Unconventional Resources最新文献

{"title":"Rear-surface water cooling for photovoltaic panels: A thermo-hydrodynamic pathway to high-efficiency and sustainable solar power in hot climates","authors":"Wassim Salameh ,&nbsp;Samer Ajeeb ,&nbsp;Kamal Itawi ,&nbsp;Mohamad Arnaout ,&nbsp;Rabih Murr ,&nbsp;Jalal Faraj ,&nbsp;Mahmoud Khaled","doi":"10.1016/j.uncres.2026.100326","DOIUrl":"10.1016/j.uncres.2026.100326","url":null,"abstract":"<div><div>Photovoltaic (PV) modules functioning in high-temperature environments face considerable efficiency declines as a result of increased cell temperatures, driving the need for innovative and resource-efficient cooling solutions. This study explores the rear-surface water cooling of photovoltaic modules through a coupled thermal–hydrodynamic numerical model, aiming to identify crucial design and operational parameters that influence thermal and electrical performance. The model undergoes initial validation using published experimental data for air-cooled PV systems, followed by an extension to include rear-surface water cooling as an added convective boundary condition. A thorough parametric analysis is conducted to evaluate the effects of duct height, flow regime, inlet water temperature, and climatic conditions on the reduction of module temperature and the improvement of electrical efficiency. The findings indicate that implementing rear-surface water cooling can lower the operating temperature of photovoltaic systems by as much as 20 % in hot urban environments, resulting in enhancements in electrical efficiency ranging from 15 % to 20 %, contingent on the hydraulic configuration employed. The analysis further illustrates that suitable duct geometry and flow management facilitate efficient cooling while minimizing water usage, underscoring the practicality of closed-loop operation. The proposed framework offers a physically consistent approach for designing and optimizing rear-surface water-cooled PV systems, effectively addressing significant limitations found in current studies that overlook the interplay between thermal and hydrodynamic effects. The results enhance the development of scalable PV cooling solutions tailored for hot climates and provide direction for future experimental validation and techno-economic evaluation.</div></div>","PeriodicalId":101263,"journal":{"name":"Unconventional Resources","volume":"10 ","pages":"Article 100326"},"PeriodicalIF":4.6,"publicationDate":"2026-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146079975","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Microbialite fabric evolution controlled by marine redox conditions in the Qigebrak Formation, NW Tarim Basin: Implications for hydrocarbon exploration","authors":"Chang Fang ,&nbsp;Da Gao ,&nbsp;Hui Zhou ,&nbsp;Lili Huang ,&nbsp;Yangxiao Hu ,&nbsp;Ngong Roger Ngia","doi":"10.1016/j.uncres.2026.100325","DOIUrl":"10.1016/j.uncres.2026.100325","url":null,"abstract":"<div><div>Microbialites constitute key archives for reconstructing the co-evolution of early life and Earth surface environments. Although the environmental controls on microbialite formation are widely acknowledged, the response of specific microbialite architectures to changes in pelagic ocean chemistry still remain poorly constrained. This paper integrates detailed field mapping, sedimentary facies analysis, and geochemical profiling of the Qigebrak Formation at the Xigou section on the northwestern margin of the Tarim Basin, to characterize microbialite fabrics and assess the role of contemporaneous marine redox conditions in shaping their development during the late Ediacaran. The microbialites at Xigou are well preserved and exhibit diverse fabrics, deposited in mid-to inner-ramp settings. Member II is dominated by laminated microbialites with subordinate clotted and binding fabrics. In contrast, Member III is typified by foam spongy fabrics, marking a significant shift in microbialite architecture. Bulk-rock δ¹³C values record a pronounced positive excursion (∼+5 ‰ to +6 ‰) at the base of the formation, followed by a prolonged interval of isotopic stability. This isotopic variation exhibits global correlation significance and, when combined with the Dengying Formation age constraints, limits the depositional interval to approximately 551.1 ± 0.7 Ma to 538.8 Ma. Trace element and rare earth element data from microbial components indicate that both δCe values and V/(V + Ni) ratios in Member III are markedly lower than those in Member II, reflecting a significant marine redox transition from anoxic to more oxic conditions during the late-Ediacaran ocean. This redox shift exerted a primary control on microbialite fabric development: anoxic conditions favored microbial mats accretion and preservation of laminated fabrics, whereas subsequent oxygenation enhanced organic matter degradation, facilitating the emergence and dominance of foam spongy fabrics. The fabric transition may also reflect increased ecological disturbance linked to the rise of metazoans, pointing to a potential coupling between microbialite decline and biotic innovation in the terminal Ediacaran. Our study underscores that changes in marine redox chemistry, coupled with ecological interactions, were primary controls on the evolution of microbialite in the late Ediacaran, and further elucidates the implications of these fabric transformations for hydrocarbon exploration.