Testing oil saturation distribution in migration paths using MRI

International audienceMagnetic Resonance Imaging (MRI) method allows to observe the distribution of different fluids in situ in porous media, and to measure oil and water saturation. Although this technique has great advantages compared to others, there remains large space for assessing the method and improving the accuracy of measurement. Using MRI, the oil secondary migration paths are scanned to measure the saturation distribution during the laboratory experiments. The resulting map can be calibrated using a device with the same pore structure as the probed sample and fully saturated with oil. This device is scanned with the probed sample at the same time in order to calibrate the saturation. The Spin-echo multi-slices sequence (SEMS) is adopted for MRI to ensure that the oil saturation in migration paths is accurately measured. The relevant spatial resolution of the mapping is defined according to the concept of REV (representative elementary volume). The oil saturation resulting from data obtained using different image formats are compared and the resulting saturation evaluation is compared to direct bulk saturation measurements. This comparison demonstrates that the calculated MRI oil saturation using DICOM image format is quite accurate, with a relative error less than 2%

The Anomalous Regional Hadley Circulation in the ENSO Cycle

Based on our previous work on El Niño-Southern Oscillation (ENSO) theory, this article investigated the relationship between regional Hadley circulation and ENSO evolution. We found that an anomalous meridional circulation (AMC) steadily appeared on both sides of equator around the dateline from a mature ENSO (September) to ENSO decay (the next May), which played a role in enhancing or weakening in situ Hadley circulation. Meanwhile, a positive or negative sea level pressure anomaly (SLPa) in the western Pacific Ocean evolved into a shape in which the western equatorial part was recessed near the dateline and protruded near the subtropical dateline regions on both sides of equator. And the SLPa area with the opposite sign over the eastern Pacific was inserted into the recessed part at the equator around the dateline like a wedge. The mirror image of capital sigma shape that is the boundary line dividing opposite SLPa distribution is formed (mirror sigma pattern). The southern and northern subtropical SLP strengths around the dateline tended to increase or decrease accordingly with mirror sigma pattern, which responded to the AMC about two months later. The subtropical SLPa area around the dateline tended to expand eastward into the Nino 3 longitude sector until next August, which impacts reducing the initially warm or cold ENSO strength months later. A mechanism of a combined operation of regional Hadley circulation and Walker circulation existed in this situation, which implies that ENSO episodes play a role in maintaining the ENSO cycle by balancing heat and circulations between tropics and mid-latitudes

Flow structure transition in thermal vibrational convection

This study investigates the effect of vibration on the flow structure transitions in thermal vibrational convection (TVC) systems, which occur when a fluid layer with a temperature gradient is excited by vibration. Direct numerical simulations of TVC in a two-dimensional enclosed square box were performed over a range of dimensionless vibration amplitudes $0.001 \le a \le 0.3$ and angular frequencies $10^{2} \le \omega \le 10^{7}$, with a fixed Prandtl number of 4.38. The flow visualisation shows the transition behaviour of flow structure upon the varying frequency, characterising three distinct regimes, which are the periodic-circulation regime, columnar regime and columnar-broken regime. Different statistical properties are distinguished from the temperature and velocity fluctuations at the boundary layer and mid-height. Upon transition into the columnar regime, columnar thermal coherent structures are formed, in contrast to the periodic oscillating circulation. These columns are contributed by merging of thermal plumes near the boundary layer, and the resultant thermal updrafts remain at almost fixed lateral position, leading to a decrease in fluctuations. We further find that the critical point of this transition can be described nicely by the vibrational Rayleigh number $Ra_\mathrm{vib}$. As the frequency continues to increase, entering the so-called columnar-broken regime, the columnar structures are broken, and eventually the flow state becomes a large-scale circulation, characterised by a sudden increase in fluctuations. Finally, a phase diagram is constructed to summarise the flow structure transition over a wide range of vibration amplitude and frequency parameters.Comment: 14 pages, 9 figure

The Okhotsk-Japan Circulation Pattern and the Heavy Rainfall in Beijing in 2012 Summer

