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Advanced Intelligent Monitoring Methods in Exploitation of Deep Green Energy Resources

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A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Energy Sustainability".

Deadline for manuscript submissions: 30 November 2024 | Viewed by 6744

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Special Issue Editors

Prof. Dr. Jizhou Tang

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Guest Editor

School of Ocean and Earth Science, Tongji University, Shanghai 200092, China
Interests: multi-physics coupling; rock mechanics; intelligent monitoring

Prof. Dr. Yuwei Li

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Guest Editor

School of Environment, Liaoning University, Shenyang 110036, China
Interests: hydraulic fracturing; rock mechanics

Dr. Xiao Ouyang

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Guest Editor

College of Nuclear Science and Technology, Beijing Normal University, Beijing, China
Interests: radiation detection; scintillator detection; experimental nuclear physics

Special Issue Information

Dear Colleagues,

From a global perspective, achieving peak carbon dioxide emissions and carbon neutrality has become an impending mission for the shared future of the human community. The majority of the nations around the world are advocating for the transition to clean and low-carbon energy; thus, marching deep into the earth and seeking green energy resources is considered as a rite of passage for this energy transition.

Deep green energy resources, which come from the deep earth or deep sea, include geothermal energy, shale gas, coal-bed methane (CBM), natural gas hydrate (NGH), etc. Spatiotemporal variabilities and heterogeneities exist in deep formations and give rise to different rock physical and mechanical properties and intangibly increase developing difficulties. Conventional monitoring approaches become inapplicable from the aspects of formation description, stimulation performance evaluation, and production forecasting. Hence, advanced intelligent monitoring methods are urgently needed to harvest green energy and lower costs and with less environmental risk. In addition, the efficient exploitation of deep green energy resources can be facilitated by the use of carbon capture, utilization, and storage (CCUS) concepts or the implementation of underground hydrogen storage (UHS) and the intelligent monitoring of fluid (i.e., CO₂, H₂) migration becomes paramount to avoiding geological risks such as fluid leakage and fault activation. Moreover, research on how to make systems for mining deep uranium ore greener and related intelligent monitoring approaches is also welcome.

This Special Issue aims to collect high-quality review and original research articles focusing on the advanced intelligent monitoring technology applied to the exploitation of deep green energy resources from deep earth or deep sea. Submissions about numerical simulation, physical experiments, and theoretical modeling are welcome.

Potential topics include but are not limited to the following:

Intelligent monitoring of fluid migration in CCUS applications for enhancing recovery of deep green energy resources;
Intelligent monitoring of geological hazards during the exploitation of deep green energy resources;
Intelligent monitoring of drained rock volume and stimulated reservoir volume in unconventional reservoirs;
Intelligent monitoring of permeable channels’ instability during NGH production;
Intelligent monitoring of well performance for geothermal energy.

Prof. Dr. Jizhou Tang
Prof. Dr. Yuwei Li
Dr. Xiao Ouyang
Guest Editors

Manuscript Submission Information

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Keywords

intelligent monitoring
deep green energy
CCUS
hydrogen storage
geological hazards

Published Papers (5 papers)

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Research

18 pages, 7380 KiB

Open AccessArticle

A Logging Data Based Method for Evaluating the Fracability of a Gas Storage in Eastern China

by Famu Huang, Lei Huang, Ziheng Zhu, Min Zhang, Wenpeng Zhang and Xingwen Jiang

Sustainability 2024, 16(8), 3165; https://doi.org/10.3390/su16083165 - 10 Apr 2024

Viewed by 407

Abstract

Underground storage of natural gas has the characteristics of clean and low-carbon, and has the ability to provide a sustainable and stable supply. It is a very high-quality green energy that can increase the storage efficiency of gas storage through fracturing, achieving the sustainable development goal of “Carbon Peaking and Carbon Neutrality”. To improve the storage efficiency of natural gas, it is necessary to carry out refracturing. Moreover, it is of great significance to estimate the fracability of the potential refracturing formation. At present, research on fracability is mainly based on qualitative characterization or quantitative evaluation based on rock mechanics and fracturing construction parameters, which cannot fully reflect the rock composition and structure of each stage. Firstly, based on logging data, this paper analyzes the evolution laws of strain energy such as elastic properties, pre-peak dissipation energy, and post-peak fracture energy during the transition of rock materials from plastic deformation to brittle fracture from an energy perspective, and determines the key energy that affects the brittle characteristics of rocks. Secondly, a brittleness index evaluation approach has been established that can comprehensively reflect the mechanical properties of rocks during pre-peak deformation and post-peak damage stages. In addition, this article focuses on the impact of a reservoir stratigraphic environment by combining the influence of geo-stresses with the rock brittleness index, and proposes a new method for evaluating reservoir fracability. Finally, this paper conducts a study on the fracability evaluation of three wells in a gas storage facility in Eastern China. The results indicate that low modulus and fracability index are beneficial for fracturing, thereby improving the gas production and peak shaving ability of gas storage. Full article

