Assessment of methane gas production from Indian gas hydrate petroleum systems

Vedachalam, N.; Ramesh, S.; Srinivasalu, S.; Rajendran, G.; Ramadass, G. A.

doi:10.1016/j.apenergy.2016.01.117

Cited by 44 publications

(12 citation statements)

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“…At present, the popular methods for extracting gas from hydrate deposits include depressurization, thermal stimulation, inhibitor injection, CO 2 replacement, and solid fluidization. 4,[6][7][8][9] However, previous numerical simulations and field trials have demonstrated that pure thermal stimulation and inhibitor injection may result in relatively high costs and only obtain a limited effectiveness [10][11][12][13] ). Furthermore, injecting inhibitors is not environmentally sound and may cause some pollution in the formation.…”

Section: Introductionmentioning

confidence: 99%

Gas production from a silty hydrate reservoir in the South China Sea using hydraulic fracturing: A numerical simulation

Sun

Ning

Liu

et al. 2019

Energy Science & Engineering

112

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The low permeability of silty hydrate reservoirs in the South China Sea is a critical issue that threatens safe, efficient, and long‐term gas production from these reservoirs. Hydraulic fracturing is a potentially promising stimulation technology for such low‐permeability reservoirs. Here, we assess the gas production potential of a depressurization horizontal well that is assisted by the hydraulic fracturing using numerical simulation according to field data at site SH2 in this area. In addition, the number of horizontal wells drilled is discussed if commercial production is to be performed at this site. The results show that the production potential can be significantly stimulated at the early production stage by adopting hydraulic fracturing in this reservoir due to a better depressurization effect. However, the increase in gas recovery gradually decreases with the continuous dissociation of gas hydrates, and the evolution trend is similar to that in a reservoir without stimulation during later periods of gas production because the dissociation front gradually moves away from the fractures. From the perspective of production potential, using a horizontal well scheme assisted by the hydraulic fracturing technology for gas recovery from a hydrate deposit can sharply reduce the number of operation wells, shorten the drilling operation time, and boost the economic efficiency. The horizontal well scheme may be an effective way to increase the gas yield if the application of quickly deployed horizontal wells and hydraulic fracturing techniques in such hydrate reservoirs greatly increases in the near future.

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Section: Introductionmentioning

confidence: 99%

Gas production from a silty hydrate reservoir in the South China Sea using hydraulic fracturing: A numerical simulation

Sun

Ning

Liu

et al. 2019

Energy Science & Engineering

112

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“…4 It has been reported that around 230 gas hydrate reservoirs have been identified to date. 7 To name a few, Gulf of Mexico, Nankai Trough in Japan, Ulleng basin in Korea, Pearl mouth basin in the South China Sea, the Krishna Godavari basin in India are some of the potential gas hydrate reservoirs around the world. 7 The amount of methane gas that can be extracted from these deposits is considered to be more than the energy of all other fossil fuels combined.…”

Section: Introductionmentioning

confidence: 99%

“…7 To name a few, Gulf of Mexico, Nankai Trough in Japan, Ulleng basin in Korea, Pearl mouth basin in the South China Sea, the Krishna Godavari basin in India are some of the potential gas hydrate reservoirs around the world. 7 The amount of methane gas that can be extracted from these deposits is considered to be more than the energy of all other fossil fuels combined. It is estimated that around ∼200 000 trillion cubic feet (TCF) of the methane gas is present in the hydrate form around the world which can provide sufficient energy for several years.…”

Section: Introductionmentioning

confidence: 99%

“…Large deposits of methane hydrates exist in offshore or permafrost regions and are considered to be a massive source of energy . It has been reported that around 230 gas hydrate reservoirs have been identified to date . To name a few, Gulf of Mexico, Nankai Trough in Japan, Ulleng basin in Korea, Pearl mouth basin in the South China Sea, the Krishna Godavari basin in India are some of the potential gas hydrate reservoirs around the world .…”

Section: Introductionmentioning

confidence: 99%

“…It is estimated that around ∼200 000 trillion cubic feet (TCF) of the methane gas is present in the hydrate form around the world which can provide sufficient energy for several years . It has been found that the Indian reservoirs are also rich in gas hydrate deposits and about 1900 TCM of methane gas has been found to be trapped in the form of solid hydrates in Krishna–Godavari (KG) basins, Mahanadi basins, and near the Andaman Islands . Due to the increasing energy demand, it is essential to explore ways to extract the enormous amount of methane gas present in the hydrate reservoirs safely and economically.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Insights into Cage Occupancies during Gas Exchange in CH₄+CO₂ and CH₄+N₂+CO₂ Mixed Hydrate Systems Relevant for Methane Gas Recovery and Carbon Dioxide Sequestration in Hydrate Reservoirs: A Thermodynamic Approach

Bhawangirkar

Sangwai

2019

Ind. Eng. Chem. Res.

