Ion-mediated desorption of asphaltene molecules from carbonate and sandstone structures [original]

Mater. Res. Express 9(2022)065101 https://doi.org/10.1088/2053-1591/ac784f

PAPER

Ion-mediated desorption of asphaltene molecules from carbonate

and sandstone structures

Pouyan Ahmadi

, Mohammadreza Aghajanzadeh

2,3

, Hamidreza Asaadian

4,∗

, Armin Khadivi

and

Shahin Kord

Department of Hydrogeology, Helmholtz-Centre for Environmental Research, UFZ, Germany

Department of Civil Engineering, Monash University, Melbourne, Australia

Department of Petroleum Engineering, Amirkabir University of Technology, Tehran, Iran

Norwegian University of Science and Technology (NTNU), Department of Geoscience and Petroleum, Trondheim, Norway

Technical University of Berlin, Berlin, Germany

Ahwaz Faculty of Petroleum, Petroleum University of Technology, Ahwaz, Iran

∗

Author to whom any correspondence should be addressed.

E-mail: [email protected] and [email protected]

Keywords: Wettability state, Molecular dynamic simulation, Asphaltene precipitation, Smart water, Bonding and non-bonding energy,

Coulomb interaction

Abstract

As more and more oil recovery scenarios use seawater, the need to identify the possible mechanisms of

wettability state changes in oil reservoirs has never been greater. By using molecular dynamics

simulations, this study sheds light on the effect of ions common to seawater (Ca

,Mg

,Na

−

, HCO

3−

,SO

2−

)on the afﬁnity between silica and carbonate as the traditional rock types and

asphaltene molecules as an important contributing factor of reservoir oil wetness. In the case of

carbonate and silica being the reservoir rock types, the measured parameters indicate good agreement

with each other, meaning that (HCO

−

&SO

2−

)and(Na

&Cl

−

)ions reached maximum bonding

energies of (25485, 25511, 4096, and −4093 eV, respectively). As with the surface charge density

measurements, the results of the non-bonding energies between the individual atomic structures agree

with those from the simulation cell. In the presence ofa silica surface, the radial distribution function

(RDF)results determine that the peak of the maximum value for the distribution of theions is 4.2.

However, these values range from 3 to 6.6, suggesting that different ions perform better under the

inﬂuence of carbonate rock. As these ions are distributed in the simulation box along with the

adsorption domain, the conditions for sequestering asphaltene from the rock surface are made ideal

for dissolution and removal. At equal ion strength, measuring the distance between the center of mass

of rocks and asphaltene structures reveals a maximum repulsion force of 22.1 Å and a maximum

detachment force of 10.4 Å in the presence of SO

2−

and Na

ions on carbonate and silica surfaces.

1. Introduction

Smart water ﬂooding has been proven to be one of the most successful methods for improving oil recovery due

to the impact of water chemistry and salinity on reservoir ﬂuid-ﬂuid and rock-ﬂuid interactions [1–5]. It has

been shown that the recovery of crude oil can be improved by manipulating the injection water [6–9]. Although

numerous studies have been conducted over the last two decades to study the effect of smart salinity water

ﬂooding on the improvement of crude oil recovery in carbonate and sandstone reservoirs, the underlying

mechanisms have not been completely revealed [2]. Multi-ion exchange (MIE), double-layer expansion (DLE),

wettability alteration, and pH effect are the most important mechanisms that have been widely reported in the

literature. Among these mechanisms, wettability alteration from oil-wet to water-wet is a widely accepted

mechanism in this ﬂooding method [10–17].

The wettability of the pore surface plays a vital role in the displacement of the crude oil by water. The

wettability state of the reservoir rock surface can be attributed to the adsorption of polar components from crude

OPEN ACCESS

RECEIVED

6 April 2022

REVISED

9 June 2022

ACCEPTED FOR PUBLICATION

13 June 2022

PUBLISHED

28 June 2022

Original content from this

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the terms of the Creative

Commons Attribution 4.0

licence.

Any further distribution of

this work must maintain

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and DOI.

oil at the mineral surfaces [18–22]. It is generally accepted that underground reservoirs are saturated with

formation brine before oil migrates into their rock pores. After the drainage of water by crude oil from the

porous media, the reservoir wettability may become less water-wet or even oil-wet because of the adsorption of

heavy components of crude oil onto rock surfaces. The main mechanisms by which crude oil compounds may

adsorb onto pore surfaces include surface precipitation, polar interactions, and acid/base and ion binding

interactions [18,23,24].

