Petroleum最新文献

{"title":"Corrigendum regarding incomplete Declaration of Competing Interest statements in previously published articles","authors":"","doi":"10.1016/j.petlm.2026.08.011","DOIUrl":"10.1016/j.petlm.2026.08.011","url":null,"abstract":"","PeriodicalId":37433,"journal":{"name":"Petroleum","volume":"12 4","pages":"Page 783"},"PeriodicalIF":5.5,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148948944","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":"Corrigendum regarding incomplete Declaration of Competing Interest statements in previously published articles","authors":"","doi":"10.1016/j.petlm.2026.08.007","DOIUrl":"10.1016/j.petlm.2026.08.007","url":null,"abstract":"","PeriodicalId":37433,"journal":{"name":"Petroleum","volume":"12 4","pages":"Pages 775-776"},"PeriodicalIF":5.5,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148948947","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":"Corrigendum regarding incomplete Declaration of Competing Interest statements in previously published articles","authors":"","doi":"10.1016/j.petlm.2026.08.005","DOIUrl":"10.1016/j.petlm.2026.08.005","url":null,"abstract":"","PeriodicalId":37433,"journal":{"name":"Petroleum","volume":"12 4","pages":"Pages 771-772"},"PeriodicalIF":5.5,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148948950","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":"Gas condensate recovery in carbonate rocks through wettability alteration: Characterization and optimization by response surface methodology (RSM)","authors":"Fatemeh Kazemi,&nbsp;Reza Azin,&nbsp;Shahriar Osfouri","doi":"10.1016/j.petlm.2026.05.001","DOIUrl":"10.1016/j.petlm.2026.05.001","url":null,"abstract":"<div><div>Liquid blockage around the wellbore region can significantly decrease the gas and condensate extraction volume from a condensate reservoir. In these kinds of reservoirs, the rock surfaces are commonly liquid-wet. Treatment to alter rock preference from liquid to gas is a versatile, permanent, and effective technique for recovery enhancement. A novel chemical solution containing fluorosurfactant and nanoparticles is suggested to modify the wettability of carbonate rock. The hydrophobicity of nano silica is achieved using (3-chloropropyl) trimethoxy silane. The chemical solution can provide a gas-wetting tendency in rock samples by inducing a combination of high surface roughness and low surface energy. Modification of wettability by this chemical was confirmed through static contact angle experiments. FTIR and FESEM were used to study the adsorption of the chemical agent on the rock surface, while EDX analysis and EDX map were employed to characterize the elemental composition of the rock surface and determine the distribution of elements on the coated surface before and after treatment. To determine the effective parameters of the chemical treatment process including fluorosurfactant and nanoparticle concentration, treatment time, and temperature, statistical analysis was conducted through analysis of variance (ANOVA) on the modified cubic model for two response variables, water contact angle (R1) and condensate contact angle (R2). The R² values of 0.9973 for the water contact angle and 0.9893 for the condensate contact angle represent a close agreement between measured and estimated values. Process parameter optimization was conducted using a desirability function to maximize the response variables associated with the liquid-repellent state. The optimal parameters for the process were identified as fluorosurfactant concentration of 4.96 wt%, SiO₂ nanoparticle concentration of 0.76 wt%, treating time of 2.49 days, and treating temperature of 23.24 °C. To validate the optimization method, a confirmatory experiment was conducted. This experiment achieved the highest water and condensate contact angles of 148.10° and 112.82° under the optimized conditions. The EDX analysis and EDX mapping imply that a homogeneous and evenly distributed fluorine-based layer formed on the rock surface through the adsorption of the chemical agent onto the surface of the rock. This layer induces liquid repellency, making the rock surfaces resistant to both water and oil. Also, the FESEM images indicate a substantial level of roughness on the treated rock surface, attributed to the presence of nanoparticles. FTIR analysis confirmed the adsorption of chemical agents onto the surface of the carbonate rock and presence of carbon and fluorine functional groups within the proposed chemical solution agents.