</div></div>","PeriodicalId":101263,"journal":{"name":"Unconventional Resources","volume":"10 ","pages":"Article 100325"},"PeriodicalIF":4.6,"publicationDate":"2026-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146079397","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Towards a sustainable energy future: Evaluating renewable energy options in Tunisia","authors":"Sassi Rekik ,&nbsp;Johnson Herlich Roslee Mensah ,&nbsp;Ali Gassim Shetwan","doi":"10.1016/j.uncres.2026.100322","DOIUrl":"10.1016/j.uncres.2026.100322","url":null,"abstract":"<div><div>Given the increasing threat of climate change, global warming, and depletion of fossil fuels, the adoption of renewable energy technologies (RETs) has become a crucial issue. Nevertheless, selecting the most appropriate technology is crucial. In this sense, developing decision support mechanisms for the identification of appropriate energy resources is one of the core decision-making challenges in the energy industry. In this paper, we address some renewable energy options for electricity generation in Tunisia namely solar photovoltaics (PV), concentrated solar power (solar CSP), onshore wind, and biomass, taking into account technical, economic, environmental, and social dimensions. This study employed a hybrid multi-criteria decision-making approach, combining CRiteria Importance Through Inter-criteria Correlation (CRITIC) and Evaluation based on Distance from Average Solution (EDAS), The considered alternative RETs were ranked and prioritized according to the proposed model. The results indicate that solar PV is the most promising renewable technology for Tunisia. Biomass is the least viable option. Validation through Monte Carlo simulation (MCS) largely corroborated these results, consistently placing solar PV first, followed by onshore wind. The only minor difference observed was an exchange in ranking between biomass and solar CSP. A sensitivity analysis was conducted to validate the outcomes and demonstrate the effect of changing the input data on the final results, revealing the considerable influence of cost-related factors on nearly all renewable energy technologies. Key differences in sensitivity were apparent, with Solar PV being more sensitive to electricity cost than capital cost, whereas solar CSP showed equal criticality to both. These distinctions imply that decision-making and risk prioritization must be tailored to each specific RET, prioritizing R&amp;D for cost reduction and economies of scale for highly cost-sensitive technologies, and technological innovation and operational optimization for those sensitive to efficiency.</div></div>","PeriodicalId":101263,"journal":{"name":"Unconventional Resources","volume":"10 ","pages":"Article 100322"},"PeriodicalIF":4.6,"publicationDate":"2026-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146039420","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhanced maximum power point tracking performance for PV systems in zero-energy buildings: An optimized SVR–TPE approach with hybrid energy storage and real-time capability","authors":"Mohammad Chegeni,&nbsp;Mohammad Tolou Askari,&nbsp;Meysam Amirahmadi,&nbsp;Vahid Ghods","doi":"10.1016/j.uncres.2026.100310","DOIUrl":"10.1016/j.uncres.2026.100310","url":null,"abstract":"<div><div>Grid-connected photovoltaic systems used in zero-energy building applications are reliable and practically deployable only when maximum power extraction, direct-current link stability, and grid power-injection control are designed and evaluated in a coordinated, cascaded manner. This study presents an integrated three-stage framework. In the first stage, maximum power point tracking is performed using a data-driven support vector regression approach, with automatic hyperparameter tuning via a tree-structured Parzen estimator. The second stage addresses power smoothing and direct-current link stabilization through a hybrid energy storage system composed of a battery and a supercapacitor, together with a two-layer control strategy for intelligent current sharing. At this stage, the impact of tracker model selection on direct-current link voltage stability is analyzed directly, demonstrating that evaluating maximum power point tracking without considering its implications for the direct-current link and the storage subsystem can lead to a misleading assessment of true system performance. In the third stage, power conversion and bidirectional exchange with the grid are ensured by a single-phase inverter equipped with a third-order filter and a modified synchronous reference frame transformation-based control scheme. Simulation results indicate that co-design of the three stages simultaneously improves renewable energy harvesting, reduces direct-current link oscillations and battery transient stresses, and enables grid-compliant power injection and stable power exchange under zero-energy building operating scenarios.