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Energies
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Novel Approaches for Natural Gas Hydrate
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Novel Approaches for Natural Gas Hydrate

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "H: Geo-Energy".

Deadline for manuscript submissions: closed (10 November 2022) | Viewed by 3770

Special Issue Editors

Prof. Dr. Yonghai Gao

E-Mail Website
Guest Editor
School of Petroleum Engineering, China University of Petroleum (East China), Qingdao, China
Interests: hydrate exploration and exploitation; wellbore multiphase flow and heat transfer
Special Issues, Collections and Topics in MDPI journals
Dr. Litao Chen

E-Mail Website
Guest Editor
School of Petroleum Engineering, China University of Petroleum (East China), Qingdao, China
Interests: fundamentals of clathrate hydrate; oil and gas flow assurance; high-pressure-fluid phase behavior and properties
Dr. Xiaohui Sun

E-Mail Website
Guest Editor
School of Petroleum Engineering, China University of Petroleum (East China), Qingdao 266580, China
Interests: wellbore multiphase flow modeling; well control; multiphase modeling; phase transition in multiphase flow
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

As a natural energy resource with huge reserves, natural gas hydrate (NGH) is considered a future alternative energy source. Countries such as Canada, Japan, the United States and China have successfully conducted NGH pilot production. The results show that the extraction of natural gas hydrate resources is technically feasible. However, the gas production rate has not reached the threshold of commercial extraction, and the safety of long-term production has not been verified. Therefore, there is an urgent need to develop novel approaches for the efficient extraction of NGH. In addition, the cost for NGH management in conventional oil and gas production is a heavy burden for the industries. It is necessary to develop novel approaches for NGH management. The study of novel technologies based on the unique characteristics of NGH is also a promising field.

This Special Issue aims to present and disseminate the most recent advances related to the theory, experiment, modelling, and application of all types of novel approaches for NGH.

Topics of interest for publication include, but are not limited to:

  • NGH exploration;
  • NGH drilling;
  • NGH well completion;
  • NGH extraction simulation;
  • NGH management in flow assurance;
  • Novel technologies based on NGH;
  • CCS related to NGH;
  • Fundamentals of NGH.

Prof. Dr. Yonghai Gao
Dr. Litao Chen
Dr. Xiaohui Sun
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Energies is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • natural gas hydrate
  • deepwater
  • drilling
  • exploration and development
  • modelling
  • flow assurance
  • simulation
  • experiment

Published Papers (3 papers)

