Investigation of Modified Water Chemistry for Improved Oil Recovery: Application of DLVO Theory and Surface Complexation Model

Author(s):  
Alireza Sanaei ◽  
Shayan Tavassoli ◽  
Kamy Sepehrnoori
2020 ◽  
Vol 146 ◽  
pp. 02003
Author(s):  
Moataz Abu-Al-Saud ◽  
Amani Al-Ghamdi ◽  
Subhash Ayirala ◽  
Mohammed Al-Otaibi

Understanding the effect of injection water chemistry is becoming crucial, as it has been recently shown to have a major impact on oil recovery processes in carbonate formations. Various studies have concluded that surface charge alteration is the primary mechanism behind the observed change of wettability towards water-wet due to SmartWater injection in carbonates. Therefore, understanding the surface charges at brine/calcite and brine/crude oil interfaces becomes essential to optimize the injection water compositions for enhanced oil recovery (EOR) in carbonate formations. In this work, the physicochemical interactions of different brine recipes with and without alkali in carbonates are evaluated using Surface Complexation Model (SCM). First, the zeta-potential of brine/calcite and brine/crude oil interfaces are determined for Smart Water, NaCl, and Na2SO4 brines at fixed salinity. The high salinity seawater is also included to provide the baseline for comparison. Then, two types of Alkali (NaOH and Na2CO3) are added at 0.1 wt% concentration to the different brine recipes to verify their effects on the computed zeta-potential values in the SCM framework. The SCM results are compared with experimental data of zeta-potentials obtained with calcite in brine and crude oil in brine suspensions using the same brines and the two alkali concentrations. The SCM results follow the same trends observed in experimental data to reasonably match the zeta-potential values at the calcite/brine interface. Generally, the addition of alkaline drives the zeta-potentials towards more negative values. This trend towards negative zeta-potential is confirmed for the Smart Water recipe with the impact being more pronounced for Na2CO3 due to the presence of divalent anion carbonate (CO3)-2. Some discrepancy in the zeta-potential magnitude between the SCM results and experiments is observed at the brine/crude oil interface with the addition of alkali. This discrepancy can be attributed to neglecting the reaction of carboxylic acid groups in the crude oil with strong alkali as NaOH and Na2CO3. The novelty of this work is that it clearly validates the SCM results with experimental zeta-potential data to determine the physicochemical interaction of alkaline chemicals with SmartWater in carbonates. These modeling results provide new insights on defining optimal SmartWater compositions to synergize with alkaline chemicals to further improve oil recovery in carbonate reservoirs.


2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Qing You ◽  
Yongchun Tang ◽  
Caili Dai ◽  
Mingwei Zhao ◽  
Fulin Zhao

To achieve in-depth profile control of injection water and improve oil recovery, a new profile control agent, termed as dispersed particle gel (DPG), has been developed and reported. In this paper, the morphology of DPG and the factors that influence its morphology are systematically investigated using atomic force microscopy (AFM). The AFM studies show that DPG is composed of small pseudospherical particles and that their sizes can be controlled by adjusting the shearing rate, the initial polymer mass concentration, and the salinity. Dynamic light scattering (DLS) is used to study the effects of the initial polymer mass concentration, the shearing rate, the salinity, and the high-temperature aging on the particle size of DPG. The aggregation ability of DPG is explained using the DLVO theory and space stability theory. This work provides a scientific basis and technical support for the formula design of DPG and its application in the oil and gas field.


SPE Journal ◽  
2018 ◽  
Vol 23 (06) ◽  
pp. 2302-2315 ◽  
Author(s):  
Rasoul Khaledialidusti ◽  
Jon Kleppe

Summary Water chemistry has been shown to affect oil recovery by affecting surface charge and rock dissolution. The single-well chemical-tracer (SWCT) test is a field method to measure residual oil saturation (Sor), in which hydrolysis reaction of an ester has been known as a key process that could displace the equilibrium state of a reservoir by changing formation-water (FW) composition. Because oil mobilization during the SWCT tests causes an error in the measurement of Sor, changes in water chemistry might be a concern for the accuracy of Sor measurements. In our previous work, the extent to which different reservoir parameters might change water composition and the effect of water-chemistry changes on the calcite dissolution and the oil liberation from the carbonate-rock surfaces were extensively evaluated. In this study, the effect of water-chemistry changes on surface-charge alteration at the carbonate/brine interface has been studied by constructing and applying a surface-complexation model (SCM) that couples bulk aqueous and surface chemistry. We present how the pH drop induced by the displacement of the equilibrium state and changes in water chemistry in the formation affect surface charge in a pure-calcite carbonate rock during the SWCT tests. The results show that a pH drop during the SWCT tests while calcium concentration is held constant in the FW by ignoring calcite dissolution yields a less-positive/more-negative surface charge so that wettability of carbonate rock might be altered to a less-oil-wetting state, when the oil is negatively charged. In reality, however, calcite dissolves by water-chemistry changes during the SWCT tests, which leads to an increasing calcium concentration in the FW. Consequently, an SWCT test in carbonates is accompanied by increasing calcium concentration while pH drops, which yields an increase in the surface charge of carbonate rocks. Therefore, the pH drop does not directly affect the surface charge of carbonate rock during an SWCT test, and calcium concentration increased from calcite dissolution could control the surface charge more significantly.


2017 ◽  
Vol 3 (3) ◽  
pp. 33-38 ◽  
Author(s):  
А.V. Аntuseva ◽  
Е.F. Kudina ◽  
G.G. Pechersky ◽  
Y.R. Kuskildina ◽  
А.V., Melgui ◽  
...  

2020 ◽  
Vol 7 ◽  
pp. 116-119
Author(s):  
R.N. Fakhretdinov ◽  
◽  
D.F. Selimov ◽  
A.A. Fatkullin ◽  
S.A. Tastemirov ◽  
...  

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