Energy & Fuels最新文献

To tackle the challenges of high viscosity, poor fluidity, and low recovery rates in heavy oil, a novel comb-like polymer viscosity reducer (GO-Z) based on nanographene oxide (GO) was developed. GO was first functionalized with a silane coupling agent and then grafted with long-chain alkyl (C16DMAAC) and polyether (APEG-8) groups. The results show that GO-Z exhibited superior emulsification, dispersion, and viscosity reduction properties under microagitation conditions (simulating the low-shear conditions of real reservoirs), achieving over 94% viscosity reduction at a concentration of 0.3 wt %. Physical simulation flooding experiments further demonstrated that GO-Z effectively improved heavy oil recovery at various injection rates, with the highest increase reaching 11.61%. This study opens up a clear and promising path for the application of functionalized GO in the emulsification and viscosity reduction of heavy oil cold production.

In this research, the impacts of the Joule flash heating (JFH) method on the generation of monomers and three-phase products during polyethylene (PE) pyrolysis were investigated by using reactive molecular dynamics (ReaxFF MD) simulations. Temperature ranges for JFH were determined through thermal pyrolysis. Meanwhile, JFH experiments at 70, 80, and 90 V were carried out by using the JFH reactor. The trends of the calculated results are consistent with those of the experimental results. Increasing the maximum (T_max) or minimum (T_min) temperatures in JFH promoted secondary reactions. Then, compared to the pyrolysis characteristics of PE under the JFH and the conventional continuous heating (CCH) conditions, the results showed that the yields of char decreased in the JFH method, and the tar produced by pyrolysis exhibited a higher H/C ratio. The yield monomer (C₂H₄) obtained by the JFH method was nearly 12 times more than that obtained by the CCH method according to ReaxFF MD simulations. Finally, by analyzing the reaction types and reaction frequencies involved in the secondary and primary reactions of C₂H₄ on PE pyrolysis, the mechanisms of the effect of the JFH method on the generation of C₂H₄ were revealed. The enhanced C₂H₄ production in JFH was attributed to two key factors during the cooling stage: (1) The cooling stage inhibited hydrogen dissociation in C₂H₄, and decreased the reactions of C₂H₄ with alkyl radicals, thus reducing C₂H₄ consumption. (2) The decrease in temperature makes the condensation reaction of ethylene less likely to occur. These findings highlight the potential of JFH as an efficient method for optimizing PE pyrolysis, maximizing C₂H₄ monomer recovery and minimizing undesirable byproducts such as tar and char.

Recent years have seen the growth of new techniques that combine conventional stratigraphic and observational approaches to characterizing the type, scope, extent, timing, and effects of diagenetic processes with petrophysical measurements of their rock microstructure. These new Quantitative Diagenesis (QD) techniques can be used to predict post- and predolomitization porosities and permeabilities as well as track petrodiagenetic pathways. The objective of this paper is to use QD to calculate changes to the CO₂ storage of a CCUS target for the first time. These QD approaches include porosity and permeability prediction resulting from varying degrees of dolomitization, calculation of porosity and permeability of the host rock before dolomitization, using petrodiagenetic pathways to track quantitatively the type, extent, and timing of diagenetic processes, and methods for determining the impact of fractures (the Fracture Effect Index, FEI). This paper reports the impact of dolomitization and fracturing on CO₂ storage by considering the Butmah and Shiranish formations (NE Iraq). The Butmah Formation data show that the CO₂ storage of the formation increased significantly 154.23 Mt (78%) due to dolomitization. The Shiranish Formation showed an increase in CO₂ storage of 144.23 Mt (70%) from the almost unfractured rocks of its U.1(A) lithofacies (FEI = 0.31) to the highly fractured rocks of its U.4 lithofacies (FEI = 15.55). The main scientific contribution of this paper is that it shows for the first time that QD techniques can be used to calculate very significant changes in CO₂ storage capacity concomitant with fracturing, dolomitization, and precipitation. Such techniques should therefore be employed when judging any legacy reservoir or aquifer in carbonates the potential CCUS use.

