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15 pages, 6611 KiB  
Article
The Use of Microwave Treatment as a Sustainable Technology for the Drying of Metallurgical Sludge
by Marta Ślęzak, Piotr Migas and Mikolaj Bernasowski
Materials 2024, 17(24), 6207; https://doi.org/10.3390/ma17246207 - 19 Dec 2024
Viewed by 273
Abstract
The modern metallurgical industry produces approximately 90% of the volume of all produced steel; for this, integrated technology based on fossil materials such as coal, fluxes, and especially iron ore is used. This industry generates large amounts of waste and by-products at almost [...] Read more.
The modern metallurgical industry produces approximately 90% of the volume of all produced steel; for this, integrated technology based on fossil materials such as coal, fluxes, and especially iron ore is used. This industry generates large amounts of waste and by-products at almost all stages of production. Alternative iron and steel production technologies based on iron ore, methane, or pure hydrogen are also not waste-free. To ensure sustainable waste management, efforts are made to seal processes as well as capture and recycle dusty waste. This work presents the results of research on the processing of sludge resulting from the dedusting of the basic oxygen furnace (BOF) process and landfilling in a lagoon. The work discusses the treatment of fine dusty sludge hydrated to 26–60% H2O, to which various amounts of caking agents were added; also discussed are the rheological characteristics of the tested suspension systems, the possibility of forming these systems into larger fractions, and rapid drying using 100–600 W microwaves with a drying time of 1–9 min. The aim was to identify, describe, and characterize the parameters of the agglomeration process and obtain a product that was durable enough to transport and dose into slag baths in order to reduce iron oxides in liquid phases. During the research, completely dried briquettes with an appropriate strength were obtained. The study demonstrates that microwave drying at 300 W for 6 min achieved complete drying with a weight loss of 35%, whereas a higher-power treatment at 750 W for 2 min enhanced compressive strength by up to 95% and reached 15 N/psc, which was comparable with green iron ore pellets. This approach offers a sustainable alternative to traditional methods, but with a reduced drying time. Full article
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Graphical abstract

Graphical abstract
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<p>Schema of the high-temperature rheometer FRS1600 system.</p>
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<p>Concentric cylinder system. (<b>a</b>) Principle of rheometric study: 1—cup (outer cylinder); 2—measured sample; 3—bob (inner cylinder). (<b>b</b>) Concentrical cylinders after the experiment.</p>
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<p>Viscosity curves of Mix1 for constant shear rates of 5 and 10 s<sup>−1</sup> (dashed lines) and for various shear rates of 5–50 and 50–5 s<sup>−1</sup> (solid lines).</p>
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<p>Viscosity curves of Mix2 for constant shear rates of 5 and 10 s<sup>−1</sup> (dashed lines) and for various shear rates of 5–50 and 50–5 s<sup>−1</sup> (solid lines).</p>
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<p>Viscosity curves of Mix3 for constant shear rates of 5 and 10 s<sup>−1</sup> (dashed lines) and for various shear rates of 5–50 and 50–5 s<sup>−1</sup> (solid lines).</p>
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<p>Viscosity curves of Mix4 for constant shear rates of 5 and 10 s<sup>−1</sup> (dashed lines) and for various shear rates of 5–50 and 50–5 s<sup>−1</sup> (solid lines).</p>
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<p>An example of a prepared and dried sample. (<b>a</b>) Freshly molded sample; (<b>b</b>) sample after microwave treatment.</p>
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<p>An example of manually formed and dried lumps. (<b>a</b>) Freshly made lumps; (<b>b</b>) lumps after drying at 300 W for 6 min in a microwave.</p>
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<p>View of manually prepared wet lumps after microwave treatment at a power of 750 W.</p>
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<p>Stereoscopic microscope photos of cores: (<b>a</b>) Lump1 (sludge only); (<b>b</b>) Lump2 (sludge with fly ash).</p>
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21 pages, 7616 KiB  
Article
Numerical Simulation of a Marine Landslide in Gas Hydrate-Bearing Sediments Using L-GSM
by Da Hui, Guangyao Wang, Yilin Huang, Guixun Zhu and Wenming Li
J. Mar. Sci. Eng. 2024, 12(12), 2274; https://doi.org/10.3390/jmse12122274 - 11 Dec 2024
Viewed by 339
Abstract
The marine gas hydrates within seabed sediments and their subsequent extraction may cause landslides. Predicting landslides in hydrate-bearing sediments is particularly challenging due to the intricate nature of the marine environment. To address this issue, we have developed a Lagrangian gradient smoothing method [...] Read more.
The marine gas hydrates within seabed sediments and their subsequent extraction may cause landslides. Predicting landslides in hydrate-bearing sediments is particularly challenging due to the intricate nature of the marine environment. To address this issue, we have developed a Lagrangian gradient smoothing method (L-GSM) based on gradient smoothing techniques. This approach effectively eliminates the tensile instability inherent in the original Smoothed Particle Hydrodynamics (SPH) method used for modeling solid flow. Then, we applied the L-GSM to investigate the mechanics of hydrate-bearing sediments by integrating a constitutive equation specific to these sediments, which were modeled based on the artificial methane-hydrate-bearing sediment. The robustness and precision of the L-GSM were verified through various numerical examples. Furthermore, we modeled the landslides associated with hydrate-bearing sediments under varying hydrate saturation levels. The numerical findings revealed that hydrate saturation significantly affects the dynamics of landslide movement. These satisfactory results suggest that the L-GSM has the potential to be applied to geotechnical problems associated with hydrate-bearing sediment. Full article
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<p>Smoothing domain and its boundary.</p>
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<p>Illustration of the GSD.</p>
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<p>Construction of the GSD: (<b>a</b>) Delaunay triangulation and (<b>b</b>) Local neighbors-searching.</p>
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<p>Boundary treatment: (<b>a</b>) free-surface particle; (<b>b</b>) solid wall particle.</p>
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<p>Six triangular meshes with different irregularities: (<b>a</b>) <math display="inline"><semantics> <mrow> <mi>γ</mi> <mo>=</mo> <mn>0.019</mn> </mrow> </semantics></math>; (<b>b</b>) <math display="inline"><semantics> <mrow> <mi>γ</mi> <mo>=</mo> <mn>0.025</mn> </mrow> </semantics></math>; (<b>c</b>) <math display="inline"><semantics> <mrow> <mi>γ</mi> <mo>=</mo> <mn>0.047</mn> </mrow> </semantics></math>; (<b>d</b>) <math display="inline"><semantics> <mrow> <mi>γ</mi> <mo>=</mo> <mn>0.078</mn> </mrow> </semantics></math>; (<b>e</b>) <math display="inline"><semantics> <mrow> <mi>γ</mi> <mo>=</mo> <mn>0.117</mn> </mrow> </semantics></math>; and (<b>f</b>) <math display="inline"><semantics> <mrow> <mi>γ</mi> <mo>=</mo> <mn>0.154</mn> </mrow> </semantics></math>.</p>
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<p>Six triangular meshes with different irregularities: (<b>a</b>) <math display="inline"><semantics> <mrow> <mi>γ</mi> <mo>=</mo> <mn>0.019</mn> </mrow> </semantics></math>; (<b>b</b>) <math display="inline"><semantics> <mrow> <mi>γ</mi> <mo>=</mo> <mn>0.025</mn> </mrow> </semantics></math>; (<b>c</b>) <math display="inline"><semantics> <mrow> <mi>γ</mi> <mo>=</mo> <mn>0.047</mn> </mrow> </semantics></math>; (<b>d</b>) <math display="inline"><semantics> <mrow> <mi>γ</mi> <mo>=</mo> <mn>0.078</mn> </mrow> </semantics></math>; (<b>e</b>) <math display="inline"><semantics> <mrow> <mi>γ</mi> <mo>=</mo> <mn>0.117</mn> </mrow> </semantics></math>; and (<b>f</b>) <math display="inline"><semantics> <mrow> <mi>γ</mi> <mo>=</mo> <mn>0.154</mn> </mrow> </semantics></math>.</p>
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<p>Results of the GSM with different irregular triangular meshes: (<b>a</b>) <math display="inline"><semantics> <mrow> <mi>γ</mi> <mo>=</mo> <mn>0.019</mn> </mrow> </semantics></math>; (<b>b</b>) <math display="inline"><semantics> <mrow> <mi>γ</mi> <mo>=</mo> <mn>0.025</mn> </mrow> </semantics></math>; (<b>c</b>) <math display="inline"><semantics> <mrow> <mi>γ</mi> <mo>=</mo> <mn>0.047</mn> </mrow> </semantics></math>; (<b>d</b>) <math display="inline"><semantics> <mrow> <mi>γ</mi> <mo>=</mo> <mn>0.078</mn> </mrow> </semantics></math>; (<b>e</b>) <math display="inline"><semantics> <mrow> <mi>γ</mi> <mo>=</mo> <mn>0.117</mn> </mrow> </semantics></math>; and (<b>f</b>) <math display="inline"><semantics> <mrow> <mi>γ</mi> <mo>=</mo> <mn>0.154</mn> </mrow> </semantics></math>.</p>
