Development and performance evaluation of bioenzyme-responsive temporary plugging materials

Ocean gas hydrate is a potentially efficient and clean oil and gas alternative energy resource. Wells with complex structure, such as horizontal wells, can improve the extraction efficiency; however, drilling operations face challenges such as wellbore instability and reservoir damage due to the complex interaction between drilling fluids and hydrate reservoirs. This work presents a ceramsite temporary plugging microcapsule that uses ceramsite modified by 3-aminopropyltriethoxysilane as the core material and chitosan and sodium alginate as shell materials. It exhibits high strength during drilling and excellent plugging effects. After the action of bioenzymes, it can easily be dissolved, leading to high permeability post-drilling. The analysis and performance evaluation of ceramsite microcapsules show that their particle size is generally 40 μm, which can match the pore size of the hydrate reservoir depending on the number of encapsulation layers. Bioenzyme optimization at 15 ◦C yields the best permeability recovery of 74.5% for the low-temperature composite enzyme. As the temperature rises, the permeability recovery rate of ceramic microcapsules gradually increases and the difference in permeability recovery rate between 5 and 25 ◦C becomes more significant. With a longer degradation time, the permeability recovery rate of ceramsite microcapsules gradually enhances and the difference in permeability recovery rate becomes smaller after 12 h. The microcapsules exhibit a specific inhibitory effect on the decomposition of hydrates. Utilizing bioenzyme- responsive ceramsite microcapsules as temporary plugging materials can establish an “isolation barrier” around the wellbore, effectively sealing off the interaction between the wellbore and the gas hydrate reservoir during the drilling process. Re-opening the flow path around the well by bio-enzymatic unblocking at the end of drilling proves to be effective in solving the problem of balancing the stability of the well wall and protecting the reservoir.Document Type: Original articleCited as: Sun, J., Li, Y., Liao, B., Bai, Y., Li, W., Wang, J. Development and performance evaluation of bioenzyme-responsive temporary plugging materials. Advances in Geo-Energy Research, 2024, 11(1): 20-28. https://doi.org/10.46690/ager.2024.01.0

Measurement of CO2 leakage from pipelines under CCS conditions through acoustic emission detection and data driven modeling

CO2 leakage from carbon capture and storage (CCS) networks may lead to ecological hazards, bodily injury and economic losses. In addition, captured CO2 often contains impurities which affect the leakage behavior of CO2. This paper presents a method for continuous and quantitative measurements of CO2 leakage flowrate and the volume fraction of impurities by combining data-driven models with acoustic emission (AE) and temperature sensors. Three data-driven models based on artificial neural network (ANN), random forest (RF), and least squares support vector machine (LS-SVM) algorithms are established. The outputs from the three data-driven models are then integrated to give improved results. Experimental work was conducted on a purpose-built CO2 leakage test rig under a range of conditions. N2 was injected to the CO2 gas stream as an impurity medium. Results show that the integrated model yields a relative error within ±4.0% for leakage flowrate and ±3.4% for volume fraction of N2

Dynamic measurement of gas volume fraction in a CO2 pipeline through capacitive sensing and data driven modelling

Gas volume fraction (GVF) measurement of gas-liquid two-phase CO2 flow is essential in the deployment of carbon capture and storage (CCS) technology. This paper presents a new method to measure the GVF of two-phase CO2 flow using a 12-electrode capacitive sensor. Three data driven models, based on back-propagation neural network (BPNN), radial basis function neural network (RBFNN) and least-squares support vector machine (LS-SVM), respectively, are established using the capacitance data. In the data pre-processing stage, copula functions are applied to select feature variables and generate training datasets for the data driven models. Experiments were conducted on a CO2 gas-liquid two-phase flow rig under steady-state flow conditions with the mass flowrate of liquid CO2 ranging from 200 kg/h to 3100 kg/h and the GVF from 0% to 84%. Due to the flexible operations of the power generation utility with CCS capabilities, dynamic experiments with rapid changes in the GVF were also carried out on the test rig to evaluate the real-time performance of the data driven models. Measurement results under steady-state flow conditions demonstrate that the RBFNN yields relative errors within ±7% and outperforms the other two models. The results under dynamic flow conditions illustrate that the RBFNN can follow the rapid changes in the GVF with an error within ±16%

