A novel hybrid energy system for hydrogen production and storage in a depleted oil reservoir

Song, Hongqing; Guo, Honghao; Wang, Yuhe; Lao, Junming; Zhu, Huayin; Tang, Luping; Li, Xuan

doi:10.1016/j.ijhydene.2020.09.081

Cited by 48 publications

(7 citation statements)

References 41 publications

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“…e microfluidic chip was initially saturated by the oil. e injection rate was set in the microinjection pump corresponding to the injection rate at the inlet of microfluidic chip [12,[50][51][52][53][54].…”

Section: Injection Experiments Schemementioning

confidence: 99%

“…Due to the fact like this, the three-phase saturation distribution (TSD) is of great significance for a deeper understanding on the three-phase porous flow and better strategies for energy development and ecological conservation [1,[6][7][8][9]. Gas production and flooding, especially during coal mining [10][11][12], have a nonnegligible impact on brine storage in mining area [13][14][15][16]. In specific, the residual oil in micropores is conducive to plug the predominant pathways for a better brine storage [17,18], while the gas flooding probably displaces the brine and oil in micropores causing brine transfer, even leakage [4,[19][20][21][22].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Research on Three-Phase Saturation Distribution Based on Microfluidic Visualization Experiment: A Case Study of Ling Xin Mining Area

Hu¹,

Huang²,

Song³

et al. 2022

Geofluids

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Flow characteristics and phase distribution of concentrated brine storage in mining area have been core factors linking to the leakage risk assessment and ecological evaluation. Notably, saturation plays a crucial role in impacting the flow characteristics and distribution of brine, while the existence of oil left by mining machines and original reservoir and gas produced from coal bed gas and air has complicated the issue. In this work, we conducted the microfluidic visualization experiments to reveal the saturation distribution during brine storage in mining area. We applied machine learning model to extract saturation data from experimental images with over 95% accuracy. Eventually, we found that the existence of gas significantly impacts on the saturation distribution in micropores accounting for more than 80% contribution. We clarified that the gas production rate of median 200 μL/min impacts the least on saturation variation. Results in this research are of significance for deeper comprehension on three-phase saturation characteristics of concentrated brine storage in mining area.

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Section: Injection Experiments Schemementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Research on Three-Phase Saturation Distribution Based on Microfluidic Visualization Experiment: A Case Study of Ling Xin Mining Area

Hu¹,

Huang²,

Song³

et al. 2022

Geofluids

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“…It can be found that the share of unconventional gas supply in China has been increasing, accounting for nearly 15% of the natural gas supply in the market [11]. However, emerging energy is still in the development stage, whose supply is unstable and the randomness characteristic is obvious, leading to the prediction method of conventional energy inapplicable to be adopted [12][13][14][15]. First of all, diverse from conventional energy, emerging energy supply demonstrates the characteristics of nonlinearity and high noise.…”

Section: Introductionmentioning

confidence: 99%

Reliable Prediction on Emerging Energy Supply for National Sustainability and Stability: A Case Study on Coal Bed Gas Supply in China Based on the Dual-LSTM Model

Kang

Lao

et al. 2021

IEEE Access

Self Cite

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Aiming to prevent from the imbalance between supply and demand of energy in which the share of emerging type is rapidly increasing, to predict the supply of emerging energy reliably is significant. However, the expected distribution uncertain and high-noise characteristics of emerging energy supply impede the reliable prediction. The Dual-LSTM (Long Short-Term Memory) model was constructed for the characteristic extracting and effective prediction of the expected distribution uncertain high-noise emerging energy supply time series. A case study on coal bed gas supply in China was conducted. Results showed that the Dual-LSTM model effectively solved the the problem of superfluous and non-quantifiable variables in the prediction of coal bed gas supply and extracted the statistical characteristics of expected distribution uncertain and high-noise data samples effectively with a relative error major less than 5% in short-term. Besides, the Dual-LSTM model has a significantly higher prediction accuracy while comparing with ARIMA model and original LSTM model. Ultimately, it is predicted that the year-on-year growth rates of coal bed gas supply of China from January to September, 2021, approximately maintains 75% in average based on the Dual-LSTM model. The Dual-LSTM model provides a reliable statistical model for policy decision to maintain national sustainability and stability. INDEX TERMSImproved deep learning model; Uncertain expected distribution high-noise sample; Emerging energy; Supply-demand stability; Reliable prediction; Time series analysis

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“…Currently, it faces two serious problems: reduced raw materials and environmental pollution resulting from its use. Based on its importance, researchers have attempted to investigate many methods to produce hydrogen and searching the raw materials [ 13 , 14 , 15 , 16 , 17 ].…”

Section: Introductionmentioning

confidence: 99%

Microwave-assisted catalysis of water-glycerol solutions for hydrogen production over NiO/zeolite catalyst

Husin

Mahidin

Pontas

et al. 2021

Heliyon

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In this study, glycerol as an abundant green feedstock was used as a hydrogen source to investigate the reaction of water-glycerol solution decomposition by microwave-assisted catalytic to produce hydrogen over NiO/zeolite catalyst. The catalyst was prepared by inception wetness and then characterized through X-ray diffraction (XRD), scanning electron microscopy (SEM), Energy diffraction X-ray (EDX), and transmission electron microscope (TEM) measurements. The conversion process of glycerol into hydrogen was performed in a fixed-bed microwave-assisted reactor. Effect of microwave power, NiO content, and feed flow rate (FFR) on glycerol conversion and hydrogen selectivity were studied. The results of XRD and EDX measurement showed that NiO crystalline exists on the catalyst sample. The particle size of NiO/zeolite was determined in the range of 30–300 nm, and the particle was found well dispersed on the zeolite surface as confirmed by TEM. Furthermore, the maximum conversion rate can achieve about 96.67 %, while the highest hydrogen production was found up to 73.5 % with the condition of 20% of NiO as an active site on natural zeolite. It was found that the NiO content of 20% gave the best glycerol conversion at the microwave power of 600 W and FFR 0.5 ml/min. Microwave-assisted catalytic irradiation of glycerol appears to be a promising candidate for the production of H 2 from an aqueous glycerol solution.

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A novel hybrid energy system for hydrogen production and storage in a depleted oil reservoir

Cited by 48 publications

References 41 publications

Research on Three-Phase Saturation Distribution Based on Microfluidic Visualization Experiment: A Case Study of Ling Xin Mining Area

Research on Three-Phase Saturation Distribution Based on Microfluidic Visualization Experiment: A Case Study of Ling Xin Mining Area

Reliable Prediction on Emerging Energy Supply for National Sustainability and Stability: A Case Study on Coal Bed Gas Supply in China Based on the Dual-LSTM Model

Microwave-assisted catalysis of water-glycerol solutions for hydrogen production over NiO/zeolite catalyst

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