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Research

14 pages, 5540 KiB  
Article
Inhibition Mechanism of EMIM-Cl to Methane Gas Hydrate by Molecular Dynamics Simulation
by Guizhen Xin, Na Xu, Hongwei Li, Faling Yin, Yaqiang Qi, Shaoqiang Li, Xinyao Su, Ye Chen and Baojiang Sun
Energies 2022, 15(21), 7928; https://doi.org/10.3390/en15217928 - 25 Oct 2022
Viewed by 999
Abstract
Deep-water gas well testing is a key technology for obtaining reservoir production and physical property parameters. However, gas hydrates could easily form and cause blockage in the low-temperature and high-pressure environment on the seafloor. Therefore, it is extremely important to inhibit hydrate growth [...] Read more.
Deep-water gas well testing is a key technology for obtaining reservoir production and physical property parameters. However, gas hydrates could easily form and cause blockage in the low-temperature and high-pressure environment on the seafloor. Therefore, it is extremely important to inhibit hydrate growth in deep-water operations. Ionic liquid is a type of hydrate inhibitor with both thermodynamic and kinetic effects. However, its intrinsic inhibiting mechanism is still unclear. By using molecular dynamics simulation, the growth process of methane hydrate in the 1-ethyl-3-methylimidazole chloride (EMIM-Cl)-containing system at the pressure of 15 MPa and temperature of 273.15 K was studied. The system energy and angular order parameters (AOP) were extracted as the evaluation indicators. It was found that the time for the complete growth of methane hydrate in the EMIM-Cl-containing system was about 10 ns, longer than that in the pure water, indicating that EMIM-Cl showed an obvious inhibition effect to hydrate growth. The results also implied that the joint action of hydrogen bond and steric hindrance might be the inhibition mechanism of EMIM-Cl. Some six-membered rings in hydrate crystal large cage structures evolved from five-membered rings under the effect of EMIM, which partly contributed to the delay of hydrate formation. Full article
(This article belongs to the Special Issue Novel Approaches for Natural Gas Hydrate)
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17 pages, 8978 KiB  
Article
Optimization of Critical Parameters of Deep Learning for Electrical Resistivity Tomography to Identifying Hydrate
by Yang Liu, Changchun Zou, Qiang Chen, Jinhuan Zhao and Caowei Wu
Energies 2022, 15(13), 4765; https://doi.org/10.3390/en15134765 - 29 Jun 2022
Cited by 1 | Viewed by 1175
Abstract
As a new energy source, gas hydrates have attracted worldwide attention, but their exploration and development face enormous challenges. Thus, it has become increasingly crucial to identify hydrate distribution accurately. Electrical resistivity tomography (ERT) can be used to detect the distribution of hydrate [...] Read more.
As a new energy source, gas hydrates have attracted worldwide attention, but their exploration and development face enormous challenges. Thus, it has become increasingly crucial to identify hydrate distribution accurately. Electrical resistivity tomography (ERT) can be used to detect the distribution of hydrate deposits. An ERT inversion network (ERTInvNet) based on a deep neural network (DNN) is proposed, with strong learning and memory capabilities to solve the ERT nonlinear inversion problem. 160,000 samples about hydrate distribution are generated by numerical simulation, of which 10% are used for testing. The impact of different deep learning parameters (such as loss function, activation function, and optimizer) on the performance of ERT inversion is investigated to obtain a more accurate hydrate distribution. When the Logcosh loss function is enabled in ERTInvNet, the average correlation coefficient (CC) and relative error (RE) of all samples in the test sets are 0.9511 and 0.1098. The results generated by Logcosh are better than MSE, MAE, and Huber. ERTInvNet with Selu activation function can better learn the nonlinear relationship between voltage and resistivity. Its average CC and RE of all samples in the test set are 0.9449 and 0.2301, the best choices for Relu, Selu, Leaky_Relu, and Softplus. Compared with Adadelta, Adagrad, and Aadmax, Adam has the best performance in ERTInvNet with the optimizer. Its average CC and RE of all samples in the test set are 0.9449 and 0.2301, respectively. By optimizing the critical parameters of deep learning, the accuracy of ERT in identifying hydrate distribution is improved. Full article
(This article belongs to the Special Issue Novel Approaches for Natural Gas Hydrate)
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12 pages, 2974 KiB  
Article
Experimental Investigation into Three-Dimensional Spatial Distribution of the Fracture-Filling Hydrate by Electrical Property of Hydrate-Bearing Sediments
by Jinhuan Zhao, Changling Liu, Qiang Chen, Changchun Zou, Yang Liu, Qingtao Bu, Jiale Kang and Qingguo Meng
Energies 2022, 15(10), 3537; https://doi.org/10.3390/en15103537 - 12 May 2022
Cited by 2 | Viewed by 1237
Abstract
As a future clean energy resource, the exploration and exploitation of natural gas hydrate are favorable for solving the energy crisis and improving environmental pollution. Detecting the spatial distribution of natural gas hydrate in the reservoir is of great importance in natural gas [...] Read more.
As a future clean energy resource, the exploration and exploitation of natural gas hydrate are favorable for solving the energy crisis and improving environmental pollution. Detecting the spatial distribution of natural gas hydrate in the reservoir is of great importance in natural gas hydrate exploration and exploitation. Fracture-filling hydrate, one of the most common types of gas hydrate, usually appears as a massive or layered accumulation below the seafloor. This paper aims to detect the spatial distribution variation of fracture-filling hydrate in sediments using the electrical property in the laboratory. Massive hydrate and layered hydrate are formed in the electrical resistivity tomography device with a cylindrical array. Based on the electrical resistivity tomography data during the hydrate formation process, the three-dimensional resistivity images of the massive hydrate and layered hydrate are established by using finite element forward, Gauss–Newton inversion, and inverse distance weighted interpolation. Massive hydrate is easier to identify than layered hydrate because of the big difference between the massive hydrate area and surrounding sediments. The diffusion of salt ions in sediments makes the boundary of massive hydrate and layered hydrate change with hydrate formation. The average resistivity values of massive hydrate (50 Ω⋅m) and layered hydrate (1.4 Ω⋅m) differ by an order of magnitude due to the difference in the morphology of the fracture. Compared with the theoretical resistivity, it is found that the resistivity change of layered hydrate is in accordance with the change tendency of the theoretical value. The formation characteristic of massive hydrate is mainly affected by the pore water distribution and pore microstructure of hydrate. The hydrate formation does not necessarily cause the increase in resistivity, but the increase of resistivity must be due to the formation of hydrate. The decrease of resistivity in fine-grains is not obvious due to the cation adsorption of clay particles. These results provide a feasible approach to characterizing the resistivity and growth characteristics of fracture-filling hydrate reservoirs and provide support for the in-situ visual detection of fracture-filling hydrate. Full article
(This article belongs to the Special Issue Novel Approaches for Natural Gas Hydrate)
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