Real-time Imaging and Holdup Measurement of Carbon Dioxide under CCS Conditions Using Electrical Capacitance Tomography

This paper presented a method for real-time cross-sectional imaging and holdup measurement of gas-liquid two-phase carbon dioxide (CO2) flow using electrical capacitance tomography (ECT). A high-pressure ECT sensor with 12 electrodes was constructed and a dedicated digital ECT system with a data acquisition rate of 757 frames/s was developed for capacitance measurement. Three widely used image reconstruction algorithms were compared for tomographic imaging and phase holdup measurement. Experiments were carried out on a DN25 laboratorial scale CO2 two-phase flow rig at a pressure of 6 MPa for the gaseous mass flowrates from 0 to 430 kg/h and liquid mass flowrates at 515, 1100, and 1900 kg/h. The experimental results show that the cross-sectional distribution of two-phase CO2 flow can be monitored using the ECT system, which matches well with the images captured by a high-speed imaging system. Compared with the reference gas holdup obtained by the flowmeters in the single phase gaseous and liquid loops, the absolute accuracy of the gas holdup measurement can reach 6%, indicating that the developed system is promising for real-time monitoring of carbon dioxide in carbon capture and storage transportation pipelines

Tree-ring stable carbon isotope-based April-June relative humidity reconstruction since AD 1648 in Mt. Tianmu, China

Based on accurate dating, we have determined the stable carbon isotope ratios (delta C-13) of five Cryptomeria fortunei specimens from Mt. Tianmu, a subtropical area in southern China. The five delta C-13 time series records are combined into a single representative delta C-13 time series using a "numerical mix method." These are normalized to remove temporal variations of delta(13) C in atmospheric CO2 to obtain a carbon isotopic discrimination (Delta C-13) time series, in which we observe a distinct correlation between Delta C-13 and local April to June mean relative humidity (RH (AMJ) ) (n = 64, r = 0.858, p < 0.0001). We use this relationship to reconstruct RH (AMJ) variations from ad 1648 to 2014 at Mt. Tianmu. The reconstructed sequence show that over the past 367 years, Mt. Tianmu area was relatively wet, but in the latter part of the twentieth century, under the influence of increasing global warming, it has experienced a sharp reduction in relative humidity. Spatial correlation analysis reveals a significant negative correlation between RH (AMJ) at Mt. Tianmu and Sea Surface Temperature (SSTs) in the western equatorial Pacific and Indian Ocean. In other words, there is a positive correlation between tree-ring delta C-13 in Mt. Tianmu and SSTs. Both observed and reconstructed RH (AMJ) show significant positive correlations with East Asian and South Asian monsoons from 1951 to 2014, which indicate that RH (AMJ) from Mt. Tianmu reflects the variability of the Asian summer monsoon intensity to a great extent. The summer monsoon has weakened since 1960. However, an increase in relative humidity since 2003 implies a recent enhancement in the summer monsoon

RNA-seq-based digital gene expression analysis reveals modification of host defense responses by rice stripe virus during disease symptom development in Arabidopsis

DEGs involved in protein phosphorylation at 14 dpi. (XLSX 52 kb

Risk assessment of malaria in land border regions of China in the context of malaria elimination

