Study of the Formation and Dissociation of Methane Hydrate System in the Presence of Pure Water

Abstract

This study investigated methane hydrate formation and dissociation within a temperature range of 280 to 290 K and a pressure range of 5.5 to 13 MPa. These conditions are relevant to natural gas systems, where methane is the primary component of natural gas. Either experimental or thermodynamic models were used to predict the conditions of formation of gas hydrates. The Van der Waals–Platteeuw model based on statistical thermodynamics is the basis of the existing thermodynamic models for predicting the conditions of hydrate formation. In this work, the stepwise heating method was applied to determine the thermodynamic equilibrium points of methane gas in a constant volume system. The CPA (Cubic Plus Association) equation of state and the Van der Waals–Platteeuw model were employed to simulate hydrate formation conditions. Experimental equilibrium data for pure methane were compared with results from previous studies (Deaton and Frost, Nakamura, Jhaveri and Robinson, De Roo, and others). The results showed excellent agreement, with an average absolute temperature error of less than 0.1%. This high level of accuracy confirms the reliability of the experimental procedures and thermodynamic modeling approaches used in the study to accurately predict hydrate formation conditions, being critical for designing and operating natural gas systems in order to avoid hydrate accumulation.

1. Introduction

Hydrate formation is a significant challenge in the oil and gas industry, particularly in gas transmission lines under low-temperature and high-pressure conditions. This problem of blockages is caused by hydrate formation, which is costly and leads to substantial losses each year due to being time-consuming to resolve [1,2,3]. Clathrate hydrate is a crystalline solid in which water molecules surround gas molecules. Gases capable of forming hydrates include carbon dioxide, hydrogen sulfide, and hydrocarbons with low carbon numbers [4]. The discovery of gas hydrates by Sir Humphery Davy began in 1810, when he observed the phenomenon by producing chlorine gas bubbles in cold water using a laboratory method, and this process continues until now. In 1832, Faraday proposed the first chemical formula for a gas hydrate, consisting of one gas molecule surrounded by ten water molecules. Later, Hammerschmid, Deaton, and Frost conducted the first experimental studies on the conditions of hydrate formation [5]. The temperature response of hydrate-bearing sediments is closely associated with the thermodynamic relationship, rather than conventional heat transfer [6]. Hydrate nucleation leads to occurrences of more realignment at the triple-phase contact line, where quartz surfaces provide a lower free energy barrier and smaller critical nucleus size compared to silicon waters [7]. The hydrate induction time in a sandy system is slightly prolonged compared to the pure gas–water systems, with the inhibition effect varying as the sand concentration increases from 0% to 5% [8]. Methane hydrate formation only occurs at the gas–liquid interface and primarily grows toward the gas phase when the gas phase and the excess liquid phase coexist in pores. Local hydrate dissociation occurs in the process of methane hydrate formation [9]. Cyclopentane hydrate is formed by consuming a part of fresh water appearing after the fusion of ice instead of at a very low temperature ≤ −20 °C [10]. Induction time for the formation of hydrate influenced by subcooling and salinity also affects the onset pressure and temperature of hydrate formation [11]. In 1983, Bishnu, Visnoskas, and Natarajan investigated the parameters affecting the kinetics of methane hydrate formation [12]. They concluded that hydrate formation kinetics depend on initial temperature and pressure, interphase level, and supercooling degree. They also highlighted the “hydrate memory” effect, which reduces induction time. Based on the obtained results, they proposed a semi-empirical kinetic model to calculate the rate of hydrate formation grounded by crystallization and mass transfer theory. According to this theory, the rate of gas consumption during the hydrate formation process is dependent on the growth rate of the hydrate crystal [13]. Later, Scoborg and Rasmussen examined the Engels model, emphasizing that the hydrate formation rate depends on the mass transfer between the gas and water phases rather than the particles surface area [14]. Lekvam and Ruf also proposed a kinetic model for methane hydrate formation in pure water [15]. On the other hand, investigating hydrate growth modelling, it is necessary to study kinetic mechanisms such as mass transfer and heat. In general, when the time-dependent hydrate formation process is considered, two fundamental questions must be answered: (1) How long does it take for the hydrate to reach the critical nucleus size (i.e., induction time)? (2) What is the role of hydrate growth after reacting to that size? (the critical nucleus size is the hydrate cluster stability and initiating further) [16]. In this study, the laboratory research of the hydrate system was investigated using the step-by-step heating method in the constant volume system to determine the equilibrium points of the hydrate. The step-by-step heating method was initially introduced by Alfond in 2012 to measure hydrate phase equilibrium points in systems with significant amounts of salt (sodium chloride) and methanol, but the results of this method are also applicable to pure water systems. For single-component gas, systems with only two components are present: guest gas and hot water. As a result, the system has only one degree of freedom and equilibrium pressure, and each temperature corresponds to a single component as long as all three phases coexist in the system stably. Given significant time, the system reaches three-phase equilibrium at the same point. In this study, the conditions for methane hydrate formation/separation were investigated experimentally, and then the obtained results were compared and validated against experimental published data conducted by other researchers. To develop a suitable kinetic model capable of predicting the induction time of gas hydrate formation, firstly, it is necessary to calculate the driving force of the kinetic model (difference between hydrate formation and equilibrium fugacity) using a suitable thermodynamic model. When designing hydrate-related processes, the main problem is predicting the temperature and pressure at which the hydrate will form. Methods for predicting the conditions for gas hydrate formation can be divided into two general categories: (1) experimental methods (manual methods) and (2) thermodynamic models (computer methods). Most models used for predicting hydrate crystal formation are based on chemical thermodynamics. The theoretical basis of existing thermodynamic models used for predicting the conditions of hydrate formation is the model described by Van der Waals–Platteeuw, which is based on statistical thermodynamics. In this study, the conditions for methane hydrate formation in the presence of pure water were predicted using the Van der Waals–Platteeuw equation, combined with a thermodynamic model and cubic plus cumulative equation of state (CPA) developed for this work.

