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Inhibition of Scale Formation Using Silica Nanoparticle

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Because of the wide use of water injection for enhanced oil recovery in the oil fields in order to displace oil into the production well, many reservoirs experience scale deposition problems. Scale formation can cause the production path to be blocked and also cause significant reduction in productivity. One of the most common methods for preventing or lowering the amount of scale formation is applying the scale inhibitors. In this work, silica nanoparticles are used as a scale inhibitor. Conductivity is used as a property of the fluid to show the amount of ion in the solution, leading us to predict the amount of scale formed in the solution. An optimum amount of silica nanoparticles could reduce the rate of conductivity decreasing the solution and consequently lowering the scale deposition, which is the aim of this challenging subject in the oil industry.
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Inhibition of Scale Formation Using Silica Nanoparticle
Mehdi Safari a , Alireza Golsefatan b & Mohammad Jamialahmadi b
a Amirkabir University of Technology , Tehran , Iran
b Petroleum University of Technology, Petroleum Engineering , Ahwaz , Iran
Accepted author version posted online: 16 Sep 2013.Published online: 10 Jul 2014.
To cite this article: Mehdi Safari , Alireza Golsefatan & Mohammad Jamialahmadi (2014) Inhibition of Scale Formation Using
Silica Nanoparticle, Journal of Dispersion Science and Technology, 35:10, 1502-1510, DOI: 10.1080/01932691.2013.840242
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Inhibition of Scale Formation Using Silica Nanoparticle
Mehdi Safari,
1
Alireza Golsefatan,
2
and Mohammad Jamialahmadi
2
1
Amirkabir University of Technology, Tehran, Iran
2
Petroleum University of Technology, Petroleum Engineering, Ahwaz, Iran
GRAPHICAL ABSTRACT
Because of the wide use of water injection for enhanced oil recovery in the oil fields in order to
displace oil into the production well, many reservoirs experience scale deposition problems. Scale
formation can cause the production path to be blocked and also cause significant reduction in
productivity. One of the most common methods for preventing or lowering the amount of scale
formation is applying the scale inhibitors. In this work, silica nanoparticles are used as a scale
inhibitor. Conductivity is used as a property of the fluid to show the amount of ion in the solution,
leading us to predict the amount of scale formed in the solution. An optimum amount of silica
nanoparticles could reduce the rate of conductivity decreasing the solution and consequently
lowering the scale deposition, which is the aim of this challenging subject in the oil industry.
Keywords Conductivity, nanoparticle, scale formation, scale inhibitor, water injection
INTRODUCTION
In order to increase production from the reservoirs,
different methods are used, that is, enhanced oil recovery
(EOR) methods. Water injection in the oil column (which
also is called water flooding) is one of the most common
secondary EOR methods used in the oilfields. The most
common type of water used for injection into the reservoir
is sea water (SW). Injection water contains high concen-
tration of the sulfate ions. Also formation water (FW) con-
tains cations with two positive charges such as calcium,
barium, and strontium ions.
[1]
When the injection of SW
into the reservoir takes place to displace the remaining oil
left in the oil column, the two waters (injection and FWs)
approach each other and mix. The difference in concen-
tration of ions in the waters causes incompatibility between
them. Thus, when the injection waterand FW in the reservoir
mixed with each other, because of incompatibility, precipi-
tates would be formed. If two waters interact chemically
and precipitate minerals when mixed, they are called
incompatible.
[2]
Incompatibility in the water injection system
Received 13 August 2013; accepted 29 August 2013.
Address correspondence to Mehdi Safari, Amirkabir University
of Technology, Tehran, Iran. E-mail: safari_mahdi64@yahoo.com
Color versions of one or more of the figures in the article can be
found online at www.tandfonline.com/ldis.
Journal of Dispersion Science and Technology, 35:1502–1510, 2014
Copyright #Taylor & Francis Group, LLC
ISSN: 0193-2691 print=1532-2351 online
DOI: 10.1080/01932691.2013.840242
1502
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mainly occurs because of the difference between the two
waters in their ion concentration. These precipitates are
known as scale deposition. Deposition of scale precipitants
is one of the major oil field problems that occurs when two
incompatible waters are mixed.