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<p>Numerical errors of GSM solution and FVM solution.</p>
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<p>Mesh penetration for <math display="inline"><semantics> <mrow> <mi>γ</mi> <mo>=</mo> <mn>0.154</mn> </mrow> </semantics></math>.</p>
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<p>Computational domain and boundary conditions.</p>
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<p>Results of Poiseuille flow problem: (<b>a</b>) velocity contour and (<b>b</b>) velocity profile.</p>
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<p>Error change with particle number.</p>
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<p>Horizontal velocity for the FEM results.</p>
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<p>Illustration of the computational domain.</p>
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<p>Velocity contour for soil shear deformation.</p>
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<p>Loading path under different confined stresses.</p>
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<p>Shear stress–strain relationships under different confined stresses.</p>
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<p>Non-cohesive soil failure.</p>
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<p>Right-most soil particle locations change with time.</p>
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<p>Sediment model with different hydrate saturations.</p>
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<p>Results of sediments with different hydrate saturations: (<b>a</b>) <math display="inline"><semantics> <mrow> <msub> <mi>η</mi> <mn>2</mn> </msub> <mo>=</mo> <mn>7.7</mn> <mo>%</mo> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <msub> <mi>η</mi> <mn>2</mn> </msub> <mo>=</mo> <mn>7.7</mn> <mo>%</mo> </mrow> </semantics></math>; and (<b>b</b>) <math display="inline"><semantics> <mrow> <msub> <mi>η</mi> <mn>1</mn> </msub> <mo>=</mo> <mn>0</mn> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <msub> <mi>η</mi> <mn>2</mn> </msub> <mo>=</mo> <mn>37.6</mn> <mo>%</mo> </mrow> </semantics></math>.</p>
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<p>Results of sediments with different hydrate saturations: (<b>a</b>) <math display="inline"><semantics> <mrow> <msub> <mi>η</mi> <mn>2</mn> </msub> <mo>=</mo> <mn>7.7</mn> <mo>%</mo> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <msub> <mi>η</mi> <mn>2</mn> </msub> <mo>=</mo> <mn>7.7</mn> <mo>%</mo> </mrow> </semantics></math>; and (<b>b</b>) <math display="inline"><semantics> <mrow> <msub> <mi>η</mi> <mn>1</mn> </msub> <mo>=</mo> <mn>0</mn> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <msub> <mi>η</mi> <mn>2</mn> </msub> <mo>=</mo> <mn>37.6</mn> <mo>%</mo> </mrow> </semantics></math>.</p>
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18 pages, 2817 KiB  
Article
A Comparative Study on Acoustic Characteristics of Methane and Tetrahydrofuran Hydrate-Bearing Sediments
by Wengao Zhao, Qingtao Bu, Zihao Wang, Tong Liu, Qingguo Meng, Yapeng Zhao and Gaowei Hu
J. Mar. Sci. Eng. 2024, 12(12), 2239; https://doi.org/10.3390/jmse12122239 - 5 Dec 2024
Viewed by 483
Abstract
Laboratory acoustic measurements of hydrate-bearing sediments serve as an important reference for the geological interpretation of seismic exploration data. Tetrahydrofuran (THF) hydrates are relatively easy to form with precise control of hydrate saturation, and they overcome the long time it takes for methane [...] Read more.
Laboratory acoustic measurements of hydrate-bearing sediments serve as an important reference for the geological interpretation of seismic exploration data. Tetrahydrofuran (THF) hydrates are relatively easy to form with precise control of hydrate saturation, and they overcome the long time it takes for methane in sediments to form hydrate. However, when THF hydrates are used as a substitute for methane hydrate, their acoustic properties yield different results. This study reports the results of a series of laboratory experiments on the formation of methane and THF hydrate in quartz sand and the evaluation of their acoustic properties. It compares the experimental results with the results of calculations from micro-distribution models of the four hydrates using effective medium theory (EMT). Methane hydrate formed by the excess gas method has higher acoustic velocities than THF hydrate at 0–80% saturation, but at 80–100% saturation, the situation reverses, with THF hydrate having a higher wave velocity. The methane hydrate synthesis process follows a mixed micro-distribution, with grain coating predominating at low saturations, the pore-filling mixing mode dominating at medium saturations, and grain coating dominating at high saturations. In addition, THF hydrate has a slow-velocity growth at low saturation and is dominated by a pore-filling model and a load-bearing model at high saturation. We compared our experimental data with a compilation of similar published results to confirm their reliability and support our conclusions. Both hydrate types exhibit distinct micro-distributions across different saturations. Therefore, when testing the elastic characteristics of hydrate sediments, the distinct hydrate synthesis methods and micro-distribution should be considered, especially when using THF hydrate as an alternative to methane hydrate. Full article
(This article belongs to the Section Geological Oceanography)
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<p>Experimental device for gas hydrate formation and acoustic velocity detection. T and P denote the temperature and pressure, respectively.</p>
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<p>Particle size distribution of the sediment. The black curve represents the cumulative distribution of natural sand particle sizes. The blue histogram shows the different distributions of natural sand particle sizes.</p>
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<p>Ultrasonic waveforms of samples with different methane hydrate saturations. A decrease in P-wave arrival times with increasing hydrate saturation can be observed.</p>
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<p>Ultrasonic waveforms of samples with different tetrahydrofuran (THF) hydrate saturations. A decrease in P-wave arrival times with increasing hydrate saturation can be observed.</p>
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<p>Comparison of the methane (<b>a</b>,<b>b</b>) and THF (<b>c</b>,<b>d</b>) hydrate-bearing sediment experimental data in this study with data from published papers [<a href="#B9-jmse-12-02239" class="html-bibr">9</a>,<a href="#B10-jmse-12-02239" class="html-bibr">10</a>,<a href="#B22-jmse-12-02239" class="html-bibr">22</a>,<a href="#B31-jmse-12-02239" class="html-bibr">31</a>,<a href="#B32-jmse-12-02239" class="html-bibr">32</a>,<a href="#B33-jmse-12-02239" class="html-bibr">33</a>,<a href="#B47-jmse-12-02239" class="html-bibr">47</a>,<a href="#B48-jmse-12-02239" class="html-bibr">48</a>,<a href="#B49-jmse-12-02239" class="html-bibr">49</a>,<a href="#B50-jmse-12-02239" class="html-bibr">50</a>]. (Lines show data approximation by the 3rd-order polynomials).</p>
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<p>Schematic diagrams of four distinct hydrate morphologies (modified from [<a href="#B56-jmse-12-02239" class="html-bibr">56</a>]). (<b>a</b>) Pore-filling; (<b>b</b>) load-bearing; (<b>c</b>) contact-cementing; (<b>d</b>) grain-coating. Blue—matrix grains; white—pore space; yellow—hydrate.</p>
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<p>Comparison of obtained compressional and shear wave velocities in samples bearing methane (<b>a</b>,<b>b</b>) and THF (<b>c</b>,<b>d</b>) hydrate with estimation by EMT.</p>
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<p>Comparison of acoustic velocities of methane and THF hydrate-bearing sediments.</p>
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15 pages, 4237 KiB  
Article
Damage Mechanism of Deep Coalbed Methane Reservoir and Novel Anti-Waterblocking Protection Technology
by Wei Wang, Jiafeng Jin, Jiang Xin, Kaihe Lv, Kang Ren, Jie Xu, Zhenyi Cao and Ran Zhuo
Processes 2024, 12(12), 2735; https://doi.org/10.3390/pr12122735 - 3 Dec 2024
Viewed by 479
Abstract
Coalbed Methane (CBM) accounts for about 5% of China’s domestic gas supply, which has been regarded as one of the most promising energies for alleviating the energy supply–demand imbalance. Deep CBM reservoirs have the characteristics of low permeability, low porosity, and low water [...] Read more.