BACKGROUND:Cross-border malaria transmission poses a challenge for countries to achieve and maintain malaria elimination. Because of a dramatic increase of cross-border population movement between China and 14 neighbouring countries, the malaria epidemic risk in China's land border regions needs to be understood.METHODS: In this study, individual case-based epidemiological data on malaria in the 136 counties of China with international land borders, from 2011 to 2014, were extracted from the National Infectious Disease Information System. The Plasmodium species, seasonality, spatiotemporal distribution and changing features of imported and indigenous cases were analysed using descriptive spatial and temporal methods.RESULTS:A total of 1948 malaria cases were reported, with 1406 (72.2%) imported cases and 542 (27.8%) indigenous cases. Plasmodium vivax is the predominant species, with 1536 malaria cases occurrence (78.9%), following by Plasmodium falciparum (361 cases, 18.5%), and the others (51 cases, 2.6%). The magnitude and geographic distribution of malaria in land border counties shrunk sharply during the elimination period. Imported malaria cases were with a peak of 546 cases in 2011, decreasing yearly in the following years. The number of counties with imported cases decreased from 28 counties in 2011 to 26 counties in 2014. Indigenous malaria cases presented a markedly decreasing trend, with 319 indigenous cases in 2011 reducing to only 33 indigenous cases in 2014. The number of counties with indigenous cases reduced from 26 counties in 2011 to 10 counties in 2014. However, several bordering counties of Yunnan province adjacent to Myanmar reported indigenous malaria cases in the four consecutive years from 2011 to 2014.CONCLUSIONS:The scale and extent of malaria occurrence in the international land border counties of China decreased dramatically during the elimination period. However, several high-risk counties, especially along the China-Myanmar border, still face a persistent risk of malaria introduction and transmission. The study emphasizes the importance and urgency of cross-border cooperation between neighbouring countries to jointly face malaria threats to elimination goals

Evaluation of a novel saliva-based epidermal growth factor receptor mutation detection for lung cancer: A pilot study.

BackgroundThis article describes a pilot study evaluating a novel liquid biopsy system for non-small cell lung cancer (NSCLC) patients. The electric field-induced release and measurement (EFIRM) method utilizes an electrochemical biosensor for detecting oncogenic mutations in biofluids.MethodsSaliva and plasma of 17 patients were collected from three cancer centers prior to and after surgical resection. The EFIRM method was then applied to the collected samples to assay for exon 19 deletion and p.L858 mutations. EFIRM results were compared with cobas results of exon 19 deletion and p.L858 mutation detection in cancer tissues.ResultsThe EFIRM method was found to detect exon 19 deletion with an area under the curve (AUC) of 1.0 in both saliva and plasma samples in lung cancer patients. For L858R mutation detection, the AUC of saliva was 1.0, while the AUC of plasma was 0.98. Strong correlations were also found between presurgery and post-surgery samples for both saliva (0.86 for exon 19 and 0.98 for L858R) and plasma (0.73 for exon 19 and 0.94 for L858R).ConclusionOur study demonstrates the feasibility of utilizing EFIRM to rapidly, non-invasively, and conveniently detect epidermal growth factor receptor mutations in the saliva of patients with NSCLC, with results corresponding perfectly with the results of cobas tissue genotyping

SARS-CoV-2 N protein induced acute kidney injury in diabetic db/db mice is associated with a Mincle-dependent M1 macrophage activation

“Cytokine storm” is common in critically ill COVID-19 patients, however, mechanisms remain largely unknown. Here, we reported that overexpression of SARS-CoV-2 N protein in diabetic db/db mice significantly increased tubular death and the release of HMGB1, one of the damage-associated molecular patterns (DAMPs), to trigger M1 proinflammatory macrophage activation and production of IL-6, TNF-α, and MCP-1 via a Mincle-Syk/NF-κB-dependent mechanism. This was further confirmed in vitro that overexpression of SARS-CoV-2 N protein caused the release of HMGB1 from injured tubular cells under high AGE conditions, which resulted in M1 macrophage activation and production of proinflammatory cytokines via a Mincle-Syk/NF-κB-dependent mechanism. This was further evidenced by specifically silencing macrophage Mincle to block HMGB1-induced M1 macrophage activation and production of IL-6, TNF-α, and MCP-1 in vitro. Importantly, we also uncovered that treatment with quercetin largely improved SARS-CoV-2 N protein-induced AKI in db/db mice. Mechanistically, we found that quercetin treatment significantly inhibited the release of a DAMP molecule HMGB1 and inactivated M1 pro-inflammatory macrophage while promoting reparative M2 macrophage responses by suppressing Mincle-Syk/NF-κB signaling in vivo and in vitro. In conclusion, SARS-CoV-2 N protein-induced AKI in db/db mice is associated with Mincle-dependent M1 macrophage activation. Inhibition of this pathway may be a mechanism through which quercetin inhibits COVID-19-associated AKI