Energy Science & Engineering最新文献

{"title":"Decarbonizing India's Industrial Sector: Analysis of the Combined Impacts of the Perform, Achieve, Trade Scheme and the National Green Hydrogen Mission","authors":"Manogna R L,&nbsp;Krishna Brinda Kanumilli","doi":"10.1002/ese3.70598","DOIUrl":"https://doi.org/10.1002/ese3.70598","url":null,"abstract":"<p>This study presents a system-level assessment for India, examining the role of the industrial sector in the nation's net-zero transformation, given its substantial contribution to greenhouse gas emissions and the distinct challenges it faces in decarbonization. This paper analyses the joint effects of two flagship Indian policy mechanisms, the Perform, Achieve, and Trade (PAT) energy efficiency program and the National Green Hydrogen Mission (NGHM) using the India Energy Policy Simulator (EPS) and the energyRt optimization model, which are sequentially coupled to link policy-driven demand evolution with cost-optimal energy and hydrogen system pathways. Model inputs are derived from the Bureau of Energy Efficiency's PAT database, the Ministry of New and Renewable Energy (MNRE), the International Energy Agency (IEA), and the International Renewable Energy Agency (IRENA) for the period 2020–2050, supplemented by datasets embedded within the EPS and energyRt frameworks. Decomposition analysis shows that deployment of green hydrogen provides around 42% of cumulative abatement potential, followed by efficiency improvements under PAT, which contributes 16%, highlighting their complementary nature. An economic and financial evaluation indicates that PAT achieves cost-effective near-term savings through energy efficiency, while NGHM leverages huge investment mobilization to render green hydrogen cost-competitive by mid-century. Sensitivity analysis stresses the key role of timely policy intervention and falling technology costs in preventing lock-in of emissions. Outcomes are sensitive to assumptions regarding technology costs, carbon pricing and data availability for small and medium enterprises (SMEs) and process emissions. By integrating policy design insights with quantitative modelling, this study demonstrates that combining PAT and NGHM offers a scalable pathway for industrial decarbonization aligned with India's long-term net-zero ambitions. The results suggest that under coordinated policy scenarios, PAT and NGHM together account for a substantial share of cumulative industrial emissions reductions by 2050, with efficiency-driven abatement dominating in the near term and hydrogen substitution becoming increasingly important after 2035.</p>","PeriodicalId":11673,"journal":{"name":"Energy Science & Engineering","volume":"14 9","pages":"4213-4229"},"PeriodicalIF":3.6,"publicationDate":"2026-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ese3.70598","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148943426","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Transmission Loss Prediction Using Neural Networks With Correlation-Derived Input Features","authors":"Jovana Tuševljak,&nbsp;Željko Đurišić","doi":"10.1002/ese3.70626","DOIUrl":"https://doi.org/10.1002/ese3.70626","url":null,"abstract":"<p>Accurate prediction of transmission losses is essential for efficient operation and planning of modern power systems under increasingly dynamic operating conditions driven by renewable energy integration and weather-dependent variability. This paper proposes a neural network–based framework for transmission loss prediction that improves predictive performance through correlation-derived input features. The methodology integrates operational power system measurements, meteorological variables, and analytically derived input features designed to capture temporal patterns and nonlinear dependencies in system behavior. Two derived input features are introduced: a 24-h loss-pattern forecast and a pattern-matched loss feature, to capture historical pattern similarity directly in the model inputs. The framework is validated using 4 years of hourly operational and meteorological data from the transmission system of Bosnia and Herzegovina. The baseline MLP achieves a mean absolute percentage error (MAPE) of 14.40% on the test dataset. Incorporating the 24-h loss-pattern forecast feature reduces the prediction error to 13.29%, while the pattern-matched loss feature provides a modest improvement relative to the baseline configuration. The results demonstrate that correlation-derived inputs enhance prediction accuracy while maintaining model simplicity and computational efficiency.