[3–9]
Scale limits sometimes
blocks oil and gas production paths by plugging the
oil-producing formation matrix or fractures, perforated
intervals, and tubing.
[3]
It can also plug production
equipment and surface facilities and damage fluid flow.
[3]
Two main types of scale deposition commonly found in the
oilfield are carbonate and sulfate scales.
[4,10–21]
The ion con-
centration of the two waters could be shown by conductivity.
This property shows the amount of ions in the solution either
before or after mixing of the two waters. The typical examples
are SW, which contains high concentration of sulfate ion, and
FW, which contains high concentrations of calcium, barium,
and strontium ions. Mixing of these two waters, therefore,
could cause precipitation of calcium sulfate, barium sulfate,
and=or strontium sulfate.
As said before, these precipitates are called scale. The
most and less common minerals are shown in Table 1.
Up to now, several experiments studied the amount of
precipitates caused by mixing of injection water and FW
in cores and sandpacks.
[22,23]
The main objective in these
experiments is to reduce the amount of scale formation
during the water injection process. In order to reduce the
amount of scale deposition, one of the most common
methods used is using scale inhibitors. The role of
inhibitors is reducing, minimizing, or preventing of scale
deposition.
[24]
In the literature, the performance of so many
different scale inhibitors are dealt with. Generally, the
inhibitors are divided into two groups: organic and inor-
ganic. The most common types of inhibitors are inorganic
phosphates, organophosphorous compounds, and organic
polymers.
[24]
The two common and commericial scale inhi-
bitors used in the oil and gas industry are poly-phosphono
carboxylic acid (PPCA) and diethylenetriamine-penta
(methylene phosphonic acid) (DETPMP).
[25]
In this work,
silica nanoparticles are used as an inhibitor. Nanoparticles
are such materials that the average diameter of their particles
is in the size of nanometer. Also these particles have surface
charges and might be effective in the scale formation
processes. In order to see whether they might be effective
or not, their performance will be investigated here. Our main
objective is reducing and minimizing the scale deposition by
using the silica nanoparticles.
SCALE FORMATION MECHANISMS
Supersaturation, accelerated kinetics, and optimum
substrates are the driving forces for scale formation
in continuous digesters. These driving forces are described
in the following
[26]
:
Supersaturation
.Supersaturation occurs when dissolved cations
and anions such as Ca
þ2
and CO32increase
in concentration to levels that exceed their normal
solubility limits in process waters.
Accelerated Kinetics
.Temperature shocks, intense mechanical and
hydrodynamic shear forces, optimum pH con-
ditions, and sudden changes in pressure can all
accelerate the kinetics of scale formation.
Optimum Substrates
.The non-uniform surfaces found on heat exchanger
tubes, washer wires, extraction screens, etc.,
TABLE 1
Types of common scales
[3]
Class Type Name
Chemical
formula
Most
common
Carbonate Calcium
carbonate
carbonate
CaCO
3
Calcium sulfate CaSO
4
Sulfate Barium sulfate BaSO
4
Strontium
sulfate
SrSO
4
Less
common
Iron
compounds
Ferrous
carbonate
FeCO
3
Ferrous sulfide FeS
Ferrous
hydroxide
Fe(OH)
2
Ferrous
hydroxide
Fe(OH)
3
FIG. 1. Schematic representation of the most important steps in the
pathway from soluble ion to a macroscopic calcium carbonate scale
deposit.
[26]
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serve as optimum substrates to promote the
attachment of inorganic microcrystals and the
build-up of adherent scale layers.
The process of scale formation occurs in a series of
steps, as illustrated in Figure 1.
ANTISCALING MECHANISMS
Polymeric antiscalants function primarily by one or
more of three possible mechanisms: threshold inhibition,
dispersion, and crystal modification. As illustrated in
Figure 2, when a microcrystal of scale begins to form, the
antiscalant adsorbs onto the growing crystal surface. At
this point, three pathways for scale prevention can occur.
[26]
MATERIALS
Salts
The salts that were used in this project are sodium
sulfate and calcium nitrate. The reason for choosing these
salts is because in the SW the sulfate ion and in the FW
the nitrate ion is usually found. Also when these two salts
react with each other leads to generation of calcium sulfate
salt that is a common scale in the reservoir.