Coalbed Methane (CBM) accounts for about 5% of China’s domestic gas supply, which has been regarded as one of the most promising energies for alleviating the energy supply–demand imbalance. Deep CBM reservoirs have the characteristics of low permeability, low porosity, and low water saturation, which easily experience reservoir damage during the drilling process, further affecting the gas productivity. Based on the analysis of coal mineral composition, pore structure distribution, and the surface micromorphology change in coal surface before and after hydration, a possible mechanism for CBM formation damage was revealed. It was found that the damage caused by drilling fluid intrusion can be divided into three stages: stripping, migration, and plugging. Based on the water-sensitive, acid-sensitive, and stress-sensitive evaluation tests, a novel anti-waterblocking agent with both wettability alteration and surface tension reduction was developed; then a reservoir protection drilling fluid for deep coal formation in Daning-Jixian block was constructed; then the reservoir protection performance of drilling fluid was evaluated. The results show that as the concentration of the anti-waterblocking agent FSS increases from 0% to 1%, the surface tension of the water phase is significantly reduced from 72.15 mN/m to 26.58 mN/m, while the maximum contact angle of water on the surface reaches 117°. This enhancement in wettability leads to an improvement in the permeability recovery rate from 56.6% to 80.0%, indicating a substantial reduction in waterblocking effects and better fluid mobility within the reservoir. These findings highlight the efficacy of FSS in mitigating formation damage and optimizing gas production in coalbed methane reservoirs. The drilling fluid has good wettability alteration, inhibition, and sealing performance, which is of great significance for protecting gas well productivity. Full article
(This article belongs to the Special Issue Advanced Nano-Materials for Oil and Natural Gas Exploration)
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<p>X-ray diffraction of coal rock from the Daning block.</p>
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<p>Surface morphology of coal rock.</p>
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<p>SEM images of coal rock surface structure before and after hydration: (<b>a</b>–<b>c</b>) surface morphology of rock cores at different magnifications before hydration; (<b>d</b>–<b>f</b>) surface morphology of rock at different magnifications after hydration.</p>
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<p>The invasion damage mechanism of drilling fluid.</p>
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<p>Swelling study of coal rock.</p>
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<p>The permeability comparison of coal before and after 10% HCl treatment.</p>
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<p>Influence of coal confining pressure change on coal permeability.</p>
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<p>Evaluation of wettability alternation performance of FSS.</p>
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<p>Effect of the anti-waterblocking agent on the spontaneous imbibition.</p>
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<p>The effect of the anti-waterblocking agent on the surface tension.</p>
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<p>Effect of drilling fluid on the core wettability.</p>
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<p>Comparison of linear expansion of drilling fluid.</p>
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16 pages, 2909 KiB  
Article
Evaluation of Gas Hydrate Saturation Based on Joint Acoustic–Electrical Properties and Neural Network Ensemble
by Donghui Xing, Hongfeng Lu, Lanchang Xing, Chenlu Xu, Jinwen Du, Xinmin Ge and Qiang Chen
J. Mar. Sci. Eng. 2024, 12(12), 2163; https://doi.org/10.3390/jmse12122163 - 27 Nov 2024
Viewed by 367
Abstract
Natural gas hydrates have great strategic potential as an energy source and have become a global energy research hotspot because of their large reserves and clean and pollution-free characteristics. Hydrate saturation affecting the electrical and acoustic properties of sediments significantly is one of [...] Read more.
Natural gas hydrates have great strategic potential as an energy source and have become a global energy research hotspot because of their large reserves and clean and pollution-free characteristics. Hydrate saturation affecting the electrical and acoustic properties of sediments significantly is one of the important parameters for the quantitative evaluation of natural gas hydrate reservoirs. The accurate calculation of hydrate saturation has guiding significance for hydrate exploration and development. In this paper, experiments regarding methane hydrate formation and dissociation in clay-bearing sediments were carried out based on the Ultrasound Combined with Electrical Impedance (UCEI) system, and the measurements of the joint electrical and acoustic parameters were collected. A machine learning (ML)-based model for evaluating hydrate saturation was established based on electrical–acoustic properties and a neural network ensemble. It was demonstrated that the average relative error of hydrate saturation calculated by the ML-based model is 0.48%, the average absolute error is 0.0005, and the root mean square error is 0.76%. The three errors of the ensemble network are lower than those of the Archie formula and Lee weight equation. The ML-based modeling method presented in this paper provides insights into developing new models for estimating the hydrate saturation of reservoirs. Full article
(This article belongs to the Special Issue Analytical and Experimental Technology for Marine Gas Hydrate)
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<p>A schematic diagram of the structure of the UCEI experimental system.</p>
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<p>An illustration of the working mode for UEC sensors. (<b>a</b>) The ultrasonic part. (<b>b</b>) The electrical part.</p>
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<p>BP network.</p>
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<p>Flow chart of hydrate saturation calculation model based on acoustic–electrical characteristic parameters.</p>
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<p>Time traces of pressure, temperature, and hydrate saturation.</p>
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<p>Variation curve of P-wave velocity with hydrate saturation during methane hydrate formation.</p>
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<p>Dispersion curves of electrical parameters in different measurement directions at stable stage (SH = 18%) after hydrate formation. (<b>a</b>) Impedance mode value; (<b>b</b>) absolute value of phase angle.</p>
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<p>Variation curve of impedance modulus and phase angle (1 kHz) with hydrate saturation during hydrate formation. (<b>a</b>) Impedance mode value; (<b>b</b>) absolute value of phase angle.</p>
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<p>Principal component analysis of broadband impedance modulus of E1–E5 sensor.</p>
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<p>Comparison of the 17 points of predicted saturations and actual saturations by combined electroacoustic model.</p>
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29 pages, 12142 KiB  
Review
Research Progress and Outlook of Molecular Dynamics Simulation on Carbon Dioxide Applied for Methane Exploitation from Hydrates
by Qiannan Yu, Chenglong Li, Boyang Peng, Huimin Tang, Tao Yang, Yang Yu, Kun Zhang and Zhijing Chen
Molecules 2024, 29(23), 5579; https://doi.org/10.3390/molecules29235579 - 26 Nov 2024
Viewed by 506
Abstract
Research progress of carbon dioxide applied for methane exploitation from hydrates is summarized, with a focus on advances in molecular dynamics simulations and their application in understanding the mechanism of carbon dioxide replacement for hydrate exploitation. The potential of carbon dioxide in enhancing [...] Read more.
