saponification of oil experiment

Determination of saponification value of the given oil/fat

Principle : Saponification value is defined as the number of milligrams of KOH required to completely hydrolyse (saponify) one gram of the oil/fat. In practice a known amount of the oil or fat is refluxed with excess amount of standard alcoholic potash solution and the unused alkali is titrated against a standard acid. 1

REQUIREMENTS

Apparatus:     Conical flask

Burette and Pipette

phenolphthalein

0.5 N alcoholic potassium-hydroxide solution

Calculation

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Saponification Value of Fats and Oils as Determined from 1 H-NMR Data: The Case of Dairy Fats

Mihaela ivanova.

1 Department of Milk and Dairy Products, Technological Faculty, University of Food Technologies, 26 “Maritsa” Blvd., 4002 Plovdiv, Bulgaria; gb.vidvolp-tfu@avonavim (M.I.); [email protected] (G.I.)

Anamaria Hanganu

2 Department of Organic Chemistry, Biochemistry and Catalysis, Research Centre of Applied Organic Chemistry, Faculty of Chemistry, University of Bucharest, 90-92 Panduri Street, 050663 Bucharest, Romania; moc.oohay@unagnah_airamana

3 “C.D. Nenitescu” Centre of Organic Chemistry of the Romanian Academy, 202B Spl. Independentei, 060023 Bucharest, Romania; moc.liamg@ehcaravatssirc (C.S.); [email protected] (C.D.)

Raluca Dumitriu

4 “C.D. Nenitescu” Organic Chemistry Department, Faculty of Chemical Engineering and Biotechnologies, University POLITEHNICA of Bucharest, 1-7 Polizu Street, 011061 Bucharest, Romania; moc.oohay@uirtimud_ular (R.D.); [email protected] (M.T.)

Mihaela Tociu

Galin ivanov, cristina stavarache.

5 Advanced Polymer Materials Group, University POLITEHNICA of Bucharest, 1-7 Gh. Polizu Street, 011061 Bucharest, Romania

Liliana Popescu

6 Department of Oenology and Chemistry, Food Technology, Faculty of Food Technology, Technical University of Moldova, 9/9 Studentilor Street, MD-2045 Chisinau, Moldova; [email protected] (L.P.); [email protected] (A.G.-M.); [email protected] (R.S.)

Aliona Ghendov-Mosanu

Rodica sturza, calin deleanu.

7 “Petru Poni” Institute of Macromolecular Chemistry of the Romanian Academy, Aleea Grigore Ghica Voda 41A, 700487 Iasi, Romania

Nicoleta-Aurelia Chira

Associated data.

Data is contained within the article or supplementary material .

The saponification value of fats and oils is one of the most common quality indices, reflecting the mean molecular weight of the constituting triacylglycerols. Proton nuclear magnetic resonance ( 1 H-NMR) spectra of fats and oils display specific resonances for the protons from the structural patterns of the triacylglycerols (i.e., the glycerol backbone), methylene (-CH 2 -) groups, double bonds (-CH=CH-) and the terminal methyl (-CH 3 ) group from the three fatty acyl chains. Consequently, chemometric equations based on the integral values of the 1 H-NMR resonances allow for the calculation of the mean molecular weight of triacylglycerol species, leading to the determination of the number of moles of triacylglycerol species per 1 g of fat and eventually to the calculation of the saponification value (SV), expressed as mg KOH/g of fat. The algorithm was verified on a series of binary mixtures of tributyrin (TB) and vegetable oils (i.e., soybean and rapeseed oils) in various ratios, ensuring a wide range of SV. Compared to the conventional technique for SV determination (ISO 3657:2013) based on titration, the obtained 1 H-NMR-based saponification values differed by a mean percent deviation of 3%, suggesting the new method is a convenient and rapid alternate approach. Moreover, compared to other reported methods of determining the SV from spectroscopic data, this method is not based on regression equations and, consequently, does not require calibration from a database, as the SV is computed directly and independently from the 1 H-NMR spectrum of a given oil/fat sample.

1. Introduction

One of the most common oil quality indices is the saponification value (SV); it is defined as the amount of alkali (expressed as mg KOH/g sample) required to saponify a defined amount of sample. It is conventionally determined through saponification of a known amount of oil/fat with excess KOH solution, followed by back titration of the excess base with acid solution in the presence of phenolphthalein as an indicator. The amount of base needed for saponification of the fatty acyl chains is then indirectly determined from the excess base that remains unreacted. Since the amount (moles) of base reacted is stoichiometrically equal to the amount (moles) of fatty acyl chains contained in 1 g of oil/fat, SV is then dependent on the length of the fatty acyl chains from triacylglycerols. Therefore, a small saponification value indicates long chain fatty acids on the glycerol backbone in a sample; on the contrary, a high SV indicates triacylglycerols with shorter fatty acyl chains. Consequently, SV becomes an easy approach to assess fatty acids’ chain length of specific fats/oils.

For example, most of the common oils/fats of vegetable or animal origin (sunflower, soybean, rapeseed, pork lard, beef tallow, chicken fat, etc.) contain almost only long chain fatty acids (C18 and C16), having similar SV values (ranging from 168–196 mg KOH/g oil) [ 1 ]. Some vegetable oils, such as the coconut and palm kernel oils, contain large amounts of lauric (C12:0) and myristic (C14:0) acids; therefore, their saponification values are significantly higher (235–260 mg KOH/g oil) [ 2 , 3 , 4 , 5 ]. Milk fat differs substantially from other fats and oils in terms of the fatty acid profile (FAP), including relevant amounts of short chain (C4–C6) and medium chain (C8–C12) fatty acids, which is subsequently reflected in its high SV (213–227 mg KOH/g fat) [ 6 , 7 ]. Consequently, SV may be helpful in the detection of the adulteration of dairy products with cheaper fats and oils, because the addition of an oil/fat rich in C18 to a dairy product will result in a decrease in the SV.

Although easy and accurate, the reference method of SV determination requires specific glassware and harmful chemicals and is time consuming (according to the protocol, the saponification step takes one hour to complete, because it is critical that the saponification be complete prior to the final titration). In addition, several factors can cause errors in the titration step including misjudging the color of the indicator near the end point, misreading volumes or faulty technique. Therefore, a new, rapid and reliable method would be preferred.

In this respect, spectroscopic methods coupled with multivariate data analysis have attracted attention, being considerably faster and more practical from a procedural viewpoint. For example, SV has been determined through Fourier transform infrared spectroscopy (FTIR) coupled with multivariate analysis [ 8 ] with good accuracy, compared to the standard method; however, the main drawback of the methods based on spectroscopic data is that they require the existence of a large spectral base for the model calibration.

1 H-NMR spectroscopy is a fast (the recording of a 1 H-NMR spectrum takes approximately 2 min) and non-destructive technique that has widely been applied in the analysis of edible oils. 1 H-NMR spectra of fats and oils display signals assigned to both the unsaturated moiety and to various methylene groups of the fatty acyl chains. These signals may be used to calculate the average fatty acyl chain length of fat samples. The 1 H-NMR technique allows for full process automation, from the recording (due to the autosamplers) to data processing. Small amounts of samples are necessary, which—if needed—can further be recovered simply through solvent evaporation, after the spectra are recorded. Very importantly, the 1 H-NMR technique is also reliable, and several papers report the fatty acid profile of fats and oils computed from 1 H-NMR data in good agreement with chromatographic data [ 9 , 10 , 11 , 12 , 13 ]. Skiera et al. briefly reported a rapid method for the determination of the SV from NMR data based on the integral of the CH 2 protons adjacent to the ester groups (δ H 2.2–2.4 ppm) and on the integral of the 1,2,4,5-tetrachloro-3-nitrobenzene (TCNB) signal at δ H 7.7 ppm, used as an internal standard for quantitative NMR experiments. Five samples (with a single measurement per sample) were tested with the new method; the NMR results were in agreement with the values obtained through the ISO method, consequently pointing at the suitability of the NMR spectroscopy for the determination of the quality indices of fats and oils [ 14 ].

Based on our previous expertise on NMR chemometrics to edible oils [ 13 ], the present work reports a general algorithm for the calculation of the SV of fats and oils from the 1 H-NMR data. The working model consists of a series of binary mixtures of tributyrin (TB) and vegetable oils in various ratios to obtain a wide range of SV. In addition, to ensure an even more variate composition also regarding the unsaturation, soybean and rapeseed oils—SO and RO, respectively—were used to prepare the model samples. The average length of the fatty acyl chains can be computed through chemometric equations from 1 H-NMR data, leading to the calculation of the average molecular weight of each sample and eventually to the SV. The new method was evaluated in comparison with the conventional method based on titration and was further applied to a series of edible fats and oils including butter and cheese extracted fats. Compared to other reported methods of determining the SV from spectroscopic data, the proposed method is not based on regression equations and, consequently, does not require calibration from a database. SV may be computed directly and independently from the 1 H-NMR spectrum of a given oil/fat sample.

2. Materials and Methods

2.1. reagents.

CH 2 Cl 2 (HPLC purity) and anhydrous MgSO 4 were from Sigma–Aldrich, as well as tributyrin (97%). The CDCl 3 (isotopic purity 99.8%D) was also from Sigma–Aldrich.

2.2. Binary Oil–Tributyrin Mixtures

A series of binary mixtures of tributyrin (TB) and vegetable oils (RO and SO) in various ratios was prepared to obtain a wide range of SVs. Owing to their different fatty acid profiles, SO and RO were chosen as components for binary mixtures to obtain an even more variate composition also with respect to the unsaturation, thus leading to more reliable results. The specific composition of the RO-TB and SO-TB series is given in the Supplementary Table S1 .

2.3. Butter and Cheese Samples

Butter ( n = 4) and cheese ( n = 9) samples of bovine origin were obtained from Romanian, Bulgarian and Moldavian dairy companies. Butter fat (BF) was extracted from butter samples with CH 2 Cl 2 , dried on anhydrous MgSO 4 , followed by evaporation of the solvent. Cheese fat was extracted according to ISO 1735|IDF 5:2004 protocol [ 15 ].

2.4. Oil and Fat Samples

Soybean, rapeseed and sunflower seeds were obtained from the National Agricultural Research and Development Institute of Fundulea (NARDI Fundulea), Romania. The oil was extracted from seeds according to the standard Soxhlet protocol [ 16 ]. Beef and sheep tallow were extracted with CH 2 Cl 2 from subcutaneous adipose tissue, dried on anhydrous MgSO 4 , followed by evaporation of the solvent. Coconut oil was purchased from Trio Verde S.R.L., Romania (distributor), and the palm stearin and palm kernel oil were from Scintilla Silk, Romania (distributor).