</div></div>","PeriodicalId":101263,"journal":{"name":"Unconventional Resources","volume":"10 ","pages":"Article 100310"},"PeriodicalIF":4.6,"publicationDate":"2026-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146079974","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Clustering analysis of nanoindentation data for shale: Curve-based versus mechanical parameter-based approaches","authors":"Peilin Zhang ,&nbsp;Kouqi Liu ,&nbsp;Zhenlin Wang ,&nbsp;Kai Feng ,&nbsp;Zhichao Wang ,&nbsp;Yamin Wang ,&nbsp;Mehdi Ostadhassan","doi":"10.1016/j.uncres.2026.100323","DOIUrl":"10.1016/j.uncres.2026.100323","url":null,"abstract":"<div><div>Clustering analysis of nanoindentation data is generally done to distinguish the mechanical phases and quantitatively obtain their related mechanical properties and fractions in the entire sample. Clustering analysis is carried out based on the mechanical parameters (Young's modulus and hardness) that are obtained from the load–displacement curves of each indent. However, the accuracy of this method and its suitability for the analysis of grid nanoindentation data on a heterogeneous composite material like shale is still unknown. Therefore, this study applied clustering analysis directly on the load–displacement curves in a shale sample for the first time and compared the results with the widely used mechanical parameter-based clustering analysis method. The results showed that the mechanical parameter-based clustering distinguished four mechanical phases with 8.62, 16.07, 24.31, and 37.16 GPa as the average Young's moduli, and hardness values of 0.15, 0.35, 0.80, and 2.56 GPa, respectively. The fractions of these phases are 34.22 %, 27.78 %, 20.89 %, and 7.11 %, respectively. Likewise, the curve clustering method also distinguished four mechanical phases with Young's moduli of 4.75, 7.91, 14.10, and 22.49 GPa, and hardness values of 0.03, 0.08, 0.23, and 0.97 GPa, with fractions of 2.67 %, 12.89 %, 40.44 %, and 44.00 %, respectively. Comparing the results with the sample's mineralogy suggests that parameter-based clustering provides a better distinction between mechanical phases, closely aligning with the mineral fractions obtained from X-ray diffraction (XRD) analysis. Therefore, this approach is recommended for analyzing grid nanoindentation data in composite materials.</div></div>","PeriodicalId":101263,"journal":{"name":"Unconventional Resources","volume":"10 ","pages":"Article 100323"},"PeriodicalIF":4.6,"publicationDate":"2026-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146039422","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A novel method for risk identification and quantitative assessment in shale gas development phase based on STPA-FTA-DEMATEL","authors":"Zhicheng Zhou,&nbsp;Haoyu Mao,&nbsp;Boxun Yang,&nbsp;Shaoxuan Sun","doi":"10.1016/j.uncres.2025.100301","DOIUrl":"10.1016/j.uncres.2025.100301","url":null,"abstract":"<div><div>With the growing strategic importance of shale gas in China's energy portfolio, effective risk assessment during the production phase has become crucial. Conventional risk analysis approaches often struggle to capture the in herent complexity and diversity of shale gas well production systems. To address this limitation, this study proposes a hybrid framework combining integrates the System-Theoretic Process Analysis (STPA), Fault Tree Analysis (FTA), and the Decision-Making Trial and Evaluation Laboratory (DEMATEL) methods to contruct a comprehensive risk assessment framework for shale gas well production. Through STPA and FTA, the study investigates four dimensions—human factors, equipment, materials, and environment—to accurately identify potential risks such as frontline operator errors, equipment failures, material supply and quality issues, and complex geological and climatic conditions. DEMATEL is subsequently employed to quantify the weights of risk factors, highlighting high-weight risks such as gas production equipment failures, gathering and transportation pipeline system failures, geological risks increasing extraction difficulty, and climatic and environmental risks that complicate extraction processes. These risks are interdependent and manifest across multiple production stages, significantly impacting the safety, stability, and efficiency of shale gas production. This research provides a more precise and comprehensive basis for shale gas production risk assessment contributing to the safe and efficient production of shale gas.