Hasil untuk "Gas industry"

H. Hartnagel

Qian Wang, Zixuan Yang, Chenxi Ye et al.

Md. Nasir Uddin, Feng Wang

The aviation industry is responsible for approximately 2–3% of worldwide CO₂ emissions and is increasingly subjected to demands for the attainment of net-zero emissions targets by the year 2050. Traditional fossil jet fuels, which exhibit lifecycle emissions of approximately 89 kg CO₂-eq/GJ, play a substantial role in exacerbating climate change, contributing to local air pollution, and fostering energy insecurity. In contrast, Sustainable Aviation Fuels (SAFs) derived from renewable feedstocks, including biomass, municipal solid waste, algae, or through CO₂- and H₂-based power-to-liquid (PtL) represent a pivotal solution for the immediate future. SAFs generally accomplish lifecycle greenhouse gas (GHG) reductions of 50–80% (≈20–30 kg CO₂-eq/GJ), possess reduced sulfur and aromatic content, and markedly diminish particulate emissions, thus alleviating both climatic and health-related repercussions. In addition to their environmental advantages, SAFs promote energy diversification, lessen reliance on unstable fossil fuel markets, and invigorate regional economies, with projections indicating the creation of up to one million green jobs by 2030. This comprehensive review synthesizes current knowledge on SAF sustainability advantages compared to conventional aviation fuels, identifying critical barriers to large-scale deployment and proposing integrated solutions that combine technological innovation, supportive policy frameworks, and international collaboration to accelerate the aviation industry’s sustainable transformation.

LIANG Yukai, ZHENG Hua’an, ZENG Qianyi, SONG Jifeng, TIAN Zhongyuan, JIANG Shu

The Yinggehai Basin is a key area for natural gas exploration in the western South China Sea. In recent years, commercially viable gas formations and abundant high-temperature formation water have been discovered in the Huangliu Formation of the X gasfield, indicating promising prospects for hydrothermal geothermal resource development. However, geothermal resource evaluation for this system are still lacking. Taking the X gasfield in the Yinggehai Basin as a case study, a heterogeneous 3D geothermal reservoir geological model was constructed by integrating drilling, logging, core, and seismic data. Key properties such as porosity, permeability, temperature, and water saturation were modeled and assigned in a gridded format. During the model construction, multiple stochastic simulations and seismic attribute constraints were introduced to enhance the rationality and accuracy of the spatial distribution of geological parameters. Based on this model, the volumetric method was applied to evaluate the geothermal resource potential of the Huangliu Formation, and the main geothermal resource-rich zones were identified. The results showed that the reservoir temperatures in the Huangliu Formation ranged from 167.0 ℃ to 197.6 ℃, with an average of 186.5 ℃, indicating favorable conditions for high-temperature geothermal development. The total geothermal resource was estimated to be 3.84×10¹⁶ kJ, equivalent to 1 310.5×10⁶ t of standard coal, with fine sandstone serving as the main reservoir lithology. Assuming a recovery coefficient of 8%, the recoverable resource was approximately 0.31×1016 kJ, equivalent to standard coal of 104.8×10⁶ t. The spatial distribution of resources revealed two major geothermal-rich zones, both located in the sand bodies of deepwater turbidite channels of the Huangliu Formation. These zones were characterized by high temperatures, favorable physical properties, and well-developed fine sandstone, making them preferred areas for future development. Meanwhile, water saturation model analysis indicated high water content in both the eastern and western parts of the Huangliu Formation, suggesting the presence of isolated water bodies that could serve as potential development areas. The research results provide clearer insights into the distribution characteristics and development potential of geothermal resources in the Yinggehai Basin and offer important guidance for promoting the integrated development of offshore gas fields and geothermal energy in China.

Ali Akbari, Ali Karami, Yousef Kazemzadeh et al.