2. Research Method and Laboratory Studies

The laboratory system used in this study to investigate the gas hydrate formation process consisted of a reactor made of SS-316 stainless steel (resistant to pressure up to 20 MPa) equipped with a stirrer. The core component consisted of a cylindrical reactor with an internal volume of 100 ± 0.5 cm³ (inner diameter: 5.5 cm; height: 4.2 cm), designed to withstand pressures up to 20 MPa. A six-blade magnetic stirrer (diameter: 3.3 cm) ensured homogeneous mixing of the fluid and hydrate crystals, with stirring speed controlled by an external system.

Temperature measurements were conducted using a calibrated platinum resistance thermometer (Pt-100; accuracy: ±0.1 K) immersed in the liquid phase, while system pressure was monitored via a precision pressure transducer (Wika CL1.6; calibration uncertainty: <5 kPa). Temperature regulation was achieved using a programmable heating/cooling system (Lauda model; stability: ±0.1 K) with a water–ethylene glycol coolant mixture. Data acquisition was performed at defined intervals using dedicated software, enabling real-time recording of pressure and temperature. During the gas hydrate production experiment, methane gas with a purity of 99.99% was used. Distilled water was used as the base fluid for hydrate formation.

There are different methods for determining hydrate equilibrium points. In this research, the laboratory research of the methane hydrate system was carried out using the step-by-step heating method in the constant volume system in order to determine the equilibrium points of the hydrate. To investigate the hydrate formation process in the laboratory, the reactor was first washed with distilled water and used in a completely clean and dry condition. The lid was then tightened, and the trapped air was evacuated by a vacuum pump. Then, a certain amount of distilled water was injected into the reactor. When the inlet valve was opened, gas entered the reactor and the pressure was adjusted to a pressure condition below the equilibrium pressure of the hydrate. The reactor temperature was then reduced to the desired temperature. After the reactor reached thermal equilibrium by opening the gas inlet valve, and after adjusting the pressure by the pressure regulator, the reactor pressure reached the desired pressure (the pressure above hydrate formation). In order to increase the mass transfer coefficient and gas penetration into the water, the agitator started working. The temperature and pressure changes were then recorded by a data logging system at any given moment in the data acquisition system. When gas was injected into the reactor, as the gas dissolved in the water, the reactor pressure began to drop suddenly, and a slight drop in temperature was also observed in the system, which was due to the cooling of the gas inside the reactor and the dissolution of some gas in the water. At the moment of hydrate formation, the reactor temperature also increased slightly due to the exothermic nature of the process. Therefore, the temperature decrease continued until the reactor temperature reached the temperature of the coolant (the desired temperature in the experiment). After that, hydrate growth began, which was accompanied by gas consumption and pressure reduction in the reactor. This pressure reduction continued until equilibrium was reached in the reactor. After the pressure changes inside the reactor became very small with time, the system pressure reached equilibrium pressure and remained almost constant. In this case, the process of hydrate formation and growth stopped and ended.