Research progress of carbon dioxide applied for methane exploitation from hydrates is summarized, with a focus on advances in molecular dynamics simulations and their application in understanding the mechanism of carbon dioxide replacement for hydrate exploitation. The potential of carbon dioxide in enhancing energy recovery efficiency and promoting carbon capture and storage is emphasized. An overview is provided of the advancements made in utilizing carbon dioxide for methane hydrate exploitation, highlighting its significance. Subsequently, the theoretical foundations and techniques of molecular dynamics simulations are delved into, encompassing key elements such as statistical ensembles, molecular force fields, and numerical solution methods. Through simulations, various characterization parameters including mean square displacement, radial distribution functions, coordination numbers, angular order parameters, and hydrogen bonds are computed and analyzed, which are crucial for understanding the dynamic changes in hydrate structures and the replacement process. Thorough research and analysis have been conducted on the two possible and widely debated mechanisms involved in the replacement of methane hydrates by carbon dioxide, with a particular emphasis on guest molecular replacement and hydrate reconfiguration. These processes encompass the intricate interactions between carbon dioxide molecules and the cage-like structure of hydrates, as well as the rearrangement and stabilization of hydrate structures. Several key issues surrounding the application of carbon dioxide for methane hydrate exploitation are identified, including the influence of thermodynamic conditions, the selection of auxiliary gases, and other potential factors such as geological conditions and fluid properties. Addressing these issues is crucial for optimizing the extraction process and enhancing economic and environmental benefits. A theoretical foundation and technical reference for the application of carbon dioxide in methane hydrate exploitation are provided, while future research directions and priorities are also outlined. Full article
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<p>Equilibrium curves of methane hydrate and carbon dioxide hydrates for different salinities.</p>
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<p>High-frequency keyword clustering co-occurrence map of natural gas hydrates.</p>
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<p>Water molecule angular order parameters for different hydrate layers (Tung, Y.T. et al., 2011 [<a href="#B54-molecules-29-05579" class="html-bibr">54</a>]).</p>
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<p>Variation in the oxygen atom pair distribution function during simulation (Qi, Y. et al., 2011 [<a href="#B56-molecules-29-05579" class="html-bibr">56</a>]).</p>
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<p>Trajectories of carbon dioxide molecules in hydrate cages at 315 K (Liang, S. et al., 2016 [<a href="#B57-molecules-29-05579" class="html-bibr">57</a>]. Where green wireframe represents cage structure of hydrate, combination of one green ball and two blue balls represents carbon dioxide molecule).</p>
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<p>Conformational diagram of the system for the replacement of methane hydrate by carbon dioxide in NaCl solution (Yi, L. et al., 2016 [<a href="#B58-molecules-29-05579" class="html-bibr">58</a>]).</p>
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<p>Coordination number of water molecules in hydrates (Iwai, Y. et al., 2012 [<a href="#B59-molecules-29-05579" class="html-bibr">59</a>]).</p>
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<p>Initial system conformation (Bai, D. et al., 2012 [<a href="#B60-molecules-29-05579" class="html-bibr">60</a>]).</p>
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<p>Hydration numbers in different regions (Bai, D. et al., 2012 [<a href="#B60-molecules-29-05579" class="html-bibr">60</a>]).</p>
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<p>Variation in the number of hydrogen bonds in methane hydrates with simulation time under different temperature conditions (Uddin, M. et al., 2014 [<a href="#B61-molecules-29-05579" class="html-bibr">61</a>]).</p>
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<p>Variation in the number of hydrate cages for pressures of 20 bar and 50 bar at 255 K temperature (Wu, G. et al., 2019 [<a href="#B62-molecules-29-05579" class="html-bibr">62</a>]).</p>
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<p>RDF values for methane hydrate at 2–210 K (Cladek, B.R. et al., 2021 [<a href="#B65-molecules-29-05579" class="html-bibr">65</a>]).</p>
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<p>RDF of particles in the system at 3MPa with different temperatures (Guo, P. et al., 2022 [<a href="#B66-molecules-29-05579" class="html-bibr">66</a>]).</p>
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<p>Changes in the number of methane and carbon dioxide molecules with temperature (Gajanayake, S. et al., 2022 [<a href="#B67-molecules-29-05579" class="html-bibr">67</a>]).</p>
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<p>Variation in tetrahedrality order parameter with temperature at 8 MPa pressure (Gajanayake, S. et al., 2022 [<a href="#B67-molecules-29-05579" class="html-bibr">67</a>]).</p>
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<p>RDF of hydrate oxygen atom pairs (<b>a</b>), methane hydrate (<b>b</b>), and carbon dioxide hydrate (<b>c</b>) at different temperatures (Cheng, L. et al., 2024 [<a href="#B68-molecules-29-05579" class="html-bibr">68</a>]).</p>
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<p>MSD of nitrogen and carbon dioxide in nitrogen hydrate and carbon dioxide hydrate (Liu, J. et al., 2016 [<a href="#B70-molecules-29-05579" class="html-bibr">70</a>]).</p>
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<p>Recovery of methane in the replacement of natural gas hydrates with pure nitrogen, pure carbon dioxide, and nitrogen–carbon dioxide gas mixtures in different ratios (Matsui, H. et al., 2016 [<a href="#B71-molecules-29-05579" class="html-bibr">71</a>]).</p>
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<p>RDF of pure carbon dioxide (<b>a</b>), pure nitrogen (<b>b</b>), and nitrogen–carbon dioxide gas mixtures (<b>c</b>) before and after gas hydrate replacement (Song, W. et al., 2020 [<a href="#B72-molecules-29-05579" class="html-bibr">72</a>]).</p>
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<p>Number of replaced methane molecules varies with time, 265 K (Li, D. et al., 2021 [<a href="#B73-molecules-29-05579" class="html-bibr">73</a>]).</p>
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<p>F4φ order parameters for different system substitutions at 260 K and 50 MPa (Palodkar, A.V. et al., 2022 [<a href="#B74-molecules-29-05579" class="html-bibr">74</a>]).</p>
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<p>RDF of carbon dioxide hydrate with time in pure water and porous media systems (Zhang, X. et al., 2023 [<a href="#B75-molecules-29-05579" class="html-bibr">75</a>]).</p>
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<p>Changes in the number of methane and carbon dioxide molecules with initial carbon dioxide concentration (Gajanayake, S. et al., 2022 [<a href="#B67-molecules-29-05579" class="html-bibr">67</a>]).</p>
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17 pages, 4292 KiB  
Article
Deviation of Phase Boundary Conditions for Hydrates of Small-Chain Hydrocarbons (CH4, C2H6 and C3H8) When Formed Within Porous Sediments
by Alberto Maria Gambelli
Energies 2024, 17(22), 5574; https://doi.org/10.3390/en17225574 - 7 Nov 2024
Viewed by 450
Abstract
This research deals with gas hydrates formation and dissociation within a marine quartz-based porous sediment and in batch conditions. Hydrates were formed with small-chain hydrocarbons included in natural gas mixtures: methane and also ethane and propane. The dissociation values were collected and provided [...] Read more.
This research deals with gas hydrates formation and dissociation within a marine quartz-based porous sediment and in batch conditions. Hydrates were formed with small-chain hydrocarbons included in natural gas mixtures: methane and also ethane and propane. The dissociation values were collected and provided both graphically and numerically. The results were then compared with the theoretical hydrate-liquid-vapor phase boundary equilibrium for the same species, defined according to the existing literature. The deviation of the experimental results from the ideal ones, associated with the porous sediment, was quantified and discussed. For the scope, the grain size distribution and chemical composition of the sediment were provided along with the text. The results proved that the different size of guest species and, consequently, the different hydrate structures formed, played a relevant role in determining the promoting, inhibiting or neutral behavior of the porous sediment during the process. Full article
(This article belongs to the Section H: Geo-Energy)
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<p>The scheme of the reactor used for this study. In the pictures above, moving from the top left to the bottom right: superior flange, hosting the pressure and temperature sensors and the gas ejection channel; bottom of the reactor, with the connections with the gas cylinders; detail of the gas ejection channel (ejection valve and pressure reducer); picture of the assembled apparatus. The scheme below includes geometrical details of the reactor used for hydrates production.</p>
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<p>Size distribution [mm] of sand grains.</p>
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<p>Temperature profile followed during hydrate formation and dissociation. The curve is divided in four parts from the dotted lines: the first and the fourth (num° 1 and 4) describe the variation in temperature, respectively, when hydrates did not already form and completely dissociated. The second and the third sectors (num° 2 and 3) instead describe the gradient of temperature during the formation and dissociation of the hydrates.</p>
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<p>Methane hydrates: comparison between theoretical H-L-V phase boundary conditions and the same experimentally obtained within the natural quartz-based porous medium. The data shown in <a href="#energies-17-05574-t001" class="html-table">Table 1</a> were used for the diagrams.</p>
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<p>Ethane hydrates: comparison between the theoretical H-L-V phase boundary conditions and the same experimentally obtained within the natural quartz-based porous medium. The data shown in <a href="#energies-17-05574-t002" class="html-table">Table 2</a> were used for the diagrams.</p>
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<p>Propane hydrates: comparison between the theoretical H-L-V phase boundary conditions and the same experimentally obtained within the natural quartz-based porous medium. The data shown in <a href="#energies-17-05574-t003" class="html-table">Table 3</a> were used for the diagrams.</p>
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23 pages, 6305 KiB  
Article
The Hydration-Dependent Dynamics of Greenhouse Gas Fluxes of Epiphytic Lichens in the Permafrost-Affected Region
by Oxana V. Masyagina, Svetlana Yu. Evgrafova, Natalia M. Kovaleva, Anna E. Detsura, Elizaveta V. Porfirieva, Oleg V. Menyailo and Anastasia I. Matvienko
Forests 2024, 15(11), 1962; https://doi.org/10.3390/f15111962 - 7 Nov 2024
Viewed by 790
Abstract
Recent studies actively debate oxic methane (CH4) production processes in water and terrestrial ecosystems. This previously unknown source of CH4 on a regional and global scale has the potential to alter our understanding of climate-driving processes in vulnerable ecosystems, particularly [...] Read more.
