Impact of the injected water salinity on oil recovery from sandstone formations: Application in an Egyptian oil reservoir

Snosy, M. Fouad; Ela, Mahmoud Abu El; El-Banbi, Ahmed; Sayyouh, Helmy

doi:10.1016/j.petlm.2021.03.006

Cited by 7 publications

(4 citation statements)

References 13 publications

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“…In addition, Alotaibi and Nasr-El-Din (2019) suggested that there is a critical salinity (not the lowest), at which the IFT between oil and brine is at a minimum level. Snosy et al (2020) and Snosy et al (2021) reported the same results from the sandstone reservoir.…”

Section: Salinity Range For the Lswf Applicationssupporting

confidence: 62%

Comprehensive investigation of low salinity waterflooding in carbonate reservoirs

Snosy

Ela

El-Banbi

et al. 2021

J Petrol Explor Prod Technol

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Waterflooding has been practiced as a secondary recovery mechanism for many years with no regard to the composition of the injected brine. However, in the last decade, there has been an interest to understand the impact of the injected water composition and the low salinity waterflooding (LSWF) in oil recovery. LSWF has been investigated through various laboratory tests as a promising method for improving oil recovery in carbonate reservoirs. These experiments showed diverse mechanisms and results. In this study, a comprehensive review and analysis for results of more than 300 carbonate core flood experiments from published work were performed to investigate the effects of several parameters (injected water, oil, and rock properties along with the temperature) on oil recovery from carbonate rock. The analysis of the results showed that the water composition is the key parameter for successful waterflooding (WF) projects in the carbonate rocks. However, the salinity value of the injected water seems to have a negligible effect on oil recovery in both secondary and tertiary recovery stages. The study indicated that waterflooding with optimum water composition can improve oil recovery up to 30% of the original oil in place. In addition, the investigation showed that changing water salinity from LSWF to high salinity waterflooding can lead to an incremental oil recovery of up to 18% in the tertiary recovery stage. It was evident that applying the optimum composition in the secondary recovery stage is more effective than applying it in the tertiary recovery stage. Furthermore, the key parameters of the injected water and rock properties in secondary and tertiary recovery stages were studied using Fractional Factorial Design. The results revealed that the concentrations of Mg2+, Na+, K+, and Cl− in the injected water are the greatest influence parameters in the secondary recovery stage. However, the most dominant parameters in the tertiary recovery stage are the rock minerals and the concentration of K+, HCO3−, and SO42− in the injected water. In addition, it appears that the anhydrite percentage in the carbonate reservoirs may be an effective parameter in the tertiary WF. Also, there are no clear relations between the incremental oil recovery and the oil properties (total acid number or total base number) in both secondary and tertiary recovery stages. In addition, the results of the analysis showed an incremental oil recovery in all ranges of the studied flooding temperatures. The findings of this study can help to establish guidelines for screening and designing optimum salinity and composition for WF projects in carbonate reservoirs.

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Section: Salinity Range For the Lswf Applicationssupporting

confidence: 62%

Comprehensive investigation of low salinity waterflooding in carbonate reservoirs

Snosy

Ela

El-Banbi

et al. 2021

J Petrol Explor Prod Technol

Self Cite

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show abstract

“…A thorough literature survey was conducted with the aim of not only including the available experimental data but also identifying the effective parameters in a coherent, logical, and technically sound methodology. In this regard, 99 studies ,,,− ,,,,,,,− ,,,− were inspected and analyzed carefully for the purpose of this research work. Five general categories of rock (13 features), oil (eight features), brine (22 features), and connate water properties (22 features) as well as the operational parameters (five features) were recognized.…”

