Energy conservation and consumption reduction is a critical technical demand in oilfield development. Fracturing and sand control, the primary technical measure for boosting and stabilizing oil and gas production in medium-high permeability unconsolidated sandstone reservoirs, is plagued by low energy utilization efficiency. Current research on oil well production energy utilization efficiency mostly focuses on surface gathering and transportation systems and artificial lift systems, with inadequate studies on perforation, sand control and fracture zones during production, and a lack of coordinated optimization methods from an energy efficiency perspective. To solve these problems, a calculation and evaluation model for energy consumption and utilization efficiency of the three zones was established and modified via energy efficiency evaluation experiments, which proved that construction parameters affect each zone’s energy consumption. A collaborative optimization case analysis of a typical fracturing and gravel packing well was conducted using the orthogonal combination design method, revealing that optimizing perforation and fracture parameters is the key to improving operational energy utilization efficiency. Specifically, perforation density should be over 24–30 holes/m, diameter larger than 12–14 mm, fracture width above 12–14 mm, and larger particle size proppants should be prioritized. Optimization balanced the energy utilization efficiency of the three zones in the typical well and raised energy utilization efficiency by about 51.2%, providing technical and theoretical support for oilfields to realize energy conservation and consumption reduction and enhance the energy utilization efficiency of fracturing and sand control operations.

The increasing demand for enhanced oil recovery (EOR) and CO2 sequestration has driven the development of novel injection strategies. This study investigates the use of Rapid Periodic Pressure Injection (RPPI) as an innovative method to enhance CO2-EOR efficiency and increase CO2 sequestration. Laboratory experiments and theoretical analysis were conducted to evaluate the impact of pressure fluctuation amplitude and the timing of RPPI initiation. The results demonstrate that RPPI significantly enhances oil recovery and CO2 sweep efficiency compared to Constant Pressure Injection (CPI). Increasing the pressure fluctuation amplitude was found to be a key factor in improving performance. Furthermore, initiating RPPI displacement earlier extends the prebreakthrough period, which enhances the CO2 sequestration volume and ultimately improves oil recovery. Relative permeability analysis reveals that higher fluctuation amplitudes reduce CO2 mobility, thereby improving oil-phase mobility. Crucially, the maximum CO2 sequestration volume prior to breakthrough was increased by up to 84.8% compared to CPI. These findings suggest that RPPI effectively enhances CO2-EOR performance and offers significant potential for improving CO2 storage in mature reservoirs.

ABSTRACT: During the shut-in period following hydraulic fracturing, a large volume of fracturing fluid is imbibed from the fracture into the reservoir matrix under high pressure, enhancing oil displacement and contributing to production improvement. However, as shut-in time increases, excessive fluid imbibition can induce elastic fracture closure and a loss of the stimulated fracture volume, which is detrimental to production. To date, no study has systematically investigated the shut-in enhancement mechanism considering the coupled effects of fracture closure and imbibition-driven oil displacement. In this work, a novel experimental design was developed to simultaneously capture fracture closure behavior and imbibition dynamics. Experiments were conducted on shale oil cores from the Jimusar reservoir. The results show that fluid imbibition reduces fracture pressure and accelerates elastic fracture closure. Meanwhile, the oil displaced from the matrix replenishes the fluid deficit within the fracture, thereby mitigating the rate of closure. These two competing mechanisms coexist throughout the shut-in process.Based on the experiments, the proppant-sand–fluid fracture closure dynamics and imbibition oil-displacement characteristics were translated into fracture porosity-permeability stresssensitivity curves and matrix capillary-pressure functions, which were incorporated into field-scale numerical simulations. The simulation results indicate that shut-in operations can significantly enhance the initial production of shale oil wells. Compared with wells without shut-in, the cumulative oil production within 30 days can increase by 49.26% in water-wet reservoirs. However, as the duration of the shut-in stimulation effect increases, the intensity of the enhancement gradually decreases, and the cumulative oil production after three years increases by only 3.36% in water-wet reservoirs. In addition, the study shows that the optimal shut-in time of shale oil wells is not affected by the intensity or duration of the stimulation effect. For the water-wet shale oil reservoir in the Jimusar area, the optimal shut-in time is 35–42 days.