Recent studies actively debate oxic methane (CH4) production processes in water and terrestrial ecosystems. This previously unknown source of CH4 on a regional and global scale has the potential to alter our understanding of climate-driving processes in vulnerable ecosystems, particularly high-latitude ecosystems. Thus, the main objective of this study is to use the incubation approach to explore possible greenhouse gas (GHG) fluxes by the most widely distributed species of epiphytic lichens (ELs; Evernia mesomorpha Nyl. and Bryoria simplicior (Vain.) Brodo et D. Hawksw.) in the permafrost zone of Central Siberia. We observed CH4 production by hydrated (50%–400% of thallus water content) ELs during 2 h incubation under illumination. Moreover, in agreement with other studies, we found evidence that oxic CH4 production by Els is linked to the CO2 photoassimilation process, and the EL thallus water content regulates that relationship. Although the GHG fluxes presented here were obtained under a controlled environment and are probably not representative of actual emissions in the field, more research is needed to fully comprehend ELs’ function in the C cycle. This particular research provides a solid foundation for future studies into the role of ELs in the C cycle of permafrost forest ecosystems under ongoing climate change (as non-methanogenesis processes in oxic environments). Full article
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<p>Map of site locations (A, B, C, D, and E) near Tura (64 N, 100 E; <a href="https://www.esri.com/" target="_blank">https://www.esri.com/</a>, accessed on 31 July 2024). The numbers indicate the number of the larch tree (from the first tree to the twenty-fifth tree).</p>
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<p>A wind rose from the Tura weather station, which indicates a predominantly westerly flow. Data from the entire observational period of 2013–2023 are included and were accessed at aisori.ru on 14 July 2024.</p>
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<p>Projecting cover (boxplots) of the ELs on the branches and stems of larches in the permafrost area. B, <span class="html-italic">Bryoria simplicior</span>; E, <span class="html-italic">Evernia mesomorpha</span>; T, <span class="html-italic">Tuckermannopsis sepincola</span>. The horizontal line within the box indicates median, box boundaries indicate 25th and 75th percentiles, and whiskers indicate highest and lowest values.</p>
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<p>Projecting cover (%) of ELs regarding the branch (<b>A</b>) or stem (<b>B</b>) exposure.</p>
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<p>Occurrence of ELs regarding the branch (<b>A</b>) or stem (<b>B</b>) exposure.</p>
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<p>Boxplots of day CO<sub>2</sub> and CH<sub>4</sub> fluxes by EL species (<span class="html-italic">Bryoria simplicior</span> and <span class="html-italic">Evernia mesomorpha</span>) occupying larch branches of various exposures and which were incubated in controlled photoperiod and thermal regimes. The horizontal line within the box indicates median, box boundaries indicate 25th and 75th percentiles, and whiskers indicate highest and lowest values. Negative values reflect CO<sub>2</sub> photoassimilation (or CH<sub>4</sub> consumption), and positive values reflect respiration (or CH<sub>4</sub> production). E, eastern exposure of the branches occupied by the ELs; N, northern exposure of the branches occupied by the ELs; S, southern exposure of the branches occupied by the ELs; W, western exposure of the branches occupied by the ELs. Small letters designate the differences between the SW and NE exposures within the same EL species according to the pairwise Wilcoxon test. Capital letters describe the differences between the EL species within the same branch exposure (SW or NE) according to the pairwise Wilcoxon test.</p>
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<p>Correlation (Spearman’s rank correlation coefficients) heat maps of the studied parameters of the ELs on the 1st (<b>A</b>), 2nd (<b>B</b>), and 3rd (<b>C</b>) days of the first incubation experiment. ***, <span class="html-italic">p</span> &lt; 0.001; **, <span class="html-italic">p</span> &lt; 0.05; *, <span class="html-italic">p</span> &lt; 0.5.</p>
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<p>Boxplots of the day CO<sub>2</sub> (<b>A</b>) and CH<sub>4</sub> (<b>B</b>) fluxes by hydrated (50%–400% of thallus water content) <span class="html-italic">Evernia mesomorpha</span> sampled from various larch branch exposures and incubated under controlled photoperiod and thermal regimes. The horizontal line within the box indicates median, box boundaries indicate 25th and 75th percentiles, and whiskers indicate highest and lowest values. Negative values reflect CO<sub>2</sub> photoassimilation (or CH<sub>4</sub> consumption), and positive values reflect respiration (or CH<sub>4</sub> production). The (<b>C</b>,<b>D</b>) panels display the relationships (mean values and standard errors) between the CO<sub>2</sub> and CH<sub>4</sub> production and accumulation processes in the ELs of various (50%–400%) thallus water contents as a summary of the (<b>A</b>,<b>B</b>) panels. The (<b>D</b>) panel represents the relationship between the CO<sub>2</sub> and CH<sub>4</sub> production processes in the EL of 400% thallus water content. N, <span class="html-italic">Evernia mesomorpha</span> occupying larch branches of northern exposure; S, <span class="html-italic">Evernia mesomorpha</span> occupying larch branches of southern exposure; W, <span class="html-italic">Evernia mesomorpha</span> occupying larch branches of western exposure. Because of the extremely low abundance of ELs on east-exposed larch branches, the GHG fluxes are not shown for the eastern exposure. Small letters designate the differences between the fluxes by ELs of various thallus water content but of the same branch exposure (N, S, W) according to the pairwise Wilcoxon test. Capital letters describe the differences between the branch exposures within the same thallus water content of the <span class="html-italic">Evernia mesomorpha</span> according to the pairwise Wilcoxon test.</p>
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<p>PCA of the relationships within the processes gathered in the CO<sub>2</sub> (<b>A</b>) and CH<sub>4</sub> (<b>B</b>) fluxes from the thallus of <span class="html-italic">Evernia mesomorpha</span> inhabiting the larch branches of various exposures and different thallus water contents. S50, south-exposed EL of 50% of water content; S100, south-exposed EL of 100% of water content; S200, south-exposed EL of 200% of water content; S400, south-exposed EL of 400% of water content; N50, north-exposed EL of 50% of water content; N100, north-exposed EL of 100% of water content; N200, north-exposed EL of 200% of water content; N400, north-exposed EL of 400% of water content; W50, west-exposed EL of 50% of water content; W100, west-exposed EL of 100% of water content; W200, west-exposed EL of 200% of water content; W400, west-exposed EL of 400% of water content.</p>
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<p>Keeling plots of δ<sup>13</sup>C in CO<sub>2</sub> samples collected before (<b>A</b>) and after 2 h (<b>B</b>) of incubation of <span class="html-italic">Evernia mesomorpha</span> (at 200% of thallus water content) during a course of three-day incubation under illumination. SW (red), larch branches of southern and western exposures; NE (blue), larch branches of northern and eastern exposures.</p>
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12 pages, 1216 KiB  
Article
Predictive Modeling of the Hydrate Formation Temperature in Highly Pressurized Natural Gas Pipelines
by Mustafa Karaköse and Özgün Yücel
Energies 2024, 17(21), 5306; https://doi.org/10.3390/en17215306 - 25 Oct 2024
Viewed by 684
Abstract
In this study, we aim to develop advanced machine learning regression models for the prediction of hydrate temperature based on the chemical composition of sweet gas mixtures. Data were collected in accordance with the BOTAS Gas Network Code specifications, approved by the Turkish [...] Read more.