(This article belongs to the Special Issue Advanced Intelligent Monitoring Methods in Exploitation of Deep Green Energy Resources)

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12 pages, 1403 KiB

Open AccessArticle

Environmental Effects of Driver Distraction at Traffic Lights: Mobile Phone Use

by Kadir Diler Alemdar, Merve Kayacı Çodur, Muhammed Yasin Codur and Furkan Uysal

Sustainability 2023, 15(20), 15056; https://doi.org/10.3390/su152015056 - 19 Oct 2023

Cited by 2 | Viewed by 952

Abstract

The transportation demands of people are increasing day by day depending on the population, and the number of vehicles in traffic is causing various problems. To meet the energy needs of vehicles, there is a huge burden on countries in terms of fossil fuels. In addition, the use of fossil fuels in vehicles has a serious impact on environmental pollution. Various studies have been carried out to prevent unnecessary fuel consumption and emissions. Behavior of drivers, who are important components of traffic, are carefully examined in the context of this subject. Driver distraction causes various environmental problems as well as traffic safety issues. In this study, the negative situations that arise as a result of drivers waiting at traffic lights dealing with their mobile phones are discussed. Roadside observations are made for drivers at considered intersections in Erzurum Province, Turkey. As a result of these observations, delays at selected intersections due to mobile phone use are calculated. Unnecessary fuel consumption and emissions due to delays are also analyzed. An annual fuel consumption of approximately 177.025 L and emissions of 0.294 (kg) NO_X and 251.68 (kg) CO₂ occur at only selected intersections. In addition, a second roadside observation is made in order to analyze driver behavior and the most preferred type of mobile phone usage is determined. It is seen that drivers mostly exhibit the “Talking” and “Touchscreen” action classes. Considering the economic conditions and environmental pollution sensitivities of countries, attempts have been made to raise awareness about fuel consumption and emissions at traffic lights. Full article

(This article belongs to the Special Issue Advanced Intelligent Monitoring Methods in Exploitation of Deep Green Energy Resources)

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17 pages, 6566 KiB

Open AccessArticle

Investigation of Mechanical Properties Evolution and Crack Initiation Mechanisms of Deep Carbonate Rocks Affected by Acid Erosion

by Weihua Chen, Jian Yang, Li Li, Hancheng Wang, Lei Huang, Yucheng Jia, Qiuyun Hu, Xingwen Jiang and Jizhou Tang

Sustainability 2023, 15(15), 11807; https://doi.org/10.3390/su151511807 - 1 Aug 2023

Cited by 2 | Viewed by 956

Abstract

Deep tight-gas carbonate reservoirs have huge reserves, with the advantages of having clean and low-carbon characteristics in addition to being a sustainable and stable supply which leads to very high-quality green energy, despite its difficult extraction. The reservoirs are usually modified using acid fracturing before exploitation, but due to acid erosion, the continuous alteration of the mechanical properties of the reservoir rocks complicates the process of predicting the crack initiation pressure. This paper aims to address the difficulties in predicting the crack initiation pressure by conducting a series of acid-etching experiments on carbonate rock samples subjected to splitting and uniaxial compression tests. By examining the variations in the elastic modulus, Poisson’s ratio, tensile strength under distinct acid systems, and acid-etching durations and temperatures, a quantified mathematical model was developed. This model was integrated into a fracture-initiation pressure prediction framework, resulting in a practical and user-friendly tool for the acid fracture-initiation pressure prediction model, which was further demonstrated through field engineering validation. The findings reveal that the elastic modulus, Poisson’s ratio, and tensile strength of carbonate rocks exhibit an inverse relationship with acid-etching time and temperature. Extended acid fracturing durations and high reservoir temperatures are conducive to acid-fracturing transformations. The fracture-initiation pressure-prediction-model analysis disclosed that, compared to the gelled acid, the diverting acid demonstrates a more pronounced reduction in the reservoir fracture pressure under high-temperature and short-duration conditions. An acid system preference diagram was constructed to provide a theoretical foundation for practical engineering applications, delivering valuable insights for optimizing acid fracturing treatments in carbonate reservoirs to provide a boost for the green energy extraction of tight gas. Full article