Section: Methodsmentioning

confidence: 99%

Data-Driven Connectionist Models for Performance Prediction of Low Salinity Waterflooding in Sandstone Reservoirs

et al. 2021

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Low salinity waterflooding (LSWF) and its variants also known as smart water or ion tuned water injection have emerged as promising enhanced oil recovery (EOR) methods. LSWF is a complex process controlled by several mechanisms and parameters involving oil, brine, and rock composition. The major mechanisms and processes controlling LSWF are still being debated in the literature. Thus, the establishment of an approach that relates these parameters to the final recovery factor (RFf) is vital. The main objective of this research work was to use a number of artificial intelligence models to develop robust predictive models based on experimental data and main parameters controlling the LSWF determined through sensitivity analysis and feature selection. The parameters include properties of oil, rock, injected brine, and connate water. Different operational parameters were considered to increase the model accuracy as well. After collecting the relevant data from 99 experimental studies reported in the literature, the database underwent a comprehensive and rigorous data preprocessing stage, which included removal of duplicates and low-variance features, missing value imputation, collinearity assessment, data characteristic assessment, outlier removal, feature selection, data splitting (80–20 rule was applied), and data scaling. Then, a number of methods such as linear regression (LR), multilayer perceptron (MLP), support vector machine (SVM), and committee machine intelligent system (CMIS) were used to link 1316 data samples assembled in this research work. Based on the obtained results, the CMIS model was proven to produce superior results compared to its counterparts such that the root mean squared rrror (RMSE) values for both training and testing data are 4.622 and 7.757, respectively. Based on the feature importance results, the presence of Ca2+ in the connate water, Na+ in the injected brine, core porosity, and total acid number of the crude oil are detected as the parameters with the highest impact on the RFf. The CMIS model proposed here can be applied with a high degree of confidence to predict the performance of LSWF in sandstone reservoirs. The database assembled for the purpose of this research work is so far the largest and most comprehensive of its kind, and it can be used to further delineate mechanisms behind LSWF and optimization of this EOR process in sandstone reservoirs.

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“…These results explained that the preflush salinity in the preflush stage affected the oil recovery. The mechanism of the salinity effect was described by others in their published works [4,66,67]. For this study, we focused mainly on the displacement efficiency when the Si-NF was used after that preflush salinity.…”

Section: Effect Of Preflush Salinitymentioning

confidence: 99%

An Experimental Study of the Influence of the Preflush Salinity on Enhanced Oil Recovery Using Silica-Based Nanofluids

et al. 2021

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The underlying effect of preflush salinity and silica nanofluid (Si-NF) on oil production is examined. The influence of salinity on the stability of Si-NFs is studied. A series of sand-pack floodings evaluating oil production was conducted at different concentrations of preflush salinity (0 to 4 wt.%), followed by the injection of a Si-NF (0.5 wt.%) at the trail of which postflush water was injected. The effluent water and solids were collected and analyzed using X-ray fluorescence (XRF). Interfacial tension (IFT) and contact angle measurements were conducted on the Si-NF in the presence of salinity to confirm the effect. The Si-NF became unstable and formed precipitate in the presence of salinity. The sand-pack flooding showed that when the preflush salinity was increased, the displacement efficiency (ED) using the Si-NF and postflush injection was increased (ED = 44%). The XRF of the precipitated effluent revealed that the preflush salinity and Si-NF caused mineral leaching, which triggered pore clogging. The IFT value reduced from 13.3 to 8.2 mN/m, and the wettability was altered to be more strongly water-wet when the salinity increased. The primary mechanisms of oil recovery using the Si-NF after preflush salinity is attributed mainly to the clogging mechanism. This clogging helps block the high-perm area, shift the fluid flow to the oil-trapped zone, and free the oil out. Other contribution mechanisms are IFT reduction and wettability alteration.

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Impact of the injected water salinity on oil recovery from sandstone formations: Application in an Egyptian oil reservoir

Cited by 7 publications

References 13 publications

Comprehensive investigation of low salinity waterflooding in carbonate reservoirs

Comprehensive investigation of low salinity waterflooding in carbonate reservoirs

Data-Driven Connectionist Models for Performance Prediction of Low Salinity Waterflooding in Sandstone Reservoirs

An Experimental Study of the Influence of the Preflush Salinity on Enhanced Oil Recovery Using Silica-Based Nanofluids

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