</p>","PeriodicalId":11673,"journal":{"name":"Energy Science & Engineering","volume":"14 9","pages":"4113-4129"},"PeriodicalIF":3.6,"publicationDate":"2026-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ese3.70626","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148943582","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Bidirectional Wireless Power Transfer for Electric Vehicle Energy Systems Integrating Modelling, Intelligent Control, Communication and Cybersecurity: A Review","authors":"P. V. Elumalai,&nbsp;Yuvaraja Shanmugam,&nbsp;A. Vivek Anand,&nbsp;Mesith Chaimanee,&nbsp;Choon Kit Chan,&nbsp;S. Prabhakar,&nbsp;R. Narayanamoorthi","doi":"10.1002/ese3.70608","DOIUrl":"https://doi.org/10.1002/ese3.70608","url":null,"abstract":"<p>Bidirectional wireless power transfer (BWPT) is emerging as a key enabler of grid-interactive electric vehicle (EV) systems, supporting vehicle-to-grid, vehicle-to-home and vehicle-to-vehicle energy exchange. However, existing research largely treats modelling, control and communication as independent domains, which limits the practical realization of BWPT systems that operate as tightly coupled cyber–physical platforms. In addition, challenges such as bidirectional power flow regulation, misalignment sensitivity and secure operation remain insufficiently addressed in an integrated manner. This review provides a unified and system-level analysis of BWPT by jointly examining modelling approaches, control strategies, communication frameworks and cybersecurity considerations. Modelling techniques, including analytical, frequency-domain and finite-element methods, are evaluated in terms of accuracy and computational complexity. Control strategies such as triple-phase-shift control, predictive methods, reinforcement learning and communication-free synchronization are comparatively assessed based on zero-voltage switching capability, efficiency and implementation requirements. A key contribution of this work is the integrated treatment of control and communication layers with cybersecurity analysis, demonstrating how power flow regulation, real-time control decisions and protocol-level interactions (e.g., ISO 15118, TLS and CAN) collectively influence system performance, stability and vulnerability. The review further examines standardization efforts and identifies practical deployment challenges, including thermal management, system complexity and large-scale validation. By establishing BWPT as a unified cyber–physical energy system, this work provides structured design insight and outlines research directions toward scalable, efficient and secure wireless EV charging infrastructures.</p>","PeriodicalId":11673,"journal":{"name":"Energy Science & Engineering","volume":"14 9","pages":"4026-4057"},"PeriodicalIF":3.6,"publicationDate":"2026-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ese3.70608","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148943650","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Design, Simulation, and Techno-Economic Evaluation of a High-Capacity Ammonia Cracking Facility for Pipeline-Grade Hydrogen Production","authors":"Amin Soleimani Mehr,&nbsp;Günter Scheffknecht,&nbsp;Reihaneh Zohourian,&nbsp;Markus Reinmöller,&nbsp;Joerg Maier","doi":"10.1002/ese3.70618","DOIUrl":"https://doi.org/10.1002/ese3.70618","url":null,"abstract":"<p>Although ammonia cracking has attracted considerable attention as a hydrogen carrier technology, comprehensive studies integrating industrial-scale process design, off-design operation, and techno-economic assessment within a single framework remain limited. This study addresses this gap by developing and evaluating a fully integrated 1000 MTPD ammonia-to-hydrogen facility, providing a transparent and reproducible framework for assessing the technical, operational, and economic performance of large-scale ammonia cracking systems. The proposed plant integrates cryogenic ammonia storage with closed-loop boil-off gas (BOG) recovery, catalytic ammonia cracking, hydrogen purification, and high-pressure hydrogen compression for pipeline delivery. Steady-state and off-design simulations performed over 50%–100% of the nominal plant capacity demonstrate stable process operation, maintaining nearly complete ammonia conversion (≈100–99.9%) and a hydrogen yield of approximately 0.78 kg H₂ per kg NH₃ feed. The integrated facility achieves a hydrogen production capacity of approximately 137 MTPD, while the hydrogen compression system constitutes the dominant electricity consumer and the overall process maintains a relatively low specific electricity consumption of approximately 1.1–1.3 kWh kg⁻¹ H₂. The techno-economic analysis estimates a Levelized Cost of Hydrogen (LCOH) ranging from 4.8 to 9.0 € kg⁻¹ H₂ under representative European market conditions. For the base-case assumptions of 0.10 € kWh⁻¹ electricity, 0.50–0.90 € kg⁻¹ NH₃ feedstock price, and 90% plant availability, the LCOH is approximately 8.3 € kg⁻¹ H₂, with ammonia feedstock identified as the dominant cost driver. When supplied with green ammonia, the proposed system can avoid approximately 0.27–0.36 t CO₂ per MWh of hydrogen energy compared with conventional fossil-based hydrogen production pathways. Overall, the results demonstrate that the proposed industrial-scale ammonia-to-hydrogen facility is a technically feasible, scalable, operationally flexible, and economically viable pathway for pipeline-grade hydrogen production. These findings provide a robust foundation for the industrial deployment, design, and techno-economic optimization of future ammonia-based hydrogen infrastructure.