Brines
SW and FWs were made up in two methods, ideal
salinity and real salinity. The ideal solution was made up
by solving sodium sulfate and calcium nitrate in deionized
water, respectively. Approximate component for made up
real solution are shown in Table 2.
Nanoparticles
In this work, nanoparticles is used as an inhibitor.
As said before nanoparticles are such materials that the
average diameter of their particles is in the size of
nanometer and these particles have surface charges and
might be effective in the scale formation processes. If the
size of particles of any material decrease the number of
particles increase. If the original particles have surface
charges, by decreasing the size of them and so increasing
the number of them the concentration of surface charges
or the surface charges per unit surface area of the particle
increases. So we see that if the size of the particles of any
material with these specifications decreases down to
nanometer a large and strong network of surface charges
will be formed through them. This network could play an
important role in the solutions where the ions exist in order
to attract or repulse the other ions and also in reactions
such as formation of salts. As said the average size of nano-
particles is in nanometer. Also because of the surface
charges of any particle of these materials a strong network
of charges will be formed through them. By addition of
nanoparticles to SW in order to add it to the FW these
particles do a really important action. Because of their
FIG. 2. Pathways of scale prevention.
[26]
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surface charges they attract the other ions with opposite
sign with them. So they adhere to them and preventing
the other ions to react with them. Also these particles
repulse the ions with the same sign with them and so
prevent the other ions to react with them too. As a result
the formation of salts or precipitates decreases. So nano-
particles could be used as scale inhibitor. The performance
of nanoparticles against the scale deposition formation will
be investigated here in the form of series of experiments.
In this work, two types of silica nanoparticle were used
as scale inhibitors. The main one is silica nanoparticles that
in the text and discussion of experiments are called as
nanoparticles only. The concentration of the nanoparticles
in the SW is expressed by weight percent (wt%).
Apparatus
The apparatuses that were used in this project are
conductivity meter, ultrasonic, magnetic stirrer balance,
and also other utensils.
EXPERIMENTAL PROCEDURE
In this work, the static test part of scale formation
experiment has been done. The procedure of the series of
experiments is as follows.
(1) First of all, components of solutions (sodium sulfate
and calcium nitrate) were weighted with the balance.
(2) Then they will be solved in deionized water in two
different beakers. The solution that contains sodium
sulfate will be named as SW and the one that contains
calcium nitrate will be named as FW as said before.
(3) Then 50 cc of FW is poured in another beaker and the
SW is added to it by 5 cc per time up to 50 cc (in order
to SW per FW ratio to reach 50%). At each time after
mixing them, the conductivity of the solution will be
measured.
(4) After that, in order to see the effect of nanoparticles
on the deposition of calcium sulfate; the nanoparticles
are added to SW in a specific concentration (0.1 wt%,
0.2 wt%, etc.). For doing this, nanoparticles are
dispersed in the SW by using ultrasonic apparatus
for about 20 minutes. Then the step 3 was done again
for this new solution.
(5) The plot of conductivity versus additive volume of SW
to FW is plotted for steps 3 and 4. Also in order to see
the difference between the plots they could be merged.
(6) This work is done for different nanoparticles concen-
tration. At the end, we could see the results between
for all the experiments as in the results section.
RESULTS AND DISCUSSION
The series of experiments were done in different steps
using different amount of salts and nanoparticles and also
different volume of solution. A series of discussion would
be before each figure and a more general discussion would
be at the end of the figures which contain curves.
According to Figure 3, the conductivity of the solution
containing 0.1 wt% nanoparticles is higher than the
solution without them. It could be concluded that the
nanoparticles could affect the precipitates generation and
the existence of them could increase the conductivity of
the solution and also decrease the precipitates generation.
The rapid slope of the curves at the beginning of the
addition of the two solutions is considerable. It reflects that
the most amount of scale precipitation would be formed
at the beginning of the addition of the two solutions.
So controlling the scale formation at the beginning of
the addition of the SW to the FW is important.
