ABSTRACT
China's shale gas production in 2020 exceeds 200 × 108 m³, which creates a miracle in the history of natural gas development in China. The Sichuan Basin has already been and will be the main battlefield of shale gas exploration and development in China. In order to further promote the large-scale efficient development of shale gas in China, under the new situation of global COVID-19 spread and domestic “carbon peak and carbon neutrality” goal, this paper analyzes the progress and challenges of shale gas exploration and development in the Sichuan Basin from four aspects, including resource exploration, gas reservoir engineering, drilling and production engineering and industry regulation, and puts forward countermeasures and suggestions for achieving large-scale efficient development of shale gas. The following research results are obtained: First, the large-scale efficient development of shale gas in the Sichuan Basin has to take the sustainable and stable production of middle–shallow shale gas and the large-scale productivity construction of deep shale gas as the base. Second, compared with the shale gas exploration and development in the North America, the Sichuan Basin has its own characteristics in terms of geographical setting, geological condition, drilling and production technology and industry regulation, which makes it difficult to copy the development pattern of large scale, high density and continuous well deployment from the North America, so it is necessary to adopt the strategy of “high production with few wells”. On the one hand, continue to apply the geology and engineering integration technology to carry out “integrated research, integrated design, integrated implementation and integrated iteration” in the whole life cycle of shale gas well;and on the other hand, carry out problem-oriented continuous researches from the aspects of geological evaluation, development policy, engineering technology and industry regulation, so as to improve geological evaluation theory and technology, innovate gas reservoir engineering theory and method, research and develop engineering technology for cost reduction and efficiency improvement, improve shale gas industry regulation, and form a new pattern of collaborative promotion of technical and non-technical elements. In conclusion, the research results provide important reference and guidance for the large-scale efficient development of shale gas in the Sichuan Basin and even the whole country.
ABSTRACT
Background: We aimed to analyse clinical characteristics and find potential factors predicting poor prognosis in patients with coronavirus disease 2019 (COVID-19). Methods: We analyzed the demographic and clinical data of COVID-19 patients and detected SARS-CoV-2 RNA in urine sediments collected from 53 COVID-19 patients enrolled in Renmin Hospital of Wuhan University from January 31, 2020 to February 18, 2020 with qRT-PCR analysis, and then classified those patients based on clinical conditions (severe or non-severe syndrome) and urinary SARS-CoV-2 RNA (URNA- or URNA+). Results: We found that COVID-19 patients with severe syndrome (severe patients) showed significantly higher positive rate (11 of 23, 47.8%) of urinary SARS-CoV-2 RNA than non-severe patients (4 of 30, 13.3%, p = 0.006). URNA+ patients or severe URNA+ subgroup exhibited higher prevalence of inflammation and immune discord, cardiovascular diseases, liver damage and renal disfunction, and higher risk of death than URNA- patients. To understand the potential mechanisms underlying the viral urine shedding, we performed renal histopathological analysis on postmortems of patients with COVID-19 and found that severe renal vascular endothelium lesion characterized by increase of the expression of thrombomodulin and von Willebrand factor, markers to assess the endothelium dysfunction. We proposed a theoretical and mathematic model to depict the potential factors determining the urine shedding of SARS-CoV-2. Conclusions: This study indicated that urinary SARS-CoV-2 RNA detected in urine specimens can be used to predict the progression and prognosis of COVID-19 severity.