</div></div>","PeriodicalId":37433,"journal":{"name":"Petroleum","volume":"12 4","pages":"Pages 629-653"},"PeriodicalIF":5.5,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148948892","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":"CO2 enhanced shale oil and carbon sequestration in kerogen nanopores: A molecular dynamics study","authors":"Tianyu Wang,&nbsp;Kangjian Tian,&nbsp;Ning Li,&nbsp;Zhengchao Ma,&nbsp;Junkai Zhang,&nbsp;Shouceng Tian,&nbsp;Gensheng Li","doi":"10.1016/j.petlm.2026.04.012","DOIUrl":"10.1016/j.petlm.2026.04.012","url":null,"abstract":"<div><div>Carbon dioxide (CO₂) injection is a promising strategy for enhancing shale oil recovery while enabling geological carbon storage. In this study, non-equilibrium molecular dynamics (NEMD) simulations were employed to investigate CO₂-driven shale oil transport in kerogen nanopores with complex surface characteristics. The distribution and migration behaviors of multiphase shale oil were analyzed, and the effects of pore size, temperature, and injection pressure on fluid flow and CO₂ sequestration were systematically evaluated. The results show that shale oil forms three distinct adsorption layers within kerogen nanopores, with the first layer exhibiting a peak density of approximately 1.13 g/cm³, which is about 1.85 times higher than that in the free region. The irregular kerogen surface increases the resistance to shale oil desorption, resulting in slower CO₂-driven displacement compared with smooth graphene pores. Increasing pore size, temperature, and injection pressure significantly promotes shale oil desorption and enhances CO₂ storage capacity. For example, when the pore size increases from 2 nm to 5 nm, the shale oil adsorption fraction decreases markedly while CO₂ storage increases significantly. Temperature also plays an important role in regulating adsorption and sequestration behavior. Overall, this study reveals the molecular-scale mechanisms governing CO₂-enhanced shale oil mobilization and carbon sequestration in kerogen nanopores, providing theoretical insights for optimizing CO₂ injection strategies in shale reservoirs.</div></div>","PeriodicalId":37433,"journal":{"name":"Petroleum","volume":"12 4","pages":"Pages 654-666"},"PeriodicalIF":5.5,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148948893","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":"Corrigendum regarding incomplete Declaration of Competing Interest statements in previously published articles","authors":"","doi":"10.1016/j.petlm.2026.08.003","DOIUrl":"10.1016/j.petlm.2026.08.003","url":null,"abstract":"","PeriodicalId":37433,"journal":{"name":"Petroleum","volume":"12 4","pages":"Pages 767-768"},"PeriodicalIF":5.5,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148948948","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":"Corrigendum regarding incomplete Declaration of Competing Interest statements in previously published articles","authors":"","doi":"10.1016/j.petlm.2026.08.002","DOIUrl":"10.1016/j.petlm.2026.08.002","url":null,"abstract":"","PeriodicalId":37433,"journal":{"name":"Petroleum","volume":"12 4","pages":"Pages 765-766"},"PeriodicalIF":5.5,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148948953","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":"Impact of inlet velocity on non-Darcian-Forchheimer oil flow in porous media: A numerical approach","authors":"Asseel M. Rasheed Al-Gaheeshi,&nbsp;Farhan Lafta Rashid,&nbsp;Hayder I. Mohammed,&nbsp;Raad Z. Homod,&nbsp;Hussein Togun","doi":"10.1016/j.petlm.2026.06.001","DOIUrl":"10.1016/j.petlm.2026.06.001","url":null,"abstract":"<div><div>Predicting fluid behaviour accurately is crucial for optimising extraction methods in petroleum engineering due to the considerable hurdles posed by the non-Darcian flow of oil through porous surfaces. This work utilises numerical methodology employing COMSOL Multiphysics to model the movement of oil through different types of porous materials. The main aim is to investigate the impact of inlet velocities and material properties on flow behaviour. This research is unique because it thoroughly investigates flow dynamics, using the Forchheimer equation to represent nonlinear flow behaviour accurately. Traditional models generally overlook this aspect. The main objectives were to clarify the connections between flow velocity, pressure drop, and friction factors across various porous materials. The main result is that the friction factor for SiLi beads reached 1.89 when the velocities exceeded 1 m/s, which indicates a shift to turbulent flow. When the inlet velocity was set to 2 m/s, the glass balls exhibited a maximum axial velocity of around 2.0231 m/s, indicating that they offered the least resistance to the flow. The pressure differential over SiLi beads was measured at 7.11 × 10⁸ Pa when the flow velocity was 10 m/s, while gravels exhibited a pressure drop of 0.52 × 10⁸ Pa and glass balls had a pressure drop of 0.15 × 10⁸ Pa. These findings emphasise the crucial significance of considering non-Darcian effects when modelling oil flow through porous surfaces, as they have a major impact on extraction efficiency. Gaining insight into these processes can enhance oil extraction rates and more efficient resource management, rendering this research vital for progress in petroleum engineering and associated disciplines.