As shown in Figure 4, the conductivity of solutions
containing 0.1 and 0.2 wt% nanoparticles are greater
than the solution without nanoparticles. It could be that
nanoparticles prevent generating of precipitates and the
ion concentration will be increased in the solution. Also,
the effect of the solution containing 0.1 wt% nanoparticles
is greater than the solution containing 0.2 wt% nanoparti-
cles in increasing the conductivity of the solution and so
decreasing the precipitates generation. It might have
resulted from the fact that in this solution, the effect
FIG. 3. Conductivity versus additive pore volume of SW to FW
containing 2 g Na
2
SO
4
per 100 cc distilled water and 3.4 g Ca(NO
3
)
2
per 100 cc distilled water, respectively.
TABLE 2
Components of real solution
Type of
salt
Siri formation
water (ppm)
Sea water (Persian
Gulf) (ppm)
NaCl 60000 20000
CaCO
3
3000 300
KNO
3
2000 0
MgSO
4
800 2000
NaHCO
3
600 200
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of nanoparticles is increasing the conductivity up to a limit
and then decreasing it. So if the amount of nanoparticles
in the solution increased, it could not be concluded that
the conductivity of the solution would be increased.
The conductivity of the real solution is shown in
Figures 5 and 6. As discussed before the effect of nano-
particles is increasing the conductivity of the solution
and decreasing the amount of precipitates generation.
The effect of the solution containing 0.5 wt% nanoparticles
is greater in increasing the conductivity of the solution
comparing the solution containing 0.2 wt% nanoparticles.
It could not be concluded that if we increase the amount
of nanoparticles in the solution the conductivity would be
increased because the types of nanoparticles that were used
in these solutions are different (called Type 1 and Type 2).
According to Figure 7, the conductivity of the solution
containing 0.5 wt% nanoparticles is less than the solution
without nanoparticles. The cause of this is not known
accurately. It might have resulted from the fact that
because of high concentration of the nanoparticles, they
were not dispersed in the water very well. As the concen-
tration of the nanoparticles increased, the ability to become
disperse in the water decreased. Also this could be because
of that if the amount of nanoparticles in the solution
increased conductivity would increase up to a limit of
amount of them and then it would be decreased (as we
will see in the following experiments and pages).
In order to see the effect of the temperature on the scale
formation, another series of experiments were done. As
shown in Figure 8, the conductivity of the solution that
contains 0.05 wt% nanoparticles is higher that the solution
without them. Again the effect of nanoparticles is
to increase the conductivity and decrease the amount of
precipitation. This experiment is done at two different
temperatures. Figure 8 is at 25C and Figure 9 is at
50C. It is obvious that the effect of nanoparticles at higher
temperatures is the same as discussed before.
The same experiments were done by the solutions that
contain 0.1 and 0.2 wt% nanoparticles at two different
temperatures. The conductivity of the solution that
contains 0.1 wt% nanoparticles is higher than the solution
without them, but the conductivity of the solution that
contains 0.2 wt% nanoparticles is lower than the solution
without them. As shown before this could be because
of increasing the amount of nanoparticles to the solution
FIG. 4. Conductivity versus additive pore volume of SW to FW
containing 1 g Na
2
SO
4
per 100 cc distilled water and 1.7 g Ca(NO
3
)
2
per 100 cc distilled water, respectively.
FIG. 6. Conductivity versus additive pore volume of SW to FW for
the real solution.
FIG. 5. Conductivity versus additive pore volume of SW to FW for
the real solution.
FIG. 7. Conductivity versus additive pore volume of SW to FW
containing 10 g Na
2
SO
4
per 100 cc distilled water and 17 g Ca(NO
3
)
2
per 100 cc distilled water, respectively.
1506 M. SAFARI ET AL.
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would not increase the conductivity no matter that how
much the amount of them increased. So the addition
of nanoparticles to the injected water would increase the
conductivity and also decrease the precipitates up to a limit
and then the conductivity would be decreased and the
precipitates generation would be increased. The rapid
decreasing of the conductivity at the beginning of the
FIG. 8. Conductivity versus additive pore volume of SW to FW
containing 1 g Na
2
SO
4
per 100 cc distilled water and 1.7 g Ca(NO
3
)
2
per 100 cc distilled water, respectively, at 25C.
