This paper is focused on the investigation of the use of laser-induced techniques to enhance the dissolution of BaSO4, SrSO4, and their mixtures in alkaline diethylenetriaminepentaacetic acid solution. A pulsed Nd:YAG laser was used. A comparison between a conventional heating plate and laser-induced heating was conducted, as well as in static and dynamic solutions. The test duration was 4 hr, with aliquots sampled at hourly intervals, and the kinetic dissolution was monitored by Sr/Ba solution determination. Laser irradiation enhanced the solubility of individual salts by 15%, mainly due to thermal effects. In mixed systems, the common ion effect was observed, where increased SrSO4 solubilization reduced BaSO4 dissolution under laser exposure. Despite the presence of salts and chelating agents reducing laser energy absorption by similar to 30%, the resulting temperature increase of 8 degrees C further enhanced dissolution rates. Although the 1,064 nm laser wavelength could heat water, it was not ideal for maximizing interaction with the solvent. Future efforts should prioritize lasers with wavelengths that better interact with water and possess sufficient power, allowing integration into scale removal tools and enhancing treatment efficiency via sustained solvent heating, mainly in deepwater offshore environments where low temperatures limit chemical treatment efficiency.
Conical polycrystalline diamond compact (PDC) cutters possess a unique 3D cutting structure and exhibit superior rock-breaking performance in hard formations through plowing. However, the rock-breaking characteristics and laws of worn conical PDC cutters remain poorly understood. In this study, a numerical model of worn conical PDC cutters under penetration-cutting conditions was established to analyze cutting force, penetration depth, temperature distribution and rock stress. The effects of wear height and weight on bit (WOB) on tangential force, penetration ability and MSE were systematically investigated. Results show that worn cutters present significant cutting force fluctuations in the penetration stage and break rock via edge shearing, forming discontinuous trapezoidal cross-section cutting grooves. With increasing wear height, cutter temperature decreases by 22% under 800 N WOB, temperature concentration shifts from the rear to front of the wear surface, and tangential force positively correlates with the cutter-rock tangential projection area. Within 0-1.0 mm wear height, tangential force rises, MSE declines and penetration ability improves; WOB increases tangential force and penetration depth with little impact on MSE. Severe blunting at 1.5 mm wear height leads to a sharp drop in rock-breaking efficiency. These findings provide theoretical guidance for the development of conical PDC bits and the extension of their service life.
Oil well anomaly detection is important to maintain operational safety and efficiency in oil production. Multiclass classifiers often force unknown data into predefined categories, potentially missing novelties that occur in real operations. This work addresses this limitation by developing a one-vs-all ensemble of binary Long Short-Term Memory (LSTM) classifiers to detect specific anomalies while maintaining the ability to identify unknown anomaly classes. The methodology uses operational data from temperature and pressure sensors, creating binary classifiers targeting one specific anomaly each against all other conditions. Validation is performed using the 3W dataset containing real-world oil well data with nine different anomaly types. The ensemble model achieves 87% overall accuracy, with hydrate formation detection reaching 90% accuracy. Compared to other approaches studied, the binary ensemble outperforms multiclass LSTM (87% vs 86%) and significantly exceeded One-Class Support Vector Machine performance trained in the same conditions (87% vs 65%). The innovation lies in the strategy's ability to classify unknown anomaly types as "none of the trained classes" rather than forcing misclassification, addressing a gap in current detection strategies. This approach demonstrates practical applicability for real-time oil well monitoring with minimal sensor requirements, providing a robust solution for industrial deployment where unknown anomalies may arise.