Gas adsorption in coalbed methane occurs primarily through micropore filling, a process complicated by pronounced structural heterogeneity. This complexity limits the accuracy of conventional adsorption models. To overcome these limitations, we developed a novel fractal adsorption model. This equation uses fractal dimensions, derived from low-temperature gas adsorption and high-pressure mercury intrusion data, to quantitatively describe the complex pore structure. By integrating this structural information with the Kelvin equation, the novel fractal adsorption equation elevates the R² value for adsorption capacity prediction to above 0.98. The results demonstrate that while adsorption capacity is influenced by pressure, temperature, and pore complexity, the spatial distribution of the pores themselves is the decisive factor. Ultimately, this model provides a critical distinction between the spaces where gas is stored (adsorption) and the pathways through which it flows. This study establishes a foundational framework for advancing our understanding of gas flow mechanisms in coalbed methane reservoirs.

The extreme post-thermal environment of extra-heavy oil reservoirs, characterized by high salinity, anaerobiosis, and nutrient depletion, severely limits the efficacy of conventional Microbial Enhanced Oil Recovery (MEOR). To address this, a mild-thermal-assisted MEOR (MT-MEOR) strategy is proposed, which strategically leverages these reservoir adversities as selective pressures. The central hypothesis posits that such conditions can induce a beneficial phenotypic shift in specific microorganisms, transforming them into deep-delivery conformance control agents. The methodology integrates stress-responsive microbiological analysis with multiscale physical simulation. Laboratory studies demonstrate that under simulated reservoir stresses, Geobacillus WJ-8 undergoes a Spo0A∼P-regulated phenotypic shift from motility to cellular filamentation and copious extracellular polymeric substance (EPS) biosynthesis. This transition enables microbes to function as structural scaffolds and biological adhesives, autonomously constructing a three-dimensional, heterogeneous bioflocculation system in porous media via mechanisms including sweep flocculation and adsorption bridging. The key findings are as follows: (1) The core mechanism involves an environmentally triggered, self-responsive microbial flocculation process, presenting a novel strategy for MEOR. (2) The resulting compliant bioflocs effectively restrict flow in high-permeability zones, extending the operational permeability threshold for microbial conformance control to 2500–3000 mD without inducing formation damage. (3) Mild thermal activation at 70 °C is established as a critical factor for enabling macroscopic profile modification, achieving a 70% fractional flow contribution from the low-permeability zone and a 13.9% incremental oil recovery. (4) The system generates in situ biomass exceeding injected volumes via subsequent crude oil metabolism, establishing a self-reinforcing recovery mechanism. This research establishes a recovery paradigm where reservoir adversities are converted into biochemical drivers via an autonomous, stress-responsive microbial system. The findings advance the potential of microbial processes to unlock ultraheavy oil reserves.

Flexible zinc-ion hybrid supercapacitors (FZHSCs) with high energy and power densities and long cycle lives are promising. However, dendrite growth and unsatisfactory cycle stability limit their applications. By adopting Zn foil as the anode, N-doped reduced graphene oxide (N-rGO) as the cathode, and cellulose-methylurea (Mu) hydrogel (CMZ-gel) as the electrolyte, we prepared high-performance FZHSCs. The presence of Mu molecules contributes to cellulose dissolution, alters zinc-ion solvation in the CMZ-gel, and guides uniform zinc deposition. The network structure of hydrophilic cellulose chains disrupts the hydrogen bonds between water molecules, hindering proton transport and reducing the HER. Simultaneously, the porous hydrogel structure facilitates three-dimensional zinc-ion diffusion. Zn//Zn symmetric cells with CMZ-gel exhibit an extended lifespan exceeding 1000 h at 1 mA cm^–2 and 1 mAh cm^–2. The Zn//CMZ-gel//N-rGO ZHSC displays a high specific capacitance of 173 F g^–1 (0.5 A g^–1), superior power density of 4287 W kg^–1 (13.1 Wh kg^–1), and high energy density of 81.2 Wh kg^–1 (562 W kg^–1). After 10,000 charge–discharge cycles (10 A g^–1), the Zn//CMZ-gel//N-rGO ZHSC shows excellent cycle stability with a high capacitance retention of 93%.