Asphaltenes are the most polar fraction in crude oil [25,26]. The adsorption of asphaltenes on mineral

surfaces is an important element of wettability changes toward oil-wet conditions and can have a strong negative

impact on rock properties. Asphaltenes are polycyclic aromatic hydrocarbons (PAHs)consisting of a sheet-like

structure of interlocked heterocyclic aromatic rings attached to hydrocarbon chains andcontaining both polar

and non-polar species [27]. In addition, heteroatoms such as oxygen, sulfur, and nitrogen atoms and trace

amounts of metals such as Fe, Ni, and V in asphaltene molecules make these molecules the most polar and

complex components of crude oil [28]. Changing the thermodynamic conditions may cause the precipitation

and adsorption of asphaltene onto the rock surface during the production and transportation of crude oil. The

adsorption of precipitated asphaltenes onto the rock surface can lead to formation damage in oil reservoirs by

reducing the effective oil permeability [29–31].

Many researchers have investigated the adsorption/desorption process of asphaltene molecules on and from

rock surface [31–36]. It was found that precipitated asphaltene molecules on the rock surface can be adsorbed in

nanoﬂuids containing metal oxide nanoparticles, such as TiO

, SiO

and Fe

[30,37,38]. Other experimental

and modeling studies have revealed that the injection of modiﬁed brine during the EOR process could desorb

asphaltene molecules and other polar components of crude oil from the mineral surfaces and alter the

wettability of the pore wall to less oil wet, resulting in improved oil recovery [7,39–42]. Ligthelm et al. showed

that a decrease in salinity increased the expansion of the diffuse double layer between the rock and oil interfaces,

facilitating the release of organic materials [11]. Yang et al. studied the desorption of asphaltenes from quartz

crystals in the presence of an electrolyte. They used a quartz crystal microbalance with dissipation (QCM-D),

atomic force microscopy (AFM), and contact angle to measure the amount of desorbed asphaltenes. They found

that desorption occurred when the rock surface was exposed to a saline solution. This is mainly because the

charge density of both the surfaces of oil-water and solid-water was promoted and the electrostatic repulsions

increased [43].

Despite extensive experimental and modeling studies on the effect of salinity on the adsorption/desorption

of asphaltene molecules from mineral surfaces, the exact mechanism that occurs at the atomic scale still needs to

be investigated in more detail; hence, the present work has concentrated on checking the inﬂuence of ions on the

absorbance tendency of polar asphaltene molecules on the surface of sandstone and carbonate rocks under

reservoir conditions. Hence, molecular dynamics simulations were used to understand the behavior of

asphaltene molecules upon exposure to cations and anions (i.e., Ca

,Mg

,Na

,Cl

−

, HCO

−

,SO

2−

)

available in smart water (salinity5000 ppm)in the presence of carbonate and sandstone rock types [44]. The

LAMMPS (stable release)software was used as the simulation tool, and all numerical calculations were crunched

using this computational package. All investigation methods, such as surfacecharge density measurement,

radial distribution function (RDF), discretizing of bonding and non-bonding energies, and measuring the

asphaltene detachment distance, have proved the importance of ion types on the fate of asphaltene molecules

that are stuck to the rock surface in reservoirs.

2. Computational method

2.1. Force ﬁeld and relative parameters

The present work employs molecular dynamics (MD)simulations to investigate the precipitation of asphaltene

on carbonate and sandstone structures in the presence of brine at a deﬁned temperature and pressure. MD

simulation is known as a computational method to estimate the dynamic translocation of particles considering

the underlying concept of intermolecular interactions at the atomic scale. In addition to the molecular

interaction for a speciﬁc time interval (time step), this method can provide an exact insight into the particle

transformation of the structures. In this method, Newton’s law, which is a numerically solving method,

determines the particle trajectories. Likewise, the interaction between the particles and their interatomic

energies is often computed using force ﬁelds in the system. In this study, Large-scale Atomic/Molecular

Massively Parallel Simulator (LAMMPS)software was used as a simulation tool, and the entire calculation of

asphaltene deposition on carbonate and sandstone structures was implemented by this computational package

using the Lennard Jones (LJ)potential [45]. This software was developed and released by Sandia National

Laboratories (SNL). Simulations of this research were carried out in the following steps, as mentioned

previously:

Mater. Res. Express 9(2022)065101 P Ahmadi et al

Step 1: In this step, the preliminaries of the simulation are set up, such as units, boundary conditions,

dimensions, bond type, atom location, and structure style. In the following simulations, the units were adjusted

real, the boundary condition was periodic, and the atomic structure was full.