FIG. 9. Conductivity versus additive pore volume of SW to FW
containing 1 g Na
2
SO
4
per 100 cc distilled water and 1.7 g Ca(NO
3
)
2
per 100 cc distilled water, respectively, at 50C.
FIG. 10. Conductivity versus additive pore volume of SW to FW
containing 1 g Na
2
SO
4
per 100 cc distilled water and 1.7 g Ca(NO
3
)
2
per 100 cc distilled water, respectively, at 25C.
FIG. 11. Conductivity versus additive pore volume of SW to FW
containing 1 g Na
2
SO
4
per 100 cc distilled water and 1.7 g Ca(NO
3
)
2
per 100 cc distilled water, respectively, at 50C.
FIG. 12. Conductivity versus additive pore volume of SW to FW
containing 1 g Na
2
SO
4
per 100 cc distilled water and 1.7 g Ca(NO
3
)
2
per 100 cc distilled water, respectively, at 25C.
FIG. 13. Conductivity versus additive pore volume of SW to FW
containing 1 g Na
2
SO
4
per 100 cc distilled water and 1.7 g Ca(NO
3
)
2
per 100 cc distilled water, respectively, at 50C.
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addition of the two waters could be because of the scale
formation would be occurred generally at this range of time
of addition.
The figures of solutions containing 0.05, 0.1, and
0.2 wt% nanoparticles are merged with each other in
Figures 14 and 15 in order to see them simultaneously.
Another series of experiments were done in order to see
a wider range of nanoparticles concentration. As discussed
before it could be seen from Figure 16 that if the amount of
nanoparticles in the solution increased the conductivity
would be increased up to a limit and then would be
decreased and also the precipitates generation would be
decreased up to that limit and then would be increased.
Generally in all of the figures we could see that the rate
of reduction of conductivity or the slope of all curves at the
beginning of the addition of the two waters is high. This
reflects that the most amounts of precipitates would be
formed at this range of addition of the two waters. This
might be because of that the difference in ion concentration
between the two waters is more at the start of addition
and become less as the additive volume of the SW to FW
gets more. So the electrical charges that exist in the solution
is more and the ions attract to each other more. Then the
inclination of the ions to react with each other and to form
the precipitants is more. As we see the addition of nano-
particles to SW will decrease this high rate of reduction
of conductivity generally up to a limit. So up to this limit
the use of nanoparticles will increase the conductivity of
the solution and then decrease the amount of precipitates
formation. As a result of this we could use nanoparticles
as an inhibitor to reduce and also prevent the scale forma-
tion. So the precipitate formation is more important at
the beginning of the addition of SW to FW and we should
consider more to prevent the precipitate formation at the
beginning of the injection of the SW by using nanoparticles.
Also we could see from the figures that the slope
of all curves that show the conductivity of the solutions
with and without nanoparticles will gradually decrease.
As previously mentioned, this might be because of that
difference in ion concentration between the two waters will
decreases as the additive volume of the SW to FW gets
more. So the electrical charges that exist in the solution
is less and the ions attract to each other less. Then the
inclination of the ions to react with each other and to form
the precipitants is less. So the slope of the curves will
gradually decrease and the importance of the precipitate
formation is not as more as before and this will decrease
as the addition of SW to FW increases.
The figures also show a limit of addition of the nano-
particles to SW. When the concentration of the nanoparticles
is less than this limit the performance of the nanoparticles
is in the direction of decreasing the amount of precipitation.
As the concentration of the nanoparticles becomes more
than this limit the performance of the nanoparticles is
in the opposite direction which means this will increase the
amount of precipitation. So for each case we should find
this limit both for optimizing the amount of precipitates
formation and optimizing the economic aspects of the case.
FIG. 14. Conductivity versus additive pore volume of SW to FW
containing 1 g Na
2
SO
4
per 100 cc distilled water and 1.7 g Ca(NO
3
)
2
per 100 cc distilled water, respectively, at 25C.
FIG. 15. Conductivity versus additive pore volume of SW to FW
containing 1 g Na
2
SO
4
per 100 cc distilled water and 1.7 g Ca(NO
3
)
2
per 100 cc distilled water, respectively, at 50C.