To find the equilibrium pressure of hydrate formation, the condition of chemical potential equality in the two phases of water and hydrate was used [17].

$${\mu }_w^L={\mu }_w^H\to ({\mu }_w^{MT}-{\mu }_w^L)=({\mu }_w^{MT}-{\mu }_w^H)$$

(1)

Three-phase water–hydrate–gas equilibrium conditions (G-H-WL) can be calculated using thermodynamic equilibrium laws. From a thermodynamic point of view, for a system in equilibrium, the fugacity of the components must be equal in all phases.

$$f_w^L=f_w^H$$

(2)

The subscripts H, L, W, and f show hydrate phase, liquid phase, water, and fugacity, respectively. In this model, the fugacity of water in the hydrate phase was obtained through Equation (3) [18]:

$$f_w^H=f_w^{MT}\mathrm{e}\mathrm{x}\mathrm{p}({\displaystyle \frac{{\mu }_w^H-{\mu }_w^{MT}}{RT}})$$

(3)

According to Langmuir theory,

$$\begin{gathered} {\displaystyle \frac{{\mu }_w^H-{\mu }_w^{MT}}{RT}}=-{\sum }_{i=1}^{N_{cavity}}{\nu }_i(1-{\sum }_{j=1}^{NH}{Y}_{ij}) \\ \hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em}{Y}_{ij}={\displaystyle \frac{C_{ij}{f}_j}{1+{\sum }_{j=1}^{NH}{C}_{ij}{f}_j}} \end{gathered}$$

(4)

Van der Wals and Platteeuw used the Lennard–Jones and Devonshire theory and showed that the Langmuir coefficients are obtained from Equation (5) [19].

$$C_{ij}=\left({\displaystyle \frac{4\pi }{K_{B}T}}\right){\int }_0^R\exp \left({\displaystyle \frac{\omega \left(r\right)}{K_{B}T}}\right)r^{2}dr$$

(5)

To calculate $\omega \left(r\right)$, Kihara’s potential energy function is used [20]:

$$\begin{gathered} W\left(r\right)=2zϵ\left[{\displaystyle \frac{{\sigma }^{12}}{R^{11}r}}\left({\delta }^N\left(N=10\right)+{\displaystyle \frac{a}{R}}{\delta }^N(N=11)\right) \\ \hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em}-{\displaystyle \frac{{\sigma }^6}{R^{5}r}} \left({\delta }^N\left(N=4\right)+{\displaystyle \frac{a}{R}}{\delta }^N\left(N=5\right)\right)\right] \end{gathered}$$

(6)

$${\delta }^N={\displaystyle \frac{1}{N}}\left[{\left(1-{\displaystyle \frac{r-a}{R}}\right)}^{-N}-{\left(1+{\displaystyle \frac{r-a}{R}}\right)}^{-N}\right] N=\mathrm{4,5},10.11$$

(7)

Kihara’s potential parameters for gas water resistance used in this work are listed in

Table 1. Kihara’s potential parameters for gas water resistance used in this research [21].

Component	${\mathit{a}(\mathbf{A}}^{°})$	${\mathit{\sigma }(\mathbf{A}}^{°})$	$\frac{\mathit{\epsilon }}{\mathit{k}}\left(\mathit{k}\right)$
$C{H}_4$	0.3834	3.1439	155.593

.