The tight conglomerate reservoirs in the Junggar Basin exhibit complex pore–throat structures and strong heterogeneity, which significantly affect reservoir seepage behavior and hydrocarbon recovery efficiency. However, the main controlling factors of their heterogeneity remain unclear, and systematic quantitative characterization is lacking. To address this, this study focuses on the Triassic Baikouquan Formation (T 1 b 1 ) tight conglomerate reservoirs in the Maxi slope area. Using X-ray diffraction (XRD) analysis, mercury intrusion, petrographic thin-section image analysis, and scanning electron microscopy (SEM), combined with grayscale image-based multifractal dimension calculations and finite element numerical simulation, the heterogeneity characteristics and seepage capacity of the reservoirs were systematically investigated. The results indicate significant heterogeneity differences among various lithologies of the target layer, with the intensity decreasing in the order: conglomeratic sandstone > sandy conglomerate > conglomerate. Among different pore types, intragranular dissolved pores exhibit the highest heterogeneity, followed by intergranular pores and microfractures. Clay minerals also exert varying influences on heterogeneity, decreasing in effect in the order: chlorite > illite–smectite mixed layer > illite > chlorite–smectite mixed layer > kaolinite. In contrast, displacement efficiency shows an inverse relationship with heterogeneity, with conglomerate exhibiting the highest efficiency (69.49%), followed by sandy conglomerate (65.32%) and conglomeratic sandstone (61.72%). Further analysis shows feldspar negatively correlates with heterogeneity and enhances storage and seepage, while clay positively correlates with heterogeneity and generally restricts permeability. The effects of different clay minerals on permeability and heterogeneity vary and cannot be simply classified as flow-inhibiting or heterogeneity-enhancing.

Carbon dioxide geological sequestration is a critical pathway for achieving carbon neutrality. Previous studies on hydrate-based CO2 sequestration have primarily focused on phase equilibrium, formation kinetics, and reservoir-scale capacity assessments. However, well placement optimization-extensively investigated for hydrate production-remains underexplored for CO2 sequestration in subsea hydrate reservoirs, particularly regarding systematic comparisons of different configurations and their effects on multi-physical field synergy, inter-well interference, and coupled deformation responses. Using multi-field coupled numerical simulations, this study systematically investigates the effects of various well placement systems on CO2 sequestration behavior, focusing on multi-physical field evolution and inter-well interference control. Results show that the three-point well pattern achieves a cumulative sequestration of 9.23 & times; 107kg, 2.14 times that of a single well, highlighting its potential for large-scale carbon storage. Horizontal well spacing exhibits a non-monotonic relationship with performance, identifying an optimal spacing window. Vertical layer and spatial configuration further enhance efficiency. Multi-field analysis reveals that a hydrate cap layer forms gradually, with CO2 and hydrate exhibiting highly overlapping distributions where field synergy concentrates, while pressure and temperature fields remain stable-key indicators for storage safety. The Field Synergy Enhancement Factor (FGE) declines exponentially from 3.00 to 2.16, quantifying inter-well interference dynamics. Reservoir deformation displays creep-like growth, with shallow uplift (max 0.6 m) causally linked to a central deformation core zone. Rational design of well spacing, vertical layers, and spatial configuration is critical for balancing capacity and stability. This study provides a theoretical basis for efficient well placement in marine hydrate reservoir CO2 sequestration.

Abstract The oxidative dehydrogenation (ODH) of light alkanes offers an energy-efficient route to olefins. Boron-based catalysts, while highly selective, often suffer from limited activity and issues of active-site aggregation. Herein, we report a rational design of high-performance B2O3/SiO2–TiO2 catalysts through polyethylene glycol (PEG) templating. By varying the PEG molecular weight, we achieve superior dispersion of active boron species and tailored pore structures. The optimized catalyst (PEG-4000 modified, 30 wt % B2O3, TiO2/SiO2 = 2/1) delivers markedly improved performance, reaching propane and ethane conversions of ∼66% and ∼71% with olefin selectivities of ∼71% and ∼73%, respectively. To decipher the complex interplay of variables, we combine extensive catalytic testing with machine learning (ML) analysis, quantitatively identifying reaction temperature and B2O3 loading as the dominant factors. Furthermore, density functional theory (DFT) calculations indicate local structural coupling between BOx and the SiO2–TiO2 support and different adsorption strengths of the alkanes and O2 at a representative interface. In the context of the currently accepted surface-initiated gas-phase radical mechanism for boron-based ODH, these results provide qualitative information about the local surface environment that may be relevant to radical initiation. This work demonstrates an effective PEG-assisted synthesis strategy and, more importantly, establishes a multifaceted experimental-theoretical framework to uncover key governing factors, offering concrete guidelines for the development of advanced boron-based ODH catalysts.