In this study, we aim to develop advanced machine learning regression models for the prediction of hydrate temperature based on the chemical composition of sweet gas mixtures. Data were collected in accordance with the BOTAS Gas Network Code specifications, approved by the Turkish Energy Market Regulatory Authority (EMRA), and generated using DNV GasVLe v3.10 software, which predicts the phase behavior and properties of hydrocarbon-based mixtures under various pressure and temperature conditions. We employed linear regression, decision tree regression, random forest regression, generalized additive models, and artificial neural networks to create prediction models for hydrate formation temperature (HFT). The performance of these models was evaluated using the hold-out cross-validation technique to ensure unbiased results. This study demonstrates the efficacy of ensemble learning methods, particularly random forest with an R2 and Adj. R2 of 0.998, for predicting hydrate formation conditions, thereby enhancing the safety and efficiency of gas transport and processing. This research illustrates the potential of machine learning techniques in advancing the predictive accuracy for hydrate formations in natural gas pipelines and suggests avenues for future optimizations through hybrid modeling approaches. Full article
(This article belongs to the Section H: Geo-Energy)
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<p>Different types of cages and hydrate structures.</p>
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<p>Flowchart of predictive modeling of hydrate formation temperature.</p>
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<p>Predictions vs. observations plots for (<b>a</b>) Decision Tree regression, (<b>b</b>) Random Forest regression, (<b>c</b>) Generalized Additive regression, and (<b>d</b>) Linear regression.</p>
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10 pages, 2462 KiB  
Article
Effect of CO2 Thickeners on CH4-CO2 Replacement in Hydrate-Bearing Sediment
by Xuebing Zhou, Jiahong Zhou, Zhen Long, Huiyun Wen, Shuanshi Fan and Deqing Liang
J. Mar. Sci. Eng. 2024, 12(10), 1861; https://doi.org/10.3390/jmse12101861 - 17 Oct 2024
Viewed by 672
Abstract
CO2 fracturing is known as the best solution to improve the efficiency of the CO2 replacement of natural gas hydrates, but the effect of CO2 thickeners on CH4-CO2 replacement are barely noticed. In this work, the effect [...] Read more.
CO2 fracturing is known as the best solution to improve the efficiency of the CO2 replacement of natural gas hydrates, but the effect of CO2 thickeners on CH4-CO2 replacement are barely noticed. In this work, the effect of four kinds of CO2 thickener—including DL-Lactic acid, polyvinyl acetate, ethyl trifluoroacetate and octamethyl trisiloxane—on the CH4-CO2 replacement in quartz sand was measured thermodynamically and kinetically. The results show that the majority of the CO2 thickeners had no effect on the equilibria of the CH4 and CO2 hydrates, except for DL-Lactic acid, where the temperature depression caused by the addition of 5.5 wt% DL-Lactic acid was about 0.52 and 0.48 K for the CH4 and CO2 hydrates, respectively. In the kinetic measurements, the CH4-CO2 replacement was promoted via the addition of the CO2 thickeners, except DL-Lactic acid. The CO2 thickeners were suggested to strengthen the CH4-CO2 replacement by enhancing the gas exchange in the pore space. Octamethyl trisiloxane, which could promote CH4 recovery and CO2 capture at a low concentration, was suggested to be an ideal CO2 thickener for CH4-CO2 replacement. Full article
(This article belongs to the Special Issue Analytical and Experimental Technology for Marine Gas Hydrate)
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<p>The schematic diagram of the apparatus.</p>
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<p>Schematic diagram of the pressure search method.</p>
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<p>Phase equilibrium profiles of the CH<sub>4</sub> and CO<sub>2</sub> hydrates in the quartz sand with the 30% water saturation and 5.5 wt% CO<sub>2</sub> thickeners.</p>
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<p>Percentage of CH<sub>4</sub> recovered from hydrate phase during CH<sub>4</sub>-CO<sub>2</sub> replacement at 277.2 K, 4.0 Mpa.</p>
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<p>CH<sub>4</sub> production in each CH<sub>4</sub>-CO<sub>2</sub> replacement reaction.</p>
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<p>Percentage of CO<sub>2</sub> captured during CH<sub>4</sub>-CO<sub>2</sub> replacements at 277.2 K, 4.0 MPa.</p>
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<p>Percentage of CO<sub>2</sub> captured during CH<sub>4</sub>-CO<sub>2</sub> replacements at 277.2 K, 4.0 MPa.</p>
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17 pages, 2821 KiB  
Article
The Experimental and Modeling Study on the Thermodynamic Equilibrium Hydrate Formation Pressure of Helium-Rich Natural Gas in the Presence of Tetrahydrofuran
by Zengqi Liu, Guangqi Zhang, Fangfang Lu, Qiyuan Ren, Zhen Xu, Shiguang Fan, Qiang Sun, Yiwei Wang and Xuqiang Guo
Molecules 2024, 29(20), 4827; https://doi.org/10.3390/molecules29204827 - 11 Oct 2024
Viewed by 512
Abstract
Hydrate-based gas separation (HBGS) has good potential in the separation of helium from helium-rich natural gas. HBGS should be carried out under a pressure higher than the thermodynamic equilibrium hydrate formation pressure (Peq) to ensure the formation of hydrate so [...] Read more.
Hydrate-based gas separation (HBGS) has good potential in the separation of helium from helium-rich natural gas. HBGS should be carried out under a pressure higher than the thermodynamic equilibrium hydrate formation pressure (Peq) to ensure the formation of hydrate so that the accurate prediction of Peq is the basis of the determination of HBGS pressure. In this work, the Peq of the helium-rich natural gases with different helium contents (1 mol%, 10 mol%, and 50 mol%) in gas and different tetrahydrofuran (THF) contents (5 wt%, 10 wt%, and 19 wt%) in liquid at different temperatures were experimentally investigated through the isothermal pressure search method. A new thermodynamic model was proposed to predict the Peq of helium-rich natural gas. This model can quantitatively describe the effects of THF and helium on Peq, and it predicts the Peq of the helium-rich natural gases in this work accurately. The average relative deviation of the model is less than 3%. This model can guide the determination of the operating condition of the HBGS of helium-rich natural gas. Full article
(This article belongs to the Section Physical Chemistry)
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<p>The schematic of differences in equilibrium hydrate formation. The bule background is the liquid phase, and the white background is the gas phase.</p>
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<p>Schematic diagram of the prediction of <span class="html-italic">P<sub>eq.</sub></span> <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>y</mi> </mrow> <mrow> <mi>i</mi> </mrow> </msub> </mrow> </semantics></math> is the mole fractions of gases in the gas phase and <span class="html-italic">w</span> is the mass fraction of THF.</p>
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<p>Equilibrium hydrate formation conditions with experimental, literature, and predicted data for CH<sub>4</sub>-THF-water system. (Lee et al., 2012) stands for [<a href="#B21-molecules-29-04827" class="html-bibr">21</a>] and (Hassan et al., 2023) stands for [<a href="#B35-molecules-29-04827" class="html-bibr">35</a>].</p>
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<p>Equilibrium hydrate formation conditions with experimental and predicted data for CH4 and HNG1-HNG3 in the presence of 5 wt% THF.</p>
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<p>Equilibrium hydrate formation conditions with experimental, literature, and predicted data for CH4 and HNG1-HNG3 in the presence of 10 wt% THF.</p>
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<p>Equilibrium hydrate formation conditions with experimental data, literature, and predicted data for CH4 and HNG1-HNG3 in the presence of 19 wt% THF.</p>
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<p>Equilibrium hydrate formation conditions with experimental data and predicted data for HNG4 in the presence of 5, 10, and 19 wt% THF.</p>
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<p>The differences in <span class="html-italic">P<sub>eq</sub></span> between pure CH<sub>4</sub> and HNG1–HNG3 in the presence of THF.</p>
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<p>The experimental results for CH<sub>4</sub> and HNGs in the presence of different concentrations of THF.</p>
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<p>Schematic diagram of experimental apparatus for the measurements of the equilibrium hydrate formation conditions.</p>
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<p>The experimental procedure of investigating the <span class="html-italic">P<sub>eq</sub></span> through the isothermal pressure search method.</p>
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<p>The pressure–temperature flash procedure for calculating <math display="inline"><semantics> <mrow> <msubsup> <mrow> <mi>P</mi> </mrow> <mrow> <mn>2</mn> </mrow> <mrow> <mi>s</mi> <mi>a</mi> <mi>t</mi> </mrow> </msubsup> </mrow> </semantics></math>. <span class="html-italic">f<sup>G</sup></span> and <span class="html-italic">f<sup>L</sup></span> are the fugacity of THF in gas and liquid phase in a pure THF system.</p>
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9 pages, 1688 KiB  
Article
A Molecular Dynamics Study of the Influence of Low-Dosage Methanol on Hydrate Formation in Seawater and Pure Water Metastable Solutions of Methane
by Rodion V. Belosludov, Kirill V. Gets, Ravil K. Zhdanov, Yulia Y. Bozhko and Vladimir R. Belosludov
J. Mar. Sci. Eng. 2024, 12(9), 1626; https://doi.org/10.3390/jmse12091626 - 12 Sep 2024
Viewed by 558
Abstract
The behavior of low concentrations of methanol (0.5 and 1.0 wt% of water) as a promoter for hydrate formation in seawater or pure water metastable solutions of methane was investigated using the classical molecular dynamics method at moderate temperature and pressure. The influence [...] Read more.
