Cellulose nanoparticles are attracting interest in diverse fields because of their availability, low cost, and benign nature. Albeit previous studies have reported excellent experimental results, the application of cellulose nanoparticles in oilfield remains a challenge. Therefore, the objective of this research is to provide vital information on how to design cellulose nanoparticles for oilfield applications. Herein, the sources of cellulose and their derivatives were presented. Subsequently, cellulose pretreatment and extraction methods were elucidated. Likewise, the design of cellulose nanoparticles for oilfield applications were discussed. Also, the enhanced oil recovery (EOR) mechanisms of cellulose nanoparticles for high temperature high pressure (HTHP) reservoirs were identified and their application in EOR was reviewed. The challenges hindering full scale field application of cellulose nanoparticles were presented while concurrently shedding light on diverse methodologies employed to maintain their stability in HTHP oil reservoirs. The results indicate that wettability alteration, asphaltene precipitation, interfacial tension and viscosity reduction are the dominant EOR mechanisms by cellulose bionanomaterials, it also demonstrate that cellulose bionanomaterials can increase the viscosity of injected fluidby 10–100%, improve sweep efficiency by 52–98% and improve oil recovery by 10–35% original oil in place. It can be concluded that bionanomaterial have potential for oil field applications and are economically viable due to their high recovery rate.

Oil reservoirs subjected to a gas recovery technique are commonly challenged by early gas break-throughs affecting the production rate. Foam is injected to block and divert gas to reservoir sections, however, achieving this mechanism requires stable foam to withstand extreme reservoir conditions, such as temperature, pressure and salinity. In this work, synergy actions between amino-propyltriethoxysilane doped SiO₂ nanoparticles (NPs) and MFomax were investigated on rheology, interfacial tension (IFT), wettability, foam stability and quality to reduce gas mobility and enhance oil recovery (EOR). The formulation was guided by optimization, and the foam studies were carried out at optimum concentrations. Core-flood equipment was used to assess the gas mobility reduction factor (MRF) and EOR. From the findings, the foamability of the nanofluidis primarily governed by synergy action between the NPs and MFomax due to significant R² value (0.9; p < 0.05). Presence of NPs in the formulation resulted in good fluid properties such viscosity and IFT. The nanofoam stability has improved tremendously to 119% relative to MFomax foam. According to the IFT and contact angle, the detachment energy of the NPs (1.4 × 10⁸ eV) is higher than 1 eV suggesting strong adsorption at aqueous interface leading to foam stability. The nanofoam reached a maximum of 50 MRF, while MFomax was below 40 MRF. Subsequently, all the foam descended to lower quality regions around 5 PVI due to the change in foam morphology. Furthermore, the EOR recorded by nanofoam demonstrates a 7% increase on top of MFomax recovery factor. Thus, it can be deduced that the synergy of SiO₂ NPs with MFomax offer several benefits in improving the foam stability, quality, MRF and EOR.

This study uses 13 proprietary data sets from sedimentary basins around the globe to constrain the permeability and porosity ranges occupied by clastic rocks (sandstones and shale). The combined data sets represent a total sample size of 21,767 data pairs of measured porosity and permeability. The data are combined in various ways and analyzed in considerable detail, in what is presently assumed the most comprehensive permeability analysis of clastic data sets. First, comprehensive porosity-permeability transforms are plotted with the aim to understand how well the two quantities actually correlate, and what may be the root cause(s) of the huge variation in their correlation. The analysis of the empirical data is embedded in a review of prior work related to permeability transforms. The Kozeny-Carman relationship is revisited and a modified scaling approach is proposed. First, it is shown how hydraulics of pore tubes of various shapes and tortuosity relate to macroscopic permeability. The key scaling factor, called here the permeability-reduction factor, β=τ, is the ratio of the coefficient of hydraulically effective pore space, β, and the tortuosity, τ. Whereas it is concluded that the porosity is a very poor predictor of the permeability, there appears to exist a close relationship between the permeability-reduction factor and the permeability, confirming the fundamental physical nature of β=τ as an excellent predictor of hydraulic transmissibility in porous media made up of sedimentary mineral aggregates. The inferred relationship provides the basis for a new method to construct permeability transforms, from bootstrapped data sets, using Monte-Carlo simulation.

Produced water is the largest waste stream generated during oil and gas production, presenting significant environmental risks due to its complex chemical composition. Characterizing the contaminant profile of produced water is crucial for assessing its environmental impact, ensuring compliance with discharge standards, and developing effective pollution mitigation strategies. This study characterizes untreated produced water from Angolan offshore Block 15 over a 50-day sampling period, analyzing over 30 target constituents. Results reveal substantial variability in key parameters, including chemical oxygen demand (394.02–526.00 mg/L), biochemical oxygen demand (9.80–20.40 mg/L), phenol (2.70–4.12 mg/L), benzene, toluene, ethylbenzene and xylene (BTEX, 2.77–7.00 mg/L), polyaromatic hydrocarbons (0.20–1.20 mg/L), total organic compounds (248–918.45 mg/L), total oil and grease (19–206 mg/L), and total petroleum hydrocarbons (12–105.02 mg/L). Metals and anions exhibited significant fluctuations, with sodium ranging from 1167.77 to 2100.00 mg/L and chloride from 400 to 2146.84 mg/L. The biodegradability index (0.028) indicates limited potential for biological treatment due to toxic and refractory organics. The results emphasize the necessity for advanced treatment technologies and stricter environmental regulations to reduce contaminant discharge and minimize the ecological footprint of offshore oil production.