To address the lack of clear criteria for well and layer selection in the offshore applications of fracturing-flooding technology, this study develops a refined numerical simulation method to quantitatively characterize the oil enhancement mechanisms associated with high-pressure fracture-induced permeability improvement, surfactant-assisted oil displacement, and soak-imbibition processes. Based on numerical simulations, selection criteria for wells and layers suitable for fracturing-flooding are systematically investigated, and the relative influence of key selection indicators on incremental oil production is analyzed. Results show that the oil-saturation condition play a more critical role than original reserves and physical properties of the reservoir in well and layer selection. Specifically, a pressure maintenance level greater than 0.4 and an oil saturation of exceeding 40% are identified as the lower limits for candidate wells and layers. After fracturing-flooding treatment of the optimized target wells and layers, the initial incremental oil production reaches 50 m3/d, and the productivity index of the target layer increases from 1.2 m3/(d·MPa) to 9.2 m3/(d·MPa), and the cumulative incremental oil production reaches 1.01 × 104 m3 within six months, indicating that the fracturing-flooding performance meets the design requirements. Field practice shows that the proposed refined numerical simulation approach—which incorporates formation energy replenishment, pore and permeability enhancement, pressure-induced fracturing, surfactant-assisted washing oil, and imbibition displacement mechanisms—together with the established well and layer selection criteria, provides effective technical support for fracturing-flooding operations in offshore low-permeability reservoirs.

Aluminum dihydrogen phosphate (ADP) is widely used in lining preparation due to its excellent bonding performance. However, 304 stainless steel (304ss) anchoring parts inside the lining were prone to corrosion by ADP, which has been rarely reported. This research systematically investigated the effects of ADP on 304ss under different conditions, including the addition amount of ADP, the treatment temperature, and the reaction time of ADP on 304ss. The results indicated that temperature was the key factor affecting the corrosion behavior of ADP on 304ss. During the dehydration reaction, ADP severely corroded the stainless steel surface, leading to severe damage of the passive film, accompanied by the dissolution of Fe and Cr from the passive film and the formation of metal phosphides or metal oxides. Density functional theory (DFT) was further used to identify the specific species responsible for the corrosion of 304ss. By elucidating the corrosive effect of ADP on 304ss, this study provides a theoretical basis for the diagnosis and improvement of related issues in industrial equipment.

The thermal development in heavy oil reservoirs with edge and bottom water is poor, while gas huff-n-puff development shows a high recovery and strong adaptability. The formation of foamy oil during gas huff-n-puff is one of the reasons for the high recovery. In order to determine the factors affecting the foamy oil flow during gas huff-n-puff, experiments using a one-dimensional sandpack were conducted. The influences of drawdown pressure and cycle number were analyzed. The formation conditions of foamy oil were preliminarily clarified, and the enhanced oil recovery (EOR) mechanism of foamy oil was revealed. The experimental results show that the drawdown pressure and cycle number are two important factors affecting the formation of foamy oil. Foamy oil flow is prone to forming under a moderate drawdown pressure of 0.5–0.75 MPa, and being too small or too large is unfavorable. Foamy oil is more likely to form in the first two cycles, and it becomes increasingly challenging with the increase in the cycle number. These two factors reflect two necessary conditions for the formation of foamy oil during gas huff-n-puff: one is allowing the oil and gas to flow adequately to provide the shear and mixing for the generation of micro-bubbles, and the other is that the oil content should not be too small to avoid the inability to disperse and stabilize bubbles. The formation of foamy oil, on the one hand, increases the volume of the oil phase, and on the other hand, it reduces the mobility of the gas phase and slows down the pressure decline rate in the core, thereby enhancing the driving force for oil displacement. So, under the influence of the foamy oil, the gas production volume in a cycle declined by about 26%, and the average oil recovery increased by 4.5–6.9%.