2.5. Saponification Value

The saponification value was determined according to the ISO 3657:2013 standard procedure [ 17 ].

2.6. 1 H-NMR Spectra

1 H-NMR experiments were recorded in a field of 6.9 T using a Bruker Fourier spectrometer (Bruker Biospin, Ettlingen) operating at an 1 H Larmor frequency of 300.18 MHz. The 1 H-NMR experiments were using the standard zg30 pulse sequence and had the following parameters: 30° pulse, 5.37 s acquisition time, 6.1 kHz spectral window, 16 scans, 65K data points, 1 s delay time; all spectra were recorded at 25 °C. Fat samples (200 mg) were dissolved in 0.6 mL CDCl 3 and transferred to 0.5 mm NMR tubes of the type Norell NOR508UP7-5EA (Sigma–Aldrich, Saint Louis, MO, USA). MestReNova 6.0.2-5475 software (Mestrelab Research, Santiago de Compostela, Spain) was used to process the spectra.

To eliminate operator errors, fixed integration limits were used to obtain the integration values ( Supplementary Materials Table S1 ). In addition, for each sample the F resonance (given by the two protons adjacent to the ester group) was considered as a reference and, therefore, calibrated to 2.000; consequently, the rest of the integrals were automatically reported to the reference. According to the general rule for signals integration (i.e., from baseline to baseline), partially overlapping signals were integrated altogether (i.e., A + B and I + J, respectively). The NMR tubes were in-house quality checked as we previously reported [ 18 ].

2.7. Statistics

The experiments were run in triplicate (NMR) and in duplicate (ISO 3657:2013). The results are expressed as the mean values ± standard deviation (sd). Tuckey’s test was applied for the significantly different means ( p < 0.05).

3. Results and Discussions

3.1. 1 h-nmr spectral characterization of fats and oils.

A typical 1 H-NMR spectrum of an oil is illustrated for a rapeseed oil (RO) in Figure 1 . The corresponding peak assignment is explained in Table 1 . Figure 1 also shows a comparison of the 1 H-NMR spectra of tributyrin (TB) and two rapeseed oil–tributyrin binary mixture: RO (30%) + TB (70%) and RO (60%) + TB (40%).

Comparative 1 H-NMR spectral characterization of tributyrin (TB ― ), rapeseed oil (RO ―) and rapeseed oil–tributyrin binary mixtures: RO (30%) + TB (70%) ― and RO (60%) + TB (40%) ― . Letters A–J were assigned to resonances according to letters in Table 1 .

Chemical shifts and peak assignment of 1 H-NMR spectra of milk fats. Adapted with permission from Refs. [ 12 , 19 ]. Copyright 2004, Eur. J. Lipid Sci. Technol .; Copyright 2021, J. Dairy Sci .

* Letters from A–J correspond to specific resonances according to Figure 1 .

As reflected from Figure 1 , certain signals (i.e., A, C, E and J) cannot be found in the spectrum of tributyrin, because butyric acid is a short chain saturated fatty acid, lacking allylic, bis-allylic and unsaturated protons. The butyric moiety displays the triplet B’ characteristic of the terminal methyl group in the structure of fatty acids, the signal D of the protons in position β relative to the ester group, the triplet F generated by the methylene groups adjacent to the ester group and the signals in the specific area of the glycerol backbone (H and I). We have previously shown the assignment of NMR signals in methyl esters of fatty acids as standards for vegetable oil characterization [ 20 ]. We have also shown [ 19 ] that the resonance characteristic to the terminal methyl group of the fatty acyl chains appears shifted downfield (0.96 ppm) only in the case of linolenic and butyric acyl moieties (B and B’, respectively), compared to the rest of the fatty acyl chains (triplet A, 0.85 ppm). It is therefore evident that as the amount of TB added to the vegetable oil increases, all the resonances related to unsaturated specific groups (J) and those in the vicinity of allylic and bis-allylic groups, (E and G) will decrease. The amplitude of signal C also decreases with the addition of TB, as this resonance is dependent on the length of the fatty acyl chains, being absent for TB.

The only signal that increases in intensity is the triplet B from 0.96 ppm, characteristic for the terminal methyl group in butyric acid or linolenic acid. In rapeseed oil, the 0.96 ppm resonance is due to the linolenic acyl moiety (signal B); as the percentage of added TB increases, this resonance also increases in intensity due to the overlapping signal B’. As expected, the unspecific signals present in all fats and oils, regardless of their specific fatty acid profile (such as H and I from the glycerol moiety, as well as D and F adjacent to the ester group), did not show modifications.

3.2. Algorithm for the SV Calculation from 1 H-NMR Data

The general pattern of triacylglycerols (TAGs), as depicted in Figure 2 , consists of a glycerol ester backbone and three fatty acyl chains, each with a terminal methyl group and various amounts of methylene and CH=CH double bonds.

General representation of a triacylglycerol structure.

As reflected from Figure 2 , triacylglycerols consist of a glycerol triple ester backbone, common to all TAGs, the differences occurring in the hydrocarbon residues from fatty acyl chains. Apart from the terminal methyl groups (-CH 3 ), the hydrocarbon chains consist only of methylene groups (-CH 2 -) and double bonds (-CH=CH-), the number of which differs depending on the length of the chain and on the degree of unsaturation, being characteristic for each individual fatty acid. For example, oleic acid contains fourteen methylene groups (-CH 2 -) and a single double bond (-CH=CH-), and linoleic acid contains twelve methylene groups (-CH 2 -) and two double bonds (-CH=CH-). Therefore, the average molecular formula of a triglyceride can be rendered as:

The integral of a resonance being the area under the resonance curve, in the next chemometric equations the following suggestive notations were adopted for the integral values of the corresponding resonances: A (A+B) , A C , A D , A E , A F , A G , A H , and A (I+J) , respectively.

The average number of methylene groups (M) and the average number of double bonds (D) in the alkyl chain can then be calculated as:

• (i) The normalization factor 3/2 appeared as a consequence of the different number of protons that generated the resonances involved in Equations (1) and (2), i.e., two protons in the case of the resonances at the numerator and three in the case of the resonances at the denominator;
• (ii) Since resonances I and J appear partially overlapped, they cannot be integrated separately. However, A I (corresponding to the single proton in the sn-2 position from the glycerol moiety) can be indirectly computed as A H / 4 , given the proton ratio of 1:4 in the case of signals I and H, respectively. Consequently, A J (corresponding to the unsaturated protons (CH=CH) may be computed as a difference A (I+J) − A I ;
• (iii) Since resonances A and B appear partially overlapped, they cannot be accurately integrated as separate signals; the integration was therefore performed according to the general rule (i.e., from baseline to baseline), leading to the integral of the envelope resonance (A+B).

The mean number of carbon atoms in the hydrocarbon chain (n C ) and the average number of hydrogen atoms in the hydrocarbon chain (n H ) can be computed as:

leading to the mean formulae of the hydrocarbon chain (C M+2D+1 H 2M+2D+3 ) and of the triacylglycerol, i.e., C 6+3 (M+2D+1) H 5+3(2M+2D+3) O 6 .

As a consequence, the average molecular weight of TAGs becomes:

The SV represents the amount of KOH (in mg) required for the saponification of 1 g of fat [ 15 ]. Therefore, SV can be computed as:

where ν represents the number of TAG moles per gram of fat (ν = 1/M TAG ), while (3 ⨯ ν) is the number of moles of ester groups per gram of oil.

An example of SV calculation from 1 H-NMR data is shown in the Supplementary Materials (Table S2) .

The SV values for the SO-TB and RO-TB series (both determined by the method based on the 1 H-NMR data and determined experimentally by the conventional ISO 3657:2013 method taken as reference) are presented in Table 2 .

SVs determined from the 1 H-NMR data and through the standard (i.e., ISO 3657:2013) method for the SO-TB and RO-TB series (95% confidence level).

a–x Means with different letters within a column are significantly different ( p < 0.05). A, B Means with different letters within a row are significantly different ( p < 0.05). * Determined in triplicate (NMR method) and in duplicate (ISO method); values are reported as the mean ± sd.

As reflected in Table 2 , the values obtained based on the 1 H-NMR data were close to the values determined by the conventional method, which reflects the accuracy of the calculation algorithm.

The accuracy of the new method was assessed by calculating for each sample the SV (NMR) deviation from the SV (ISO), taken as a reference and expressed as percentages relative to the SV (ISO) (see details in Table S3 ). The mean percent deviation of SV (NMR) from SV (ISO) was found to be 2%, which stands for a robust NMR algorithm. The accuracy of the proposed method was also reflected by the SV (NMR) plotted against the SV (ISO) in Figure 3 . The concordance between the values obtained by the NMR method and the titration values is reflected by values close to 1 for both the slope of the trendline (in the case of perfect concordance, tg α = 1, corresponding to an angle of 45°) and for the coefficient of correlation R 2 . As reflected from Figure 3 , values close to 1 were obtained for the two parameters, indicating a good correlation between the two methods.

SV (NMR) plotted against the SV (ISO 3657:2013). Values for slope a and intercept b reported as the mean ± sd. The NMR experiments were performed in triplicate; ISO determinations were performed in duplicate.

3.3. Determination of the SV for Edible Oils and Fats

Subsequently, the algorithm for determining the saponification value was applied to a series of commercial samples of vegetable oils and fats, butter, cheeses and spreadable fat mixtures (margarine type). The results are presented in Table 3 .

SVs determined from 1 H-NMR data and through the standard (ISO 3657:2013) method for a series of edible fats and oils (95% confidence level).

a–c Means with different letters within a column are significantly different ( p < 0.05). A, B Means with different letters within a row are significantly different ( p < 0.05). * Determined in triplicate (NMR method) and in duplicate (ISO method), respectively; values reported as the mean ± sd. ** Variable composition (various amounts of butter and different vegetable oils).

As reflected from Table 3 , there was agreement between the SVs calculated from the 1 H-NMR data and the SVs determined through the wet (ISO 3657:2013) method. However, in the case of the oil and fat samples, the mean percent deviation of SV (NMR) from SV (ISO) was 3%, higher than in the case of the oil–TB series (2%), which may be due to the fact of their more complex composition compared to the binary mixtures.