The behavior of low concentrations of methanol (0.5 and 1.0 wt% of water) as a promoter for hydrate formation in seawater or pure water metastable solutions of methane was investigated using the classical molecular dynamics method at moderate temperature and pressure. The influence of methanol on the dynamics of the re-arrangement of the hydrogen bond network in seawater and pure water solutions of methane was studied by calculating order parameters of the tetrahedral environment and intermolecular torsion angles for water molecules, as well as by calculating the number of hydrogen bonds, hydrate, and hydrate-like cavities. It was found that hydrate nucleation can be considered a collective process in which the rate of hydrate growth is faster in systems with low concentrations of methanol, and confident hydrate growth begins earlier in a metastable solution without sea salt with a small amount of methanol than in systems without methanol. Full article
(This article belongs to the Special Issue Analytical and Experimental Technology for Marine Gas Hydrate)
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<p>Time dependence of the averaged values of the normalized numbers of (<b>a</b>) hydrogen bonds <span class="html-italic">N<sub>H-bond</sub>/N<sub>Mol</sub></span> and (<b>b</b>) long-lived hydrogen bonds <span class="html-italic">N<sub>LLHb</sub>/N<sub>Mol</sub></span> in pure water and seawater-based solutions.</p>
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<p>Time dependence of the averaged values of the order parameters (<b>a</b>) <span class="html-italic">F</span><sub>3</sub> and (<b>b</b>) <span class="html-italic">F</span><sub>4</sub> in methane solutions based on pure water and seawater.</p>
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<p>(<b>a</b>) Time dependence of the average number of cavities <span class="html-italic">N<sub>Cav</sub></span> in solutions based on pure water and seawater. (<b>b</b>) Spatial distribution of cavities: 5<sup>12</sup> (orange), 5<sup>12</sup>6<sup>2</sup> (red), 5<sup>12</sup>6<sup>3</sup>, and 5<sup>12</sup>6<sup>4</sup> (blue), as well as topologically similar cavities (light blue), Na<sup>+</sup> ions (cyan), Cl<sup>−</sup> ions (pink), methane (yellow) and methanol (gray).</p>
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14 pages, 2152 KiB  
Article
Experimental and Modeling Study on Methane Hydrate Equilibrium Conditions in the Presence of Inorganic Salts
by Qiang Fu, Mingqiang Chen, Weixin Pang, Zhen Xu, Zengqi Liu, Huiyun Wen and Xin Lei
Molecules 2024, 29(15), 3702; https://doi.org/10.3390/molecules29153702 - 5 Aug 2024
Viewed by 840
Abstract
The aim of this study was to determine the influence of four inorganic salts, KCl, NaCl, KBr and NaBr, on the thermodynamic conditions of methane hydrate formation. In order to achieve this, the vapor–liquid water-hydrate (VLWH) equilibrium conditions of methane (CH [...] Read more.
The aim of this study was to determine the influence of four inorganic salts, KCl, NaCl, KBr and NaBr, on the thermodynamic conditions of methane hydrate formation. In order to achieve this, the vapor–liquid water-hydrate (VLWH) equilibrium conditions of methane (CH4) hydrate were measured in the temperature range of 274.15 K–282.15 K by the isothermal pressure search method. The results demonstrated that, in comparison with deionized water, the four inorganic salts exhibited a significant thermodynamic inhibition on CH4 hydrate. Furthermore, the inhibitory effect of Na+ on methane hydrate is more pronounced than that of K+, where there is no discernible difference between Cl and Br. The dissociation enthalpy (Hdiss) of CH4 hydrate in the four inorganic salt solutions is comparable to that of deionized water, indicating that the inorganic salt does not participate in the formation of hydrate crystals. The Chen–Guo hydrate model and N–NRTL–NRF activity model were employed to forecast the equilibrium conditions of CH4 hydrate in electrolyte solution. The absolute relative deviation (AARD) between the predicted and experimental values were 1.24%, 1.08%, 1.18% and 1.21%, respectively. The model demonstrated satisfactory universality and accuracy. This study presents a novel approach to elucidating the mechanism and model prediction of inorganic salt inhibition of hydrate. Full article
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Graphical abstract
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<p>Thermodynamic consistency of CH<sub>4</sub> hydrate formation conditions in the presence of inorganic salts. (<b>a</b>) VL<sub>W</sub>H of CH<sub>4</sub> hydrate in different inorganic salt solutions. (<b>b</b>) Linear relationship between ln(<span class="html-italic">P</span>) and 1/<span class="html-italic">T</span> in different inorganic salt solutions. (<b>c</b>) The result of linear consistency assessment. (<b>d</b>) The result of <math display="inline"><semantics> <mrow> <mo>∆</mo> <msub> <mrow> <mi>H</mi> </mrow> <mrow> <mi>d</mi> <mi>i</mi> <mi>s</mi> <mi>s</mi> </mrow> </msub> </mrow> </semantics></math> consistency assessment. (<b>e</b>) The values of <math display="inline"><semantics> <mrow> <mstyle scriptlevel="0" displaystyle="true"> <mfrac> <mrow> <mo>∆</mo> <mi>T</mi> </mrow> <mrow> <msub> <mrow> <mi>T</mi> </mrow> <mrow> <mn>0</mn> </mrow> </msub> <mi>T</mi> </mrow> </mfrac> </mstyle> </mrow> </semantics></math> in different inorganic salt solutions. (<b>f</b>) The result of <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>a</mi> </mrow> <mrow> <mi>w</mi> </mrow> </msub> </mrow> </semantics></math> consistency assessment.</p>
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<p>∆P values of CH<sub>4</sub> hydrate in the presence of inorganic salts at different conditions.</p>
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<p>Experimental and predicted results of VL<sub>W</sub>H equilibrium conditions in different solutions. (<b>a</b>) Experimental and predicted results in KCl and NaCl solutions. (<b>b</b>) Experimental and predicted results in KBr and NaBr solutions.</p>
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<p>Schematic diagram of the experimental setup.</p>
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18 pages, 10772 KiB  
Article
Properties and Model of Pore-Scale Methane Displacing Water in Hydrate-Bearing Sediments
by Dongfeng Ge, Jicheng Zhang, Youxun Cao, Cheng Liu, Bin Wu, Haotian Chu, Jialin Lu and Wentao Li
J. Mar. Sci. Eng. 2024, 12(8), 1320; https://doi.org/10.3390/jmse12081320 - 5 Aug 2024
Cited by 1 | Viewed by 779
Abstract
The flow characteristics of methane and water in sedimentary layers are important factors that affect the beneficial exploitation of marine hydrates. To study the influencing factors of methane drive-off water processes in porous media, we constructed nonhomogeneous geometric models using MATLAB 2020a random [...] Read more.