The fractal characteristics of shale significantly influence pore distribution patterns and surface roughness, thus impacting reservoir properties such as permeability, porosity, and diffusion coefficients. However, existing studies have not fully characterized these fractal features, particularly in ultralow-pressure regions. This study comprehensively investigated the fractal characteristics of shale by integrating low-pressure N2 adsorption, CO2 adsorption, mercury intrusion, focused ion beam-scanning electron microscopy (FIB-SEM), and three-dimensional reconstruction techniques. The Sierpinski fractal model was employed to determine fractal dimensions in the ultralow-pressure interval based on the N2 isotherms and adsorption mechanism. By extracting pores from images obtained using the FIB-SEM technique, the fractal dimensions (D 3) of the three-dimensional digital cores were calculated based on the box-counting model. Additionally, investigating the correlation between porosity and D 3 values revealed a direct logarithmic relationship between porosity and D 3 values. This correlation suggests that the fractal dimensions in shale can extend to other physical parameters associated with porosity. A machine learning algorithm was applied to predict the fractal dimensions of shale from the Sichuan Basin. These findings not only deepen the understanding of shale reservoir properties but also offer a solid theoretical foundation for shale gas development and enhanced recovery.

The propped fracture inflow capacity in unconventional reservoirs' fracture networks is vital for assessing fracturing effects. It's influenced by factors like fracture width (sand spreading concentration), proppant type, and closure pressure. Based on extensive experimental data, a BP neural network prediction model based on genetic algorithm was established to realize its efficient and accurate prediction. Experiments were conducted using an API-standard flow-conducting chamber to test the flow-conducting ability of ceramic and quartz sand proppants under different sand placement concentrations, based on unconventional reservoir slickwater sand-carrying proppant placement experiments. Through model learning and training, the optimal values of parameters such as learning rate and the number of hidden layer nodes were determined, and then flow capacity prediction was carried out. The experimental results show that the quartz sand proppant under high closure pressure conditions has an abrupt change in the change trend of the flow-conducting capacity of the propped cracks due to crushing and other reasons. And the prediction model can achieve good prediction results for both ceramic and quartz sand. Comparing the predicted test set value and the actual inflow capacity value, its MAE is 0.582 D-cm and R2 is 0.993.

Measurement-while-drilling (MWD) and guidance technologies have been extensively deployed in the exploitation of oil, natural gas, and other energy resources. Conventional control approaches are plagued by challenges, including limited anti-interference capabilities and the insufficient generalization of decision-making experience. To address the intricate problem of directional well trajectory control, an intelligent algorithm design framework grounded in the high-level interaction mechanism between geology and engineering is put forward. This framework aims to facilitate the rapid batch migration and update of drilling strategies. The proposed directional well trajectory control method comprehensively considers the multi-source heterogeneous attributes of drilling experience data, leverages the generative simulation of the geological drilling environment, and promptly constructs a directional well trajectory control model with self-adaptive capabilities to environmental variations. This construction is carried out based on three hierarchical levels: “offline pre-drilling learning, online during-drilling interaction, and post-drilling model transfer”. Simulation results indicate that the guidance model derived from this method demonstrates remarkable generalization performance and accuracy. It can significantly boost the adaptability of the control algorithm to diverse environments and enhance the penetration rate of the target reservoir during drilling operations.

