In recent decades, the global generation of solid oil-containing sludge has increased significantly. Such wastes represent a valuable secondary resource due to high contents of petroleum hydrocarbons, water, and mineral impurities. However, their heterogeneous composition and complex multiphase structure hinder direct utilization and disposal, which makes the selection of appropriate pretreatment methods a critical step in their processing. This article presents a systematic review of pretreatment technologies for solid oil-containing sludge, with a particular focus on grinding, sorting, and beneficiation methods. The advantages and limitations of these methods are analyzed, and promising directions for further technological development are identified. The implementation of integrated pretreatment approaches can facilitate the transition of solid oil-containing sludge from environmentally hazardous waste to valuable secondary resources, thereby promoting resource efficiency and reducing environmental impact.
Fracturability evaluation in naturally fractured reservoirs is essential for optimizing hydraulic fracturing design and enhancing hydrocarbon recovery efficiency. This study proposes a comprehensive fracturability evaluation method based on geology–engineering integration, incorporating key controlling factors including rock brittleness, fracture initiation and propagation capacity, in-situ stress contrast, and natural fracture intensity, with their relative weights quantitatively determined using the Analytic Hierarchy Process (AHP). A major contribution of this work lies in the improved characterization of natural fracture intensity through the integration of seismic interpretation and conventional well-logging data, enabling the construction of a more reliable three-dimensional fracture model. Based on this framework, a three-dimensional fracturability evaluation model is established to quantitatively describe the spatial distribution of reservoir stimulation potential. The method is applied to a typical low-permeability fractured oilfield, where results demonstrate a strong positive correlation between the calculated fracturability index and actual production performance, thereby validating the reliability and applicability of the proposed approach. The findings provide a robust and practical basis for hydraulic fracturing design and optimization in naturally fractured reservoirs, with significant implications for field-scale development planning.
Results are presented for a study of the properties of adsorbents obtained by the sulfonation of wild blackthorn seed shells using sulfuric acid under various conditions. Nitric acid treatment of the sulfonated adsorbent gave an increase in static exchange capacity from 3.2 to 3.7 meq/g. The structural and functional group composition of the adsorbents was characterized by FTIR spectroscopy. The thermal stability, surface morphology, and acid-base surface properties were determined for the most useful samples along with the adsorption capacity and their efficiency in the removal of divalent cations from binary nickel-cadmium and mercury-lead solutions. A pseudo-second-order model was used to accurately describe the adsorption kinetics. The complementary use of the Boyd kinetic model with the Weber-Morris intraparticle diffusion model showed that the adsorption proceeds through a mixed-diffusion mechanism. The introduction of a nitro group into the sulfonated adsorbent improves the adsorption kinetics of the heavy metal cations studied.
In response to the urgent need for energy conservation and consumption reduction in the oil and gas storage and transportation system under the dual carbon goal, this paper aimed to solve the problem of calculation deviation caused by parameter drift in traditional mechanism models under complex working conditions such as equipment aging and environmental variability. Based on the massive SCADA data of an 850 km wax-containing crude oil pipeline, a PSO-CNN-LSTM-Attention combined energy consumption prediction model optimized by the particle swarm algorithm was constructed. The research results showed that this model achieves a 98
In this study, a computational molecular modeling framework was established by integrating force-field-based molecular dynamics simulation, trajectory analysis algorithms, mean square displacement calculation, radial distribution function analysis, and spatial concentration profiling. These computational algorithms were used to quantitatively characterize the diffusion behavior, aggregation tendency, interaction distance, and microstructural evolution of heavy oil components in ionic liquid–solvent systems. The interaction mechanism between [Emmim][NTf2] ionic liquid and five organic solvents (acetone, toluene, methylcyclohexane, carbon tetrachloride, ethyl acetate) and four components of heavy oil (saturated, aromatic, colloidal, and asphaltene) was studied by molecular dynamics simulation. The dynamic evolution of molecular diffusion behavior, interaction intensity and microstructure in different systems was revealed. The results show that the saturation fraction has the strongest diffusion ability due to its simple structure and small molecular weight. The addition of ionic liquid [Emmim][NTf2] significantly changed the interaction mode of the system: in the saturated subsystem, its diffusion resistance was the smallest; In the aromatic subsystem, the ϖ-cationic action inhibits its movement. In colloidal and asphaltene systems, strong polar interactions lead to hindered diffusion. In addition, solvent properties have an important influence on system behavior: polar solvents bind to components by dipolar action, while non-polar solvents rely on van der Waals forces and π-π accumulation. The energy and temperature equilibrium analysis showed that all systems reached a steady state within 2000 ps, which verified the reliability of the simulation. This study provides a theoretical basis for the application of ionic liquids in heavy oil modification and solvent extraction, reveals the interaction mechanism at the molecular scale, and has guiding significance for optimizing process conditions.
