Unconventional Resources最新文献

{"title":"Offshore wind technology of India: Potential and perspectives","authors":"Tejaswini Gautam ,&nbsp;Anirbid Sircar ,&nbsp;Kriti Yadav","doi":"10.1016/j.uncres.2025.100150","DOIUrl":"10.1016/j.uncres.2025.100150","url":null,"abstract":"<div><div>India has 7600 km of coastline, making offshore wind energy a promising sustainable energy source that could satisfy the country's energy requirements. In contrast to onshore equivalents, offshore wind energy systems provide several benefits like availability of high and steady wind speeds, huge energy potential, and less noise. This study reviews the advancement in offshore wind technology and discusses the recent advancement in offshore wind turbines, foundations, and transmission systems. It highlights the different types of controls and the reliability of turbines along with some general maintenance issues encountered in offshore wind turbines. The different types of foundations and their characteristic features of recent transmission systems is also discussed. The offshore wind energy potential of India was reviewed. The three models employed by India to attract Indian and foreign investors serve as the scope of the framework for this study. Models A, B, and C represent the viability gap funding model, non-viability gap funding model (with exclusivity over the seabed), and non-viability gap funding model (without exclusivity over the seabed). The available site characteristics of the most promising regions for offshore wind energy, Gujarat and Tamil Nadu were outlined. The study discusses the feasibility of offshore wind energy in India and the CAPEX, OPEX, and levelized cost of energy for generated energy considering the met-ocean, wind and geotechnical characteristics of the potential offshore wind farm regions. This study includes the role of subsidies in the cost of offshore wind energy in India. The prevalent policies and regulatory frameworks for the development of offshore wind energy in India are outlined with the comparative study of other offshore wind markets. This study aims to present the technological advancement and availability of technologies in offshore wind energy along with the potential of offshore energy development in India with its characteristic engineering, financial, environmental, and regulatory features.</div></div>","PeriodicalId":101263,"journal":{"name":"Unconventional Resources","volume":"6 ","pages":"Article 100150"},"PeriodicalIF":0.0,"publicationDate":"2025-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143132969","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhancing heat recovery efficiency in chimney exhaust systems using thermoelectric generators – Thermal modeling and parametric analysis","authors":"Obeida Farhat ,&nbsp;Mahmoud Khaled ,&nbsp;Jalal Faraj ,&nbsp;Khaled Chahine ,&nbsp;Farouk Hachem ,&nbsp;Cathy Castelain","doi":"10.1016/j.uncres.2025.100148","DOIUrl":"10.1016/j.uncres.2025.100148","url":null,"abstract":"<div><div>The rising demand for sustainable energy solutions has made the utilization of waste heat from industrial processes a priority. Thermoelectric generators present an effective method for recovering and converting waste heat into useable electrical energy, therefore enhancing energy efficiency and sustainability. This study presents a parametric study of thermoelectric generators for waste heat recovery from heating chimney exhaust. In order to investigate the impact of placing the thermoelectric generators at different locations, simplified thermal resistance modeling was performed. Performance metrics demonstrate that the positioning of the thermoelectric generator site can bring about major improvements including thermal resistance, generated power, temperature of water heated, and energy conversion efficiency, which ranged from 0.57 % to 5.6 %, depending on thermoelectric generators configuration and operating parameters. By positioning thermoelectric generators on the exterior walls of the exhaust pipe, close to the heat source, a significant amount of electrical power—up to 37.67 W—could be produced. Additionally, a parametric analysis was conducted on important operating parameters: the mass flow rate and input temperatures of the exhaust gas and water. The application of 6 different cases showed that Case 5 of thermoelectric generator modules, with ṁ_g = 0.25 kg/s, T_g,i = 390 °C, ṁ_w = 0.3 kg/s and T_w,i = 20 °C, was the optimal condition, based on observations. The results demonstrate notable advancements in power production and energy recovery, and includes clear recommendations for future research that will bring about a shift in the direction of sustainable industrial operations.</div></div>","PeriodicalId":101263,"journal":{"name":"Unconventional Resources","volume":"6 ","pages":"Article 100148"},"PeriodicalIF":0.0,"publicationDate":"2025-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143132905","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Heating water using the hot air of condensers and tubes-and-fins heat exchangers – Thermodynamic modeling and parametric study with economic and environmental insights","authors":"Ahmad Al Takash ,&nbsp;Jalal Faraj ,&nbsp;Sary Awad ,&nbsp;Hicham El Hage ,&nbsp;Mahmoud Khaled","doi":"10.1016/j.uncres.2025.100146","DOIUrl":"10.1016/j.uncres.2025.100146","url":null,"abstract":"<div><div>Recovering the waste heat from condensers of Heating, Ventilating and Air Conditioning (HVAC) is taking big importance nowadays in the building energy management sector. Advances in this area are still needed due to the high amount of heat released from the condensers versus