The gas/vapor and water phase factors are calculated using the CPA equations of state, which are summarized below. The fugacity of the hydrate network in the empty state can also be calculated using the following equation:

$$f_w^{MT}=P_w^{MT}\mathrm{e}\mathrm{x}\mathrm{p}({\displaystyle \frac{{\nu }_w^{MT}(P-P_w^{MT})}{RT}})$$

(8)

To calculate ${\nu }_w^{MT}$ in sI hydrate structure, the following relationship is used [22]:

$$\begin{gathered} {\nu }_w^{MT}=\left(11.835+2.217\times {10}^{-5}T+2.242\times {10}^{-6}{T}^2\right){\displaystyle \frac{{10}^{-30}{N}_A}{N_w^{MT}}}+1.6155\times {10}^{-9}P \\ -2.5054\times {10}^{-12}{P}^2 \end{gathered}$$

(9)

where NA is Avogadro’s number, and the unit of pressure is MPa; $P_w^{MT}$ for the sI structure can be calculated using the Dharmawardhana method and through the following equation [23]:

$$P_w^{MT}=0.1\exp \left(17.44-{\displaystyle \frac{6003.9}{T}}\right)$$

(10)

Since the fugacity of water in the system is low, we ignore the water vapor pressure in the gas phase. To calculate the fugacity of water in the liquid and gas phases, we used the CPA equation. The CPA equation of state is a combination of a cubic equation of state and an accumulation term. The cubic equation of state used, the SRK equation of state [24], and the cumulative expression are obtained from the Wertheim theory [25,26,27,28,29].

The CPA equation of state is expressed by Michelson and Hendrick as the sum of the SRK equation of state and the cumulative expression as follows [20]:

$$P={\displaystyle \frac{RT}{V_m-b}}-{\displaystyle \frac{a\left(T\right)}{V_m\left(V_m+b\right)}}-{\displaystyle \frac{1}{2}}{\displaystyle \frac{RT}{V_m}}\left(1+\rho {\displaystyle \frac{\partial lng}{\partial \rho }}\right)\sum _i{x}_i\sum _{A_i}\left(1-X_{A_i}\right)$$

(11)

In Equation (11), $V_m$ is the molar volume, $x_i$ is the mole fraction of component i, and $X_{A_i}$ is the fraction of molecules i that are not bonded through site A, and it is calculated through Equation (12).

$$X_{A_i}={\displaystyle \frac{1}{1+\rho {\sum }_j{x}_j{\sum }_{A_j}{x}_{B_i}{∆}^{A_i{B}_j}}}$$

(12)

$B_j$ represents the sum of all binding sites on molecule j. ${∆}^{A_i{B}_j}$ is the cumulative strength between site A on molecule i and site B on molecule j and is obtained by this equation:

$${∆}^{A_i{B}_j}=g\left(\rho \right)\left[\exp \left({\displaystyle \frac{{\epsilon }^{A_i{B}_j}}{RT}}\right)-1\right]b_{ij}{\beta }^{A_i{B}_j}$$

(13)

${\epsilon }^{A_i{B}_j}$ and ${\beta }^{A_i{B}_j}$, respectively, are the cumulative energy and volume of the interaction between site A on molecule i and site B on molecule j, and $g\left(\rho \right)$ is the radial distribution function for the reference fluid. The value of the radial distribution function is reported by Kontogeorgi et al. as follows [19]:

$$g\left(\rho \right)={\displaystyle \frac{1}{1-1.9\mathsf{\eta }}} , \mathsf{\eta }={\displaystyle \frac{1}{4b\rho }}$$

(14)

The CPA equation for pure components that have aggregative properties has five parameters. Three parameters (a₀, b, c₁) are related to the KRS equation of state, and two parameters (${\epsilon }^{A_i{B}_j}$), (${\beta }^{A_i{B}_j}$) are related to the cumulative effect. The parameters of the CPA equation used in this work are listed in

Table 2. CPA equation parameters used in this work [22].