Wave impedance is widely applied in hydrocarbon seismic research, whereas integrated geophysical-geochemical understanding of organic-rich rocks remains insufficient for marginal marine basins. This study conducts a typical geological case investigation in the Pearl River Mouth Basin, using 48 core samples from ten wells and 3D seismic data. Geochemical analyses reveal favorable hydrocarbon generation potential, mature thermal evolution, and strong heterogeneity controlled by sedimentary facies in target source rocks. With well-log constraints, wave impedance data assist in characterizing the spatial distribution of organic-rich rock thickness and regional TOC variation across different sags. It clarifies the geochemical heterogeneity and source-rock distribution of the Pearl River Mouth Basin, demonstrates how core geochemical results can be reasonably extended to the regional scale via seismic constraints, and provides robust geological evidence for future hydrocarbon resource evaluation and strategic exploration deployment in this petroliferous basin.
To address the critical challenge where the excessively high Minimum Miscibility Pressure (MMP) restricts the effectiveness of CO2 flooding, this study proposes a novel strategy utilizing SiO2-ethanol nanofluids (SiO2-C2H6O NFs) as additives to reduce the MMP. By systematically optimizing particle size, concentration, and dispersant types, a 5 nm/5 wt% SiO2 nanofluid with polyvinylpyrrolidone (PVP) as the dispersant was successfully prepared, demonstrating excellent long-term dispersion stability. Phase equilibrium experiments indicate that after adding 20 vol% of the optimized nanofluid into crude oil model components (n-alkanes and cycloalkanes), the solubility of CO2 in the oil phase is significantly enhanced. The maximum average equilibrium pressure reduction (P-AVG) reached 2.24 MPa, effectively lowering the MMP of the system. Furthermore, a modified PR-vdW1 equation of state considering nano-confinement effects was developed and validated to systematically reveal the phase equilibrium behavior of CO2-alkane systems within nanopores. This research not only enriches the fundamental thermodynamic data for CO2-hydrocarbon systems but also provides a novel and efficient technical pathway for improving CO2 flooding efficiency and achieving synergistic carbon emission reduction.
Low permeability of China's coal reservoirs and the high adsorption capacity of coalbed methane represent core constraints on coalbed methane extraction. Microwave heating technology has enhanced recovery rates in low-permeability reservoirs. However, existing studies typically simplify coal's dielectric constant as a fixed value and adopt a single-point heating injection pattern. This study proposes a novel coalbed methane enhancement technique, based on directional drilling and continuous tubing technology, enabling large-scale coal seam heating. A fully coupled electromagnetic-thermal-fluid-solid model, incorporating the actual temperature-dependent dielectric properties of coal seams, was established. This model simulates and thoroughly investigates the enhancement and migration patterns of coalbed methane under varying microwave power levels. Results show microwave heating significantly promotes methane desorption and enhances reservoir permeability. 1600 W heating for 120 days, the effective desorption radius exceeded 3.6 m, with maximum permeability increases near the wellbore reaching 18.4%. Under 2400 W microwave irradiation, cumulative gas production reached 5781.5 m3, 15.7% higher than the 4996.3 m3 produced under the non-microwave heating. Due to excessively high power may cause overheating, 1600 W was determined as the optimal power level, balancing efficiency and safety. The study provides both theoretical foundations and practical strategies for optimizing microwave-enhanced coalbed methane recovery rates.
Thin-layer extra-heavy oil reservoirs commonly experience significant heat loss and poor sweep efficiency during conventional steam flooding. Multi-component thermal composite flooding, integrating chemical agents, non-condensable gases, and steam, has been proposed as an effective approach to improve thermal efficiency and reservoir sweep. In this study, the synergistic mechanisms and recovery characteristics of multi-component thermal composite flooding integrating a water-soluble viscosity reducer, N2, and steam were investigated. Static experiments were conducted to evaluate the interfacial tension reduction, emulsification behavior, viscosity reduction performance, and oil-film stripping capability of the viscosity reducer. Three-dimensional physical experiments and numerical simulation models were established to compare the recovery characteristics of conventional steam flooding and multi-component thermal composite flooding. The evolution of oil saturation and sweep efficiency was then analyzed. Results show that the composite flooding process effectively suppresses steam override, improves thermal utilization, and expands the heated reservoir region. Compared with steam flooding, the final recovery factor increases from 31.4% to 51.8%, while numerical simulations indicate a 16% reduction in unswept zones. These findings clarify the coupled thermal-chemical-gas mechanisms governing multi-component thermal flooding and provide guidance for improving recovery efficiency in thin-layer extra-heavy oil reservoirs.
