Spiral Arm Pattern Motion in the SAO 206462 Protoplanetary Disk

Spiral arms have been observed in more than a dozen protoplanetary disks, yet the origin of nearly all systems is under debate. Multi-epoch monitoring of spiral arm morphology offers a dynamical way to distinguish two leading arm formation mechanisms: companion-driven and gravitational instability induction, since these mechanisms predict distinct motion patterns. By analyzing multi-epoch J-band observations of the SAO 206462 system using the SPHERE instrument on the Very Large Telescope in 2015 and 2016, we measure the pattern motion for its two prominent spiral arms in polarized light. On one hand, if both arms are comoving, they can be driven by a planet at 86₋₁₃⁺¹⁸ au on a circular orbit, with gravitational instability motion ruled out. On the other hand, they can be driven by two planets at 120₋₃₀⁺³⁰ au and 49₋₅⁺⁶ au, offering tentative evidence (3.0σ) that the two spirals are moving independently. The independent arm motion is possibly supported by our analysis of a re-reduction of archival observations using the NICMOS instrument on board the Hubble Space Telescope (HST) in 1998 and 2005, yet artifacts including shadows can manifest spurious arm motion in HST observations. We expect future re-observations to better constrain the motion mechanism for the SAO 206462 spiral arms

Effects of Wettability and Minerals on Residual Oil Distributions Based on Digital Rock and Machine Learning

AbstractThe wettability of mineral surfaces has significant impacts on transport mechanisms of two-phase flow, distribution characteristics of fluids, and the formation mechanisms of residual oil during water flooding. However, few studies have investigated such effects of mineral type and its surface wettability on rock properties in the literature. To unravel the dependence of hydrodynamics on wettability and minerals distribution, we designed a new experimental procedure that combined the multiphase flow experiments with a CT scan and QEMSCAN to obtain 3D digital models with multiple minerals and fluids. With the aid of QEMSCAN, six mineral components and two fluids in sandstones were segmented from the CT data based on the histogram threshold and watershed methods. Then, a mineral surface analysis algorithm was proposed to extract the mineral surface and classify its mineral categories. The in situ contact angle and pore occupancy were calculated to reveal the wettability variation of mineral surface and distribution characteristics of fluids. According to the shape features of the oil phase, the self-organizing map (SOM) method, one of the machine learning methods, was used to classify the residual oil into five types, namely, network, cluster, film, isolated, and droplet oil. The results indicate that each mineral’s contribution to the mineral surface is not proportional to its relative content. Feldspar, quartz, and clay are the main minerals in the studied sandstones and play a controlling role in the wettability variation. Different wettability samples show various characteristics of pore occupancy. The water flooding front of the weakly water-wet to intermediate-wet sample is uniform, and oil is effectively displaced in all pores with a long oil production period. The water-wet sample demonstrates severe fingering, with a high pore occupancy change rate in large pores and a short oil production period. The residual oil patterns gradually evolve from networks to clusters, isolated, and films due to the effects of snap-off and wettability inversion. This paper reveals the effects of wettability of mineral surface on the distribution characteristics and formation mechanisms of residual oil, which offers us an in-deep understanding of the impacts of wettability and minerals on multiphase flow and helps us make good schemes to improve oil recovery

A demand-response method to balance electric power-grids via HVAC systems using active energy-storage: simulation and on-site experiment

With the increasing popularity of renewable energy sources and the globally increasing electricity demand, the task of balancing the intermittent energy supply with varying demand becomes increasingly difficult. Instead of adjusting the supply, improving the demand response (DR) can be a more efficient way to optimize power balance. HVAC (heating, ventilation, and air-conditioning) systems, which operate on the demand side of power-grids, have a huge potential to improve the power balance. To assess their potential in a variable air volume (VAV) air-conditioning system with energy storage tank we introduce a demand response method that combines active cool-energy storage (ACES) with global temperature adjustment (GTA). To confirm the effectiveness of this combined ACES+GTA approach, we conduct measurements with the help of a full-scale VAV air-conditioning test setup. The experimental results are compared with a TRNSYS simulation. The measurements indicate that an energy-storing water-tank can effectively reduce the number of starts and stops for the heat pump. The simulation confirms that the ACES+GTA method can also effectively reduce the peak load of the power grid with little impact on the thermal comfort of the energy consumers. The cost-saving rate, compared to the conventional operating mode (no energy-storage during other periods), reaches 7.02% for an entire cooling season if the GTA method (with DR) is used

Extrinsic controls on turbidity fan lobes spatial distribution and potential reservoir presence prediction in half-graben lacustrine basin during early syn-rift: Insights from stratigraphic forward modelling

Turbidite strata are common along faulted margins of half-graben lacustrine basins, but complex lobe evolution may cause significant variability and uncertainty in the spatial distribution of turbidite sand bodies. This study integrates core samples, seismic and well log data from the Dongying Depression lacustrine basin in East China, and uses these data as inputs to a reduced-complexity stratigraphic forward model of turbidite fan lobe evolution. Data-unconstrained sensitivity analysis is used to investigate sensitivity of fan-lobe spatial distribution to fault-related subsidence rate, basin-margin slope, sediment input volume, and sediment input volume oscillation period. A data-constrained multiple-scenario approach then varied parameters within defined uncertainty ranges to generate a series of best-fit models to predict optimal reservoir presence locations. Results indicate that syn-rift segmentation of the Shengbei fault leads to spatial and temporal variation of fault-related subsidence in the hanging wall basin. External controls exert systematic impact on the spatial distribution of both smaller-scale flow beds and larger-scale fans on basin floor. Higher rates of fault-related subsidence and smaller sediment input volume produce more laterally confined fan lobe distribution. Higher basin-margin slope gradient produces more laterally clustered turbidites, but does not change fan lobe location, indicating break of slope is a more significant control on fan location. Multiple scenario reservoir presence probability maps suggest that bypass-dominated middle and inner fan areas, and smaller lengths of retrogradation-dominated feeder channels are most promising reservoir locations