Component	${\mathit{a}}_0\left(\frac{\mathit{b}\mathit{a}\mathit{r}·{\mathit{L}}^2}{{\mathit{m}\mathit{o}\mathit{l}}^2}\right)$	$\mathit{b}\left(\frac{\mathit{L}}{\mathit{m}\mathit{o}\mathit{l}}\right)$	${\mathit{c}}_{\mathit{i}}$	${\mathit{\beta }}^{{\mathit{A}}_{\mathit{i}}{\mathit{B}}_{\mathit{j}}}$	${\mathit{\epsilon }}^{{\mathit{A}}_{\mathit{i}}{\mathit{B}}_{\mathit{j}}}\left(\frac{\mathit{b}\mathit{a}\mathit{r}·\mathit{L}}{\mathit{m}\mathit{o}\mathit{l}}\right)$
${\mathrm{C}\mathrm{H}}_4$	2.3203	0.0291	0.4472	-	-
${\mathrm{H}}_2\mathrm{O}$	1.2277	0.0145	0.6736	0.0692	166.55

. Critical data used in this work are listed in

Table 3. Critical data used in this work [23].

Component	${\mathit{P}}_{\mathit{c}}\left(\mathit{M}{\mathit{P}}_{\mathit{a}}\right)$	${\mathit{T}}_{\mathit{c}}\left(\mathit{k}\right)$	$\mathit{\omega }$
${\mathrm{C}\mathrm{H}}_4$	4.599	190.56	0.0115
${\mathrm{H}}_2\mathrm{O}$	22.055	647.13	0.3449

.

The CPA equation of state for pure materials that do not have aggregate properties transforms into a third-order SRK equation of state:

$$a=\sum _i\sum _j{x}_i{x}_j\sqrt{a_i{a}_j}\left(1-k_{ij}\right)$$

(15)

$$b=\sum _i\sum _j{x}_i{x}_j{b}_{ij}$$

(16)

$$b_{ij}={\displaystyle \frac{b_i+b_j}{2}}$$

(17)

For cumulative parameters, combination rules are used, which are in the form of the following equations:

$${\epsilon }^{A_i{B}_j}={\displaystyle \frac{{\epsilon }^{A_i{B}_i}+{\epsilon }^{A_j{B}_j}}{2}}$$

(18)

$${\beta }^{A_i{B}_j}=\sqrt{{\beta }^{A_i{B}_i}{\beta }^{A_j{B}_j}}$$

(19)

$${∆}^{A_i{B}_j}=\sqrt{{∆}^{A_i{B}_i}{∆}^{A_j{B}_j}}$$

(20)

Using the aforementioned mixing rules and the simplified relationship obtained for the chemical potential of component i of the aggregation effect, the fugacity coefficient of component i of the mixture is written using the CPA equation of state as follows:

$$\begin{gathered} ln{\varnothing }_i=-ln\left({\displaystyle \frac{V-b}{V}}\right)+{\displaystyle \frac{b_i}{V-b}}-{\displaystyle \frac{a}{bRT}}\left[{\displaystyle \frac{2{\sum }_i{X}_i{a}_{ij}}{a}}-{\displaystyle \frac{b_i}{b}}\right]ln\left({\displaystyle \frac{V-b}{V}}\right)-{\displaystyle \frac{a}{bRT}}\left({\displaystyle \frac{b_i}{V-b}}\right) \\ \hspace{1em}\hspace{1em}+\sum _{A_i}^{N{S}_i}\ln \left(x_{A_i}\right)-{\displaystyle \frac{1}{2}}\left(n{\displaystyle \frac{\partial \ln \left(g\right)}{\partial n_i}}\right)\sum _{j=1}^{nc}{x}_j\sum _{A_j}^{N{S}_j}\left(1-x_{A_j}\right)-\ln \left(Z\right) \end{gathered}$$

(21)

where $n{\displaystyle \frac{\partial \ln \left(g\right)}{\partial n_i}}={\displaystyle \frac{1.9b_i}{4v-1.9b}} , Z={\displaystyle \frac{PV}{RT}}$.