FIG. 16. Conductivity versus additive pore volume of SW to FW
containing 1 g Na
2
SO
4
per 100 cc distilled water and 1.7 g Ca(NO
3
)
2
per 100 cc distilled water, respectively.
1508 M. SAFARI ET AL.
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In order to see that the nanoparticles are stable in
the final solution, Figure 17 was captured by laboratory
camera at different times after the end of the experiment.
It could be seen that the nanoparticles are stable in the
solution even after the hours that passed the end of the
experiment.
Also in order to see the scale precipitates and stability
of the nanoparticles in the final solution, Figure 18 was
taken by scanning electron microcopy (SEM) apparatus.
The scale precipitates are clear in the images. As it
could be seen from these images, the scale precipitates
are separate from each other. It could be concluded that
the nanoparticles could prevent the scale precipitates from
aggregation very well and so the amount of precipitation
would be reduced.
Also, Figure 19 was taken by an ordinary camera, the
amount of scale precipitates that was formed before
(the left beaker) and after (the right beaker) adding nano-
particle is shown.
CONCLUSION
1. Addition of the minimum amount of the nanoparticles
to the injected water (SW) increases the conductivity
of the solution.
2. By adding the minimum amount of the nanoparticles
to the injected water (SW), the probability of scale
formation of the solution will decrease.
3. Increasing the amount of nanoparticles to the SW will
increase the conductivity of the solution up to a limit.
4. By increasing the amount of nanoparticles to the SW
the probability of scale formation of the solution will
decrease up to a limit.
5. After the limit that is said above, addition of nano-
particles to the SW will not increase the conductivity
of the solution but also decrease.
6. After the limit that is said above, addition of nano-
particles to the SW will not decrease the probability
of scale formation of the solution but also increases.
7. Nanoparticles could be used as an inhibitor in order
to decrease, minimize, or prevent scale formation.
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FIG. 18. Images of the final solution by SEM apparatus.
FIG. 19. Scale formation before and after of experiment.
FIG. 17. Images of the final solution by laboratory camera.
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... Consequently, scale deposition negatively affected the stability of NPs in brine. As a result, NPs with optimum concentration could reduce scale formation in solution [49][50][51] . Also, scale deposition is inversely related to the stability of NPs in brine 49 . ...
... As a result, NPs with optimum concentration could reduce scale formation in solution [49][50][51] . Also, scale deposition is inversely related to the stability of NPs in brine 49 . ...
... Sandstone surface has some active sites for potential determining ions, such as Ca 2+ , Mg 2+ , and SO 4 2to attach and alter the rock-brine interface charge. Therefore, when the salinity of injection brines changes, the ionic compositions for binding sites and their reaction with OH − and H + ions in solution also change, resulting in ZP values that can differ 49 . The OLSW solution prompted a higher negative surface charge due to ions adsorption on the rock particles' surface. ...
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Recent studies showed the high potential of nanofluids as an enhanced oil recovery (EOR) agent in oil reservoirs. This study aimed to investigate the effects of salts and ions, the salinity of aqueous solution, total dissolved solids (TDS), scale deposition of mixing brines, surface charge as zeta potential (ZP) value, and pH of injected brines as low salinity water (LSW) on the stability of silica nanoparticles (NPs). The experiments were conducted on the stability of silica NPs at different concentrations and brines to determine optimum salinity, dilution, cations, and anions concentrations. The results showed that 10 times diluted seawater (SW#10D) was optimum low salinity water (OLSW) as injected LSW and water-based nanofluids. Results showed that by decreasing the salinity, increasing seawater dilution, and removing Mg²⁺ and Ca²⁺ cations, the amount of scale deposition decreased, and the brine's brine's brine stability of NPs in brine improved. At the optimum salinity and dilution conditions, compared with other salinities, there was less scale formation with more nanofluid stability. Obtained results from ZP measurements and dynamic light scattering (DLS) showed that by removing divalent ions (Mg²⁺ and Ca²⁺) of water-based nanofluid (low salinity hard water (LSHW) composition), more NPs were attached to the surface due to the reduction in repulsive forces between the NPs. Therefore, at optimum low salinity soft water (OLSSW), more wettability alteration occurred compared with optimum low salinity hard water (OLSHW) due to the more stability of NPs in OLSSW. The obtained results from the contact angle measurements, surface adsorption of the NPs by FESEM images, and ZP measurements showed that the predominant mechanism in enhancing oil recovery by nanofluid was the wettability alteration by disjoining pressure. According to wettability alteration results, the silica NPs with an optimized concentration in the optimized LSHW and LSSW compositions could be improved the wettability alteration by up to 23.37% and 55.81% compared with the without NPs. The optimized LSSW compared with LSHW composition could be improved the wettability alteration by up to 11.69%. In addition, OLSSW-based nanofluid compared with OLSHW could be increased wettability alteration toward strongly water-wet by up to 33.44%.