This paper describes an innovatively designed experimental method for fracturing fluid energy storage to explore the energy storage mechanism during the well shut-in process of fractured shale reservoirs. By improving the existing core clamp and adding fracturing fluid cavities and large volume intermediate containers to simulate artificial fractures and remote shale reservoirs, the pressure changes in the core during the well shut-in process were monitored under the conditions of a real oil–water ratio and real pressure distribution to explore the energy storage law of the shut-in fluid in fractured shale reservoirs. Compared to the 0.62 MPa energy storage obtained from traditional energy storage experiments (without artificial fractures or remote shale reservoirs), the experimental scheme proposed in this paper achieved a 2.45 MPa energy storage, consistent with the field’s monitoring results. The energy storage effects of four fracturing fluids were compared, namely pure CO2, CO2 pre-fracturing fluid, slickwater pre-fracturing fluid, and pure slickwater fracturing fluid. Due to the characteristics of a high expansion coefficient and low interfacial tension of pure CO2, the energy storage effect was the best, and the pressure equilibrium time was the shortest. Considering factors such as comprehensive economy and energy storage efficiency, the optimal range for CO2 pre-injection is between 20% and 30%. Based on the optimization criterion of energy storage pressure balance, it is recommended that the optimal CO2 shut-in time be 5 h and the slickwater be 12.8 h. Considering the economic, sand carrying, and energy storage effects, and other factors, CO2 pre-storage has the best imbibition effect, and the optimal CO2 pre-storage range is 20~30%. The research results provide theoretical support for energy storage fracturing construction in other shale oil reservoirs of the same type.

By providing sufficient time for oil to migrate from the matrix into the fractures through imbibition, the extended shut-in period contributes to immediate oil production in shale oil reservoirs. Previous studies have demonstrated that flowback data can be used for fracture characterization. However, the developed models mainly analyze water production and do not address the quantification of imbibition oil recovery. The objective of this paper is to propose a two-phase oil/water flowback analysis method to estimate the effective fracture pore volume (V efi ) and the efficiency of imbibition-driven oil recovery, providing an early opportunity to understand the effects of fracturing operations. The method incorporates rate decline analysis, an extended flowing material balance (FMB) model, and producing oil/water ratio analysis to form a workflow for predicting fracture properties. The signature of fracture depletion is described through a set of diagnostic plots, which represent a key period for assuming the fracture system as a closed-tank system. Using water-phase flowback data, the semilog plot shows a linear trend of harmonic decline, indicating the water volume within the effective fracture system. By using oil-phase flowback data, the developed FMB model identifies the fracture depletion period and estimates imbibition-driven oil volume through a diagnostic plot. Moreover, the model incorporates two-phase oil/water flow in both propped and unpropped fractures. The imbibition recovery in different fracture domains is further determined by combining the production oil/water ratio analysis during flowback. The accuracy and applicability of the entire workflow are tested against numerical simulations. Under a series of variable set parameters, the inversion results show good accuracy and stability. Furthermore, we apply the new method to estimate V efi and the efficiency of imbibition-driven oil recovery in different fracture domains using field flowback data. The results show a significant decrease in fracturing fluid efficiency after long-term well shut-in and demonstrate vastly different imbibition efficiencies in propped and unpropped fractures.

Summary In the actual construction process, well path control is a challenging task mainly due to the inevitable well deflection caused by geological factors, drilling tools as well as borehole enlargement. Most conventional well path control methods focus on elaborate mechanism model construction. The methods are typically constructed on the basis of certain constraints or assumptions, which reflect their limited ability to accurately capture the actual drilling process, low level of intelligence, poor anti-interference performance, and weak adaptive capacity. To address these challenges, this paper proposes a target-aware well path control method that integrates reinforcement learning and transfer learning. The proposed method employs a deep deterministic policy gradient model based on the prioritized experience replay mechanism and leverages transfer learning to accelerate model learning. This enables the construction of a target-aware well path adaptive control system with strong anti-interference capability. The proposed target-aware control method of well path based on reinforcement learning and transfer learning can accurately track the preset trajectory in diverse geological environments, reach the target area with high precision, and make reasonable trajectory optimization decisions with measurement while drilling (MWD) even when the target trajectory does not match the actual distribution of the reservoir. This approach exhibits excellent anti-interference and adaptive abilities.