Using station precipitation and reanalysis data, we examined the evolution of the large-scale circulations associated with the heavy rainfall event that occurred around July 21, 2012 (721 heavy rainfall). This study focuses on a role that the large-scale circulations named “the Okhotsk-Japan (OKJ) circulation pattern” played in causing the heavy rainfall case. We found that the 721 heavy rainfall occurred under a background of the OKJ circulation that persisted for about 10 days. However, the pattern was different from the normal OKJ circulation, for this circulation pattern accompanied a blocking high between the Ural Mountains and the Baikal Lake. This difference resulted from the seasonal change of the basic flow. The related Rossby wave propagated eastward during the persisting period of the dominated OKJ pattern. This caused the development of a low-pressure system around the Baikal Lake and the weakening of a ridge around the Okhotsk Sea. The slow evolution of the OKJ circulation created a favorable environment for the moisture transport to northern China, assisting in the generation of the 721 heavy rainfall

A Two-Stage Adverse Weather Semantic Segmentation Method for WeatherProof Challenge CVPR 2024 Workshop UG2+

This technical report presents our team's solution for the WeatherProof Dataset Challenge: Semantic Segmentation in Adverse Weather at CVPR'24 UG2+. We propose a two-stage deep learning framework for this task. In the first stage, we preprocess the provided dataset by concatenating images into video sequences. Subsequently, we leverage a low-rank video deraining method to generate high-fidelity pseudo ground truths. These pseudo ground truths offer superior alignment compared to the original ground truths, facilitating model convergence during training. In the second stage, we employ the InternImage network to train for the semantic segmentation task using the generated pseudo ground truths. Notably, our meticulously designed framework demonstrates robustness to degraded data captured under adverse weather conditions. In the challenge, our solution achieved a competitive score of 0.43 on the Mean Intersection over Union (mIoU) metric, securing a respectable rank of 4th

Computable features required to evaluate the efficacy of drugs and a universal algorithm to find optimally effective drug in a drug complex

Background The H1N1 pandemic in 2009 and the H5N1 pandemic in 2005 demonstrated that the drugs approved to treat influenza A viruses have low efficacy. This provided a stimulus for new studies of influenza A viruses in the context of the methods used in drug design developed over the past 100 years. Finding new universal drugs is the ultimate goal but its long time horizon is incompatible with emergency situations created by reoccurring influenza outbreaks. Therefore, we propose a computer-aided method for finding efficacious drugs and drug complexes based on the use of the DrugBank database. Methods (1) We start by assembling a panel of target proteins. (2) We then assemble a panel of drugs. (3) This is followed by a selection of benchmark binding pockets based on the panel of target proteins and the panel of drugs. (4) We generate a set of computational features, which measure the efficacy of a drug. (5) We propose a universal program to search for drugs and drug complexes. (6) A case study we report here illustrates how to use this universal program for finding an optimal drug and a drug complex for a given target. (7) Validation of the Azirchromycin and Aspirin complex is provided mathematically. (8) Finally, we propose a simple strategy to validate our computational prediction that the Azirchromycin and Aspirin complex should prove clinically effective. Result A set of computable features are mined and then based on these features, a universal program for finding the potential drug &drug complexes is proposed. Using this universal program, the Azirchromycin and Aspirin complex is selected and its efficacy is predicted mathematically. For clinical validation of this finding, future work is still required

Wildland Fires Worsened Population Exposure to Pm

As wildland fires become more frequent and intense, fire smoke has significantly worsened the ambient air quality, posing greater health risks. to better understand the impact of wildfire smoke on air quality, we developed a modeling system to estimate daily P

Intensified Positive Arctic–Methane Feedback under IPCC Climate Scenarios in the 21st Century