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Carbon dioxide injection for methane replacement from hydrate reservoirs is considered as one of the effective techniques for both methane production and carbon dioxide sequestration. To understand the gas exchange process, a thermodynamic model based on the classical fugacity approach has been utilized to predict the phase behavior and the cage occupancies of both binary CH4+CO2 and ternary CH4+N2+CO2 mixed gas hydrate systems in three phase (L–H−V) equilibria. A total of 256 experimental phase equilibrium data points on binary CH4+CO2, and ternary CH4+N2+CO2 gas hydrate systems have been selected from various literatures. For the ternary system, various compositions of CH4+N2+CO2 gas mixtures with varying N2/CO2 gas ratio, i.e., 0.13, 0.19, 0.27, 0.33, 0.37, 0.5, 0.98, 2.6, and 4, and varying CH4 compositions, i.e., 20, 50, 60, 70, 80, and 90%, have been considered. The absolute average deviations (%AAD) in the predicted equilibrium pressures with the experimental results are observed to be within 2.9% and 6.4% for binary and ternary mixed hydrate systems, respectively. For CH4+CO2 mixed hydrate systems, the average distribution coefficient of methane has been found to be 2.06, which indicates that the CH4 molecules are selectively replaced by CO2 molecules preferentially from large cages. For the ternary CH4+N2+CO2 mixed hydrate system, the N2/CO2 ratio in small cages of the hydrate is found to be almost 20 times larger than that in the large cages revealing the capacity of N2 and CO2 molecules to replace most of the CH4 molecules from small and large cages of the hydrate, respectively. The N2/CO2 ratio in small and large cages is temperature independent at low N2/CO2 gas ratio, which becomes temperature dependent at higher ratios, i.e., 2.6 and 4. From this study, we conclude that the injection of N2/CO2 gas mixture having ∼1:3 ratio is a good choice for enhancing the production of methane gas and carbon dioxide sequestration deep into the hydrate reservoirs.

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Application of machine learning on hydrate formation prediction of pure components with water and inhibitors solution

Nasir,

Suleman,

Abdul Majeed

2024

Can J Chem Eng

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The present work investigates the use of machine learning approaches for the prediction of hydrate formation pressure (HFP) in gas hydrate systems. Advanced machine learning models, including the decision tree regressor (DTR), random forest regressor (RFR), extreme gradient boosting (XGB), gradient boosting regressor (GBR), histogram gradient boosting regressor (HGBR), and CatBoost regressor (CB), are trained and evaluated on a large dataset consists of 3137 experimental data points. The models are evaluated using R‐squared (R2), mean squared error (MSE), mean absolute error (MAE), and root mean squared error (RMSE). The study indicates that for the intent of HFP prediction, CatBoost outperformed all other machine learning models. It demonstrated high accuracy on the testing set with an R2 value of 0.9922, and with the lowest RMSE (1.61 × 10−3), MAE (7.90 × 10−4), and MSE (2.58 × 10−6), CatBoost strengthened its prediction ability.

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Assessment of methane gas production from Indian gas hydrate petroleum systems

Cited by 44 publications

References 47 publications

Gas production from a silty hydrate reservoir in the South China Sea using hydraulic fracturing: A numerical simulation

Gas production from a silty hydrate reservoir in the South China Sea using hydraulic fracturing: A numerical simulation

Insights into Cage Occupancies during Gas Exchange in CH₄+CO₂ and CH₄+N₂+CO₂ Mixed Hydrate Systems Relevant for Methane Gas Recovery and Carbon Dioxide Sequestration in Hydrate Reservoirs: A Thermodynamic Approach

Application of machine learning on hydrate formation prediction of pure components with water and inhibitors solution

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Assessment of methane gas production from Indian gas hydrate petroleum systems

Cited by 44 publications

References 47 publications

Gas production from a silty hydrate reservoir in the South China Sea using hydraulic fracturing: A numerical simulation

Gas production from a silty hydrate reservoir in the South China Sea using hydraulic fracturing: A numerical simulation

Insights into Cage Occupancies during Gas Exchange in CH4+CO2 and CH4+N2+CO2 Mixed Hydrate Systems Relevant for Methane Gas Recovery and Carbon Dioxide Sequestration in Hydrate Reservoirs: A Thermodynamic Approach

Application of machine learning on hydrate formation prediction of pure components with water and inhibitors solution

Contact Info

Product

Resources

About

Insights into Cage Occupancies during Gas Exchange in CH₄+CO₂ and CH₄+N₂+CO₂ Mixed Hydrate Systems Relevant for Methane Gas Recovery and Carbon Dioxide Sequestration in Hydrate Reservoirs: A Thermodynamic Approach