To meet the technological demand for high-temperature completion aids for deep and ultra-deep well development, a novel high-temperature cement retarder with a hyperbranched structure was synthesized. A hyperbranched polymer retarder (HB-PR) was formed via solution polymerization, pentaerythritol polyallyl ether (AP), as the starting material/macromonomer, sulfonate monomer 2-acrylamido-2-methylpropanesulfonic acid (AMPS) as the thermally resistant monomer, and acrylic acid (AA) and itaconic acid (IA) as the functional chelating monomers. At an AMPS:AA:IA molar ratio of 6:2:2 and adding 0.5 wt % AP, the hyperbranched retarder exhibited good temperature-resistant retarding performance, and the temperature resistance of the cement slurry system reached 220 degrees C, which is primarily attributed to its superior conformational and dimensional stability under high-temperature conditions. In addition, HB-PR shows excellent compatibility stability when combined with the cement slurry system, and its retardation effect is less affected by temperature. The hyperbranched structure offers a new approach and direction for the design and development of high-temperature completion cement additives.
To increase the lead time of overflow warnings and achieve more accurate risk assessment, this article proposes a drilling overflow prediction algorithm based on a temporal convolutional network (TCN)-Transformer-long short-term memory (LSTM) fusion network (TTL network). The TTL network replaces the positional encoding layer with TCN to capture robust temporal dependencies and local features; utilizes the Transformer encoder based on the self-attention mechanism to model complex global dependencies; and employs LSTM instead of the Transformer's decoder to learn long-term patterns and short-term fluctuations in time series data. To more precisely assess the risk of overflow, we divide the overflow risk into five levels. Experimental results demonstrate that, using the time of issuing a Level A warning as the reference point, the TTL network advances overflow warning lead times by 60 s (vs. TCN-Transformer), 219 s (vs. LSTM), 227 s (vs. GRU), 94 s (vs. Transformer-LSTM), and 129 s (vs. Attention-LSTM), achieving a 10-min advance in early warning. The TTL network performs well in terms of evaluation metrics, achieving an accuracy of 0.840 and a recall of 1.000. This study proposes an innovative method for predicting drilling overflow, which is significant for ensuring the safety of drilling operations.
To address the development challenge in the "dual ultra-high" stage of the Daqing Oilfield, where more than 30% of oil remains unrecovered after polymer flooding, this study investigates the evolution of pore structures and residual oil occurrence in sandstones of different sedimentary facies. A multi-scale quantitative characterization was conducted using high-pressure mercury intrusion, micro-computed tomography, scanning electron microscopy, and UV fluorescence thin section analysis to analyze pore structure and residual oil distribution before and after polymer flooding. The results show that polymer flooding induces a pronounced "dual-directional reconstruction" of pore structures. In dominant flow channels, erosion by high-viscosity polymer solutions leads to fragmentation and detachment of framework minerals, resulting in a significant increase in the volume fraction of macropores (>50 mu m). In contrast, in branched channels, polymer adsorption/bridging effects and clay mineral migration cause pore-throat shrinkage, increasing the proportion of micropores (<1 mu m) by 10-15% and reducing their contribution to permeability by 16-20%. Sedimentary facies exert a strong control on pore evolution: channel sandstones are dominated by macropore expansion and enhanced heterogeneity, whereas sheet sandstones exhibit increased microporosity and specific surface area, further restricting effective flow pathways. In terms of residual oil distribution, a "mobilization-recapture" microscopic model was proposed. Polymer flooding effectively mobilizes large-cluster residual oil, reducing its proportion by 15-20%; however, it simultaneously promotes oil migration toward grain surfaces and micropores, increasing the proportions of grain-adsorbed and film-type residual oil. These results indicate that polymer flooding enhances displacement efficiency while strengthening oil-rock interfacial adsorption, providing theoretical support for polymer flooding optimization and subsequent profile control strategies in heterogeneous reservoirs.