the low effectiveness of and high volume of the heat recovery medium. As compact and high effectiveness heat exchangers, tubes and fins heat exchangers constitute a potential candidate to overcome the concerns. In this context, the primary goal of this research is to investigate the effect of employing tubes and fins heat exchangers to recover heat from the condenser. To accomplish this goal, a thermodynamic modeling, in addition to analytical approach of the system performance were introduced. Then, a parametric study was performed to examine the effect of the mass flow rate of air and water on the suggested heat recovery system. Finally, economic, and environmental insights based on the energy analysis are presented. It was observed that increasing the mass flow rate from 0.417 kg/s to 2.5 kg/s enhanced the power output from 14.5 kW to 15.1 kW. Similarly, lowering the water inlet temperature from 35 °C to 15 °C increased the power output from 11.28 kW to 15 kW The study highlighted the notable savings with various COP and cooling load, particularly at low COP and a cooling load of 30 kW. Moreover, the investigation revealed that maintaining a constant COP of 2 and increasing cooling loads contributed to higher CO2 emission reduction, ranging from 3.8 kg at 5 kW to 16.5 kg at 25 kW. The findings confirm that the suggested heat recovery system is effective in reducing energy waste and minimizing environmental impact. Finally, it was observed that the proposed system has 95 % capacity of heat recovery.</div></div>","PeriodicalId":101263,"journal":{"name":"Unconventional Resources","volume":"6 ","pages":"Article 100146"},"PeriodicalIF":0.0,"publicationDate":"2025-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143132970","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhanced dry SO₂ capture estimation using Python-driven computational frameworks with hyperparameter tuning and data augmentation","authors":"Robert Makomere ,&nbsp;Hilary Rutto ,&nbsp;Alfayo Alugongo ,&nbsp;Lawrence Koech ,&nbsp;Evans Suter ,&nbsp;Itumeleng Kohitlhetse","doi":"10.1016/j.uncres.2025.100145","DOIUrl":"10.1016/j.uncres.2025.100145","url":null,"abstract":"<div><div>Dry flue gas desulfurization is an invaluable technique to curb sulfur dioxide. In this study, an in-depth comparison of regression models for predicting sulfur dioxide removal was performed. The data-driven models executed were multilayer perceptron, support vector regressor, random forest, categorical boosting, and light gradient boosting machine. The limited experimental samples were magnified to 342 datasets using the random interpolation and random scaling augmentation procedures and analyzed using the empirical cumulative distribution function and box plots. Model training incorporated grid search with cross-validation to identify the optimal hyperparameter sets. The practicality of the resultant customized models was quantified by leveraging the coefficient of determination, mean squared error and root mean square error. The model complexity arising from hyperparameter configurations was appraised based on the Bayesian information criterion and the Akaike information criterion. SHapley Additive exPlanations was essential for comprehending the prediction mechanism through feature significance and the impact of varying feature thresholds on the predicted output. Results obtained evidence that random forest obtained the strongest accuracy, and generalizability from the high coefficient of determination, and lowest error scores. In addition, it was the least convoluted algorithm according to Akaike information criterion and Bayesian information criterion assessments. The SHapley Additive exPlanations analysis revealed that each model interacts with the metadata features uniquely during training, contributing to a varied selection of dominant factors. This paper endorses the technical implementation of machine learning in dry sulfation processes and provides insights into how computer systems perceive data characteristics and make forecasts.</div></div>","PeriodicalId":101263,"journal":{"name":"Unconventional Resources","volume":"6 ","pages":"Article 100145"},"PeriodicalIF":0.0,"publicationDate":"2025-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143132972","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integrating solar and wind energy into the electricity grid for improved power accessibility","authors":"Collins N. Nwagu ,&nbsp;Chika Oliver Ujah ,&nbsp;Daramy V.V. Kallon ,&nbsp;Victor S. Aigbodion","doi":"10.1016/j.uncres.2024.100129","DOIUrl":"10.1016/j.uncres.2024.100129","url":null,"abstract":"<div><div>A rise in the need for the integration of renewable energy sources, such as wind and solar power, has been attributed to the search for sustainable energy solutions. To strengthen community grids and improve access to electricity, this article investigates the potential of combining solar and wind hybrid systems. This is viable approach to address energy-related issues, like grid dependability, energy accessibility, and greenhouse gas reduction. This research focuses on the examination of the environmental, technological, financial, and operational effects, and features of hybrid solar and wind systems for grid support. To further demonstrate the practical uses and advantages of such hybrid systems; case studies are presented. This study attempts to shed light on how solar and wind systems can affect grid resilience, increase electricity accessibility, and shape the direction for sustainable energy in the future. The obstacles preventing the broad use of a hybrid system for grid support were investigated, and the intricacies required in implementing such systems at a large scale are comprehensively presented. It was observed that developments of demand-side management, energy storage technology, and hybrid system optimization algorithms would improve the dependability, effectiveness, and cost of the hybrid system. In summary, the motivation of this study was to provide an effective tool for the interaction of hybrid solar and wind systems in the changing the energy landscape, in order to provide communities with dependable access to electricity, and fostering a more sustainable future. This work offers stakeholders insights into utilizing the hybrid system for electricity access and shift towards cleaner and renewable energy.