科研成果

CO2 flooding is considered one of the most important methods for reducing CO2 emissions and increasing oil production from reservoirs. However, the challenges of low recovery rates and poor economic benefits in CO2 immiscible flooding significantly hinder its widespread application. To address these issues, this paper proposes the use of ultrasonic-assisted CO2 immiscible flooding to enhance oil recovery (EOR) and analyzes its underlying mechanisms. First, the distribution characteristics of residual oil in CO2 immiscible flooding were examined using high pressure mercury injection (HPMI), nuclear magnetic resonance (NMR), and microscopic visualization displacement (MVD) experiments. Next, the changes in oil recovery and residual oil distribution after applying ultrasonic-assisted CO2 immiscible flooding were analyzed. Finally, the mechanism of EOR through ultrasonic-assisted CO2 immiscible flooding was summarized based on the results of interfacial tension (IFT) tests. The findings indicate that the recovery rate of CO2 immiscible flooding without ultrasound is 53.33 %, with residual oil primarily distributed in the form of films and flakes within the pores. The ultrasonic assisted CO2 immiscible flooding with frequency of 28 KHz and power of 200 W was provided by ultrasonic horn, and the recovery rate increased by 62.84 % after 60 min. With ultrasonic assistance, the recovery rate increased to 62.84 %, and the maximum radius of residual oil droplets was reduced from 81.8 μm to 36.5 μm. Additionally, the amount of residual oil in the 0.1 μm to 1 μm range slightly decreased, suggesting that ultrasonic assistance mainly improves the recovery of flake residual oil, with a slight improvement in film residual oil recovery as well. Ultrasound can enlarge the pore and throat radius and reduce the interfacial tension in the CO2-oil system, allowing more flake residual oil to be displaced. Moreover, the high-frequency vibrations of the ultrasound can reduce the thickness of the oil film, enhancing the recovery of film residual oil. This study supports the further application of ultrasonic-assisted CO2 immiscible flooding in both scientific research and engineering practice.

The digital economy has become a driving force for global economic development, resulting in high demand for balanced regional development. Using surname distance as a proxy variable for cultural distance, this study examined the impact of cultural differences on the development of a regional digital economy. The results of the analysis of panel data from 31 Chinese provinces from 2011 to 2019 indicated that the development of a region's digital economy positively contributes to the development of the digital economy in areas of cultural proximity. Further analysis of the mechanisms of cultural differences in the digital economy showed that cultural distance affects the development of the digital economy in a province through three mechanisms: birth rate, divorce rate, and the share of small families. Moreover, the findings suggest regional, divorce, and demographic heterogeneity in the impact of cultural distance on the digital economy.

Conventional room geometry blind inference techniques with acoustic signals often rely on prior knowledge, such as source signals or source positions, limiting their applicability when the sound source is unknown. To solve this problem, the authors propose a novel multitask deep neural network (DNN) model that jointly estimates sound source localization and room geometry using signals captured by a spherical microphone array. Considering the coupling between sound source content and environmental parameters in reverberation signals, extracted early reflection direction and delay information as network inputs to estimate spatial parameters is used, ensuring independence from the sound source signal. The proposed model employs a hierarchical architecturewith dedicated subnetworks to process direction-of-arrival (DOA) andtime-difference-of-arrival features, followed by a shared fusion module that exploits geometricconstraints between source and boundary positions. Compared with traditional methods, thismodel requires less prior environmental information and performs sound source localizationand room geometry inference with single-position sound field measurements. Experimentalresults from simulations and real measurements demonstrate the method’s effectiveness andprecision compared with conventional approaches across various scenarios.