To address limitations of conventional numerical simulation in characterizing micro-scale remaining oil after multi-cycle steam stimulation and thermal instability in traditional sand-pack models, this study uses a Gudao Oilfield heavy oil reservoir as the research object. A high-temperature-resistant cemented core model combined with cryogenic fluorescence analysis was employed to investigate viscosity/rheology changes and micro-scale remaining oil distribution after multi-cycle stimulation. Results show that temperature significantly reduces heavy oil viscosity, with a maximum viscosity reduction of 97.71%. After steam stimulation, post-stimulation oil exhibits increased viscosity due to light component loss and heavy component enrichment, showing shear-thinning behavior. The steam front mainly advances along the mainstream line and diffuses toward the wings. Clustered oil accounts for 44.79% along mainstream lines, dispersed oil droplets account for 36.82% in wing areas, and connected oil reaches 44.97% at distal wings. Interlayer heterogeneity significantly affects remaining oil occurrence. In high-permeability layers, clustered oil and dispersed oil droplets increase by 6.54% and 5.48%, respectively, compared with low-permeability layers, while connected oil in low-permeability layers reaches 38.43%. This study reveals "mainstream channeling-wing retention" and "high-permeability shearing-low-permeability retention" mechanisms, providing guidance for remaining oil identification and development optimization after multi-cycle steam stimulation.
Diesel engines remain indispensable in energy production and transportation, necessitating effective strategies to mitigate toxic unregulated emissions. Despite extensive research on oxygenated fuels, the influence of higher alcohol molecular structure on polycyclic aromatic hydrocarbon (PAH) formation and toxicity remains poorly understood. This study systematically investigates the effects of 7.5% (v/v) n-propanol (C3), n-butanol (C4), and n-pentanol (C5) blending with diesel (D100) and biodiesel (B100) on total PAH emissions, relative distribution, and toxicity-weighted (BaPeq) emissions under identical operating conditions using gas chromatography-mass spectrometry (GC-MS) analysis. The addition of higher alcohol markedly reduced total PAHs and suppressed the formation of higher-ring carcinogenic species. Among the tested blends, n-propanol consistently delivered the greatest reduction in both total PAH concentration and toxicity. This superior performance is attributed to structure-dependent combustion effects, including enhanced charge homogeneity, moderated local temperature evolution, and suppression of aromatic growth pathways. Overall, these findings provide a basis for the rational design of oxygenated fuel mixtures to reduce unregulated emissions associated with toxicity in future diesel combustion systems.
Conventional underground gas drainage proves inefficient for outburst prevention, necessitating surface coalbed methane (CBM) development. However, complex geological conditions frequently hinder its extraction. Based on experimental tests and log interpretation, this study selects favorable areas to guide well placement and proposes a drainage optimization chart to address poor production stability, both validated through engineering practice. This study proposes a "TOPSIS + One-Veto" method integrated with a comprehensive weighting approach for favorable area optimization, identifying a favorable area of 0.91 km2 and a sub-favorable area of 6.93 km2. A horizontal well (A-1) drilled into the coal roof within the favorable area achieved a peak gas production exceeding 5000 m & sup3;/d, validating the optimization results. However, the conventional drainage scheme leads to a mismatch between production intensity and formation liquid deliverability, resulting in excessive permeability damage before desorption and rapid fluid energy depletion, which compromises the stable production of Well A-1. To address this, a "Three-Stage Control + Eight-Level Quantification" drainage strategy was developed and applied to Well B-1. This approach enabled stable production and increased average daily gas output by 25%. Overall, this study provides a geology-engineering integration approach for optimizing CBM development in mining areas with complex geological conditions.