Step 2: In the next step, atoms and molecules were introduced into the simulation environment. After

packing molecules with another software named Packmole and obtaining their data ﬁles, they were presented as

input to the designated simulation cell by the read data command. Furthermore, speciﬁc groups of atoms (i.e.,

,Mg

,Na

,Cl

−

, HCO

−

,SO

2−

)were assigned and distinguished with unique names by group

commands to achieve better control over them during simulations. In this stage, everything is well deﬁned and

the software is ready to start the simulation.

Step 3: In the last step, an approximate velocity must be estimated to minimize the convergence time by the

velocity command before reaching system stability. The more related system velocity according to the system

convergence temperature was estimated so that the computational time of the software used reached its

minimum as much as possible. The convergence temperature was set to 60°C or 333.15 K for all scenarios to

resemble reservoir conditions.

Pairstyle commands outline interactions (potential of forces)between atoms and molecules, such as

intermolecular, bond, and nonbonding energies. All interaction calculations were based on the Lennard-Jones

equation in the following simulation work.

Lennard-Jones presented the ﬁrst formula for this relationship in 1924 [45]. The following equation is called

the Lennard (LJ)potential.

⎜⎟ ⎜⎟

⎡

⎣

⎢⎛

⎝

⎞

⎠

⎛

⎝

⎞

⎠

⎤

⎦

⎥

=e s-s<rrr

rrU4 1

ij ij

12 6

() ()

where U(r)represents the Dreiding force ﬁeld [45], is the non-bond interaction, εis the depth of the potential

well, σis the distance at which the potential is 0, and r

is the distance between the atoms and molecules. This

equation can theoretically estimate the interactions between a pair of particles (atoms and molecules). Table 1

presents the scale of the length and energy parameters of various atoms in the simulated structures. The cutoff

radius was set to 12 Å for interactions between pairs of particles. Furthermore, Coulomb interaction was

implemented for the simulated structures using the following equation:

=<rrrrECQ Q 2

() ()

Where C is the energy-conversion constant, and εrepresents the dielectric constant. Q

and Q

are the charges on

two atoms. The cut-off radius is set to 10 Å forthis type of non-bonding interaction, and all atomic structures

with distances larger than the cut-off radius will not be taken into account in the numerical calculations

<rr.

(

)

The bond and angle strengths for the Dreiding potential are deﬁned by a simple harmonic oscillator

equation as follows:

EKrr12 3

() ()

=-EKrr12 4

r02

() ()

where K

and K

are harmonic oscillator constants, and r

and θ

represent the length of the atomic bondand

equilibrium value of the angle, respectively. In this work, the harmonic oscillator constants were adjusted to 700

((kcal/mol)/Å

)and 100 ((kcal/mol)/degree

)for K

and K

, respectively. The atomic bond lengths and

Table 1. The εand σparameters for

non-bond interactions in simulated

atomic structure [45].

ε(kcal/mol)σ(Å)

C 0.1450 3.9800

H 0.0100 3.20000

O 0.4150 3.71

S 0.3050 4.24

N 0.4150 3.9950

Ca 0.0500 3.4720

Si 0.0950 4.4350

Cl 0.3050 3.9150

F 0.3050 3.2850

K 0.3050 3.398

Mg 0.111 2.692

Na 0.5 3.144

Mater. Res. Express 9(2022)065101 P Ahmadi et al

equilibrium values of the angles for each bonded interaction are listed in table 2[45]. Furthermore, the dihedral

interactions in these simulations were based on previously reported bonding interactions. These bonding

interactions were calculated using the harmonic equation, and the coefﬁcients were selected from the Dreiding

force ﬁeld [45]:

=+ ÆEK dcosn15(()) ()

where K is the harmonic oscillator constant, d=+1or−1 and n is the integral number [45].