The Paleocene marked a critical structural transition period from tectonic subduction to extensional rifting in the Bohai Bay Basin. To reconstruct the spatiotemporal structural framework, evolutionary process, and basin prototype during the Paleocene Kongdian period of the Dongying Depression in the eastern Bohai Bay Basin, this study integrated seismic interpretation, core observation, ⁴⁰Ar/³⁹Ar dating, and structural restoration. The ⁴⁰Ar/³⁹Ar dating of basalts (approximately 57.58 ± 0.77 Ma) revealed that the depression entered an active rifting stage with intense volcanism in the early Paleocene Kongdian period. Regional faults, including the Chennan, Wangjiagang Shicun, and Gaocheng faults, were well developed during the first member of the Kongdian sedimentary stage. Their activity indicates rapid rift expansion and resulted in a half-graben pattern characterized by faulting in the north and onlap in the south. Structural restoration showed that the stretching ratio during the Paleocene Kongdian period was approximately 7.3%, which reflects rapid rifting. The development of the early Paleocene rift has important implications for deep hydrocarbon exploration in the Bohai Bay Basin.

Underground hydrogen storage (UHS) in saline aquifers is a promising solution for large-scale, long-duration energy storage in a low-carbon energy system. Cushion gases, such as N₂, CO₂, and CH₄, are commonly used to regulate reservoir pressure and enhance storage efficiency. However, despite recent advancements in understanding the interfacial tension (IFT) behavior of H₂–gas mixtures in contact with brine under reservoir conditions, key gaps persist in systematic data for H₂–cushion gas mixtures (e.g., with N₂, CO₂, and CH₄) across specific thermophysical ranges, despite its influenceon capillary sealing, gas mobility, and recovery. This study presents systematic experimental measurements of IFT and density for H₂–N₂, H₂–CO₂, and H₂–CH₄ gas mixtures (70:30 mol%) with both distilled water and brine (30,000 ppm NaCl) at different temperatures (25, 50, and 70 °C) and pressures (1, 5, and 10 MPa). The IFT was measured using a high-pressure, high-temperature drop tensiometer, and density was obtained via an Anton Paar DMA 4500 densitometer. Results show a consistent decrease in IFT with rising temperature and pressure across all systems. Notably, the H₂–CH₄ mixture exhibited an IFT of 69.4 mN/m in distilled water at 25 °C and 1 MPa, decreasing to 57.3 mN/m at 70 °C; in contrast, the same mixture in 30,000 ppm brine showed a larger reduction from 61.3 mN/m to 47.8 mN/m under identical conditions, highlighting the amplifying effect of salinity on IFT decline. Among the gas mixtures, CH₄ yielded the approximately lowest overall IFT values, favoring injectivity, whereas N₂ maintained the highest IFT, supporting enhanced capillary retention. These findings address a critical data gap for realistic cushion gas performance and provide foundational insight for modeling UHS in saline aquifers.

The low production of tight gas reservoirs arises from complex and multifaceted causes, and elucidating these factors is crucial for guiding the formulation of effective stimulation strategies. Conventional analytical methods predominantly emphasize the role of individual factors, thereby lacking necessary systematic and integrative perspective to comprehensively reveal underlying mechanisms of poor well performance. To overcome these limitations, a comprehensive diagnostic approach is proposed to identify controlling factors of low production in multilayer tight gas reservoirs. Taking three typical cluster well groups of LX tight gas reservoirs in the Ordos Basin as examples, the causes for the low production of the gas wells were analyzed from different aspects by using geological, engineering, and developmental data after excluding the special reasons such as defects in drilling and completion process, reservoir water lock, and water floding. The results show that the main causes for the low production of gas wells in LX reservoirs include fewer exploited gas layers, poor physical properties, poor fracturing and fracture making effects, and insufficient formation energy. In addition, corresponding treatment measures such as reperforation and refracturing were proposed. Finally, effects of the measures in the two low-yield wells where the reperforation was implemented were analyzed: the production and Tubing-head pressure increased significantly, and the low-yield wells were transformed into non-low-yield wells with good results. The results of the measures demonstrate the feasibility of the new method.