Abstract The naturally fractured carbonate gas reservoir of Majiagou formation in Ordos Basin is characterized by mixed mineralogy. Since mineralogy determines acid-rock reaction rate, mineral distribution has significant effect on the fracture surface etching profile. Therefore, it is necessary to investigate effect of mixed mineralogy on etching profile and fracture conductivity. In this paper we conducted the research from two aspects: experiment and numerical modeling. In the experiment, we firstly measured mineral distribution by hyperspectral scanning on the core slabs, then did acid flooding, next did 3D scanning to get etching profile, and finally measured acid fracture conductivity, based on which an acid fracture conductivity correlation was built. In numerical modeling, based on mass conservation principle, acid-rock reaction kinetics, and momentum theorem, a 3D acid flow, acid-rock reaction, surface etching model was developed. Mineral distribution on the surfaces was coupled as boundary conditions. Experimentally measured mineral distribution on the slab surface are coupled into the numerical simulation. The model is validated by the experimental results. Based on the model, extensive numerical simulation was conducted to analyze mineral distribution, acid-rock contact time, and temperature on the surface etching pattern and acid concentration distribution. By combining the experimental results and numerical simulation, how the mineral distribution affect etching profile, facture conductivity, and acid concentration distribution is analyzed. The study shows that for mixed mineralogy carbonate, the distribution of mineral is strongly spatially correlated instead of random distribution. Mineral stripes are observed from the mineralogy scanning of core slabs. Due to reaction rate contrast of different minerals and strong spatially correlated distribution, the surface etching profiles are rough, and the channel is obvious. The channels resulted from multiple mineral distribution contributes remarkably to the fracture conductivity. With the similar amount of rock dissolved, the fracture with channels has a much higher conductivity. Temperature has remarkable effect on etching profile. At a high temperature (e.g. 90°C), the difference of overall reaction rate for limestone and dolomite is small, and the etching discrepancy for calcite and dolomite is less. At a low temperature (e.g. 60°C), the difference of overall reaction rate is large, so the etching discrepancy is more distinct. Dolomite surface has an apparent higher acid concentration than limestone at a low temperature, while surface acid concentration is close for calcite and dolomite at a high temperature. The impurities such as quartz, clay, gypsum, etc. are not dissolved by the acid. Even small amount of impurities contributes to the differential etching on the surfaces. In the lab scale, the acid concentration inside the fracture has identifiable decrease from the inlet to the outlet.

In addition to main fractures, a large number of secondary fractures are formed after the volumetric fracturing of shale gas wells. The secondary fracture properties are so complex, that it is difficult to identify and diagnose by direct monitoring methods. In this study, a new approach to model and diagnose secondary fracture properties is presented. First, a new pressure decline model, which is composed of four interconnected domains, i.e., wellbore, main fractures, secondary fractures, and reservoir matrix pores, is built. Then, the fracturing fluid pumping and post-fracturing soaking processes are simulated. The simulated pressure derivatives reflect five fracture-dominated flow regimes, which correspond to multiple alternating positive and negative slopes of the pressure decline derivative. The results of sensitivity simulation show that the density, permeability, and width of secondary fractures are the main controlling factors affecting the size ratio. Finally, based on the simulated pressure decline characteristics, a diagnostic method for the identification and analysis of secondary fracture properties is formed. This method is then applied to three platform wells in the Changning shale gas field in China. This study builds the correlation between the secondary fracture properties and the shut-in pressure decline characteristics, and also provides a theoretical method for comprehensive post-fracturing evaluation of shale gas horizontal wells.

The CO2-enhanced oil recovery (EOR) technology has the dual significance of enhancing oil recovery and realizing carbon storage in onshore and offshore oil and gas exploitation. This study investigates the adsorption of crude oil components on quartz surfaces and the microscopic mechanisms of CO2 stripping from crude oil using molecular dynamics simulations. A four-component model representing C6H14, benzene, resins, and asphaltenes was constructed to simulate the oil phase, while the quartz surface model was created using Materials Studio. Simulations were conducted under different temperature conditions to understand the distribution and adsorption behavior of crude oil components, as well as the impact of CO2 on the oil film at pressures up to 10 MPa. The results indicate that the resin–asphaltene interactions are significantly weakened at elevated temperatures, affecting the adsorption capacity. Furthermore, CO2 stripping primarily extracts light components such as C6H14 and aromatic hydrocarbons, while heavy components remain in the oil phase. The highest extraction efficiency and expansion effect of CO2 were observed at 35 °C, demonstrating optimal conditions for enhanced oil recovery through CO2 flooding. These findings provide insights into the effective use of CO2 for crude oil extraction and its interactions with oil components on a quartz substrate, which is crucial for optimizing CO2-enhanced oil recovery operations.