3. Results and Discussion

In this research, the thermodynamic conditions for methane hydrate separation were obtained experimentally, and then the results obtained were compared and evaluated with experimental data from other researchers published in articles and the model proposed in this work. In theoretical calculations, by calculating $P_w^{MT}$ and ${\nu }_w^{MT}$ from Equations (9) and (10), the Langmuir coefficients can be obtained from Equation (5). Then, the value of the chemical potential difference ${∆\mu }_w^{H-MT}$ can be calculated from Equation (4). Finally, the fugacity of water in the hydrate phase f is calculated from Equation (3). In this method, an appropriate function of the desired parameters is used to form the objective function for minimization. The following equation was used for this study based on the equations proposed by Clarke and Bishnaoi [30,31,32]:

$$Objective Function={\displaystyle \frac{1}{N}}\sum _{i=1}^N\left({\displaystyle \frac{\left|x_{exp·i}-x_{cal·i}\right|}{x_{exp·i}}}\right)$$

(22)

where N is the number of laboratory data, and $x_{exp·i}$ and $x_{cal·i}$ are the experimental and calculated values of the molar fraction of the substance in question, respectively. The comparison of experimental and predicted conditions for methane hydrate dissociation is shown in Figure 1 and in

Table 4. Comparison of experimental and predicted conditions for methane hydrate dissociation.

T(K)	P (MPa) Experimental	P (MPa) Predicted	AAD
288.4	13.15	13.42	2.05
287.8	12.14	12.46	2.63
286.9	11.02	11.17	1.35
286.0	10.10	10.04	0.58
285.2	8.92	9.14	2.46
284.2	8.09	8.15	0.73
283.1	7.11	7.19	1.12

.

The average absolute deviation (AAD) is calculated from Equation (23).

$$\mathrm{A}\mathrm{A}\mathrm{D}={\displaystyle \frac{1}{N}}{\sum }_{i}N\left({\displaystyle \frac{\left|P_{exp}-P_{cal}\right|}{P_{exp}}}\right)$$

(23)

Based on the results reported in Table 4, the experimental data obtained from methane hydrate separation are in good agreement with the values predicted by the model presented in this study. Also, the model developed in this study using the CPA equation of state has acceptable predictions in a wide range of pressures (4 to 15 MPa) and temperatures (280 to 290 Kelvin) with laboratory data and experimental data reported in the literature, and the mean absolute errors in terms of pressure and temperature for the thermodynamic model are 1.57 and 0.04 percent. Also, as shown in

Table 5. Experimental data of methane hydrate dissociation available in articles and PC-SAFT/CPA model results.

${\mathbf{C}\mathbf{H}}_4$	Deaton and Frost		Nakamura		Jhaveri and Robinson		De Roo		This Study
	T (K)	P (MPa)	T (K)	P (MPa)	T (K)	P (MPa)	T (K)	P (MPa)	T (K)	P (MPa)
Exp	280.4	5.35	282.7	6.88	280.4	5.58	282.8	7.04	283.1	7.13
PC-SAFT	281.05	4.96	283.3	6.42	281.4	4.96	283.5	6.49	283.6	6.72
CPA	279.7	5.34	282.6	6.87	280.8	5.34	282.9	6.96	283	7.19
Exp	280.9	5.71	283.2	7.25	284.7	8.67	284	8.05	284.2	8.09
PC-SAFT	281.65	5.24	283.7	6.8	285.2	8.1	284.6	7.46	284.7	7.64
CPA	281	5.64	283.1	7.27	284.6	8.63	284.1	7.96	284.1	8.15
Exp	281.5	6.06	283.7	7.65	287.3	11.65	285	9.04	285.2	8.91
PC-SAFT	282.2	565	284.2	7.21	287.6	11.14	285.6	8.39	285.5	8.6
CPA	281.6	6.02	283.6	7.69	287.2	11.73	285.1	8.93	285	9.14
Exp	282.6	6.77	284.3	8.1	288.9	14.05	286	10.04	286	10.12
PC-SAFT	283.15	6.35	284.7	7.73	289.1	13.69	286.5	9.47	286.5	9.48
CPA	282.5	6.8	284	8.24	288.8	14.28	285.9	10.3	286.1	10.04
Exp	284.3	8.12	284.8	8.55	-	-	-	-	286.9	11.03
PC-SAFT	284.7	7.73	285.1	8.2	-	-	-	-	287.2	10.59
CPA	284.2	8.24	284.6	8.73	-		-	-	287.8	11.17
Exp	285.9	9.78	285.2	9.03	-	-	-	-	287.8	12.14
PC-SAFT	286.2	9.36	285.6	8.6	-	-	-	-	288.8	11.86
CPA	285.8	9.92	285.1	9.14	-	-	-	-	287.6	11.46
Exp	-	-	284.8	9.54	-	-	-	-	288.4	13.16
PC-SAFT	-	-	286	8.2	-	-	-	-	288.6	12.82
CPA	-	-	285.6	8.73	-	-	-	-	288.2	12.42
PC-SAFT	0.19	6.37	0.2	6.58	0.17	6.16	0.21	7	0.12	4.28
AAD%
CPA	0.07	0.9	0.09	2.07	0.06	1.77	0.04	0.89	0.05	1.55
AAD%