Edible fats have variable SVs, depending on the species. As expected, vegetable oils, such as sunflower, soybean and rapeseed, had similar SVs, ranging from 194 to 196 mg KOH/g oil (as determined from the 1 H-NMR data). These values are in agreement with the fatty acid composition consisting of C18 fatty acids (i.e., linoleic C18:2 and oleic C18:1 as the main constituents, various amounts of stearic C18:0 and linolenic acid C18:3 in small amounts) and modest amounts of C16:0 (palmitic) acid [ 21 , 22 , 23 ]. They are also in agreement with similar SVs reported in the literature [ 21 ]. On the other hand, lauric fats, such as coconut oil and palm fat, showed significantly higher SVs (mean values of 248.5 and 236.5 mg KOH/g oil, respectively) due to the fact of their specific fatty acid profiles rich in lauric (C12:0), myristic (C14:0) and myristoleic (C14:1) fatty acids. In the case of the coconut oil, its fatty acid profile is dominated by medium chain length fatty acids, with lauric acid ranging between 30 and 50% [ 24 , 25 , 26 ], while myristic was also reported in high levels (accounting for more than 20%) [ 24 , 25 , 26 ]. Palm fats are abundant in palmitic (C16:0) acid [ 25 , 27 ], with large amounts of lauric and myristic acids (especially palm kernel oil [ 3 ]). The high levels of C12 and C14 explain the marked increase in the SVs of coconut and palm fats compared to the rest of the vegetable oils.

In the case of dairy products (i.e., butter and cheese fats), the average saponification values were approximately 242 mg KOH/g fat in both cases. The SV results correlated with their particular fatty acid profile, containing mainly long chain (C14–C18) as well as important amounts of short (butyric, caproic) and medium (C8–C14) chain fatty acids [ 19 , 28 ]. It is worth mentioning that milk fats contain high amounts (up to 32.4% [ 29 ]) of palmitic acid (C16:0), whereas myristic (C14:0) and myristoleic (C14:1) acids occur in important amounts, accounting for more than 10–12% altogether [ 30 , 31 ]. Consequently—although belonging to the long chain fatty acids category—C14 fatty acids contributed to the global lowering of the average molecular weight of the triacylglycerols of milk fats compared to vegetable oils (mainly consisting of C16–C18 fatty acids). Altogether, the short and medium chain fatty acids, myristic and palmitic acid levels explain the high SV in the case of dairy products.

On the other hand, spreadable fat mixtures, the analyzed samples consisted of mixtures of butter with various amounts of vegetable fats. Given the variable composition of these samples (depending on the producers’ recipes), an average SV cannot be calculated. The spreadable fat mixtures have SV lower than those of butters and cheeses, due to the higher amounts of C16 and C18 fatty acids from the oils and fat ingredients of vegetal origin.

4. Perspectives

Milk fat is one of the most expensive ingredients in the food industry [ 19 , 32 , 33 ]; therefore, it may be subject to fraudulent practices such as its partial replacement with cheaper oils and fats. The addition of nondairy fats and oils to dairy fats will result in lower SVs. Of course, an altered butter or cheese fat composition would be difficult to detect through SVs if coconut oil (SV = ~249 mg KOH/g oil) combined with a common C16–C18 oil (such as sunflower, rapeseed or soybean oil, with SV = ~193 mg KOH/g oil) is used as an adulterant. On the other hand, except for the producing countries, coconut oil is an expensive commodity [ 34 ] in the rest of the regions (for example, in Europe), which makes it improbable as an adulterant. Consequently, SVs may be an indicator for dairy products adulteration with other fats and oils of nondairy origin. Therefore, further studies correlating the amount of vegetable fats added into dairy fats with the variation of the SV may lead to the rapid detection of adulterated dairy products.

5. Conclusions

All structural patterns of triacylglycerols were reflected as specific resonances in the 1 H-NMR spectra of fats and oils. Chemometric equations leading to the mean molecular weight of triacylglycerol species may be derived from the integral values of the 1 H-NMR signals, which may further be used to compute the number of moles of triacylglycerol species per gram of fat, which will further lead to the calculation of the SV, expressed as mg KOH/g of fat. Consequently, 1 H-NMR spectroscopic data may be used to rapidly compute the saponification values of oils and fats based on the resonances associated with the fatty acyl chain lengths. The obtained 1 H-NMR-based saponification values differed from the conventionally determined SVs by a mean percent deviation of 2.3%, which is sufficient to properly characterize various types of fats. Although the NMR method is more expensive than the official method, as was proven both by us and other groups, one can obtain more information (e.g., fatty acid composition and iodine number) in addition to the saponification value from the same NMR analysis in a very short time. Thus, for combined analyses both for advanced research and authentication purposes, SV by NMR is a valuable alternative.

Acknowledgments

Support provided by Alina Nicolescu for testing the results on a second NMR spectrometer, as well as occasional support for spectrometers troubleshooting is warmly acknowledged.

Supplementary Materials

The following are available online at https://www.mdpi.com/article/10.3390/foods11101466/s1 , Examples of the SV algorithm’s application—Table S1: Reference intervals for resonance integration; Table S2: 1H-RMN integral values for the UR-TB-20 sample; Table S3: Assessment of the accuracy of the NMR method; Table S4: Influence of various delays on the calculated SV.

Funding Statement

This work was funded through the international research grant “Méthode rapide basée sur la spectroscopie de 1 H-RMN pour déceler les fromages adultérés par addition de graisses végétales (FRAUDmage)”, code AUF-ECO_SRI_2021_FRAUDmage_2144-2638, financed by the Agence Universitaire de la Francophonie (AUF) and co-funded by the University POLITEHNICA of Bucharest (Bucharest, Romania), the Technical University of Moldova (Chişinău, Republic of Moldova) and the University of Food Technologies (Plovdiv, Bulgaria). The APC was funded by the Agence Universitaire de la Francophonie (AUF) through FRAUDmage research grant.

Author Contributions

Conceptualization, N.-A.C.; methodology, N.-A.C., C.D. and A.H.; formal analysis, N.-A.C., M.I., R.D. and M.T.; investigation, A.H., R.D., M.I., N.-A.C., M.T., C.S., C.D., L.P. and A.G.-M.; resources, N.-A.C., L.P., M.I., G.I. and R.S.; writing—original draft preparation, N.-A.C. and M.I.; writing—review and editing, C.D., A.H., G.I., R.S. and A.G.-M.; supervision, N.-A.C.; project administration, N.-A.C.; funding acquisition, N.-A.C., M.I. and L.P. All authors have read and agreed to the published version of the manuscript.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Data availability statement, conflicts of interest.

The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

The Science Notes

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Determination of saponification value of oil or fats sample

Saponification  value is defined as the number of milligrams of KOH required to completely hydrolyze (saponify) one gram of the oil/fat.

Saponification is a chemical reaction that occurs when fats and oils are hydrolyzed (or broken down) in the presence of an alkali, such as sodium hydroxide (NaOH) or potassium hydroxide (KOH). It is frequently used in the production of soap.

The main objective of the saponification test for oil or fats in a food sample is to determine the presence and amount of fats or oils in the sample. This test helps assess the quality and composition of the food product, particularly regarding its fat content.

The saponification value test involves converting the fats or oils present in the food sample into soap through the saponification process.

Apparatus required

• Balance machine
• Burette with stand
• Reflux condenser
• Heating mantle
• Distillation unit

Chemical and reagents

• Potassium hydroxide
• Absolute ethanol
• Phenolphthalein
• Hydrochloric acid
• Aluminum foil 

Chemical preparation

Step-1 , 4% ethanolic koh.

• Weight 1.67g potassium hydroxide pellets.
• Take the potassium hydroxide pellets into distillation flask.
• Now, weight 1g aluminum foil.
• Transfer the aluminum foil into the same distillation flask.
• Measure 200ml absolute ethanol and pour into the same flask.
• Attach a reflux condenser with the flask.
• Now, heat the flask and reflux the alcohol with KOH and Al foil for 30min.
• After 30min of reflux, remove the reflux condenser and set a distillation unit.
• Distil and collect 180ml ethanol after discarding first 10ml.
• Now, turn off the heating of the distillation unit.
• Now, label the collected Ethanol flask.
• Bring a clean mortar and pestle and KOH pellets.
• Take some KOH pellets in the mortar and grind the pellets with pestle.
• Now, take weight of 6g of KOH pellets.
• Transfer KOH pellets in the flask to which 4% Ethanolic KOH solution will be prepared.
• Now, measure 150ml ethanol which were collected from the distillation.
• Pour the ethanol into flask containing KOH pellets.
• Mix and dissolve the KOH in ethanol, keeping the flask into cold water.
• Now, 4% alcoholic potassium hydroxide solution is prepared.

0.5N Hydrochloric Acid

• Dilute 4.1ml of HCL (concentrated) with distilled water to make the total volume of 100ml.
• Standardize newly prepared 0.5N HCL with standard NaOH solution and find the actual normality.

Phenolphthalein indicator

Dissolve 2g phenolphthalein indicator powder into 100ml of ethanol and mix well by shaking.

Sample and blank preparation

• Bring two flasks of 250ml for sample and blank preparation.
• Take approx. 5g of oil or fats in the flask labelled with sample.
• Note the sample weight.
• Now, measure 50ml of 4% ethanolic KOH and pour into the sample flask and Sample is prepared.
• Again, measure 50ml of 4% ethanolic KOH and pour into the blank flask.
• Blank flask contains no sample but it contains only 4% ethanolic KOH.
• Now, sample and blank are ready to go the next step.

Reflux sample

• Prepare heating mantle.
• Place the sample flask on the heating mantle carefully.
• Now, attach a condenser with the sample flask.
• Heat the sample flask at the boiling points for 30min. 
• Turn on the cold-water flow through the condenser.
• After 30 min of reflux, pull up the flask and check it for the separated oil layer.
• Transparent mixture indicates the end of the saponification.
• Now, cool the flask and remove the condenser.
• (If any separated oil is seen, continue saponification for another 15min. In that case, blank should be reflux for 15min more as done for sample).

Reflux blank

• In the same way, boil and reflux the blank for 30 min.
• After 30 min of reflux, stop heating, cool the blank flask and remove the condenser.

Titration of sample

• After saponification, bring the cooled sample flask for titration.
• Add a few drops of phenolphthalein indicator solution in the flask.
• Shake the flask for the proper mixing.
• Take 0.5N HCL solution in the burette.
• Note the initial burette reading for sample titration.
• Start titration using 0.5N HCL solution.
• Titration should be carried out with vigorous agitation of the flask.
• Disappearance of pink colour indicated the end points of titration.
• Shake the flask well and add few more drops of 0.5N HCL if needed.
• Stop titration when the pink colour is disappeared completely.
• Note the final reading for sample titration.