... R represents the retardation factor, and J d (min −1 ) is the SINM deposition rate coefficient to medium surfaces. J d value can be calculated based upon the filtration theory (Ryan and Elimelech, 1996;de Jonge et al., 2004): ...
... Another commonly investigated metal oxide for its impact in scaling control is silica (SiO 2 ) NP (Safari et al., 2014). One study showed that the presence of silica NP can slow down solution conductivity reduction rate in an oversaturated solution, indicative of reducing scale deposition. ...
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... Scale inhibitors are low-dosage, water-soluble chemicals such as water-soluble polymers and nonpolymeric compounds, that prevent nucleation, crystal growth, and deposition of scales in the first place [189]. The potential usage of silica NPs as a scale inhibitor was demonstrated by Safari et al. [190]. They observed an increase in the solution conductivity when they added a small amount of silica NPs to the injected seawater which indicated a higher concentration of ions in the solution and thus, reduced scale deposition. ...
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A wide range of enhanced oil recovery (EOR) methods has been proposed to accelerate the recovery of remaining oil in subsurface reservoirs. One important class of methods is water-based chemical EOR (CEOR). The existing screening workflows for CEOR assessment and selection for a particular field focus primarily on the subsurface performance evaluation while a holistic, full-cycle assessment that considers all surface and subsurface challenges is missing. Some of the pre-injection/injection challenges of a CEOR method are the high cost of chemicals, preparation, transportation, storage, scaling, corrosion, and low injectivity. Some of the production/post-production issues include environmental problems of toxic chemicals, separation, treatment, recycling, and safe disposal of the produced chemicals. All of these necessitate the deployment of complex surface facilities which are in turn affected by issues such as the location of the field (e.g., offshore, onshore, close to roads) and the age of the existing facilities. A further important consideration is the overall lifecycle carbon footprint associated with the CEOR deployment and operation. These challenges may overshadow the significant technical benefits of CEOR for extracting the remaining oil while addressing them can accelerate the deployment of CEOR to target fields. In this review paper, a full-cycle review and analysis of different CEOR methods is presented. The technical, economical, surface, subsurface, and environmental challenges, together with the determining factors for success, are critically reviewed. The outcome of this integrated investigation can then be used as a basis for the development of a holistic CEOR screening workflow.
... The crucial problems of scale formation in the oil and gas fields motivate scientists to probe the nucleation/growth process mechanisms [249]. The thermodynamic instability and incompatibility of solutions often cause scale nucleation and growth in the bottom-hole formation zone, injection and production wells, valves, electric submersible pumps (ESP), production tube, and transport and treatment systems, which could result in serious damages and economic losses [250][251][252]. ...
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In the last decade, there has been a swift development in several scientific research works in which the quartz crystal microbalance (QCM) technique has played a critical role in unravelling different aspects of energy and environmental materials and biological substances as well as all corresponding molecular interactions within those media. We comprehensively review the numerous types of surface chemistries, including but not limited to hydrogen bonding, hydrophobic and electrostatic interactions, self-assembled monolayers and ionic bonding, that are monitored using QCMs in a variety of fields such as energy and chemical industries in addition to the biology, medicine and nanotechnology disciplines. Furthermore, we critically review the QCM's diverse applications, which include the detection of organic and inorganic scale formation and deposition onto solid surfaces and evaluation of respective inhibitors, monitoring of adsorption/desorption of hydrocarbon surface-active species onto/from solid rock surface, detection of virions on the surface, diagnostics of various diseases, detection of protein aggregation, and detection of medicines. Focusing on the recent growth of applications of QCMs in each field within the last few years, some of the barriers, limitations, and prospective uses are succinctly highlighted. We hope that this review can pave the way for other researchers worldwide to expand their surface chemistry studies in the abovementioned fields using QCM based technologies.
