conducted by MINITAB and predicted coarse-grained soils structure by the model is compared with 4 sifted soils. The results of the sensitivity analysis showed that the porosity obtained from the model is strongly sensitive to the resolution factor and should be chosen with a sufficiently large amount (higher than 250). Results showed good consistency (up to 95%) between predicted porosity and only 10% difference in pressure drop and permeability with observed measurements.


SPE Journal ◽  
2020 ◽  
pp. 1-15
Author(s):  
Chengdong Yuan ◽  
Wanfen Pu ◽  
Mikhail A. Varfolomeev ◽  
Junnan Wei ◽  
Shuai Zhao ◽  
...  

Summary Conformance control treatment in high-temperature and ultrahigh-salinity reservoirs for easing water/gas channeling through high-permeability zones has been a great challenge. In this work, we propose a deformable microgel that can be used at more than 373.15 K and ultrahigh-salinity conditions (total dissolved solids &gt; 200 kg/m3, Ca2+ + Mg2+ &gt; 10 kg/m3) and present a method for choosing the suitable particle size of the microgel to achieve an optimal match with the pore throat of the core. First, the particle size distribution of the microgel was analyzed to decide d50, d10, and d90 (diameter when cumulative frequency is 50, 10, and 90%, respectively). Coreflooding experiments were conducted under different permeability conditions from 20 to 900 md to investigate the migration and plugging patterns of the microgel by analyzing and fitting injection pressure curves together with the change in the morphology of the produced microgel analyzed by a microscope. The migration and plugging patterns were divided into three patterns: complete plugging; plugging—passing through in a deformation or broken state—deep migration; and inefficient plugging—smoothly passing through—stable flow. The second pattern can be further divided into three subpatterns as strong plugging, general plugging, and weak plugging. Finally, on the basis of five patterns, we build a quantitative matching relation between the particle size distribution of microgel and the pore-throat size of cores by defining three matching coefficients a = d10/d, ß = d50/d, γ = d90/d (d is the average pore-throat diameter). The effectiveness of this quantitative matching relation was verified by evaluating the plugging ability (residual resistance factor) in a post-waterflooding process after the injection of 1.5 pore volume (PV) of microgel. For a strong permeability heterogeneity, the strong plugging is believed to be the expected pattern. The particles size and the pore-throat size should meet the following relationship: 1 &lt; a &lt; 2, 2 &lt; ß &lt; 4, 4 &lt; γ &lt; 6. In this scenario, the deformable microgel particles could achieve both an effective plugging and a deep migration. The quantitative matching relation with multiple matching coefficients determined based on the particle size distribution might help to choose suitable particles more precisely in comparison to the method based on one matching coefficient (mostly, the ratio of the average diameter of particles to the average pore-throat diameter). In addition, the method itself to build a quantitative matching relation according to particle size distribution can be used for designing different particle-type conformance control agents for profile control and water shutoff treatment in field applications.


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