Abstract Hydraulic fracturing (HF) is a pivotal technique in the oil and gas industry, aimed at enhancing hydrocarbon recovery by increasing reservoir permeability through high-pressure fluid injection. Despite its effectiveness, traditional methods used to evaluate HF performance often struggle to capture the complex, nonlinear interactions among operational and geological parameters. This study presents a comprehensive machine learning (ML)-based framework to address this challenge by predicting HF efficiency using three widely used algorithms: Random Forest (RF), Support Vector Machine (SVM), and Neural Networks (NN). The novelty of this research lies in the combined application of advanced statistical characterization and comparative ML modeling over a large-scale dataset comprising 16,000 records. Key statistical metrics, including mean, median, variance, skewness, and quartiles, were used to explore data distribution and inform model training. Additionally, the study uniquely evaluates model robustness across varying train/test data ratios (from 0.1 to 0.9), providing deeper insights into algorithm performance stability. Among the tested models, RF outperformed others by achieving the highest coefficient of determination (R2 = 0.9804), alongside the lowest Mean Absolute Deviation (MAD) and Root Mean Square Error (RMSE) for both training and testing phases. These results demonstrate RF’s capability in handling complex subsurface data with high accuracy and low computational cost. The proposed framework not only enhances predictive accuracy in HF evaluation but also serves as a practical tool for optimizing fracturing design and decision-making in field operations. This integrated approach represents a step forward in applying artificial intelligence for data-driven reservoir engineering and contributes to the advancement of intelligent hydraulic fracturing practices in heterogeneous and data-rich environments.

PENG Yang, DAI Zhixiang, HU Zixia et al.

<b>[Objective]</b> China's backbone natural gas pipeline network comprises numerous large-diameter and long-distance pipelines.Periodic pigging operations play a crucial role in ensuring the safe, stable and efficient operation of these pipelines. However, since current pigging operations rely heavily on operator experience and the establishment of monitoring points, the inability to simulate pigging schemes in advance prevents accurate prediction of parameters such as the operating speed, position and arrival time of the pig, and pressure changes in the pipe. <b>[Methods]</b> To address this challenge, a mathematical model for dynamic prediction of the pigging process was constructed and put into practice according to the characteristics of actual pigging operations. Subsequently, the software for dynamic prediction of the pigging process was developed and applied to the actual pigging operations of several sections(A-B, B-C and D-E) of a designated pipeline for predicting the pigging time and pigging speed. <b>[Results]</b> The improved two-phase flow transient pigging model and the dynamic prediction software accurately forecast critical parameters, including the running speed, position and arrival time at each station of the pig during the pigging process; The accuracy of the dynamic pigging prediction technology and the reliability of the software were verified using the monitoring data of 52 actual pigging operations; And compared with actual measurements, the software's predictions had average relative errors of 5.94% for pigging time and 6.56% for pigging speed. <b>[Conclusion]</b> The utilization of the dynamic prediction technology and software enables efficient preparation of pigging operation schemes for natural gas pipelines, reduces manual workload, ensures pigging process safety, and enhances pipeline management intelligence.

ZHOU Zhaoheng, ZHOU Donglin, WANG Jianfu et al.

<b>[Objective]</b> Due to the scarcity of helium resources, insufficient production, high external dependence and single source, the security situation of helium resources in China is very severe. Utilizing salt caverns for helium storage is a significantly advantageous technology for large-scale helium storage that can effectively guarantee the helium supply capacity and improve helium security. However,China is devoid of underground salt cavern helium storage in operation, and related research and construction are still in the stage of initial development, requiring targeted feasibility and key technology researches. <b>[Methods]</b> Based on an investigation of helium resources and helium storage construction as well as China's experience in salt cavern gas storage construction, the feasibility of salt cavern helium storage construction in China was analyzed, and the suggestions on the development of key technologies for salt cavern helium storage were proposed,such as site evaluation, airtightness evaluation, cavern construction, storage construction, and helium injection and extraction. <b>[Results]</b> China is facing a high risk of helium supply disruption, necessitating the enlargement of reserve capacity. Salt cavern is suitable for large-scale helium storage for its satisfying performance in security and airtightness. The construction of salt cavern helium storage is feasible to increase China's helium reserve, giving that China has abundant salt cavern resources and a technological base for cavern construction. In addition, it is necessary to perform targeted research on key technologies for salt cavern helium storage construction, considering the geological conditions and helium resource conditions for storage construction in China differ from those in foreign countries. The salt mine in the southeast coastal area is close to the import and consumption of helium, and the transportation cost is low, so it can be used as the preferred storage site for the construction of salt cavern helium storage in China. <b>[Conclusion]</b> It is recommended to construct salt cavern helium storage in China in stages.At the early stage, 1 to 2 helium storage caverns should be constructed to explore and verify the construction technology of helium storage and ensure a stable supply of helium in China, after that more caverns should be constructed gradually to build up a strategic reserve that can meet China's helium demand for 5 to 10 years.