Titration for blank

• Blank should be reflux for the time needed to saponify the sample completely.
• Bring the cooled blank flask for titration.
• Add a few drops of phenolphthalein indicator solution into the flask.
• Shake the flask for proper mixing.
• Take 0.5N HCL solution in a burette.
• Note the initial burette reading for blank titration.

Calculation

•  V S  = for sample
• V B  = for blank
• W S = weight of sample.

Application of saponification value in fats and oil 

Determining fat content:  .

The saponification test can quantify fats and oils in food samples . The amount of soap generated after converting the fats and oils into soap can be used to determine the original fat content of the sample. This information is essential for nutritional labeling and quality control.

Quality Assessment:  

Saponification can be used to evaluate the quality and authenticity of food items. Different fats and oils have different saponification values, and by comparing the saponification values of the sample to established standards, the authenticity or potential adulteration of the product may be determined.

Analysis of Lipid Composition:  

Saponification is frequently used as a first step in the study of lipid content in food samples. After saponification, the resultant soap can be examined further using methods such as gas chromatography or mass spectrometry to identify and quantify individual fatty acids in the sample.

Removal of Undesirable Components:  

Unwanted Component Removal: Saponification can be used to eliminate some undesired components from food samples. The saponification process, for example, can aid in the removal of certain impurities or contaminants found in fats and oils, such as free fatty acids or rancid compounds, resulting in a cleaner and purer product.

Soap Production:  

Saponification is also utilized in the making of soap, which is not directly connected to food analysis. As a byproduct, certain food producers may create soaps made from food-grade fats and oils.

References:

• Association of Official Analytical Chemists (AOAC). (2016). AOAC Official Method 966.06: Fat (Total, Saturated, and Unsaturated) in Foods. AOAC International.
• Fox, J.B., and others. (2010). Food Analysis Laboratory Manual. Springer Science & Business Media.
• Gamlath, C.B. (2017). Fats and Fatty Acids in Human Nutrition: A Literature Review. Ceylon Medical Journal, 62(1), 25-30.
• Thirumalesh, B.V., and Sashikala, V.B. (2019). Determination of Saponification Value of Different Oils for Biodiesel Production. International Journal of Chemical Studies, 7(2), 1910-1912.

Comparison between Butter and Ghee

Determination of Crude Fat Analysis in Food samples

Sarmila K C

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Saponification

What is saponification, examples of saponification [2-6], saponification mechanism, saponification value, applications of saponification.

• Esterification vs. Saponification[8]

The process of converting fats, oil, and lipid into soap using an aqueous alkali is called saponification. Vegetable oil and animal fats are triesters or triglycerides that can be saponified in one or two steps. During this process, the triglyceride reacts with an aqueous hydroxide ion to form a mixture of glycerol and fatty acid derivative. The sodium or potassium salts of long-chained fatty acids are a significant component of soap [1-6] .

General Equation for Saponification

During saponification, esters are cleaved in the presence of aqueous alkali to form an alcohol and an alkali-metal salt of carboxylic acid. The alkali used in this process is sodium hydroxide (NaOH) or lye for hard soap and potassium hydroxide (KOH) for soft soap.

The general reaction, using NaOH, is given by:

RCOOR’ + NaOH → ROH + R’COO – Na +

Here is a simple video explaining the saponification process:

1. Sodium Stearate

Sodium stearate (C 18 H 35 NaO 2 ) is the sodium salt of stearic acid (C 18 H 36 O 2 ). It is used as a soap and a detergent. It is a significant component of soaps and contains both a hydrophobic and a hydrophilic part. It is produced when glyceryl tristearate ((C 18 H 35 O 2 ) 3 C 3 H 5 ), the triglyceride of stearic acid, is hydrolyzed with aqueous sodium hydroxide (NaOH).

(C 18 H 35 O 2 ) 3 C 3 H 5 + 3 NaOH → C 3 H 5 (OH) 3 + 3 C 18 H 35 O 2 Na

2. Sodium Palmitate

Sodium palmitate (C 16 H 31 NaO 2 ) is the sodium salt of fatty palmitic acid (C 16 H 32 O 2 ). It is found in soaps and detergents. It can be derived by the saponification of glyceryl palmitate ((C 16 H 31 O 2 ) 3 C 3 H 5 ) using sodium hydroxide (NaOH) in the form of caustic soda, lye, or lime.

(C 16 H 31 O 2 ) 3 C 3 H 5 + 3 NaOH → C 3 H 5 (OH) 3 + 3 C 16 H 31 O 2 Na

3. Methyl Salicylate

Methyl salicylate (HOC 6 H 4 COOCH 3 ) reacts with sodium hydroxide (NaOH) to form a thick white solid of sodium salicylate (HOC 6 H 4 COO – Na + ).

HOC 6 H 4 COOCH 3 + NaOH → HOC 6 H 4 COO – Na + + CH 3 OH

4. Methyl Acetate

Methyl acetate (CH 3 COOCH 3 ) saponifies in the presence of sodium hydroxide (NaOH) to sodium acetate (CH 3 COO − Na + ).

CH 3 COOCH 3 + NaOH → CH 3 COO − Na + + CH 3 OH.

5. Methyl Benzoate

Methyl benzoate (C 8 H 8 O 2 ) reacts with aqueous sodium hydroxide (NaOH) to give sodium benzoate (water-soluble) and methanol (miscible with water).

C 8 H 8 O 2 + NaOH → C 7 H 5 O 2 Na + CH 3 OH

The mechanism of saponification is a nucleophilic carbonyl substitution process, which is explained in the following steps [4-6] .

Step 1 : The nucleophilic hydroxide ion attacks the ester group and forms an intermediate.

Step 2 : The intermediate splits by releasing the leaving group to form a carboxylic acid and an alkoxide.

Step 3 : Deprotonation removes the hydrogen from the carboxylic acid resulting in a carboxylate ion and alcohol.

Saponification value (SV) or saponification number (SN) represents the number of milligrams of potassium hydroxide (KOH) required to saponify one gram of fat under a specific condition. The saponification value is a significant parameter used to characterize and evaluate the quality of edible fats and oils. Also, the saponification number provides information about the fatty acids’ average molecular weight. The higher the number, the lower the molecular weight of all fatty acids [7] .

Unit : mg KOH/g

The following table gives the saponification values of various oils and fats.

The main application of saponification is in the manufacture of soaps. Different kinds of soaps serve different purposes like laundry, cleaning, and lubrication. Soaps may be precipitated by salting them out with saturated sodium chloride. Saponification also works with fire extinguishers. Fire extinguishers use it to convert burning fats and oil into non-combustible soap, which helps to reduce fire [7] .

Saponification is significant in the food industry because it helps to know the amount of free fatty acid in a food item. The amount of free fatty acid can be distinguished by determining the quantity of alkali added to the fat or oil to make it neutral.

Esterification vs. Saponification [8]

Why is Saponification the Reverse of Esterification

During esterification, acid and alcohol combine to form an ester and release water. On the other hand, saponification breaks the bonds in an ester to form alcohol and long-chained fatty acid derivative.

Example of Esterification

C 2 H 5 OH + CH 3 COOH → CH 3 COOC 2 H 5 OH + H 2 O

The following table shows the difference between saponification and esterification.

Ans. Ethanol is less polar than water. It helps to dissolve the nonpolar fat so that it can react with sodium hydroxide.

Ans. The saponification reaction is endothermic as it takes heat from the surroundings.

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4 responses to “Saponification”

Wow the page is so good

Wonderful illustration indeed.may you include some essential precautions for the reaction, possible dangers to one performing the experiment/s or procedures, necessary condition to be maintained. Also attached a model video for the process and designed small plant to perform the procedure.

Thank you for your suggestion. We have included a simple video explaining the process. However, the essential precaution, possible dangers, and designing a small plant are beyond the scope of the article.

I love knowing the chemical reaction. I am on batch four and switched from well water (calcium carbonate and ferrous something) to distilled water and wow what a difference. I am a retired engineer not a chemist but I wonder what the reaction would be.

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Green Chemistry in Teaching Laboratory Microwave Induced Reactions Home Green Chemistry Microwave Chemistry Industrial Perspective Safety Tips Experiments Links High School Teachers  Workshop Downloads Contact     Saponification of Fat - Synthesis of Soap     Saponification is the process of making soap from alkali and fat (or oil). Vegetable oils   and   animal fats   are fatty esters in the form of   triglycerides . The alkali breaks the ester bond and releases the   fatty acid   salt and glycerol . If necessary, soaps may be   precipitated   by   salting out   with   saturated   sodium chloride . Usually, sodium hydroxide is used in formation of hard soap while potassium hydroxide is used in case of soft soap.                                                        Scheme 2 . Saponification Reaction. Mechanism of cleaning by Soap It is not possible to remove dirt (especially oil and grease) by just using water. The non-polar components present in the dirt repel the polar constituent of the solvent. In presence of a detergent (soap) which has both polar and non-polar ends, the non-polar ends of the detergent which is repelled by water interacts with the nonpolar grease. At the same time, the polar ends are attracted towards the hydrophilic molecules. Thus the two complementary polar and nonpolar components of the dirt are dissolved and removed during washing. The soap forms micelles in water, where the polar ends align along the circumference and non-polar constituents carrying the nonpolar species are remain in the center of the micelle. * Figure 8. Typical micelle formation * Source: http://www.images.google.com Materials Required Animal Fat Ethanol 6N Sodium Hydroxide Sodium Chloride Isoproply alcohol Two 100 ml Beaker Two glass rods Two 250ml conical flask Distilled water Microwave Hot plate Safety goggles Towels for clean up Stop watch Experimental Procedure Ten grams of commercially available animal fat/shortening was weighed and dissolved in 50 ml of ethanol by constant stirring. To this mixture was added 15ml of freshly prepared 6N sodium hydroxide solution. This mixture was heated on a hot plate until all the fat was completely dissolved. 20ml of distilled water was added and the mixture was cooled on an ice bath. The cooled mixture was then poured into a beaker containing 50ml of 0.2 % Sodium Chloride solution. Soap was formed upon cooling. The solution was filtered to separate the soap from the glycerol thus formed. The experiment was repeated using microwave. The corresponding efficiencies and energy consumptions were calculated. Result & Discussion As a result of the Saponification process, the fatty acids are hydrolyzed in presence of an alkali so as to form salts of alkali and alcohol. Upon cooling of the dissolved mixture, solid soap was observed the end of the process. Energy consumed by each process is tabulated below.  One way to test the formation of soap is by dissolving the solid in water and checking foam formation. It can also be confirmed by performing pH test, which involves dissolving the soap in a freshly prepared 1:3 water and isopropyl alcohol mixture. The dissolved soap solution can be tested with phenolphthalein indicator and the soap formation is indicated by the color of the solution. A dark pink and clear solution indicates presence of excessive caustic solution, the one with colorless or yellowish clear solution indicates a fairly neutral pH, hazy solution indicates untreated oil, hazy and pink solution indicates the reaction was complete. A clear, pale pink solution indicates good results.                                      (a)                                             (b)                                                (c) Figure 9. (a) Untreated soap solution, (b) Hazy pink solution with untreated oil, (c) Clear pink solution indicating the formation of soap.   Table 4. The energy consumed for saponification of 10g of animal fat. Heating Device Time (min) Power Rating (KJ/min) Actual Energy Consumed (KJ) Microwave Oven 1 51.0 36 Hot Plate 4 51.9 108  Therefore, the percentage of energy saved by the microwave oven over the conventional oven as recorded by the power meter is, The Saponification process using conventional heating took four times as much time to complete than the microwave process, and consumed more energy. The quality of soap was also tested. From the Fig. 9 (c) we see the solution thus formed after the addition of phenolphthalein, was a clear pink solution indicating the formation of good soap with a nominal pH in the range of 7-9. In Fig 9 (b) we see a hazy pink solution with yellow droplets in it, indicating the presence of unreacted oil. The solution also appears dark in color indicating the presence of excessive caustic soda. Fig 9 (a) shows a clear solution which indicates the absence of soap formation.        The amount of energy consumed by the hotplate was significantly higher than what was consumed by microwave. This was attributed to the direct interaction of the reactants with the microwave radiation.     Back     Top          