Traditional three-dimensional geomechanical modeling is hindered by several limitations, including time-consuming workflows, challenges in effectively updating models, constraints in available computational resources, and issues related to software compatibility. To address these challenges, this study introduces a machine learning-based multiscale (well-log and seismic scales) geomechanical modeling approach. It leverages the complementary advantages of well-log data (providing vertical resolution at borehole locations) and seismic data (offering lateral continuity), where machine learning algorithms utilize the spatial constraints from seismic data to guide interpolation and extrapolation of well-log information in 3D space. This methodology integrates geological structural data, well-log information, and seismic data, leveraging machine learning techniques to construct intelligent digital models that can represent subsurface geomechanical behavior. To evaluate prediction performance at both well-log and seismic scales, we conducted extensive model training and completed the method selection. Results indicate that the multitask learning approach achieved R² scores of 0.9826 at the well-log scale and 0.9379 at the seismic scale, with mean absolute percentage errors in blind-zone prediction falling within acceptable engineering standards. In the application test for predicting geomechanical parameters of planned wells, the average prediction error for key mechanical parameters is 10.17%, validating the method’s applicability to field development planning, reserve estimation, and drilling decision-making. Additionally, this study implemented interactive visualization using the VisPy library with support for synchronized display of multiscale data and real-time zooming functionality, providing extensible technical support for intelligent oilfield exploration and decision-making. In summary, this research can be applied to scenarios including geomechanical parameter prediction for planned wells, well-log parameter prediction, and seismically driven geomechanical modeling.

The western segment of the Qionghai Uplift is a major oil-bearing block in the Zhu III depression. However, diverse crude oil phases and types occur within this area, characterized by complex geochemical signatures, and the origin and genesis of these crude oils remain unclear. Through the analysis of crude oil physical properties, biomarker compounds, and carbon isotope data, this study clarifies the geochemical characteristics and genetic origins of the crude oils. The results indicate that (1) response characteristics of typical biomarkers (C₂₅-norhopane) to biodegradation indicate PM 1 to PM 3 biodegradation levels in the study area’s crude oils. Correction of whole-oil δ¹³C values to account for biodegradation effects enables a more accurate oil-source correlation. (2) Crude oils in the study area can be classified into two types: A and B. Type A crude oil is derived from sapropelic-humic organic matter, exhibiting characteristics of both the shallow lacustrine and mid-deep lacustrine source rocks of the Wenchang formation, indicating mixed contributions from these two sets of source rocks. In contrast, Type B crude oil is predominantly sapropelic and is sourced solely from the mid-deep lacustrine source rocks of the Wenchang formation. The source rocks of the Enping formation do not contribute to the oil reservoirs in this area. (3) Two distinct phases of hydrocarbon charging, occurring at 15–4.8 Ma and 3.5–0 Ma, respectively, have been identified in the study area. The initial charge was solely supplied by the basal mid-deep lacustrine source rocks, leading to the accumulation of Type B crude oil. During the late stage, as the shallow lacustrine source rocks entered the oil window, both source rock units contributed simultaneously, resulting in the formation of Type A crude oil. The present-day variation in crude oil properties in the Q area of the western Qionghai Uplift is attributed to spatiotemporal differences in hydrocarbon charging from the two source rock units and their coupling with subsequent tectonic activity consequently, and an accumulation model is established, summarized as “dual-source hydrocarbon supply from the Wenchang B Sag, fault-sandstone composite migration, differential charging, and late-stage adjustment”. These results provide critical insights for evaluating hydrocarbon accumulation mechanisms and optimizing exploration targets.

The fuel cell products exhibit different power levels across various application scenarios or R&D stages. However, the performance exhibits a nonlinear mapping relationship across the material-single cell short stack-long stack hierarchy. This study constructs for the first time a model of ″identical core materials + identical test conditions + different power levels″, isolating the variables of materials and operating conditions, and conducted a comparative study on the 1000 h durability degradation behavior of three stacks (4 kW short stack, 45 kW medium stack, and 130 kW long stack). The results indicate that the long stack exhibited higher initial performance and better consistency than the medium stack, though its degradation rate was intermediate between the short and medium stacks. The results of linear fitting and the “beginning to the end” difference method are similar in evaluating the degradation rate, and both are applicable to the durability evaluation. Higher current densities lead to more severe degradation and increased inconsistency among individual cells. All stacks exhibit dynamic periodic fluctuations in performance, highlighting the non-negligible impact of reversible losses during long-term operation and providing an experimental basis for implementing regular maintenance. The conclusions offer practical engineering implications for stack design, process uniformity improvements, and lifetime prediction with multiple power levels.