The Cretaceous Sarvak Formation in the Zagros Basin exhibits complex reservoir heterogeneity controlled by depositional facies and sequence stratigraphy-constrained diagenesis. This study integrates petrographic and petrophysical analyses of an Abadan Plain oilfield to establish predictive relationships between microfacies, diagenesis, and automated hydraulic flow units (HFUs). Eight microfacies were identified, representing four depositional environments: open marine, shoal complex, patch-reefs, and lagoon, supporting a ramp model. Reservoir quality varies systematically across four HFU classes, ranging from poor (HFU1: 0–0.1 FZI, 2.76 mD permeability, 10.85% porosity) to excellent (HFU4: >0.7 FZI, 45.99 mD permeability, 17.4% porosity). Diagenetic processes show distinct relationships with sequence stratigraphy: marine cementation dominates transgressive systems tracts, while meteoric dissolution and fracturing prevail in regressive systems tracts and at sequence boundaries. Maximum floding surfaces record chemical compaction and authigenic mineralization. Facies-selective diagenesis primarily controls reservoir quality. Grain-supported facies develop dissolution-enhanced porosity, whereas mud-dominated facies experience porosity reduction through cementation and compaction. Dolomitization and fracturing provide secondary permeability enhancement, particularly in mid-ramp settings. HFU clasification reveals optimal reservoir performance in zones where dissolution and fracturing enhance pore networks (HFU3–HFU4). In contrast, non-reservoir zones (HFU1–HFU2) are affected by extensive cementation and compaction. These findings highlight the predictive potential of integrating sequence stratigraphy with diagenetic analysis for reservoir characterization in carbonate systems. The established facies-to-diagenesis relationships provide a robust framework for understanding reservoir heterogeneity and fluid flow behavior in the Sarvak Formation and analogous carbonate reservoirs.

The integrity of welded X65 carbon steel (CS) pipelines in oil and gas systems is significantly compromised by preferential weldment corrosion (PWC) and pitting in sour conditions. This study clarifies that the effect of pre-corrosion conditioning and inorganic deposits (SiO₂ or CaCO₃) on welded CS pipelines, with SiO₂ deposits leading to the most substantial damage at weld metal (WM) and heat-affected zone (HAZ) relative to parent metal (PM). Due to localized acidification and differences in potential, corrosion rates (CRs) hierarchies are SiO₂-deposited > CaCO₃-deposited > non-deposited. Microstructural analysis reveals that deposited CS-WM has carbide redistribution and increase residual stress from the welding thermal process, with increased aggressive species and stabilized iron oxides, leading to intensified PWC. However, amine-based inhibitor CRW11 suppresses the CRs below 0.1 mmpy through chemisorbed films that disrupt microgalvanic coupling and protective corrosion product layers with inhibition efficiency (IE > 85%). CS-PM-CaCO₃ has a high pit depth (68.3 ± 2.7 μm) and propagation rate (1.2 ± 0.2 mmpy), making it the most vulnerable region to pitting relative to CS-WM-CaCO₃ (52.5 ± 1.1 μm; 0.9 ± 0.1 mmpy) and CS-HAZ-CaCO₃ (29.3 ± 0.6 μm; 0.5 ± 0.1 mmpy). This proves that CaCO₃ deposit on welded CS creates a physical barrier for the surface nucleation effect and improves anodic dissolution. Machine learning models (Random Forest (RF), Decision Tree (DT), Gradient Boosting (GB), and Extreme Gradient Boosting (XGBoost)) accurately predict IE (R² = 0.99). However, RF performs best for data without deposits (RMSE = 0.9), while DT is most appropriate model for those with SiO₂ and CaCO₃ deposits (lowest RMSE = 0.5 and 0.2). These findings provide coupled electrochemical, microstructural, and machine learning frameworks for PWC mitigation, allowing for adaptive corrosion management methods in sour service pipes and material designs optimized for topology.

Accurate reservoir characterization is essential for optimizing hydrocarbon exploration and production, particularly in complex deep-water environments. The Simsat Field, Offshore Nile Delta, features a Pliocene deep-water turbidite reservoir, primarily composed of interbedded sand channels and shale, which poses significant challenges for reservoir delineation due to lateral lithological variations, limited well control, and complex stratigraphic architecture. Traditional seismic interpretation methods often struggle to capture the heterogeneity and connectivity of these reservoirs, leading to uncertainties in hydrocarbon prospect evaluation. To address these challenges, this study integrates seismic attributes, post-stack seismic inversion, and a multi-layer feed-forward neural network (MLFN) to enhance quantitative reservoir characterization. This integrated approach outperforms the limitations of individual techniques by combining the spatial resolution of seismic attributes, the lithology-fluid sensitivity of inversion, and the non-linear predictive capabilities of machine learning. The workflow provides a synergistic solution that improves property prediction accuracy and reduces interpretation uncertainty, particularly in data-limited, structurally complex settings. Spectral decomposition improves the visualization of channel morphology and stratigraphic variations, while seismic inversion generates acoustic impedance volumes that aid in lithology differentiation and fluid detection. The MLFN model, trained using well log data and multiple seismic attributes, provides high-accuracy predictions of shale volume (Vsh), porosity, and water saturation, significantly improving the assessment of reservoir quality. The results confirm a wel-defined gas-bearing sandstone reservoir with high porosity (>18%) and low water saturation, indicating strong hydrocarbon potential. This integrated approach demonstrates the effectiveness of combining advanced seismic interpretation with machine learning techniques to reduce interpretation uncertainties, improve reservoir connectivity analysis, and optimize field development strategies in the West Delta Deep Marine (WDDM) concession. The findings provide valuable insights into reservoir heterogeneity and contribute to more effective hydrocarbon exploration and production in the Offshore Nile Delta.