Tang T, Wang Y, Li T et al.

Tiantian Tang,1,2,&ast; Yujiao Wang,1,2,&ast; Taotao Li,1,2,&ast; Ding Liu,1,2 Kai Yang,1,2 Jing Sun,1,2 Yajun Shi,1,2 Dongyan Guo,1,2 Junbo Zou,1,2 Fengyun Bai,3 Ying Sun,3 Mei Wang,1,2 Xiaofei Zhang1,2 1Key Laboratory of Basic and New Drug Research in Chinese Medicine, Shaanxi University of Chinese Medicine, Xianyang, Shaanxi, People’s Republic of China; 2Shaanxi Provincial University Engineering Research Center of Chinese Medicine Aromatic Industry, Shaanxi University of Chinese Medicine, Xianyang, Shaanxi, People’s Republic of China; 3Shaanxi Dongtai Pharmaceutical Co., Ltd., Xianyang, Shaanxi, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Mei Wang; Xiaofei Zhang, Key Laboratory of Basic and New Drug Research in Chinese Medicine; Shaanxi Provincial University Engineering Research Center of Chinese Medicine Aromatic Industry, Shaanxi University of Chinese Medicine, Xianyang, Shaanxi, 712046, People’s Republic of China, Email wangmei0708@163.com; 2051028@sntcm.edu.cnObjective: To explore the mechanism and active components of the anti-colitis effects of myrrh essential oil (MEO).Methods: In this study, we investigated the anti-inflammatory effects and molecular mechanisms of MEO on dextran sulfate sodium (DSS)-induced colitis with in vitro cell experiments, RNA-seq (RNA Sequencing), Weighted gene co-expression network analysis (WGCNA), combined with “weighting coefficient” network pharmacology, as and in vivo pharmacodynamic experiments. A 3% DSS solution was used to induce colitis in BALB/c mice and MEO was administered orally. We performed gas chromatography-mass spectrometry (GC-MS) analysis of the MEO components. The disease activity index (DAI) was evaluated by observing body weight, fecal characteristics, and blood in the stool of mice. The levels of inflammatory cytokines (TNF-α and IL-1β) in mouse serum were measured using ELISA (Enzyme-linked immunosorbent assay) kits. Additionally, the expression of MAPK-related proteins (JNK, p-JNK, ERK, and p-ERK) in mouse colonic tissues was detected by Western blotting and immunohistochemistry.Results: MEO (0.0625– 0.125μg/g, p.o). significantly inhibited the expression of the inflammatory mediator Nitric oxide (NO) in lipopolysaccharide (LPS)-induced RAW264.7 macrophages. After treatment, there was a significant increase in body weight and alleviation of diarrhea and bloody stools in colitis mice. It also reduced inflammatory cell infiltration. Furthermore, it decreased the serum levels of TNF-α and IL-1β, and reduced the activity of p-JNK and p-ERK in the MAPK pathway.Conclusion: MEO relieved DSS-induced colitis by modulating the MAPK pathway. The experimental results indicate that the MAPK pathway might be inhibited by the synergistic effect of gamma-Muurolene, Curzerene, beta-Elemene, and Furanoeudesma 1.3-diene in MEO, which provides a novel idea for subsequent research and development of new anti-colitis drugs. Keywords: colitis, myrrh essential oil, MAPK signaling pathway, RNA sequencing, weighted gene co-expression network analysis

Shuvendhu Gupta, Amrat Pal Singh, Gurpreet Singh et al.

Sophisticated analytical instruments are used for quality evaluation and scientific validation to compliance the market demands. Recently, increase in demand of Curcuma longa has led to a high swing in small and medium food industry. The present review is devoted to an in-depth information on metabolite database of C. longa from different analytical techniques such as high-performance thin-layer chromatography (HPTLC), liquid chromatography-mass spectrometry, gas chromatography-mass spectrometry and nuclear magnetic resonance. This work highlights different extraction methods, phytochemistry along with structure activity relationship, nutritional profiling, market viability and pharmacology of C. longa. The bioactives of C. longa depends on various factors such as plants growth, temperature, humidity, soil type, collection, drying and extraction process. These factors can contribute in quality evaluation of the food supplements if need to be included. The introduction of omics approaches can helpful to explore the quality and identification of potential lead of C. longa. The results could play an essential role in the area of food-phyto based profiling. Further, metabolomics techniques may provide an analytical platform by combination of different “omics” data sources for future research to food and herbal based products.