</p>","PeriodicalId":11673,"journal":{"name":"Energy Science & Engineering","volume":"14 9","pages":"4197-4212"},"PeriodicalIF":3.6,"publicationDate":"2026-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ese3.70618","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148943626","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comparative Study of Electric Vehicle Propulsion Systems Using Field-Oriented Controlled Dual PMSMs With Novel Control Strategies Based on an EPS Filter and a Fuzzy Logic Regulator for Enhanced Stability and Safety","authors":"Rachad Moumni,&nbsp;Idriss Benlaloui,&nbsp;Kouider Laroussi,&nbsp;Amor Fezzani,&nbsp;Mohamed Metwally Mahmoud,&nbsp;Vojtech Blazek,&nbsp;Daniel Eutyche Mbadjoun Wapet,&nbsp;Ezzeddine Touti","doi":"10.1002/ese3.70582","DOIUrl":"https://doi.org/10.1002/ese3.70582","url":null,"abstract":"<p>The growing demand for electric vehicles (EVs) has driven research into improving propulsion control systems, focusing on performance, efficiency, and safety. This study addresses a gap in advanced control systems for EV differentials and presents two solutions. First, an innovative electric power steering (EPS) filter algorithm is introduced, drawing inspiration from mechanical steering systems. Second, a newly designed fuzzy logic controller (FLC) is presented. This controller utilizes the vehicle's measured speed and turning angle to control dynamics and stability. These solutions aim to regulate speed and steering angle to enhance stability at high speeds, improve user comfort, and minimize the risk of sliding or overturning. To validate and compare these approaches, three propulsion control configurations for an EV with dual permanent magnet synchronous motors (PMSMs) using field-oriented control (FOC) were simulated in MATLAB-Simulink under a Federal Test Procedure (FTP 75) signal. These strategies include: (1) an EV without differential gears using a classical electric differential (CED), (2) an EV with the proposed EPS filter algorithm to regulate speed and steering angle, and (3) an EV incorporating a new fuzzy controller to improve stability and safety by controlling the driver-input angle. Performance analysis focused on motor speed, torque, and differential speed. The CED setup served as a baseline, while the EPS filter was assessed for cornering stability, and the fuzzy controller for smoother torque distribution and reducing motor speed differences. This comparative study highlights the strengths and weaknesses of each strategy, offering insights into their impact on EV performance and stability. Results show that the EPS filter enhances cornering stability, while the fuzzy controller ensures smoother torque distribution and reduces motor speed differences. These contributions optimize EV propulsion systems, improving performance and safety.</p>","PeriodicalId":11673,"journal":{"name":"Energy Science & Engineering","volume":"14 9","pages":"4344-4361"},"PeriodicalIF":3.6,"publicationDate":"2026-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ese3.70582","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148943627","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Selecting Between Hydrogen and Methanol for Fuel Cell-Organic Rankine Cycle Hybrid Power Systems: A Comparative 4E Analysis","authors":"Zahra Piryaei,&nbsp;Maryam Karami,&nbsp;Iman Khazaee","doi":"10.1002/ese3.70575","DOIUrl":"https://doi.org/10.1002/ese3.70575","url":null,"abstract":"<p>Rising electricity demand and growing concerns over climate change underscore the urgent need for efficient and low-carbon power generation technologies. In this context, selecting the suitable fuel cell technology becomes critical to achieving both high technical performance and environmental sustainability. This study presents a comprehensive model for two different hybrid power generation systems: one comprising a hydrogen-fueled proton exchange membrane fuel cell (PEMFC) with an Organic Rankine Cycle (ORC) heat recovery system, and the other comprising a direct methanol fuel cell (DMFC) with ORC. A comparative assessment is conducted to investigate and compare the energetic, exergetic, economic, and environmental (4E) performance of these systems as a function of current density. Both systems are designed to produce the same peak electrical output (≈70 kW), allowing for a meaningful comparison. The 4E analysis reveals that PEMFC-ORC achieves greater energy efficiency (35% vs. 29%), while DMFC-ORC demonstrates superior exergy performance (55% vs. 42%) and a more favorable levelized cost of electricity ($0.27/kWh vs. $0.63/kWh). Nonetheless, DMFC-ORC incurs a significantly higher environmental burden, with annual CO₂-equivalent emissions nearly twice those of PEMFC-ORC. These identified trade-offs inform technology choices that align with the interconnected objectives of Sustainable Development Goal 7 (Affordable and Clean Energy) and Sustainable Development Goal 13 (Climate Action).