Processes

The interlayer is a key geological factor that regulates reservoir heterogeneity and remaining oil distribution, and its accurate identification directly affects the reservoir development effect. To address the strong subjectivity of traditional identification methods and the insufficient recognition accuracy of single machine learning models under imbalanced sample distributions, this study focuses on three types of interlayers (argillaceous, calcareous, and petrophysical interlayers) in the W Oilfield, and proposes an accurate identification method integrating the Synthetic Minority Over-Sampling Technique (SMOTE) and heterogeneous ensemble learning. Firstly, the corresponding data set of interlayer type and logging response is established. After eliminating the influence of dimension using normalization, the sensitive logging curves are optimized using the crossplot method, mutual information, and effect analysis. SMOTE technology is used to balance the sample distribution and solve the problem of the identification deviation of minority interlayers. Then, a heterogeneous ensemble model composed of the k-nearest neighbor algorithm (KNN), decision tree (DT), and support vector machine (SVM) is constructed, and the final recognition result is output using a voting strategy. The experiments show that SMOTE technology improves the average accuracy of a single model by 3.9% and effectively improves the model bias caused by sample imbalance. The heterogeneous integration model improves the overall recognition accuracy to 92.6%, significantly enhances the ability to distinguish argillaceous and petrophysical interlayers, and optimizes the F1-Score simultaneously. This method features a high accuracy and reliable performance, providing robust support for interlayer identification in reservoir geological modeling and remaining oil potential tapping, and demonstrating prominent practical application value.

The high rate of photovoltaic integration poses significant challenges in terms of violations of voltage limits in power grids. Additionally, the operational behavior of PV systems under fault conditions requires thorough investigation in receiving-end grids. This paper analyzes the dynamic coupling characteristics between reactive power and transient voltage in a receiving-end grid with high PV penetration and multiple HVDC infeeds, considering typical AC and DC fault scenarios. Voltage adaptability issues in PV generation systems are also examined. Through an enhanced sensitivity analysis method, the suppression capabilities of transient voltage peaks are quantified in the control parameters of low-voltage ride-through (LVRT) and high-voltage ride-through (HVRT) photovoltaic inverters. On this basis, a hierarchical optimization strategy for PV inverter control parameters is proposed to mitigate post-fault transient voltage peaks and improve the transient voltage response both during and after faults. The feasibility of the proposed method has been verified through simulation on a revised 10-generator 39-bus power system. Following optimization, the transient voltage peak is reduced from 1.263 to 1.098. This validation offers support for the reliable grid connection of the Henan Power Grid. In the events of the N-2 fault at 500 kV and Tian-zhong HVDC monopolar block fault, the post-fault voltage at each node remains below 1.1 p.u. This serves as evidence of a significant enhancement in transient voltage stability within the Henan Power Grid, demonstrating effective improvements in power supply reliability and operational performance.

In response to the intermittent discharge and frequent flow interruptions characteristic of rural domestic wastewater, this study evaluated the treatment performance and microbial mechanisms of basalt fiber (BF) felt as a novel biofilm carrier, with comparative analyses against traditional polyurethane (PU) carrier. Under continuous-flow conditions, both carriers showed no significant difference in the removal efficiencies of COD and NH₄⁺-N. However, when switching to intermittent feeding mode with flow interruption, the BF reactor maintained high removal efficiencies for pollutants (COD, NH₄⁺-N and TN removals averaged 90.5%, 89.4% and 64.5%, respectively), significantly outperforming the PU reactor (COD, NH₄⁺-N and TN removals averaged 82.3%, 32.7% and 20.7%, respectively). High-throughput sequencing results revealed that the BF carrier significantly enriched nitrifiers (e.g., Nitrospira) and aerobic denitrifiers (e.g., Terrimonas and Bacillus) during the intermittent operation phase. Functional prediction further indicated increased abundances of functional genes associated with nitrification (amoA, hao), complete denitrification (narG, nosZ), as well as glycolysis (GAPDH) and the TCA cycle (IDH1, korA) related to NADH generation, suggesting an enhanced coupling mechanism of carbon and nitrogen metabolism in the BF system. Conversely, a significant reduction in microbial diversity and the abundance of relevant functional genes was observed on the traditional carriers. This study confirms that BF felt, serving as a biocarrier for rural domestic wastewater treatment, exhibits superior shock load resistance and nitrogen removal performance, which provides an efficient and reliable carrier option for decentralized wastewater treatment in rural areas.