(This article belongs to the Special Issue Advanced Intelligent Monitoring Methods in Exploitation of Deep Green Energy Resources)

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15 pages, 15837 KiB

Open AccessArticle

An Approach for the Classification of Rock Types Using Machine Learning of Core and Log Data

by Yihan Xing, Huiting Yang and Wei Yu

Sustainability 2023, 15(11), 8868; https://doi.org/10.3390/su15118868 - 31 May 2023

Cited by 2 | Viewed by 1743

Abstract

Classifying rocks based on core data is the most common method used by geologists. However, due to factors such as drilling costs, it is impossible to obtain core samples from all wells, which poses challenges for the accurate identification of rocks. In this study, the authors demonstrated the application of an explainable machine-learning workflow using core and log data to identify rock types. The rock type is determined utilizing the flow zone index (FZI) method using core data first, and then based on the collection, collation, and cleaning of well log data, four supervised learning techniques were used to correlate well log data with rock types, and learning and prediction models were constructed. The optimal machine learning algorithm for the classification of rocks is selected based on a 10-fold cross-test and a comparison of AUC (area under curve) values. The accuracy rate of the results indicates that the proposed method can greatly improve the accuracy of the classification of rocks. SHapley Additive exPlanations (SHAP) was used to rank the importance of the various well logs used as input variables for the prediction of rock types and provides both local and global sensitivities, enabling the interpretation of prediction models and solving the “black box” problem with associated machine learning algorithms. The results of this study demonstrated that the proposed method can reliably predict rock types based on well log data and can solve hard problems in geological research. Furthermore, the method can provide consistent well log interpretation arising from the lack of core data while providing a powerful tool for well trajectory optimization. Finally, the system can aid with the selection of intervals to be completed and/or perforated. Full article

(This article belongs to the Special Issue Advanced Intelligent Monitoring Methods in Exploitation of Deep Green Energy Resources)

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19 pages, 9657 KiB

Open AccessArticle

Study on the Hydraulic Fracturing Failure Behaviour of Granite and Its Comparison with Gas Fracturing

by Ning Li, Heping Xie, Ziqi Gao and Cunbao Li

Sustainability 2022, 14(21), 14593; https://doi.org/10.3390/su142114593 - 6 Nov 2022

Cited by 4 | Viewed by 1722

Abstract

Efficient technology is needed to realise reservoir stimulation for deep geothermal energy exploitation. However, the main control parameters of traditional hydraulic fracturing technology are not clear, as well as their coupling effects; besides, the damage mechanism of novel gas fracturing technology is still not determined, which restricts the mining of hot dry rock resources. Therefore, through a series of true triaxial hydraulic fracturing tests, this paper explores the coupling effect of horizontal stress difference and injection rate on hydraulic fracturing; then, the cohesive element is used to establish hydraulic fracturing and gas fracturing models under the same test conditions. Differences in fracture width and fracture network morphology between the two technologies were compared, and the rock-breaking effects in in-situ reservoirs were analysed. The results show that the breakdown pressure of granite increases gradually with the increase of injection rate, at the small horizontal stress difference; but this trend is opposite at the large horizontal stress difference. Under a higher horizontal stress difference, the increment of the maximum fracture width of gas fracturing becomes larger than that of hydraulic fracturing after increasing the injection rate. When the fracturing cluster spacing is reduced, the fracture width and length of gas fracturing gradually become larger than those of hydraulic fracturing; when the injection rate is increased, the hydraulic fracturing network becomes more complex than gas fracturing. This study can provide useful information for applying hydraulic fracturing and gas fracturing in deep geothermal reservoirs. Full article

(This article belongs to the Special Issue Advanced Intelligent Monitoring Methods in Exploitation of Deep Green Energy Resources)

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