and Figure 2, the equilibrium temperature and pressure data of the methane system reported in selected articles and the equilibrium values obtained from the experimental test of this research were compared with the predicted values of the proposed model and reported along with the AAD% values. Thus, it can be concluded that the thermodynamic model developed in this study is capable of relatively accurately predicting the equilibrium conditions for methane hydrate formation in the presence of pure water.

Methane hydrates dissociated ~30% faster with microwaves (2.45 GHz) vs. hot water at the same energy input [33].

Hydrates from the process at the inlet section of the pore models cause gas flow blockage before being formed in the middle and outlet sections. The evolution of permeability during hydrate dissociation calculated using SDR models best matches the experimental data [34].

To improve the dissociation of hydrates, it is proposed to inject hot water at a relatively higher velocity and lower temperature [35].

During the process of hydrate dissociation, with decreasing pressure, liquid water initially turns into metastable supercooled water, which then turns into solid ice under external disturbance. Ice nucleation occurs mainly in two places: in the free water phase and on the surface of hydrate particles. A higher rate of pressure drop can accelerate both nucleation and formation of ice, which in turn shortens the freezing induction time. An increase in water saturation and a decrease in hydrate saturation can significantly increase the rate of hydrate dissociation [36].

The global spatial distributions of pressure, hydrate saturation, and structure are one pattern during hydrate dissociation, while the temperature and hydrate dissociation rate exhibit four and three standard patterns, respectively. The effective specific area of the hydrate regulator, the coefficient effect, and the pressure difference play different roles in dominating and affecting the hydrate dissociation rate [37].

Figure 2. Comparison of experimental values and prediction of methane hydrate dissociation conditions by the developed model with experimental data of several articles in this field. Deaton and Frost [38], Nakamura [39], Jhaveri and Robinson [40], and De Roo [41].

Figure 2. Comparison of experimental values and prediction of methane hydrate dissociation conditions by the developed model with experimental data of several articles in this field. Deaton and Frost [38], Nakamura [39], Jhaveri and Robinson [40], and De Roo [41].

4. Conclusions

This research focuses on the thermodynamic study of methane hydrate formation in the presence of pure water, with an emphasis on understanding phase equilibrium conditions and developing a reliable thermodynamic model for predicting hydrate formation. Laboratory experiments were conducted to measure the phase equilibrium points of methane hydrate over a temperature range of 280–290 K and pressure range of 5.5–13 MPa. The stepwise heating method in a constant volume system was employed or applied to determine or thermodynamic equilibrium points conditions. Experimental results were compared with data from similar studies. Good agreement between the model predictions and experimental data was observed, with the average absolute error in temperature of less than 0.1%. The experimental results for methane hydrate phase equilibrium showed high accuracy and consistency with published data. The developed thermodynamic model demonstrated excellent predictive capabilities for methane hydrate equilibrium conditions. This study highlights the importance of understanding hydrate formation conditions and kinetics to prevent hydrate-related damage in natural gas systems.