The flow characteristics of methane and water in sedimentary layers are important factors that affect the beneficial exploitation of marine hydrates. To study the influencing factors of methane drive-off water processes in porous media, we constructed nonhomogeneous geometric models using MATLAB 2020a random distribution functions. We developed a mathematical model of gas–water two-phase flow based on the Navier–Stokes equation. The gas-driven water processes in porous media were described using the level-set method and solved through the finite element method. We investigated the effects of the nonhomogeneous structure of pore media, wettability, and repulsion rate on gas-driven water channeling. The nonhomogeneity of the pore medium is the most critical factor influencing the flow. The size of the throat within the hydrophilic environment determines the level of difficulty of gas-driven water flow. In regions with a high concentration of narrow passages, the formation of extensive air-locked areas is more likely, leading to a decrease in the efficiency of the flow channel. In the gas–water drive process, water saturation changes over time according to a negative exponential function relationship. The more hydrophilic the pore medium, the more difficult the gas-phase drive becomes, and this correlation is particularly noticeable at higher drive rates. The significant pressure differentials caused by the high drive-off velocities lead to quicker methane breakthroughs. Instantaneous flow rates at narrow throats can be up to two orders of magnitude higher than average. Additionally, there is a susceptibility to vortex flow in the area where the throat connects to the orifice. The results of this study can enhance our understanding of gas–water two-phase flow in porous media and help commercialize the exploitation of clean energy in the deep ocean. Full article
(This article belongs to the Special Issue Exploration and Drilling Technology of Deep-Sea Natural Gas Hydrate)
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<p>Hydrate mining and pore-scale two-phase flow characterization.</p>
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<p>The construction process of random distribution pore model.</p>
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<p>Extraction of geometric feature information of porous media: (<b>a</b>) Pore-scale heterogeneous geometric model; (<b>b</b>) binarization processing; and (<b>c</b>) geometric characteristics of pore structure.</p>
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<p>Hydrate mining and pore frequency distribution.</p>
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<p>Comparison of dynamic contact angle with simulation results.</p>
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<p>Flow diagram and local mesh division of heterogeneous model.</p>
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<p>The volume fraction and pressure distribution of gas drive the water process in porous media.</p>
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<p>The change in water saturation with time in the upper, middle, and bottom regions.</p>
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<p>The frequency distribution of pore model throat width: (<b>a</b>) upper; (<b>b</b>) middle; and (<b>c</b>) bottom.</p>
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<p>Phase diagram distribution of the breakthrough and the final moment when the inlet displacement velocity is 3.5 mm/s.</p>
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<p>Phase diagram distribution of the breakthrough and the final moment when the inlet displacement velocity is 17.5 mm/s.</p>
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<p>Relationship between water saturation changes and methane release in porous media with varying wettability under two different flow rates. (<b>a</b>) The entrance interface moves at a speed of 3.5 mm/s. (<b>b</b>) The entrance interface moves at a speed of 17.5 mm/s.</p>
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<p>Comparison of parameters for water saturation fitting curves. (<b>a</b>) Fitting the relationship between changes in parameter <span class="html-italic">A</span>; (<b>b</b>) fitting the relationship between changes in parameter <span class="html-italic">B</span>.</p>
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<p>Cloud diagram of the two-phase and pressure distribution at the time of breakthrough.</p>
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<p>Cloud diagram of the two-phase and pressure distribution at the time of end time.</p>
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<p>The influence of displacement speed on water saturation.</p>
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<p>Transient flow characteristics in local areas.</p>
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15 pages, 3826 KiB  
Article
Data Acquisition of Logging While Drilling at the Newly Discovered Gas Hydrate Reservoir in Hyuganada Sea, Japan
by Toshinori Imai, Than Tin Aung, Akira Fujimoto, Satoshi Ohtsuki, Kotaro Tano, Shuhei Otomo, Naoyuki Shimoda, Takanao Yoshii, Ryugen Sakata, Jun Yoneda and Kiyofumi Suzuki
Energies 2024, 17(15), 3815; https://doi.org/10.3390/en17153815 - 2 Aug 2024
Viewed by 757
Abstract
From December 2021 to January 2022, MH21-S conducted an exploratory drilling campaign using logging-while-drilling tools to confirm the methane hydrate concentrated zone (MHCZ) for future offshore production tests. In a preliminary screening study using seismic survey data, methane hydrate (MH) prospects have been [...] Read more.
From December 2021 to January 2022, MH21-S conducted an exploratory drilling campaign using logging-while-drilling tools to confirm the methane hydrate concentrated zone (MHCZ) for future offshore production tests. In a preliminary screening study using seismic survey data, methane hydrate (MH) prospects have been extracted in The Hyuganada Sea, offshore Kyushu. In the exploration drilling site, a previous study had reported that MH prospects were inferred from four indices. We have selected two MH prospects: one with an anticlinal structure and another with a planus structure. As a result of drilling, a resistivity value higher than 3 Ω·m, which was a criterion for interpreting MHCZs from log data, was confirmed at a depth of 336–376 mBSF in the prospect with an anticlinal structure. The MH saturation calculated using Archie’s formula was 12–95% (average saturation of 70%). The average density porosity at the same depth was 52%. P-wave velocities were faster than the upper layers. Compared with those of the MHCZ at Daini Atsumi Knoll, the MH saturation is expected to be higher, the spread of some strong-amplitude reflectors has been interpreted from seismic survey data, and the potential MH resources in this area can be sufficiently expected. Full article
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<p>Outline of the key tasks in an offshore survey using short-term flow tests.</p>
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<p>General tectonic setting and location map of the Hyuganada sea survey area. The left shows an enlarged view of the framed places.</p>
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<p>Integrated stratigraphy of the surrounding land area and interpretation unit. Stratigraphy and lithology are based on the studies by Oda et al. [<a href="#B3-energies-17-03815" class="html-bibr">3</a>], Kato [<a href="#B4-energies-17-03815" class="html-bibr">4</a>], Nakamura et al. [<a href="#B8-energies-17-03815" class="html-bibr">8</a>], Takashimizu [<a href="#B10-energies-17-03815" class="html-bibr">10</a>], Suzuki [<a href="#B13-energies-17-03815" class="html-bibr">13</a>], Torii and Oda [<a href="#B15-energies-17-03815" class="html-bibr">15</a>], and Iwatani et al. [<a href="#B16-energies-17-03815" class="html-bibr">16</a>]. The planktonic foraminiferal fossil zone is based on the study by Chunllan et al. [<a href="#B17-energies-17-03815" class="html-bibr">17</a>].</p>
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<p>Interpreted four strong-amplitude reflectors indicated by the white double-headed arrow, BSR (above the red arrows), and high-velocity anomaly at the HY1-LM1 drilling site.</p>
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<p>Interpreted strong-amplitude reflectors indicated by the white double-headed arrow, BSR (above the red arrows), and high-velocity anomaly at the HY1-L2 drilling site.</p>
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<p>Acquired LWD data at the HY1-LM1 drilling site. Tracks from left to right represent (1) the measured depth (mBSF), (2) natural gamma ray (GRMA) and caliper (UCAV_EC), (3) bit, shallow, medium, deep, and extra-deep resistivity (RES_BIT, BS, BM, BD, and BX), (4) thermal neutron porosity (BPHI_EC) and bulk density (RHON_EC), (5) grain sigma (SIGE) and sigma formation (SIFA_EC), (6) elemental spectroscopy (quartz–feldspar–mica weight fraction: WQFM_EC; clay weight fraction: WCLA_EC; calcite weight fraction: WCLC_EC; pyrite weight fraction: WPYR_EC), (7) NMR T2 distribution, (8) bound fluid volume (BFV_PV) and magnetic resonance porosity (MRP_PV), (9) Timur Coates and Schlumberger Doll Research permeabilities based on the T2 distribution and MRP (KTIM_PV and KSDR_PV), (10) compressional (DTCO) and shear slowness (DTSH), and (11) ultrahigh-resolution resistivity image. The green shading in the resistivity track denotes that the resistivity value is lower than 3 Ω·m. Orange represents the target depth.</p>
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<p>Acquired LWD data at the HY1-L2 drilling site. The track is the same as that in <a href="#energies-17-03815-f006" class="html-fig">Figure 6</a>.</p>
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<p>Detailed log response at the HY1-L2 drilling site. The rightmost track is the MH saturation using Archie’s method. In Archie’s method, a = 1, n = 2, and m = 1.8 were applied.</p>
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<p>Conventional coring well (HY1-GT) location and coring depth.</p>
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