Angelos Angelopoulos, Anastasios Giannopoulos, Nikolaos Nomikos et al.

The next generation of shipping industry, namely Shipping 4.0 will integrate advanced automation and digitization technologies towards revolutionizing the maritime industry. As conventional maintenance practices are often inefficient, costly, and unable to cope with unexpected failures, leading to operational disruptions and safety risks, the need for efficient predictive maintenance (PdM), relying on machine learning (ML) algorithms is of paramount importance. Still, the exchange of training data might raise privacy concerns of the involved stakeholders. Towards this end, federated learning (FL), a decentralized ML approach, enables collaborative model training across multiple distributed edge devices, such as on-board sensors and unmanned vessels and vehicles. In this work, we explore the integration of FL into PdM to support Shipping 4.0 applications, by using real datasets from the maritime sector. More specifically, we present the main FL principles, the proposed workflow and then, we evaluate and compare various FL algorithms in three maritime use cases, i.e. regression to predict the naval propulsion gas turbine (GT) measures, classification to predict the ship engine condition, and time-series regression to predict ship fuel consumption. The efficiency of the proposed FL-based PdM highlights its ability to improve maintenance decision-making, reduce downtime in the shipping industry, and enhance the operational efficiency of shipping fleets. The findings of this study support the advancement of PdM methodologies in Shipping 4.0, providing valuable insights for maritime stakeholders to adopt FL, as a viable and privacy-preserving solution, facilitating model sharing in the shipping industry and fostering collaboration opportunities among them.

Clavijo-Bernal Enrique J., Martínez-Force Enrique, Garcés Rafael et al.

Climate change is forcing our societies to undertake socioeconomic changes to mitigate greenhouse gas emissions, primarily carbon dioxide, which continue to rise globally. Governments are applying policies to offset carbon emissions, despite the significant economic impact. Biotechnology offers solutions to dampen this impact, particularly in agriculture and industry, where plant biotechnology enhances production efficiency while reducing environmental impact. Camelina sativa, a climate-flexible oilseed crop with low agronomical exigence, offers promising alternatives to petroleum-derived oils. Oil derived from camelina seeds has the potential to substitute petroleum as the feedstock for the production of oleochemicals, which are compounds derived from vegetable or animal oils and/or petrochemical feedstock. The deep knowledge of the camelina genome, together with the optimized process to obtain genetically engineered camelina lines with on-demand modified oils, makes this oilseed crop a workhorse to counteract the environmental impact derived from human activity.

Xixia Zhang, S. Y. Teng, A. Loy et al.

The material characteristics and properties of transition metal dichalcogenide (TMDCs) have gained research interest in various fields, such as electronics, catalytic, and energy storage. In particular, many researchers have been focusing on the applications of TMDCs in dealing with environmental pollution. TMDCs provide a unique opportunity to develop higher-value applications related to environmental matters. This work highlights the applications of TMDCs contributing to pollution reduction in (i) gas sensing technology, (ii) gas adsorption and removal, (iii) wastewater treatment, (iv) fuel cleaning, and (v) carbon dioxide valorization and conversion. Overall, the applications of TMDCs have successfully demonstrated the advantages of contributing to environmental conversation due to their special properties. The challenges and bottlenecks of implementing TMDCs in the actual industry are also highlighted. More efforts need to be devoted to overcoming the hurdles to maximize the potential of TMDCs implementation in the industry.

K. Xie

Abstract It is important to develop the advanced coal to chemicals industry (ACCI) against a backdrop of coal-based energy structures, excessive imported oil and natural gas, and strict environmental constraints in China. In this study, the technology and industry of China's ACCI are reviewed to explain the effect of using coal to replace oil and natural gas, and the corresponding resource and environmental burdens that this will create. Development trends in technology and industry are also proposed to explore future scenarios. The review shows that although excellent progress has been made on an industrial scale, demonstrative level, and in terms of technology and equipment, the lack of strategic understanding, severe external constraints, partly underdeveloped technologies, and weak foundations must be immediately addressed. Therefore, it is necessary to clarify the importance that the ACCI has on the energy revolution and energy system. Based on technological innovation, a variety of external factors should be considered as a whole with emphasis on filling the knowledge gap of theoretical foundations and industry standards to support high-quality development for ACCI.