• Chemistry in Everyday Life

Saponification

Soaps are an integral part to maintain the good health and hygiene of individuals. Soaps are essential to cleanse dirt and oil off the objects including the skin surface. Soaps are widely used in bathing, cleaning, washing and in other household chores.

Table of Content

Saponification definition, what is saponification, related videos on saponification, saponification reactions, saponification reaction mechanism.

• Example of a Saponification Reaction

Saponification Value

Effects of saponification, uses of saponification.

Saponification is the hydrolysis of an ester with NaOH or KOH to give alcohol and sodium or potassium salt of the acid.

Soap is now an essential everyday item and finds its importance in everyday life. But, how is soap made? The process of making soap is called saponification . Here, the soap making process or saponification is discussed in a detailed and easy way.

Saponification is simply the process of making soaps . Soaps are just potassium or sodium salts of long-chain fatty acids. During saponification, ester reacts with an inorganic base to produce alcohol and soap.

Generally, it occurs when triglycerides are reacted with potassium or sodium hydroxide (lye) to produce glycerol and fatty acid salt, called ‘soap’.

Triglycerides are generally animal fats and vegetable oils. When they are reacted with sodium hydroxide, a hard form of soap is created. This is where potassium comes in and creates a softer version of the soap.

The equation can be written as:

Orthoester formation:

Examples of a Saponification Reaction:

In a saponification reaction, a base (for example sodium hydroxide) reacts with any fat to form glycerol and soap molecules. One of the saponification reactions taking triglyceride as an ester and sodium hydroxide as the base is as follows:

1-Step Saponification vs 2-Step Saponification

There can be either one-step saponification or two-step saponification process to convert triglycerides to soaps. The examples mentioned above are a one-step saponification process in which triglycerides, when treated with a strong base, split from the ester bond to release glycerol and soaps (i.e. fatty acid salts).

On the other hand, in the two-step saponification process, the steam hydrolysis of the triglyceride yields glycerol and carboxylic acid (rather than its salt). In the second step, alkali neutralizes fatty acids to produce soap.

Saponification value or saponification number refers to the amount of base that is required to saponify a fat sample. Generally, saponification values are listed in KOH and so, saponification value can also be defined as that value which represents the number of milligrams required to saponify 1 gram of fat under the specified conditions.

In case sodium hydroxide is used for the saponification process, the saponification value must be converted from potassium to sodium by dividing the KOH values by the ratio of the molecular weights of KOH and NaOH (i.e. 1.403).

The effects of saponification can either be desirable or undesirable. Some effects of saponification are mentioned in the below-given points.

• One of the major desirable effects of saponification is seen in fire extinguishers. Saponification is used by wet chemical fire extinguishers to convert burning fats and oils into non-combustible soap which helps in extinguishing the fire. Further, the reaction is endothermic and lowers the temperature of the flames by absorbing heat from the surroundings.
• In an undesirable scenario, saponification damages oil paintings. In oil paintings, the heavy metals used in pigments react with the oil containing free fatty acids and form soaps. This way, the paintings get damaged gradually.
• Soaps formed are used in everyday life like sodium soaps are used for laundry, potassium soaps are used for cleaning and lithium soaps are used as lubricating greases. There are various other soaps which are used for different purposes.
• Wet chemical fire extinguishers: To extinguish cooking oils and fats, we use a saponification reaction. This is because cooking oils and fats have a flashpoint which is above 37 degrees which renders regular fire extinguishers useless.
• Using KOH: We can obtain soft soaps
• Using NaOH: We can obtain hard soaps

This was all about the saponification process. This topic is one of the most crucial topics in chemistry and students are required to be thorough with the reactions and terms to be able to answer questions in the exam.

Frequently Asked Questions – FAQs

What is saponification and its reaction.

Ester reacts with an inorganic base during saponification to create alcohol and soap. It normally happens as potassium or sodium hydroxide (lye) reacts to triglycerides to create glycerol and fatty acid salt, called ‘soap’.

What is a saponification example?

Saponification is the hydrolysis of an ester to form an alcohol and the salt of a carboxylic acid in acidic or essential conditions. Saponification is usually used to refer to the soap-forming reaction of a metallic alkali (base) with fat or grease. Example: In the presence of conc., ethanoic acid reacts with alcohol.

What is the definition of saponification in science?

Saponification can be characterized as a “hydration reaction in which free hydroxide breaks the bonds of ester between triglyceride fatty acids and glycerol, resulting in free fatty acids and glycerol,” each of which is soluble in aqueous solutions.

Why is saponification important?

Saponification is the hydrolysis of fats or oils for the extraction of glycerol and the salt of the resulting fatty acid under simple conditions. Knowing the amount of free fatty acid present is essential to the industrial consumer, as this determines the processing loss to a large degree.

What type of reaction is saponification?

Saponification is a type of chemical reaction in which ester molecules are broken to create a functional group of carboxylic acid and alcohol. A collection of molecules or atoms that we can readily recognize in a compound is a functional group. To produce soap goods, this reaction is most widely used.

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• Open access
• Published: 30 August 2024

Theoretical and experimental investigation of the impact of oil functional groups on the performance of smart water in clay-rich sandstones

• Alireza Kazemi 1 ,
• Saeed Khezerloo-ye Aghdam 1 &
• Mohammad Ahmadi 2  

Scientific Reports volume  14 , Article number:  20172 ( 2024 ) Cite this article

Metrics details

• Energy science and technology
• Engineering

This research investigated the effect of ion concentration on the performance of low salinity water under different conditions. First, the effect of injection water composition on interparticle forces in quartz-kaolinite, kaolinite-kaolinite, and quartz-oil complexes was tested and modeled. The study used two oil samples, one with a high total acid number (TAN) and the other with a low TAN. The results illustrated that reducing the concentration of divalent ions to 10 mM resulted in the electric double layer (EDL) around the clay and quartz particles and the high TAN oil droplets, expanding and intensifying the repulsive forces. Next, the study investigated the effect of injection water composition and formation oil type on wettability and oil/water interfacial tension (IFT). The results were consistent with the modeling of interparticle forces. Reducing the divalent cation concentration to 10 mM led to IFT reduction and wettability alteration in high TAN oil, but low TAN oil reacted less to this change, with the contact angle and IFT remaining almost constant. Sandpack flooding experiments demonstrated that reducing the concentration of divalent cations incremented the recovery factor (RF) in the presence of high TAN oil. However, the RF increment was minimal for the low TAN oil sample. Finally, different low salinity water scenarios were injected into sandpacks containing migrating fines. By comparing the results of high TAN oil and low TAN oil samples, the study observed that fine migration was more effective than wettability alteration and IFT reduction mechanisms for increasing the RF of sandstone reservoirs.

Introduction

Using low salinity water is a challenging method for enhanced oil recovery 1 , 2 , 3 . The mechanism that comprehensively explains the function of this approach has not been proposed 4 , 5 . Low salinity water flooding alters the rock porous media substantially 6 , 7 , 8 , which can result from different interactions like rock/fluid interplay, fluid/fluid interplay, and rock/rock interplay 9 . Therefore, investigating and identifying the strength of this approach in extended situations is essential. The pivotal mechanism of this approach to rock inner structure is challenging 10 , 11 . These mechanisms can either upgrade or worsen the EOR approach 12 .

Recent papers have identified several impactful mechanisms such as altering the rock wettability, Migration of fine particles, lowering oil/water IFT, pH, and salt-in effects 6 , 13 , 14 . Alteration of wettability and migration of fine particles have more effect than other mechanisms 11 . However, numerous studies have already demonstrated that altering rock wettability does not always happen 15 . This mechanism relies on the reservoir rock and fluid characteristics 15 . There are cases in which implementing low-salinity water can worsen the condition of wettability, particularly in reservoirs with carbonate lithology. Additionally, the fine migration mechanism is controversial, as researchers do not fully agree on its effectiveness 13 .

In the field of petroleum engineering, the migration of fine particles has been introduced deteriorating and potentially harmful phenomenon in production and injection wells, injection wells, which is an essential topic for researchers 16 , 17 , 18 , 19 . Various approaches to deal with this problem have already been suggested, including adjusting the injection rate in injection wells as well as the production rate in production wells 20 , using clay inhibitors 21 and surfactants 22 , 23 to stop the occurrence of this phenomenon. Fine particles are stable in the porous media in a normal situation where the production rate is low and stable 24 . However, applying IOR and EOR approaches may impact the reservoir adversely 25 . Under the implementation of EOR and with changes in injection or production conditions, as well as the reservoir fluid compositions, fines can become suspended and separated from the facing of the pores 26 , 27 . Drag forces from fluid flow move the fine particles that detach the porous media. This continues unless the fine particles trap behind a narrower pore throat. Therefore, the connection level between pores is reduced, which lowers the formation permeability 28 , 29 , 30 .