The positive Arctic–methane (CH 4 ) feedback forms when more CH 4 is released from the Arctic tundra to warm the climate, further stimulating the Arctic to emit CH 4 . This study utilized the CLM-Microbe model to project CH 4 emissions across five distinct Arctic tundra ecosystems on the Alaska North Slope, considering three Shared Socioeconomic Pathway (SSP) scenarios using climate data from three climate models from 2016 to 2100. Employing a hyper-resolution of 5 m × 5 m within 40,000 m 2 domains accounted for the Arctic tundra’s high spatial heterogeneity; three sites were near Utqiaġvik (US-Beo, US-Bes, and US-Brw), with one each in Atqasuk (US-Atq) and Ivotuk (US-Ivo). Simulated CH 4 emissions substantially increased by a factor of 5.3 to 7.5 under the SSP5–8.5 scenario compared to the SSP1–2.6 and SSP2–4.5 scenarios. The projected CH 4 emissions exhibited a stronger response to rising temperature under the SSP5–8.5 scenario than under the SSP1–2.6 and SSP2–4.5 scenarios, primarily due to strong temperature dependence and the enhanced precipitation-induced expansion of anoxic conditions that promoted methanogenesis. The CH 4 transport via ebullition and plant-mediated transport is projected to increase under all three SSP scenarios, and ebullition dominated CH 4 transport by 2100 across five sites. Projected CH 4 emissions varied in temperature sensitivity, with a Q 10 range of 2.7 to 60.9 under SSP1–2.6, 3.8 to 17.6 under SSP2–4.5, and 5.7 to 17.2 under SSP5–8.5. Compared with the other three sites, US-Atq and US-Ivo were estimated to have greater increases in CH 4 emissions due to warmer temperatures and higher precipitation. The fact that warmer sites and warmer climate scenarios had higher CH 4 emissions suggests an intensified positive Arctic–CH 4 feedback in the 21st century. Microbial physiology and substrate availability dominated the enhanced CH 4 production. The simulated intensified positive feedback underscores the urgent need for a more mechanistic understanding of CH 4 dynamics and the development of strategies to mitigate CH 4 across the Arctic

Dominant Edaphic Controls on Particulate Organic Carbon in Global Soils

The current soil carbon paradigm puts particulate organic carbon (POC) as one of the major components of soil organic carbon worldwide, highlighting its pivotal role in carbon mitigation. In this study, we compiled a global dataset of 3418 data points of POC concentration in soils and applied empirical modeling and machine learning algorithms to investigate the spatial variation in POC concentration and its controls. The global POC concentration in topsoil (0-30 cm) is estimated as 3.02 g C/kg dry soil, exhibiting a declining trend from polar regions to the equator. Boreal forests contain the highest POC concentration, averaging at 4.58 g C/kg dry soil, whereas savannas exhibit the lowest at 1.41 g C/kg dry soil. We developed a global map of soil POC density in soil profiles of 0-30 cm and 0-100 cm with an empirical model. The global stock of POC is 158.15 Pg C for 0-30 cm and 222.75 Pg C for 0-100 cm soil profiles with a substantial spatial variation. Analysis with a machine learning algorithm concluded the predominate controls of edaphic factors (i.e., bulk density and soil C content) on POC concentration across biomes. However, the secondary controls vary among biomes, with solid climate controls in grassland, pasture, and shrubland, while strong vegetation controls in forests. The biome-level estimates and maps of POC density provide a benchmark for modeling C fractions in soils; the various controls on POC suggest incorporating biological and physiochemical mechanisms in soil C models to assess and forecast the soil POC dynamics in response to global change

Carbon in Chinese grasslands : meta-analysis and theory of grazing effects

Unidad de excelencia María de Maeztu CEX2019-000940-MGlobally, livestock grazing is an important management factor influencing soil degradation, soil health and carbon (C) stocks of grassland ecosystems. However, the effects of grassland types, grazing intensity and grazing duration on C stocks are unclear across large geographic scales. To provide a more comprehensive assessment of how grazing drives ecosystem C stocks in grasslands, we compiled and analyzed data from 306 studies featuring four grassland types across China: desert steppes, typical steppes, meadow steppes and alpine steppes. Light grazing was the best management practice for desert steppes (< 2 sheep ha−1) and typical steppes (3 to 4 sheep ha−1), whereas medium grazing pressure was optimal for meadow steppes (5 to 6 sheep ha−1) and alpine steppes (7 to 8 sheep ha−1) leading to the highest ecosystem C stocks under grazing. Plant biomass (desert steppes) and soil C stocks (meadow steppes) increased under light or medium grazing, confirming the 'intermediate disturbance hypothesis'. Heavy grazing decreased all C stocks regardless of grassland ecosystem types, approximately 1.4 Mg ha−1 per year for the whole ecosystem. The regrowth and regeneration of grasslands in response to grazing intensity (i.e., grazing optimization) depended on grassland types and grazing duration. In conclusion, grassland grazing is a double-edged sword. On the one hand, proper management (light or medium grazing) can maintain and even increase C stocks above- and belowground, and increase the harvested livestock products from grasslands. On the other hand, human-induced overgrazing can lead to rapid degradation of vegetation and soils, resulting in significant carbon loss and requiring long-term recovery. Grazing regimes (i.e., intensity and duration applied) must consider specific grassland characteristics to ensure stable productivity rates and optimal impacts on ecosystem C stocks