</div></div>","PeriodicalId":101263,"journal":{"name":"Unconventional Resources","volume":"5 ","pages":"Article 100129"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143149760","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Insights from field applications of miscible gases based EOR for unconventional oil reservoirs: A review","authors":"Dheiaa Alfarge ,&nbsp;Ahmed M. Aljarah ,&nbsp;Najeh Alali","doi":"10.1016/j.uncres.2024.100132","DOIUrl":"10.1016/j.uncres.2024.100132","url":null,"abstract":"<div><div>The oil industry has experienced notable changes due to the development of unconventional liquids rich reservoirs over the past decade. Shale oil reservoirs have become a primary focus for oil and gas investors as traditional onshore deposits have dwindled. These non-traditional reserves hold substantial original oil, but their recovery rate is less than 10 %. Utilizing miscible gas-based enhanced oil recovery (EOR) techniques, which are effective in tight oil reservoirs, has the potential to enhance oil recovery in these formations.</div><div>This research conducts an analysis of the feasibility of using miscible gas-based EOR methods in shale oil reservoirs. Initially, the EOR mechanisms involving various miscible gases are introduced, including molecular diffusion, adsorption, swelling, and viscosity reduction, are summarized and explored. Subsequently, the impact of operational factors such as injection rate, cycle count, and injection duration on the efficacy of miscible gases in boosting oil recovery from unconventional oil reservoirs are examined. Moreover, the outcomes of pilot tests employing diverse miscible gas-based EOR in shale oil reservoirs are discussed. The findings reveal that molecular diffusion is the primary mechanism enhancing oil recovery in shale oil reservoirs. This mechanism positively influences the oil recovery factor through CO₂ injection, while it has no effect when injecting natural gas. Adsorption, however, negatively affects well performance in CO₂-EOR. Additionally, the number of huff-n-puff cycles negatively impacts CO₂-EOR but benefits NGs-EOR. Overall, the performance of natural gas (NG) injection surpasses that of CO₂ injection in enhancing oil recovery in field pilot tests. Moreover, the study concludes that unconventional reservoirs respond much quicker to injected natural gas compared to CO₂.</div></div>","PeriodicalId":101263,"journal":{"name":"Unconventional Resources","volume":"5 ","pages":"Article 100132"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143150285","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Balancing conflicting objectives in pre-salt reservoir development: A robust multi-objective optimization framework","authors":"Auref Rostamian,&nbsp;Amir Davari Malekabadi,&nbsp;Marx Vladimir De Souda Miranda,&nbsp;Vinicius Edurado Botechia,&nbsp;Denis José Schiozer","doi":"10.1016/j.uncres.2024.100130","DOIUrl":"10.1016/j.uncres.2024.100130","url":null,"abstract":"<div><div>Optimizing production strategies for gas and oil fields is a critical challenge in petroleum engineering as it involves balancing multiple and often conflicting objectives, for instance, enhancing production rates, reducing operational costs, and mitigating the environmental effects of cumulative water or gas production. This study aims to develop and apply a robust multi-objective optimization framework to the UNISIM-II-D reservoir, which represents Brazilian pre-salt fields on nine representative models (RMs) to address geological uncertainties while considering three economic scenarios. The study focuses on maximizing expected monetary value (EMV) and the net present value of RM4 considering economic uncertainty (NPVeco of RM4), of the most pessimistic scenario among the RMs. The optimization variables are location, type (injection or production), and number of wells, while the non-dominated sorting genetic algorithm II (NSGA-II) is employed for multi-objective optimization. The study indicates that prioritizing EMV, the primary objective function, does not inevitably result in the NPVeco of RM4 achieving its optimal or near-optimal value. However, by employing the proposed framework, a 3 % improvement in EMV and a 28 % enhancement in the NPVeco of RM4 is achieved compared to the single objective optimization of EMV, which highlights the strength and robustness of the framework.