In addition, the Dreiding force ﬁeld is used for rock-asphaltene, rock–ion, ion–asphaltene, and rock-ﬂuid

interactions. Moreover, Newton’s second law at the atomic level was used for computations of the particle

motion through the simulation time. The following formula shows the gradient of the potential relation:

== = =-

Frv

dt md

dt grad V r 7

ij i

iiiij

() ()

The association of previous relations is performed using the velocity-Verlet algorithm to integrate Newton’s law

as follows:

dd+= +vttvtatt 8( ) () () ()

dd+= +vttrtvtt 9( ) () () ()

In these two relations, r(t+δt)and v(t+δt)are the ﬁnal position and velocity of the atoms (respectively)and r

(t)and v(t)are the initial rates of these mechanical parameters.

2.2. Designed atomic structures of molecules in the simulation cell

The designed simulation cells containing carbonate and sandstone surfaces along with the ions and asphaltene

molecules were adjusted according to the Dreiding force ﬁeld parameters to deﬁne the atomic structures and

force ﬁeld. Figure 1shows the frame in which the studied ions were randomly arranged by Packmole software

(version 20.010)in such a way that the ion strength for all scenarios was kept constant with a view to having an

exact comparison of ion impact on the way rock that the asphaltene molecule deals with rock surfaces in all cases.

In support of this idea, 10 asphaltene molecules considered in all scenarios and 100 of each ion were randomly

distributed in the designed cell, and the effect of the mixture of all ions was examined to observe the behavior of

asphaltene. Moreover, because most of the carbonate and sandstone rock constituents are made of SiO

and

CaCO

, respectively, and to eliminate the impact of impurities, the pure structures of each rock type were

considered in all simulations.

In all scenarios, water molecules were also added to thecells considering their real number, which was

proportional to the designed simulation cell volume. The pressure and temperature were adjusted to 60°C and

2500 psi, respectively, to make the situation more thermodynamically similar to real reservoir conditions. In this

study, the asphaltene molecule is precipitated due to thermodynamic disturbance and is not soluble in the water

Figure 1. Atomic structures with minimum tolerance of 2 Angstrom, a)Oil wet carbonate surface surrounded by common active ions

of seawater (left).b)Oil wet sandstone surface surrounded by common active ions of seawater (right).

Mater. Res. Express 9(2022)065101 P Ahmadi et al

bulk, which implies that the asphaltene molecule detachment could either intensify or alleviate under the

inﬂuence of what happens in the brine solution. Figure 2shows the structure of the polar asphaltene molecules,

which was used to check the effect of their tendency to be adsorbed on the rock surfaces. The asphaltene

structure belongs to one of the southern Iranian oilﬁelds, which contains heteroatoms (nitrogen, oxygen, and

sulfur)as the electronegative part of the asphaltene molecule.

3. Results and discussion

This study investigated a wide variety of possible aspects that could explain the interaction tendency between

rock, asphaltene molecules, and ions. The appropriate parameters that could reveal the afﬁnity between

individual structures in an atomic-scale simulation cell, including bonding and non-bonding energies, surface

charge density, asphaltene angle on the rock, ion density inside the simulation cell, radial distribution function

(RDF), and displacement of the atomic structure center, will be discussed in order to gain a thorough

understanding of the behavior of asphaltene molecules on carbonate and sandstone surfaces. These surfaces

have been selected because they comprise the majority of conventional and unconventional rock types

worldwide.

Table 2. The equilibration distance/

angle for bond strength and bond-angle

bend in MD simulations [45].

Parameter r

(Å)θ

(degree)

C-C bond 1.530 —

N-F bond 1.371 —

C-H bond 1.090 —

C-N bond 1.462 —

C-O bond 1.420 —

C-S bond 1.800 —

C-Cl bond 1.757 —

H-N bond 1.022 —

H-O bond 0.980 —

H-S bond 1.360 —

O-S bond 1.690 —

O-Si bond 1.587 —

S-S bond 2.070 —

C-C-C —109.471

C-C-F —109.471

C-C-H —109.471

C-C-N —109.471

C-C-O —109.471

C-H-S —180.000

C-N-C —106.700

C-N-H —106.700

C-S-C —92.100

C-S-H —92.100

C-S-O —92.100

C-S-S —92.100

H-C-H —109.471

H-C-N —109.471

H-C-S —109.471

H-O-H —104.51

H-S-H —92.100

H-S-O —92.100

H-S-S —92.100

N-C-O —109.471

O-S-S —92.100

O-Si-O —109.471

S-C-S —109.471

S-O-S —104.51

Si-O-Si —104.51

Mater. Res. Express 9(2022)065101 P Ahmadi et al

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