Maja Bašić, Mile Bošnjak, Ivan Novak

This study examines the industry-specific effects of productivity shocks on exports and the internationalisation of the largest Croatian exporters. In order to answer two research questions: (1) Which hypothesis, the productivity-led hypothesis or export-led hypothesis, holds in the case of the largest Croatian exporters? (2) Are the effects of productivity shocks on exports and internationalization sectoral dependent, and in what way? The authors tested 300 largest exporters’ micro- financial data for the 2006-2015 period by using a vector autoregression (VAR) method. Three productivity measures examined are total factor productivity, labour productivity and capital productivity. The results imply that productivity-led hypothesis holds for majority of Croatian largest exporters’ sectors. Rather than a specific export-led hypothesis, a bi-directional flow has proved to have greater influence on several industrial sectors, including professional and scientific services and administrative services sectors, and to a lesser extent, transport and warehousing, accommodation and food sectors. It is predominantly negative in terms of TFP and positive in terms of labour productivity (agriculture, electricity and gas supply, wholesale and transport and warehousing, and information and communication) and capital productivity (electricity and gas supply). Managerial and policy implications of productivity shocks are discussed in the paper.

Elydio Soares, Talita santos, Filipe Mazzaro et al.

Brazil is the world's largest supplier of niobium to industry, accounting for 98% of world production, with Minas Gerais supplying 80% of total production. The mineral exploration industry generates millions of tons of waste annually. In several mining industries, waste is considered a burden for companies. Based on the radiation protection exemptions for the disposal of mining waste, the study analyses the use of waste as a raw material for the construction industry. The minimum dose rate found for gamma radiation in the waste was 0.24 µSv/h and a maximum dose of 0.33 µSv/h, which corresponds to an annual dose above the population exposure limit. The radio concentrations from gamma spectrometric analyses with the Ge(HP) detector for the two samples are a maximum of 240 Bq/kg for Ra-226 and a maximum of 840 Bq/kg for Ra-228. Despite the dose values determined for gamma radiation, CNEN Resolution 179 of 2014 considers materials with natural radioactive concentrations of radium 226 and 228 of up to 1000 Bq/kg suitable for use in the cement industry. Nevertheless, further analysis must be carried out. Since the tailings contain a concentration of Ra-226 and the radio is a source of radon gas, new analyses need to be carried out targeting the exhalation of radon.

Lang Zhou

TAO Jinyu, SHEN Baojian, HU Zongquan et al.

The upper Paleozoic Marine shale in middle Guangxi Depression, namely Guizhong Depression, has experienced complex tectonic evolution and thermal evolution. As the main production layer of shale gas, the microscopic pore structure characterization and reservoir pore evaluation of the shale in lower Carboniferous need to be studied urgently. Focus on the Lower Carboniferous Luzhai Formation shale reservoir in the northern Guizhong Depression, the material composition and reservoir pores of the shale are characterized and evaluated in detail by rock thin section, scanning electron microscope, Xray diffraction, porosity and isothermal adsorption tests on samples both from fields and cores. The results show that the <i>TOC</i> in the shale of Luzhai Formation is 0.4 % ~ 6.6 %. The organic matter is in the stage of high mature to over-mature thermal evolution. The content of brittle minerals such as quartz is high, with a good fracturing ability. The shale in Luzhai Formation, with an average porosity of 2.91 % and an average permeability of 0.007 9 ×10^-3μm², is a kind of low porosity, ultra-low permeability and good breakthrough pressure shale gas reservoir. There are five types of pores in the shale reservoir: the residual intergranular pore, intergranular pore, intragranular dissolved pore, clay minerals interlayer pore and organic pore. The main contributors are the clay minerals interlayer pores, the organic pores and the pyrite intergranular pores. The aperture rangs from 17 nm to 65 nm, most of which are microporous or mesoporous with the scale less than 50 nm. The connectivity between the pores is poor and there is a certain connectivity inside the pores.