</div></div>","PeriodicalId":101263,"journal":{"name":"Unconventional Resources","volume":"5 ","pages":"Article 100130"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143150283","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mechanistic controls on permeability evolution in thermally-upgraded low-maturity oil shales: Application of machine learning outputs","authors":"Bo He ,&nbsp;Lingzhi Xie ,&nbsp;Xin Liu ,&nbsp;Jun Liu ,&nbsp;Derek Elsworth","doi":"10.1016/j.uncres.2024.100133","DOIUrl":"10.1016/j.uncres.2024.100133","url":null,"abstract":"<div><div>In-situ thermal upgrading aids recovery from low-maturity oil shales where low permeability is the rate-limiting feature. We use machine leaning classified pore and pore network morphological descriptions recovered at elevated temperatures to define the dynamic thermal evolution of permeability. These descriptions define key factors influencing permeability evolution, in particular the development of anisotropy and its implication for recovery. Heating enhances permeability by increasing both the number and total cross-sectional area (SEM) of pores. Fractal dimensions indicate that the pore microstructure is anisotropic in the bedding-parallel and bedding-perpendicular directions and is upgraded by elevated temperature. The permeability anisotropy endures throughout the entire heating process and fluctuates at elevated temperature, quantified by the index called anisotropic coefficient of permeability. A newly proposed “aggregation degree” indexes the relative contribution of minority pores to overall permeability – 50 % of the permeability (<em>K)</em> is sourced from &lt;8 % pores in the SEM section. Increased temperature elicits increased permeability – thus, the temperature applied at the injection well defines the flow limiting permeability threshold at the production wells and thus controls flow rates from the entire heated reservoir. This work provides fresh insights in defining the thermal permeability response of low-maturity oil shales and guides fluids recovery.</div></div>","PeriodicalId":101263,"journal":{"name":"Unconventional Resources","volume":"6 ","pages":"Article 100133"},"PeriodicalIF":0.0,"publicationDate":"2024-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143132971","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Design and implementation of a waterless solar panel cleaning system","authors":"Charity M. Nkinyam ,&nbsp;Chika O. Ujah ,&nbsp;Kingsley C. Nnakwo ,&nbsp;Obiora Ezeudu ,&nbsp;Daramy V.V. Kallon ,&nbsp;Ikechukwu Ike-Eze C. Ezema","doi":"10.1016/j.uncres.2024.100131","DOIUrl":"10.1016/j.uncres.2024.100131","url":null,"abstract":"<div><div>Manual cleaning of large solar installations is often labor-intensive and time-consuming, primarily due to the accumulation of dust on solar panels, which significantly impairs their efficiency. The study introduces a novel, waterless, cost-effective automatic cleaning system for small solar panels. The rationale behind this innovation stems from the necessity to mitigate efficiency losses caused by dirt and contaminants on solar surfaces. The automated system employs an Arduino microcontroller enhanced with a real-time clock to optimize cleaning schedules based on environmental conditions. The system consists of a two-stage mechanism which includes an ejector blower that produces a strong air jet, complemented by a flexible brush that effectively removes dust as well as sticky dirt. Cleaning intervals are strategically determined to ensure consistent maintenance without manual intervention, thus maximizing energy output. Tests on a 60 W solar panel revealed an impressive average power output increase of 26.23 % following cleaning. This prototype demonstrates the efficacy of the cleaning approach and underscores its potential to alleviate efficiency losses attributed to dust accumulation. Particularly advantageous in arid regions where water conservation is paramount, this automated system enhances energy production and operational efficiency for solar plant operators, promoting sustainable energy practices.</div></div>","PeriodicalId":101263,"journal":{"name":"Unconventional Resources","volume":"5 ","pages":"Article 100131"},"PeriodicalIF":0.0,"publicationDate":"2024-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142757709","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Reservoir evaluation method based on explainable machine learning with small samples","authors":"Haojiang Xi ,&nbsp;Zhifeng Luo ,&nbsp;Yue Guo","doi":"10.1016/j.uncres.2024.100128","DOIUrl":"10.1016/j.uncres.2024.100128","url":null,"abstract":"<div><div>Reservoir classification and evaluation of fractured gas reservoirs are essential for optimizing development strategies and enhancing oil and gas recovery rates. In this study, we utilized geological and engineering parameters to construct new feature dimensions and applied the K-means clustering algorithm to classify reservoirs into three categories based on unobstructed flow rates. We developed a novel machine learning framework that integrates Explainable Artificial Intelligence (XAI), Synthetic Minority Over-sampling Technique (SMOTE), and Stacking models, addressing class imbalance in small sample datasets. This framework achieved a classification accuracy of 92 %, demonstrating significant improvements over traditional methods. Through global and local interpretability analysis using SHAP values, we identified the critical features influencing the model's predictions, enhancing transparency and practicality. Using data from the Bozi-Dabei Block in the Tarim Basin, we validated the accuracy and applicability of our approach. This framework not only deepens the understanding of complex reservoir characteristics but also optimizes reservoir classification accuracy, providing robust technical support for the efficient development of unconventional oil and gas resources.</div></div>","PeriodicalId":101263,"journal":{"name":"Unconventional Resources","volume":"5 ","pages":"Article 100128"},"PeriodicalIF":0.0,"publicationDate":"2024-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142705757","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}