</div></div>","PeriodicalId":101263,"journal":{"name":"Unconventional Resources","volume":"10 ","pages":"Article 100301"},"PeriodicalIF":4.6,"publicationDate":"2026-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146039419","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Resilient control of AC microgrids via MSOGI-FLL and virtual complex impedance","authors":"Mohamed Said Adouairi ,&nbsp;Saad Motahhir ,&nbsp;Badre Bossoufi","doi":"10.1016/j.uncres.2026.100321","DOIUrl":"10.1016/j.uncres.2026.100321","url":null,"abstract":"<div><div>This paper presents a novel and resilient control strategy for isolated AC microgrids based on a Multiple Second-Order Generalized Integrator with Frequency-Locked Loop architecture and a complex virtual impedance design. The proposed method addresses key challenges associated with power sharing accuracy, harmonic distortion, and system robustness in the presence of nonlinear loads, frequency variation, and complex inverter-to-load impedance characteristics. The main innovation lies in the integration of multi-harmonic Multiple Second-Order Generalized Integrator with Frequency-Locked Loop signal decomposition with adaptive complex virtual impedance and coordinated droop-based control, providing improved harmonic suppression, precise power sharing, and enhanced transient stability compared to existing approaches. A novel signal conditioning scheme based on Multiple Second-Order Generalized Integrator with Frequency-Locked Loop is employed to extract fundamental and selected harmonic components of inverter currents while rejecting DC offsets. The extracted signals are used to synthesize an adaptive virtual complex impedance that enhances droop-based power sharing under coupled resistive-inductive line conditions. To accurately assess system dynamics, a linear time-periodic model is developed for the Multiple Second-Order Generalized Integrator with Frequency-Locked Loop, enabling the derivation of harmonic transfer functions and stability margins. The control strategy is further augmented by a coordinated Battery Management System, ensuring energy balance and flexibility in transient scenarios. Simulation results involving three parallel single-phase inverters confirm the proposed method's ability to achieve accurate active and reactive power sharing, minimize circulating currents, and maintain robust performance under distorted and unbalanced operating conditions. The effectiveness of the proposed control is validated through detailed comparisons with conventional droop methods.</div></div>","PeriodicalId":101263,"journal":{"name":"Unconventional Resources","volume":"10 ","pages":"Article 100321"},"PeriodicalIF":4.6,"publicationDate":"2026-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146039421","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Real time implementation for robust adaptive sliding mode predictive control of PMSM","authors":"Rachid Ibrahimi ,&nbsp;Mohamed said Adouairi ,&nbsp;Abdennabi Morchid ,&nbsp;Badre Bossoufi ,&nbsp;Paweł Skruch ,&nbsp;Saleh Mobayen","doi":"10.1016/j.uncres.2026.100304","DOIUrl":"10.1016/j.uncres.2026.100304","url":null,"abstract":"<div><div>Model Predictive Control is recognized as a promising approach for electric drives, with particular interest in the development of robust and high-performance predictive models. In this work, we propose an Adaptive Integral Sliding Mode Predictive Control for Permanent Magnet Synchronous Motors, combining a predictive model with an adaptive law based on the integral sliding mode. This method automatically adjusts the sliding function limit, reducing the chattering phenomenon while enhancing the system dynamics.</div><div>To ensure compatibility with industrial electronic boards, the Adaptive Integral Sliding Mode Predictive Control was implemented following the V-cycle development process, including Model-in-the-Loop, Software-in-the-Loop, and Processor-in-the-Loop validation. This framework facilitates the deployment of embedded control software in the automotive sector and provides a cost-effective evaluation of the hardware implementation.</div><div>Furthermore, real-time simulations of control, Invariant Sliding Mode Predictive Control, and Sliding Mode Control configurations were carried out on the dSPACE DS1104 platform, showing excellent correlation with MATLAB/Simulink results. Experimental validation on the STM32F4 board confirms that the proposed approach offers faster response to load torque disturbances and better performance over a wide speed range, demonstrating its reliability, robustness, and effectiveness.