Contrary to the findings of many papers, some researchers claim that fine migration is an important mechanism 25 , 26 . Tor Austad states that clay particles are mandatory for performing the low salinity water approach 26 . The migration of fine particles may raise the recovery factor through two mechanisms. The first one is related to the pore bodies sweeping. When clay particles move forward in the porous media, the oil is expended from the pore bodies 31 , 32 . The second mechanism is related to the conformance control. The pore throats that have been affected by the injected low salinity water becomes plugged. Thus, water can enter the areas that have not been swept 33 , 34 , 35 .

Another important mechanism is IFT reduction, which has also been identified in some research as a mechanism for improving RF 13 , 36 , 37 , 38 . However, it is essential to note that this mechanism does not occur in all cases, and sometimes, the IFT between oil and water is entirely indifferent to water salinity 38 , 39 , 40 . In other cases, it is classified as having lower importance than wettability alteration and fine migration 41 . Indeed, it is crucial to recognize that each of these mechanisms occurs under specific conditions. Thus, some low salinity water projects have been unsuccessful due to a lack of attention to the specific conditions required to successfully implement these mechanisms 6 , 42 . Exploring the science behind phenomena is crucial to recognizing and controlling the impactful factors. This understanding can help researchers design low salinity water formulations tailored to each reservoir's specific characteristics, leading to a more effective and successful EOR approach.

So far, there have been papers in the field of fine migration, as well as a qualitative study of the effect of interparticle forces. However, this study, for the first time, uses these forces to quantify the composition of injected fluids, in which the concentration and types of ions are changing to investigate their effect on the possibility of fine migration, both theoretically and experimentally. It also examines the effect of functional groups in oil on the recovery enhancement mechanism from the point of view of interparticle forces both in the laboratory and in theory. The study used the plate and sphere model and assumed that quartz particles are plates, water denotes the fluid, clay particles, and oil droplets are spheres. The study then performed IFT and wettability measurements to identify the impact of interparticle force on these phenomena. Additionally, several sandpacks with and without clay were made to observe the effect of interparticle force on the migration of fine particles. The study injected various scenarios to investigate the effect of interparticle force on the migration of fine particles and the impact of fine migration on the oil recovery factor. Ultimately, the study aimed to understand the factors that activate and control mechanisms at the particle scale and investigate their contribution to improving RF.

Methodology

Theoretical aspect.

This area illustrates up to examine the impact of the encompassing water composition on interparticle powers. The DLVO hypothesis was, to begin with, presented for steadiness calculations of colloidal liquids, and it can be utilized to recognize the sort of overwhelming drive between particles 43 . That is rectified. The overall constraint calculated by the DLVO hypothesis decides the attraction and repugnance between two particles. On the off chance that the entire drive is attractive, the particles will tend to total and shape more giant clusters, while on the off chance that the overall constrain is terrible, the particles will tend to scatter and stay isolated 44 .

Researchers illustrated that the attraction force within rock porous media and oil particles may lead to the injection water being released from pores. As a result of the attraction force, most of the oil is adsorbed to the facing of the rock. In contrast, by flooding water, oil with repulsive forces on the facing of the matrix is peeled off from the rock surface. The first case is likely to occur in reservoir conditions. Thus, an effective increment in the recovery factor may be achieved by altering the injected water composition to change this force into repulsion. It is also evident that migrating fine particles exist in most sandstones, and changing the magnitude and size of interparticle force impacts the movement of the particles. Fine migration may damage the rock media and lower the permeability of the rock. Furthermore, migrating fines may also move oil droplets forward in the porous media, enhancing oil recovery. Thus, investigating interparticle forces in various complexs is necessary.

Generally, DLVO theory models the energy of interplay between particles based on the Lifshitz-van der Waals (ULV) and electrostatic (UEL) energies 45 .

The interplay of van der Waals is a microscopic force that results in particles being attracted to one another by their mass. The sphere and planar model has been used to calculate the amount of this force. The Van der Waals energy value shall be calculated using a Hamaker approximation method for short distances. Hamaker is needed to compute the ULV interplay strength of the facing particles, which depends on the dielectric features of the particles 45 .

where A 132 is the Hamaker constant, r denotes the particle radius, and H is the distance between the sphere and plane.

When two particles with EDL come closer, they impose electrostatic forces on each other, which depend on various parameters. The electrostatic energy of particles depends on the distance between them. The below equation calculates the electrostatic interaction energy 45 .

where, \( \varepsilon \) denotes the electrolyte's dielectric constant (F/m), \( {\varepsilon_0} \) presents the vacuum permittivity coefficient (F/m), r illustrates the particle radius (m), \( \zeta \) denotes the zeta potential value (V), and h presents the particles' distance in meters. KB indicates Boltzmann's constant (J/K), and T illustrates the average temperature in Kelvin.

Within the over condition, the parameter 1/k is the Debye length consistent in meters, demonstrating the EDL's thickness around the particle. This parameter is calculated through the taking-after condition.

Here, N A is Avogadro's number, e denotes the electron's electric charge, and I refers to the electrolyte's ionic strength (mole/Liter), calculated through the equation below.

C represents the target ion concentration in moles per liter (M), while Z denotes the electric charge of the ion. By utilizing the equations above, the energy levels of various particles can be computed relative to their distance from one another. These energy level values are then graphed against particle separation in various complexes such as kaolin-kaolin or kaolin-quartz. By utilizing the generated illustration alongside the given equation, it becomes feasible to forecast the overall interplay force present between differing particles.

Thus, the force direction can be identified according to the slope of the energy diagram. The presence of a significant hump in the diagram indicates that the colloid is stable and the particles are not agglomerated. In contrast, a uniform diagram illustrates particle agglomeration.

Experimental section

Water samples.

Various salts such as sodium chloride (NaCl), calcium chloride (CaCl 2 ), magnesium chloride (MgCl 2 ), and sodium sulfate (Na 2 SO 4 ) were used to make formation water (FW) and low salinity water samples. Table 1 illustrates the composition of different waters and their characteristics.

All brines were made in the laboratory. For this purpose, the required amount of salt was slowly added to the distilled water and mixed with a magnetic stirrer for 24 h to prevent the formation of sediments. Finally, the brine fluid was filtered by filter paper.

Oil samples

Here, two samples of crude oil gathered from the southwestern oil fields of Iran were tested. The characteristics of tested samples are presented in Table 2 .

Based on the table above, oil(A) is richer in aromatic and asphaltic molecules than oil(B). Timothy et al. illustrated that the concentration of aromatic and asphaltic functional groups highly depends on oxygenated and hydrogenated groups in oil composition. Hence, oil(A) contains more acidic functional groups than oil(B). A total acid number (TAN) experiment was conducted to bring concrete evidence, which confirmed the fact.

Zeta potential measurement

This work utilized a Zetasizer Nano ZS (Malvern Instruments, UK) to identify the potential in the zeta layer of various particles in different brine samples. This setup utilizes electrophoretic light scattering to identify the value.

This test measures the amount of electric potential on the surface of suspended particles. Therefore, the particles should be well suspended in the aqueous solution. Therefore, 6000 rpm rod mixers were used for 20 min to prepare the measured samples. After the mixing process for clays, sands, and oil samples, the uniformity of the fluid was visible, and this fluid was used to measure the zeta potential.

Interfacial tension (IFT) measurement

This work utilized the Pendent drop approach to determine the interfacial tension (IFT) between various fluids. The setup in this regard consists of various devices, such as an online image-capturing camera, a glass for the lighter liquid, and a narrow syringe pump. The IFT between oil droplets and different brine samples was determined in this study. In this experiment, an oil droplet was dropped into the brine, the bulk fluid. The injection was performed smoothly and slowly. After reaching the equilibrium, the injected droplet's image was captured and analyzed. In this study, IFT experiments have been conducted at 60 °C.

Wettability measurement

The impact of different brines on the rock slices' wettability was determined through a sessile drop experiment. Rock slices were prepared via a Hitti DD130 rock cutter, and the roughness of their facing was smoothed through ultra-fine sandpaper. Afterwards, the smoothed slices were washed in soxhelet via methanol to eliminate salts and then dried at 100 °C. The smooth and polished slices were immersed in crude oil for two weeks at 60 °C to approach an oil-wet condition. Aged flat pellets were then immersed in various brines to investigate their effect on wettability alteration.

Then, slices were placed on top of a chamber filled with brine. An oil droplet was poured on the facing of the slices, and a photograph was taken after stabilizing the droplet on the slice. The wettability state of the slices was determined Based on the droplet's shape. It should be noted that the contact angle measured through this experiment refers to the apparent contact angle, and to minimize the effect of hysteresis, the experiment should be conducted very slowly 46 .

Sandpack flooding experiment

The Pars Ore company provided quartz grains and kaolinite powder. A disk mill mortared quartz grains. The compounds of quarts and kaolinite were determined through an X-ray diffraction test after removing impurities, as illustrated in Table 3 .

XRD analysis was also conducted to characterize sand particles used in this study. Figure  1 shows the XRD results obtained from sand particle analysis, showing that 97% of the rock sample is quartz and 1.5% is clay minerals.

XRD analysis graph of sand particles.

Based on a two-step procedure, the impurities were eliminated through rock samples. Firstly, rock powder was washed with toluene in soxhelet for 4 h to eliminate all organic impurities. Acetone was then utilized to wash toluene and soluble organic materials. Deionized water was then implemented to eliminate acetone and salts. At the end of this step, the washed powders were dried at 80 °C for 1 week.

The next step, conducted only on a quartz sample, removed inorganic materials through 15% HCl acid. Afterward, the quartz grains were washed through distilled water to eliminate the acid and achieve the inlet water's pH at the outlet.

Sandpack preparation procedure

Sandpacks were used instead of plugs taken from shaly sand cores. To do this, kaolinite and quartz grains were sieved to obtain the desired sizes. The mean size of kaolinite grains was 3 µm. Thus, grains were sieved through a 400 mesh to make sure that the grains were not agglomerate. Quartz grains were used in various sizes, including 177 to 250 µm, 125 to 177 µm, and 74 to 125 µm.