... Recently nanotechnology has been the subject of interest in various studies [10,11], including the drilling fluid design given their efficiency to improve the rheology and flirtation control [8,12e14]. Such studies appear to improve borehole stability, reduce the drag and torque during trip-in/out [8] and prevent stuck pipes [12]. ...
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Chapter
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Chapter
Silicon–metal hybrid nanoparticles have been used as nanofluid scale inhibitors in oil and gas applications. These nanofluids have drawn much recent attention because of their unique physicochemical properties, as well as potential oilfield scale inhibitor squeeze treatment performance. This chapter focuses on the application of silicon–metal hybrid nanoparticles in oilfield scale inhibition.
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Article
A new approach for computing calcite scaling tendencies is described. Computed values are obtained by exactly solving the chemical equilibria expressions for calcite precipitation. To date, extremely accurate predictions of calcite scale deposition in oilfield systems have been made based on this computed scaling value. Introduction The deposition of water-formed scales causes the yearly expenditure of substantial funds by the petroleum industry. In addition to the cost of petroleum industry. In addition to the cost of chemicals to treat the water, additional expenses are incurred in clean-up costs to remove scale deposits from surface systems and from producing wells. Several techniques have been developed to predict scaling tendencies. Stiff and Davis predict scaling tendencies. Stiff and Davis modified Langelier's method for evaluating calcite scaling tendencies in oilfield brines. Because of the ease of computing Stiff-Davis values, this method has been widely applied in assessing scaling potentials in oilfield systems. Martin described a potentials in oilfield systems. Martin described a method for determining gypsum scaling tendencies, while Vetter has detailed a procedure for quantitatively evaluating the severity of gypsum, celestite, and barite scaling. In Vetter's computer method, the different scales are precipitated sequentially in order of their solubility product constants. After deposition (if any) of each solid, new equilibrium concentrations are determined for the other ions in solution. The missing factor in all these techniques, however, is the correlation between the calculated scaling potentials and actual field experiences. This paper describes a computer program which quantitatively determines the amount of supersaturation of each of the commonly encountered, oilfield-mineral scales. The novelty of this technique is that for the first time this quantitative determination of the supersaturation is the basis for making scaling predictions. Although this method has been most successful when applied to the prediction of calcite scale formation, this technique prediction of calcite scale formation, this technique theoretically can be used in predicting any of the other oilfield scales such as gypsum, barite, and celestite. Most of the discussions in this paper will concentrate on calcite scaling problems, since it is most frequently encountered in oilfield production systems. production systems. THEORY Because of its ease of calculation, the Stiff-Davis Stability Index, SI, is commonly used for predicting the tendency for calcite scale deposition predicting the tendency for calcite scale deposition in petroleum environments. This index compares the pH of the water with the pH at which the water would pH of the water with the pH at which the water would be exactly saturated with calcium carbonate. The Stiff-Davis Stability Index expression can be written as: (1) where: "pH" is the pH of the water sample as actually determined, "pCa" is the negative logarithm of the calcium concentration, "palk" is the negative logarithm of the total alkalinity, and "k" is a constant which was determined by Stiff and Davis and which depends on salinity and temperature. A positive SI value indicates that calcite scale deposition positive SI value indicates that calcite scale deposition could occur while a negative value is interpreted to mean that the water is undersaturated with respect to that particular scale. At Texaco a second approach to predicting the occurrence of oilfield scale deposits has been developed. A computer program has been written which quantitatively determines the amounts of scale which exist in oilfield brines (or mixtures of several brines) under various conditions of temperature and pH. This second method is both an extension and an pH. This second method is both an extension and an improvement upon the Stiff-Davis calculation method. The Texaco scaling predictions are based on a special interpretation of the results obtained from the exact solution of the chemical equilibria expressions for each particular mineral scale. P. 19