</div></div>","PeriodicalId":37433,"journal":{"name":"Petroleum","volume":"12 4","pages":"Pages 684-697"},"PeriodicalIF":5.5,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148948838","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":"Permeability prediction of tight sandstone reservoirs under few-shot and imbalanced conditions: A generative data enhancement and bi-directional attention fusion framework","authors":"Zhenyu Pang,&nbsp;Yuqing Lu,&nbsp;Zhicong Chen,&nbsp;Sijie Lu,&nbsp;Zhenbo Cai","doi":"10.1016/j.petlm.2026.04.010","DOIUrl":"10.1016/j.petlm.2026.04.010","url":null,"abstract":"<div><div>Permeability prediction in tight sandstone reservoirs is strongly influenced by diagenesis, multiscale pore structures and multiphase flow effects, resulting in pronounced spatial heterogeneity. Traditional empirical models based on homogenization assumptions suffer from inherent physical limitations, making their predictive accuracy insufficient for practical applications. Although existing data-driven deep learning methods offer advantages in nonlinear modeling, their performance is constrained by few-shot samples, imbalanced distributions, low-density information and the absence of physical constraints, which hinder the extraction of effective representations of inter-features and lead to biased learning and physical deviations. To address these challenges, this study proposes a framework including a data enhancement strategy based on high-order feature construction for quality improving and adversarial generation for quantity expanding, and a deep learning model termed DAFM-PI, which integrates bidirectional attention fusion with physical information constraints. Experimental results show that the test accuracy <em>R</em>² of DAFM-PI improves from 0.444 before enhancement to 0.969 after that, representing a 52.2% improvement. Furthermore, compared with conventional POR-LR, ResNet, and Transformer Encoder models, DAFM-PI achieves accuracy improvements of 61.9%, 18.1%, and 6.2%, demonstrating its effectiveness in enhancing both prediction accuracy and generalization for permeability prediction in tight sandstone reservoirs.</div></div>","PeriodicalId":37433,"journal":{"name":"Petroleum","volume":"12 4","pages":"Pages 698-710"},"PeriodicalIF":5.5,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148948839","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":"A review on functional group chemistry and structure-to-function design for mechanism-centric nanoparticle EOR","authors":"Seyed Masoud Ghalamizade Elyaderani,&nbsp;Tarek Al-Arbi Ganat","doi":"10.1016/j.petlm.2026.04.001","DOIUrl":"10.1016/j.petlm.2026.04.001","url":null,"abstract":"<div><div>A significant challenge in advancing nanoparticle-based enhanced oil recovery (EOR) is the gap between synthesis and application. Many reviews catalog surface modification techniques but fail to explain why specific molecular features lead to success in EOR mechanisms. Our work addresses this gap by providing a mechanism-centric framework focused on structure-to-function relationships. This approach is vital because while nano-EOR promises to overcome the drawbacks of traditional recovery, the base nanoparticles themselves are often ineffective. Their low stability and poor interfacial performance in challenging reservoir environments necessitate surface functionalization. Instead of focusing on modification methods, we analyze how the deliberate addition of chemical groups like sulfonates, carboxylates, hydroxyls, amines, and alkyl chains directly impacts core EOR functions, including reducing interfacial tension (IFT), altering rock wettability, stabilizing emulsions and foams, and enhancing viscoelasticity. By elucidating the underlying molecular interactions (electrostatic, hydrogen bonding, hydrophobic), we build a clear pathway from chemical design to functional outcome. This review extends to advanced applications, including trigger-responsive smart nanoparticles and asphaltene inhibition. Ultimately, we provide a comparative analysis and a selection guide to empower researchers to rationally design nanoparticles for specific reservoir challenges, thereby accelerating the field's transition from empirical testing to predictive engineering.</div></div>","PeriodicalId":37433,"journal":{"name":"Petroleum","volume":"12 4","pages":"Pages 562-577"},"PeriodicalIF":5.5,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148948841","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}