</p>","PeriodicalId":11673,"journal":{"name":"Energy Science & Engineering","volume":"14 9","pages":"4248-4260"},"PeriodicalIF":3.6,"publicationDate":"2026-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ese3.70575","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148942080","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Urban–Rural Comparative Assessment of Hybrid Energy Systems in Southern Africa: A Systematic Review and Bibliometric Analysis","authors":"Kehinde A. Adeyeye,&nbsp;Charles Mbohwa","doi":"10.1002/ese3.70605","DOIUrl":"https://doi.org/10.1002/ese3.70605","url":null,"abstract":"<p>Urban electricity systems in Southern Africa are characterized by persistent grid unreliability, ageing infrastructure, and continued dependence on fossil fuels, despite substantial renewable energy potential. Hybrid energy systems (HES) have emerged as a pathway to enhance urban energy resilience, reduce costs, and support decarbonization. However, despite high urban electricity access, they remain underexplored relative to rural systems, limiting their role in addressing urban reliability challenges. This study presents a systematic review and cross-country synthesis of urban-rural HES deployments in Southern Africa between 2010 and 2025, focusing on dominant system configurations, modes of integration, sectoral applications, and techno-economic and environmental performance. Findings show that PV–battery(–grid) systems dominate urban deployments, particularly in South Africa. More complex systems incorporating biomass, hydrogen, pumped hydro, or concentrated solar power remain scarce in urban contexts. Reported levelized cost of electricity ranges from $0.009 to $1.13/kWh, with a mean of $0.18/kWh. Net present cost spans $662 to $111.8 million, while financial savings range from $30,207 to $953,564 (14.4%–69.3%). Environmental performance is more consistent, with CO₂ emission reductions of 56.8%–90.3% and renewable fractions of 42–100%. Overall, the urban HES demonstrates strong decarbonization potential alongside improved economic viability, while highlighting the need for standardized reporting and supportive policy frameworks.</p>","PeriodicalId":11673,"journal":{"name":"Energy Science & Engineering","volume":"14 9","pages":"4077-4094"},"PeriodicalIF":3.6,"publicationDate":"2026-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ese3.70605","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148943390","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Seepage Characteristics of Single Rough Joint of Granite Based on NMR Technology: A Modified Cubic Law","authors":"Hao Cheng,&nbsp;Xiujie Zhong","doi":"10.1002/ese3.70576","DOIUrl":"https://doi.org/10.1002/ese3.70576","url":null,"abstract":"<p>Understanding the seepage mechanisms of rough granite joints under stress–seepage coupling is essential for predicting fluid flow in jointed rock masses. In this study, seepage–stress coupling tests are conducted on granite specimens containing a single rough joint, and the fluid migration process is continuously monitored using low-field nuclear magnetic resonance (NMR). The evolution of the transverse relaxation time (<i>T</i>₂) spectra is used to characterize the dynamic change of joint aperture and pore connectivity. Results reveal that fluid migration follows a sequential path: preferentially entering large pores, then invading smaller pores under increasing seepage pressure, and finally refilling large pores after saturation. These transitions reflect the cyclic redistribution of water governed by asperity deformation and stress-induced joint closure or dilation. Quantitative analysis shows that permeability increases with higher seepage pressure and joint roughness coefficient (<i>JRC</i>) but decreases nonlinearly with confining pressure. Based on these observations, a modified cubic law is established by incorporating <i>JRC</i> and stress-dependent joint width correction, which accurately captures the nonlinear coupling between roughness, stress, and flow. This study provides new insights into the hydro-mechanical mechanisms controlling seepage evolution in rough granite joints.