The sieved grains were packed in a rubber sleeve with a diameter of 1 cm. A 400 No. mesh screed was glued to the sleeve outlet to hinder sandpack disassociation. The grains that were sieved were packed in three steps. The biggest grains were poured into the sleeve in the first step, and in the last step, the smallest grains were packed.

The noteworthy point is that the inner diameter of the sandpack was 1 inch, which is considered in all calculations. However, the outer diameter is 1.5 inches, which fits in a regular core plug holder.

Sandpack flooding setup

A flooding test was conducted to assess the efficiency of low salinity water samples in raising the recovery factor in shaly sandstones. The apparatus used for this step is illustrated in Fig.  2 . Various devices were used to assemble the apparatus, including a syringe pump, three cylinders for various fluids, a core plug holder, and two pressure indicator transmitters to measure the differential pressure (dP).

Schematic of core flooding apparatus 47 .

Along with the test, the low salinity water samples were flooded into the shaly sandpacks, and the dp across the sandpacks was recorded. The syringe pump controlled the injection rate, and the pressure transmitters were used to measure the pressure drop across the sandpacks as the low salinity water samples flowed through them. The vacuum pump was used to maintain a constant and zero outlet pressure. The experiment was performed for various low salinity water samples, and the results were analyzed to evaluate their ability to improve RF in shaly sandpacks. In this study, all flooding experiments have been conducted at 60 °C.

Firstly, the dried and cleaned sandpacks were placed into the core holder. In the next step, they were saturated with FW. The porosity of the sandpacks can be determined by the obtained data (see Eq.  7 ).

V refers to the fluid volume in which the index of i and o pertain to the inlet and outlet, and the index b is bulk.

To measure the absolute permeability of sandpacks, they were saturated and then flooded by formation water. The magnitude of this parameter was obtained from Eq. ( 8 ) (Darcy equation).

In the core flooding experiment, the injection flow rate (q) was calculated based on the viscosity of the flooded brine (µ), the length (l) and area (A) of the core plug, and the pressure difference (∆P) between the inlet and outlet of the plug.

After determining the injection flow rate, the sandpack was saturated with brine until it reached irreducible water saturation (S wir ). Brine-saturated sandpacks were flooded by crude oil samples to achieve this condition.

The produced oil volume was plotted versus the time to investigate the impact of different parameters on crude oil recovery. The RF for different scenarios was determined through Eq. ( 9 ).

Fine migration causes the permeability reduction in the porous medium, and as a result, the injection pressure increases while fluctuating. Therefore, it is necessary to conduct a statistical study to compare the intensity of fine migration in different sandpacks. This work calculates and determines the moving average for pressure data over time. Then, the deviation of each data is calculated concerning this moving average, and the result shows the mean absolute deviation (MAD), which can be used to compare the intensity of fine migration.

In Eq. ( 10 ), P t is the magnitude of pressure at a specific time, and MAP t denotes the magnitude of calculated moving average pressure.

Results and discussion

Here, the zeta potential measurement results and particle size determination tests are discussed. The force between particles for various conditions is modeled according to the DLVO theory. The impact of different parameters, including interparticle force, ion type, and concentration on the oil/brine IFT and wettability alteration, is identified.

In the end, fluids are synthesized according to the results of the batch experiments to maximize the oil recovery factor. This process is surveyed, and the oil recovery is recorded. The obtained data is investigated to determine the effect of the injected fluids in oil recovery augmentation.

Interparticle interaction

According to the procedures above, measuring zeta potential and particle size calculates the interaction energy between particles in various systems. Figure  3 plots the magnitude of energy versus interparticle distance.

Interparticle interplay illustration in the complex ( A ) kaolinite-kaolinite ( B ) kaolinite-quartz ( C ) Oil(A)-quartz ( D ) Oil(B)-quartz.

Based on Fig.  3 A, kaolinite particles in FW attract each other, which leads to sedimentation. However, using low salinity water stimulates repulsion force between particles. This figure also illustrates that the repulsive force between kaolinite particles becomes dominant with a further reduction of water ionic strength by eliminating divalent cations. Thus, kaolinite particles in Na50LSW, Na10LSW, and Ca10LSW water samples are expected to repel each other, leading to a homogenous dispersion.

Figure  3 B illustrates that the presence of divalent cations leads to a dominant attraction force between quartz and kaolinite particles. Therefore, quartz grains attract kaolinite particles in the FW, Ca50LSW, and Ca10LSW bulk phases. However, the interparticle forces of this complex in Na10LSW and Na50LSW are repulsive.

Figure  3 C illustrates that Oil(A), which contains large amounts of acidic functional groups, behaves like kaolinite during dispersion in water. The oil droplets only attract quartz grains in the presence of formation water or water samples with divalent cations higher than 50 mM. Thus, when the concentration of these cations is low, the interparticle force in the oil-quartz complex is repulsive.

In contrast, Fig.  3 D illustrates that the interparticle force between oil and quartz highly depends on the oil composition and its TAN. Unlike Oil(A), Oil(B) tends to be adsorbed on the facing of quartz particles under any conditions.

In general, it can be seen in this figure that using ten mM of monovalent ions has no substantial effect on the interparticle forces diagram, and the hump is apparent under any condition. However, by increasing the ionic strength of the fluid to the extent that it contains 50 mM of divalent cations, the hump is eliminated under any condition and makes them uniform. Therefore, investigating this concentration range is critical, and researchers must give it importance.

The results of the IFT measurement

This research measured the effect of injection water composition on the IFT of Oil(A) and Oil(B) samples. The results are presented in Table 4 .

The table illustrates that injecting Ca50LSW and Na50LSW into the oil samples significantly reduces IFT compared to FW. The IFT reduction is more significant for Oil(A) than Oil(B). Injecting Ca10LSW and Na10LSW into the oil samples also reduces IFT, but the reduction is less significant compared to Ca50LSW and Na50LSW.

The results suggest that low salinity water injection can effectively increment RF by reducing the IFT between oil and brine. The effectiveness of this mechanism may depend on the oil composition and its TAN. Oil samples with a higher TAN, such as Oil(A), may experience a more significant reduction in IFT than oil samples with a lower TAN, such as Oil(B).

The coefficient of variation (CV) was calculated for both oil(A) and oil(B) IFT data. CV for oil(A) data was 5.36, however, it was 0.92. The big difference in this parameter shows that the IFT of the first oil sample varies in different water compositions, but the IFT for the second sample is not intensely sensitive to the water composition. The data in Table 4 illustrate that the reduction in water salinity reduces the concentration of divalent cations, making a slight decline in the IFT value. This reduction is more noticeable when oil(A) is used. So, using Na10LSW reduces the IFT value from 41.4 to 36.3 mN/m. The effective mechanism of this IFT reduction is EDL expansion. The total acid number (TAN) in the Oil(A) sample is high due to acidic functional groups. Thus, the oil droplets' EDL expands with the reduction in the bulk water salinity. EDL Expansion results in a repulsive force between oil droplets, which makes them smaller and thus lowers the oil–water IFT 48 , 49 . Also, oil's acidic functional groups are slightly soluble in water 50 . Decreasing the salinity of water and the components dissolved in it increases their solubility, resulting in IFT reductions. However, the reduction of IFT in oil (B) is meager. This is due to the absence of acidic functional groups in this oil sample, and the brine/oil IFT value in this complex is not dependent on water salinity. It should be noted that IFT reduction is not a primary mechanism in low salinity water flooding, and wettability alteration and fine migration phenomenon are much more effective than IFT reduction.

Wettability alteration results

The contact angle test was performed to evaluate the effect of different brines on the wettability of reservoir rock. The figures obtained for different oil samples (oil(A) and oil(B)) are illustrated in Figs.  4 , 5 , respectively.

Contact angel images of an oil drop on a quartz slice in different conditions.

Contact angel images for brine/oil complex (B) in different bulk fluids.

Figure  5 illustrates that the quartz facing is initially water-wet, with an oil apparent contact angle 46 of 45.1°. However, after aging the quartz slices for 14 days, the facing becomes oil-wet, with an apparent contact angle of 129°. This wettability alteration is attributed to acidic functional groups in the oil composition, which adsorb onto the silicate facings and change the facing's wettability to oil-wet.

When aged rock is exposed to low-salinity water, wettability alteration can occur for two reasons. Firstly, EDL expansion in quartz slices and oil droplets can lead repulsive forces to prevail in the quartz-oil(A) complex, separating oil droplets from the rock facing. This repulsive force results from reduced water salinity, significantly reducing the concentration of divalent cations in the water. Secondly, the solubility of functional groups in water increments as the water salinity reduces. This incremented solubility leads the functional groups to dissolve in the water, separating oil droplets from the rock facing.

Figure  6 illustrates that the wettability alteration of the complex containing Oil(B) is minimally affected by the reduction of water salinity. This may be due to differences in the composition of Oil(B) compared to Oil(A), leading to different adsorption and interplay behavior with the rock facing.

The results of ( A ) pressure, ( B ) permeability, and ( C ) recovery volume obtained from flooding of sandpack No. 1 by FW, Na50LSW, and Na10LSW.

Overall, wettability alteration is essential for improving oil recovery in low salinity water injection. The mechanism is complex and can be affected by various factors, including the oil composition, rock properties, and injection water composition. Thus, careful evaluation and optimization are necessary to maximize the potential benefits of this technique.

Figure  5 displays contact angle images for the brine/oil complex (B) in different bulk fluids. Similar to the previous figure, aging the rock with Oil(B) increases the oil wetness of the rock face, but the contact angle increment is less significant compared to Oil(A). This observation can be attributed to the lower concentration of acidic functional groups in Oil(B) compared to Oil(A).

Moreover, reducing water salinity and removing divalent cations had a limited effect on the wettability alteration of the complex containing Oil(B). This could be due to the absence of repulsive forces between the oil and the rock facing resulting from EDL expansion or the low concentration of functional groups in Oil(B), which cannot alter the wettability by dissolving in water.

In summary, the wettability alteration mechanism in low salinity water injection can be influenced by various factors, such as the oil composition, rock properties, and injection water composition. Thus, it is crucial to thoroughly evaluate and optimize these factors to achieve optimal results with low salinity water injection in improving oil recovery.

Sandpack flooding results

Eight quartz sandpacks containing zero and 5 wt% of kaolinite particles were prepared. The sandpacks' permeability and porosity were measured by injecting formation water (FW) at a rate of 0.1 ml/min (equivalent to 3 ft/day). Based on the established procedure, the sandpacks were saturated with Swir and prepared for flooding, as outlined in Table 5 .