</div></div>","PeriodicalId":101263,"journal":{"name":"Unconventional Resources","volume":"10 ","pages":"Article 100304"},"PeriodicalIF":4.6,"publicationDate":"2026-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145950283","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Modeling and simulation of hybrid fuzzy-PID and model predictive control for enhanced dual-axis photovoltaic tracking precision","authors":"Rezi Delfianti ,&nbsp;Mohammed Mareai ,&nbsp;Federico Minelli ,&nbsp;Catur Harsito ,&nbsp;Fauzan Nusyura","doi":"10.1016/j.uncres.2025.100303","DOIUrl":"10.1016/j.uncres.2025.100303","url":null,"abstract":"<div><div>This paper presents a comprehensive evaluation of several control strategies for dual-axis solar tracking systems, including proportional–integral–derivative, fuzzy logic, fuzzy–PID, and fuzzy–PID enhanced with model predictive control. Each controller was implemented in MATLAB/Simulink to analyse its dynamic and steady-state behaviour under identical conditions. The findings reveal that hybrid and MPC-based controllers achieve superior tracking precision and response smoothness compared to single-loop designs. Specifically, the fuzzy-tuned PID exhibits the fastest rise time of 12.53 <span><math><mrow><mi>m</mi><mi>s</mi></mrow></math></span> but with a higher overshoot of 18.45 %. In contrast, the standalone fuzzy controller offers superior stability with a minimal overshoot of 0.50 %, though at the expense of slower dynamics with a rise time of 91.81 <span><math><mrow><mi>m</mi><mi>s</mi></mrow></math></span>. The proposed MPC–Fuzzy–PID Series hybrid achieves a rapid rise time of 16.02 <span><math><mrow><mi>m</mi><mi>s</mi></mrow></math></span> and a settling time of 0.2 <span><math><mrow><mi>s</mi><mtext>,</mtext></mrow></math></span> providing a balanced trade-off between speed, stability, and computational efficiency, making it suitable for real-time solar tracking applications. Overall, the study demonstrates that controller performance depends on the specific operational goals whether prioritizing rapid response, precision, or robustness highlighting the importance of adaptive hybrid control design in sustainable energy systems.</div></div>","PeriodicalId":101263,"journal":{"name":"Unconventional Resources","volume":"9 ","pages":"Article 100303"},"PeriodicalIF":4.6,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145924563","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Modeling geothermal reservoirs permeability based upon NMR laboratory data","authors":"Kusum Yadav ,&nbsp;Lulwah M. Alkwai ,&nbsp;Shahad Almansour ,&nbsp;Debashis K. Dutta ,&nbsp;Ahmad Adel Abu-Shareha ,&nbsp;Mehrdad Mottaghi","doi":"10.1016/j.uncres.2026.100307","DOIUrl":"10.1016/j.uncres.2026.100307","url":null,"abstract":"<div><div>Accurate permeability characterization is crucial for the efficient and sustainable development of geothermal resources. However, conventional methods like well testing and core analysis are often expensive and fail to capture the complex, heterogeneous nature of geothermal reservoirs. While Nuclear Magnetic Resonance (NMR) logging provides valuable insights into pore structure, its traditional permeability models are often unreliable in high-temperature, high-salinity geothermal environments. A novel data-driven methodology is introduced for modeling permeability in geothermal reservoirs by integrating Nuclear Magnetic Resonance (NMR) laboratory measurements with advanced machine learning algorithms. The approach employs a curated dataset of geothermal core samples, utilizing porosity, logarithmic mean transverse relaxation time (T2lm), and mode transverse relaxation time (T2mode) as predictive features across multiple learning models. Outlier detection was conducted using the Leverage technique, while model reliability was validated through K-fold cross-validation. Among the tested algorithms, the Decision Tree model demonstrated superior performance, yielding the highest coefficient of determination (R²) and the lowest error metrics. Sensitivity analysis further revealed porosity as the most dominant factor influencing geothermal permeability. The findings validate the utility of using ensemble soft computing to boost the accuracy of permeability prediction, presenting a valuable and affordable alternative to traditional techniques. Our findings bridge the gap between core analysis and computational modeling, paving the way for more accurate geothermal reservoir characterization and optimization.</div></div>","PeriodicalId":101263,"journal":{"name":"Unconventional Resources","volume":"9 ","pages":"Article 100307"},"PeriodicalIF":4.6,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145924565","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}