Change-point multivariable quantile regression to explore effect of weather variables on building energy consumption and estimate base temperature range

Mean regression analysis may not capture associations that occur primarily in the tails of the outcome distribution. In this study, we focused on multiple weather factors to find the extent to which they impact heating-related gas consumption at higher quantiles. We used change-point multivariable quantile regression models to investigate distributional effects and heterogeneity in the gas consumption-related responses to weather factors. Subsequently, we analyzed quantile regression coefficients that corresponded to absolute differences in specific quantiles of gas consumption associated with a one-unit increase in weather factors. We found that the association of weather factors and gas consumption varied across 19 quantiles of gas consumption distribution. Heterogeneities varied between case study buildings: right tails of gas consumption for the community and educational buildings were more susceptible to weather factors than those of the healthcare building. The base temperature of the community buildings across quantiles of gas consumption indicated a flat trend, but the uncertainty ranges were relatively large compared with those for the community and educational buildings. The developed method in this study can be widely utilised to identify the most important factors and the extent to which they affect gas consumption at specific quantiles

Lithofacies Characteristics and Sweet Spot Distribution of Lacustrine Shale Oil: A Case Study from the Dongying Depression, Bohai Bay Basin, China

AbstractLacustrine shale is characterized by rapid lithofacies transformation and compositional heterogeneity, which present challenges in shale oil sweet spot evaluation and distribution prediction and should be systematically studied. Field emission-scanning electron microscopy (FE-SEM), low-pressure adsorption isotherm analysis, mercury intrusion porosimetry (MIP), and triaxial compression testing were employed to comprehensively analyze the oil-bearing capacity, reservoir properties, fluidity, and frackability of different lithofacies. Via analyses of mineral composition, total organic carbon (TOC) content, and sedimentary structure, seven lithofacies were identified: organic-rich calcareous shale (L1), organic-rich laminated calcareous mudstone (L2), organic-rich laminated carbonate-bearing mudstone (L3), intermediate-organic laminated calcareous mudstone (L4), organic-poor laminated calcareous mudstone (L5), organic-poor thin-bedded calcareous mudstone (L6), and organic-rich laminated silty mudstone (L7). Considered together, the oil-bearing capacity, reservoir properties, fluidity, and frackability suggested that the L1 and L7 lithofacies were high-quality sweet spots, with satisfactory oil-bearing capacity (TOC>3.5%; S1>10 mgHC/grock), well-developed pores and microfractures, notable fluidity (as indicated by a high oil saturation index value), and suitable brittleness. The sweet spot distribution was predicted according to multiresolution graph-based clustering analysis of well logs. The results indicate that comprehensive research of the key factors for shale oil and lithofacies prediction can promote sweet spot prediction and enhance shale oil exploration

Characterization of LC-MS based urine metabolomics in healthy children and adults

Previous studies reported that sex and age could influence urine metabolomics, which should be considered in biomarker discovery. As a consequence, for the baseline of urine metabolomics characteristics, it becomes critical to avoid confounding effects in clinical cohort studies. In this study, we provided a comprehensive lifespan characterization of urine metabolomics in a cohort of 348 healthy children and 315 adults, aged 1 to 78 years, using liquid chromatography coupled with high resolution mass spectrometry. Our results suggest that sex-dependent urine metabolites are much greater in adults than in children. The pantothenate and CoA biosynthesis and alanine metabolism pathways were enriched in early life. Androgen and estrogen metabolism showed high activity during adolescence and youth stages. Pyrimidine metabolism was enriched in the geriatric stage. Based on the above analysis, metabolomic characteristics of each age stage were provided. This work could help us understand the baseline of urine metabolism characteristics and contribute to further studies of clinical disease biomarker discovery

Flow Patterns and Pore Structure Effects on Residual Oil during Water and CO₂ Flooding: In Situ CT Scanning

Carbon dioxide (CO2) enhanced oil recovery (EOR) is an important technology to achieve carbon neutrality by sequestering CO2 underground while simultaneously recovering crude oil. Reservoir pore structure is a key factor influencing CO2 EOR. In this study, we utilized advanced online in situ CT scanning and digital rock techniques to obtain, for the first time, evolution profiles of the finger area during water flooding and CO2 flooding processes, quantitatively assessing the differences in fluid patterns. Additionally, we first introduced an innovative approach using advanced machine learning techniques, especially XGBoost and SHAP, to construct a predictive model of the relative change of oil phase occupancy (RCPOC) based on pore structure parameters and evaluated the importance of each pore structure parameter. Importantly, our results revealed that CO2 can significantly increase the sweep efficiency area while substantially reducing residual oil saturation, in stark contrast to the relatively uniform water front observed during water flooding. Furthermore, we elucidated the critical role of capillary forces, demonstrating that water flooding primarily extracts trapped oil from small pores, while CO2 flooding effectively extracts oil from larger pores. During CO2 flooding, there is a positive correlation between coordination number, mean throat radius (MeanTR), and mean throat length (MeanTL) and the change in oil occupancy, whereas their influence during water flooding is limited. In summary, this study contributes to the understanding of flow patterns and pore structure effects on residual oil during water flooding and the CO2 flooding processes. It also provides a novel approach based on pore structure parameters to predict RCPOC and assess the importance of influencing factors, thereby expanding our research perspective on this issue