The CV parameter for no clay samples is 0.47%, and it is 1.9% for clay-rich sandpacks, which shows that the process is repeatable and there is no significant variation in the porosity in identical samples. In the next step, to check the effect of different factors on the recovery factor and the fine migration phenomenon, each of these sandpacks was flooded by various scenarios.

Test No. 1: Successfully, Sandpack No. 1 was flooded by FW, Na50LSW, and Na10LSW samples. The results of this test are illustrated in Fig.  6 .

During the initial stages of sandpack flooding, the injection pressure increments until it reaches a hump, after which it reduces. This hump is resulted from the water phase being trapped behind the oil bank, and the pressure starts to reduce when the water breaks through. The pressure becomes stable after injecting about 1.6 PV, and no significant changes occur in the sandpack's parameters. However, before this region, the pressure drop and effective permeability increment due to oil exiting from the sandpack outlet, leading to an increment in water saturation in the porous media, as illustrated in Fig.  7 C.

The results of ( A ) pressure, ( B ) permeability, and ( C ) recovery volume obtained from flooding of sandpack No. 2 by FW, Na50LSW, and Na10LSW.

When Na50LSW is injected into the sandpack, the injection pressure starts to reduce, and the permeability increments after about 0.5 PV. This is likely due to the separation of some oil from the rock due to Na50LSW entering the sandpack, increasing water saturation and effective permeability of the water phase. The positive effect of Na50LSW on oil recovery is observed in IFT and wettability alteration tests, and the recovery factor increments by 6% at the end of the injection.

Injecting Na10LSW leads to a remarkable increment in the recovery factor and permeability. This is because Na10LSW entering the porous media makes the facing of the oil droplets and rock charge, resulting in a prevailing repulsive force. IFT and wettability data also support this finding.

In summary, the injection of Na50LSW and Na10LSW can positively impact oil recovery through their effects on water saturation, effective permeability, and interfacial tension. However, the optimal injection strategy may depend on various factors, such as reservoir characteristics, oil properties, and injection water composition, and careful evaluation and optimization are necessary to achieve the best results.

According to Fig.  6 , pressure decreases smoothly over time, which shows that no fine migration occurs in this porous media. To make a better index for comparison with other experiments, the parameter MAD for pressure data obtained from this experiment was calculated, equaling 0.0127.

Test No. 2: Sandpack No. 2 was displaced by Oil(B) to S wir . Then it was flooded by FW, Na50LSW, and Na10LSW, successively. The results of this test are illustrated in Fig.  7 .

Contrary to the previous experiment, the recovery factor did not increase when these low salinity water samples were injected. In the wettability alteration and IFT test, it was also observed that these water samples are unsuitable for improving this oil's recovery factor. The parameter MAD for pressure data was equal to 0.0119, which is very low and shows a negligible fluctuation in data, illustrating no fine migration status.

Test No. 3: In this test, the third sandpack was flooded by FW, Ca50LSW, and Ca10LSW. Figure  8 illustrates the results of this test.

The results of ( A ) pressure, ( B ) permeability, and ( C ) recovery volume obtained from flooding of sandpack No. 3 by FW, Ca50LSW, and Ca10LSW.

Figure  8 clearly illustrates that the injection of Ca50LSW does not improve conditions. The previous experiments also discussed that this concentration of divalent cations resulted in a severe contraction of EDL in matrix particles and oil droplets. As a result, wettability and IFT do not improve. However, by reducing the concentration of this cation to 10 mM, EDL expansion occurs, and RF increments as repulsive forces dominate. Here, the permeability value incremented from 36 to 45 md, which can be affected by various factors such as wettability alteration, IFT reduction, and Sw increment. The MAD parameter for pressure data obtained from this experiment was 0.0108, which shows a smooth pressure change over time.

Test No. 4: Sandpack No. 4 was flooded by FW, Ca50LSW, and Ca10LSW successively. The data obtained from this experiment is illustrated in Fig.  9 .

The results of ( A ) pressure, ( B ) permeability, and ( C ) recovery volume obtained from flooding of sandpack No. 4 by FW, Ca50LSW, and Ca10LSW.

The data in this figure illustrate that reducing water salinity is ineffective in raising the RF of Oil(B). Also, the wettability and IFT data illustrated that the expansion of EDL does not increment the values of repulsive forces by reducing the salinity of injected water. The MAD parameter is 0.0111 showing smooth change in pressure; therefore, it is a convincing reason that fine migration does not occur.

Test No. 5: In this test, sandpack No. 5, which contains five wt% kaolinite, was flooded by FW, Na50LSW, and Na10LSW. The results of this test are illustrated in Fig.  10 .

The results of ( A ) pressure, ( B ) permeability, and ( C ) recovery volume obtained from flooding of sandpack No. 5 by FW, Na50LSW, and Na10LSW.

Based on the data in this figure, it is clear that the amount of RF increments with the injection of Na50LSW. This paper previously explained that Na50LSW can alter the matrix's wettability to water-wet. Thus, the positive effect of this brine in increasing RF is apparent. However, there is a fundamental difference here with the increment of RF, which increments the S w in the sandpack, and the value of K eff for the water phase reductions. Also, the increment in RF for this experiment (from 57 to 80%) is much higher than in experiment number 1 (from 62 to 75%), where kaolinite particles were absent in the sandpack. Thus, injecting this water and Na10LSW into the sandpack is a more effective phenomenon than wettability alteration. Based on the analysis of interparticle forces in the kaolinite-quartz complex, it was found that these brines result in repulsive forces prevailing. Thus, this phenomenon is fine migration, which increments the recovery factor.

Statistical analysis of pressure data in this experiment shows a moving average of pressure increases over time. Furthermore, the magnitude of MAD for pressure data was equal to 0.0636, which is much higher than the previous experiment and shows fluctuation in data. As previously discussed, pressure increments with fluctuation are a clue to the occurrence of fine migration.

Test No. 6. Here, sandpack No. 6 containing 5 wt% kaolinite particles and Oil(B) is flooded by FW, Na50LSW, and Na10LSW.

Figure  11 illustrates that injection of Na50LSW and Na10LSW increments RF. Also, in this process, contrary to experiments 1–4, the increment in RF is accompanied by a reduction in permeability. Also, it was found earlier in this article that these brines cannot alter the wettability of oil (B) and quartz. Also, IFT changes can be ignored for this oil sample. Thus, it is clear that fine migration leads this oil to be swept from the pores. Figure  12 illustrates that this phenomenon increments RF by 14%. While the only possible phenomenon in this test is fine migration, it has had an acceptable performance and has resulted in RF improvement even more than wettability alteration and IFT reduction. The parameter MAD was equal to 0.0692, which shows fluctuation in pressure data.

The results of ( A ) pressure, ( B ) permeability, and ( C ) recovery volume obtained from flooding of sandpack No. 6 by FW, Na50LSW, and Na10LSW.

The results of ( A ) pressure, ( B ) permeability, and ( C ) recovery volume obtained from flooding of sandpack No. 7 by FW, Ca50LSW, and Ca10LSW.

Test No. 7: In this test, sandpack No. 7, which contains 5 wt% kaolinite and oil(A), was flooded by FW, Ca50LSW, and Ca10LSW. The results are illustrated in Fig.  12 .

It can be seen here that when the concentration of divalent cations in the injection water is high, the benefits of low salinity water injection do not occur. Neither fine migration nor wettability alteration nor IFT reduction has happened. For this reason, the amount of RF did not improve much with the injection of Ca50LSW. However, with the reduction in the concentration of divalent cations, the number of RF increments. Considering that the rise in oil production from sandpack coincides with the reduction in permeability, it is sure that fine migration is also effective. The parameter MAD for pressure data was 0.0302 in this experiment, which shows that a lower degree of fine migration occurred.

Test No. 8. Sandpack No. 8 was flooded by FW, Ca50LSW, and Ca10LSW; the results are illustrated in Fig.  13 .

The results of ( A ) pressure, ( B ) permeability, and ( C ) recovery volume obtained from flooding of sandpack No. 8 by FW, Ca50LSW, and Ca10LSW.

Figure  13 illustrates that RF starts to increase when the concentration of divalent cations reduces to 10 mmol. Meanwhile, none of the wettability alteration and IFT reduction mechanisms are expected for this condition. Also, because the increment in RF occurs after the reduction in permeability, it is evident that fine migration is the effective mechanism. The parameter MAD for pressure data was 0.0412, which shows partial fine migration.

This research first studied the impact of various parameters such as salinity, divalent cation concentration, and oil type on interparticle forces in a clay-rich porous media. The below results were obtained from this step.

Lowering salinity stimulates repulsive forces between various particles. This occurs when TDS is less than 3000 ppm and divalent cation concentration is less than ten mmol.

The interparticle force in the oil-quartz system is mainly related to the chemistry of the crude oil. Acidic functional groups present in oil make the oil sensitive to water salinity. Thus, reducing salinity, particularly divalent cation concentration, makes the oil droplets smaller.

Interparticle repulsive forces between oil droplets lead to IFT reduction. Thus, water salinity can affect the IFT value of oil with a high total acid number (TAN), but not for other oils. It should be noted that IFT reduction is less effective than wettability alteration and fine migration for oil recovery.

A core flooding experiment was conducted in the next step, which showed that.

Reducing the TDS of the injected brine to less than 3000 ppm and the concentration of divalent cations to 10 mM leads to fine migration in the porous media, which positively impacts the recovery factor (RF) for both types of oil.

Fine migration increments the RF of any oil, while wettability alteration and IFT reduction depend on the oil type in the porous media and are less effective than fine migration.

In conclusion, the study provides valuable insights into the interparticle forces and their effects on low salinity water performance, highlighting the importance of careful evaluation and optimization of injection water composition to achieve optimal results in oil recovery.

Data availability

The authors declare that the data supporting of this study are available within the paper and its Supplementary Information files.

Abbreviations

Base number

Derjaguin, Landau, Verwey, and Overbeek

Electric double layer

Enhanced oil recovery

Formation water

Interfacial tension

• Low salinity water

Mean absolute deviation

• Recovery factor

Total acid number

X-ray differaction

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Kazemi, A., Khezerloo-ye Aghdam, S. & Ahmadi, M. Theoretical and experimental investigation of the impact of oil functional groups on the performance of smart water in clay-rich sandstones. Sci Rep 14 , 20172 (2024). https://doi.org/10.1038/s41598-024-71237-1

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DOI : https://doi.org/10.1038/s41598-024-71237-1

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