</p>","PeriodicalId":11673,"journal":{"name":"Energy Science & Engineering","volume":"14 9","pages":"4261-4281"},"PeriodicalIF":3.6,"publicationDate":"2026-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ese3.70576","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148942314","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Techno-Economic Analysis and Multi-Objective Optimization of a Novel Combined Cooling and Power System Driven by Geothermal Source and Waste Heat From Data Center","authors":"Zerui Chen,&nbsp;Xin Wu,&nbsp;Zhukui Tan,&nbsp;Jian Xiao,&nbsp;Nan Wang","doi":"10.1002/ese3.70579","DOIUrl":"https://doi.org/10.1002/ese3.70579","url":null,"abstract":"<p>The development of renewable energy and the recovery of data-center waste heat are important pathways toward green data centers. To address the limited integration of geothermal energy with low-grade data-center waste heat in existing cooling- or power-oriented systems, this study proposes a novel combined cooling and power (CCP) system featuring a strongly coupled organic Rankine cycle (ORC) and absorption refrigeration cycle (ARC). In the proposed configuration, geothermal water is cascade-utilized to drive the ORC evaporator and the ARC generator, while data-center waste heat, together with the heat rejected from the absorption side, is further recovered for low-temperature preheating of the ORC working fluid. The effects of working-fluid selection and key design parameters on thermodynamic and economic performance are investigated, followed by multi-objective optimization, exergy-loss analysis, benchmark comparison, and economic sensitivity analysis. Results show that R245fa provides the best thermodynamic performance in the parametric study, while R601a achieves the most favorable trade-off within the present thermo-economic framework. Under the optimal operating condition, the system reaches an exergy efficiency of 40.34%, an annual cost of 130.29 k$/year, and a static payback period of 4.62 years. Compared with a simplified reference system, the proposed integrated configuration increases the net power output from 274.31 to 286.97 kW and improves the exergy efficiency from 38.69% to 40.34% with nearly unchanged cooling capacity. In addition, simplified part-load analysis indicates stable power output under moderate waste-heat fluctuation, while economic sensitivity analysis shows that electricity price and annual operating hours are the dominant factors affecting economic viability.</p>","PeriodicalId":11673,"journal":{"name":"Energy Science & Engineering","volume":"14 9","pages":"4300-4315"},"PeriodicalIF":3.6,"publicationDate":"2026-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ese3.70579","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148942685","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluation of Drillability of the Mahu Conglomerate Formation in Xinjiang, China","authors":"Yun Xia,&nbsp;Wan Zhu,&nbsp;Rui Chen,&nbsp;Hui Zhang,&nbsp;Boyuan Yang,&nbsp;Kunhong Lv,&nbsp;Baokang Wu,&nbsp;Xinrui Wang,&nbsp;Hu Wu","doi":"10.1002/ese3.70597","DOIUrl":"https://doi.org/10.1002/ese3.70597","url":null,"abstract":"<p>The conglomerate formation in China's Mahu oilfield is characterized by complex lithology, gravel development, and strong non-homogeneity, resulting in difficult bit selection, low mechanical drilling speed, long drilling cycle, and difficulty in evaluating its formation drillability by conventional methods. In this paper, the relationship models of gravel volume content, median particle size, uniaxial compressive strength, and conglomerate drillability value of PDC bit are discussed; a conglomerate drillability logging evaluation model and a depth neural network prediction model are established based on logging data and depth learning method. The results show that the drillability value of PDC bit conglomerate is linearly related to the volume content of conglomerate, logarithmically related to the median size of conglomerate, and power function related to the uniaxial compressive strength of conglomerate, and the prediction accuracy of the model ranges from 80.8% to 96.8%, with an average accuracy of 91.2%. The deep learning method can predict the drillability of PDC bits in conglomerate formations more accurately and provide a basis for bit selection and drilling parameter optimization in conglomerate formations, thus improving drilling efficiency in conglomerate formations.</p>","PeriodicalId":11673,"journal":{"name":"Energy Science & Engineering","volume":"14 9","pages":"4095-4112"},"PeriodicalIF":3.6,"publicationDate":"2026-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ese3.70597","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148942485","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}