Reservoir Characteristics and Resource Potential of Marine Shale in South China: A Review

Many sets of Paleozoic marine organic-rich shale strata have developed in South China. However, the exploration and development results of these shale formations are quite different. Based on the data of core experiment analysis, drilling, fracturing test of typical wells, the reservoir differences and controlling factors of four sets of typical marine organic-rich shale in southern China are investigated. The four sets of shale have obvious differences in reservoir characteristics. Ordovician–Silurian shale mainly develops siliceous shale, mixed shale and argillaceous shale, with large pore diameter, high porosity, moderate thermal maturity, large pore volume and specific surface area. Cambrian shale mainly develops siliceous shale and mixed shale, with small pore diameter, low porosity, high thermal maturity and smaller pore volume and specific surface area than Ordovician–Silurian shale. Devonian–Carboniferous shale has similar mineral composition to Ordovician–Silurian shale, with small pore diameter, low porosity, moderate thermal maturity and similar pore volume and specific surface area to that of Cambrian shale. Permian shale has very complex mineral composition, with large pore diameter, low to medium thermal maturity and small specific surface area. Mineral composition, thermal maturity and tectonic preservation conditions are the main factors controlling shale reservoir development. Siliceous minerals in Cambrian shale and Ordovician–Silurian shale are mainly of biological origin, which make the support capacity better than Devonian–Carboniferous shale and Permian shale (siliceous minerals are mainly of terrigenous origin and biological origin). Thermal maturity of Ordovician–Silurian shale and Devonian–Carboniferous shale is moderate, with a large number of organic pores developed. Thermal maturity of Cambrian shale and Permian shale is respectively too high and too low, the development of organic pores is significantly weaker than the two sets of shale above. There are obvious differences in tectonic preservation conditions inside and outside the Sichuan Basin. Shale reservoirs inside the Sichuan Basin are characterized by overpressure due to stable tectonic activities, while shale reservoirs outside the Sichuan Basin are generally normal–pressure. Four sets of marine shale in South China all have certain resource potentials, but the exploration and development of shale gas is still constrained by complicated geological conditions, single economic shale formation, high exploration and development costs and other aspects. It is necessary for further research on shale gas accumulation theory, exploration and development technology and related policies to promote the development of China’s shale gas industry

Reservoir Characteristics and Resource Potential of Marine Shale in South China: A Review

Many sets of Paleozoic marine organic-rich shale strata have developed in South China. However, the exploration and development results of these shale formations are quite different. Based on the data of core experiment analysis, drilling, fracturing test of typical wells, the reservoir differences and controlling factors of four sets of typical marine organic-rich shale in southern China are investigated. The four sets of shale have obvious differences in reservoir characteristics. Ordovician–Silurian shale mainly develops siliceous shale, mixed shale and argillaceous shale, with large pore diameter, high porosity, moderate thermal maturity, large pore volume and specific surface area. Cambrian shale mainly develops siliceous shale and mixed shale, with small pore diameter, low porosity, high thermal maturity and smaller pore volume and specific surface area than Ordovician–Silurian shale. Devonian–Carboniferous shale has similar mineral composition to Ordovician–Silurian shale, with small pore diameter, low porosity, moderate thermal maturity and similar pore volume and specific surface area to that of Cambrian shale. Permian shale has very complex mineral composition, with large pore diameter, low to medium thermal maturity and small specific surface area. Mineral composition, thermal maturity and tectonic preservation conditions are the main factors controlling shale reservoir development. Siliceous minerals in Cambrian shale and Ordovician–Silurian shale are mainly of biological origin, which make the support capacity better than Devonian–Carboniferous shale and Permian shale (siliceous minerals are mainly of terrigenous origin and biological origin). Thermal maturity of Ordovician–Silurian shale and Devonian–Carboniferous shale is moderate, with a large number of organic pores developed. Thermal maturity of Cambrian shale and Permian shale is respectively too high and too low, the development of organic pores is significantly weaker than the two sets of shale above. There are obvious differences in tectonic preservation conditions inside and outside the Sichuan Basin. Shale reservoirs inside the Sichuan Basin are characterized by overpressure due to stable tectonic activities, while shale reservoirs outside the Sichuan Basin are generally normal–pressure. Four sets of marine shale in South China all have certain resource potentials, but the exploration and development of shale gas is still constrained by complicated geological conditions, single economic shale formation, high exploration and development costs and other aspects. It is necessary for further research on shale gas accumulation theory, exploration and development technology and related policies to promote the development of China’s shale gas industry

A reduced latency regional gap-filling method for SMAP using random forest regression

Summary: The soil moisture active/passive (SMAP) mission represents a significant advance in measuring soil moisture from satellites. However, its large spatial-temporal data gaps limit the use of its values in near-real-time (NRT) applications. Considering this, the study uses NRT operational metadata (precipitation and skin temperature), together with some surface parameterization information, to feed into a random forest model to retrieve the missing values of the SMAP L3 soil moisture product. This practice was tested in filling the missing points for both SMAP descending (6:00 AM) and ascending orbits (6:00 PM) in a crop-dominated area from 2015 to 2019. The trained models with optimized hyper-parameters show the goodness of fit (R2 ≥ 0.86), and their resulting gap-filled estimates were compared against a range of competing products with in situ and triple collocation validation. This gap-filling scheme driven by low-latency data sources is first attempted to enhance NRT spatiotemporal support for SMAP L3 soil moisture

Estimation and Assessment of the Root Zone Soil Moisture from Near-Surface Measurements over Huai River Basin

Root zone soil moisture (RZSM) is a vital variable for agricultural production, water resource management and runoff prediction. Satellites provide large-scale and long-term near-surface soil moisture retrievals, which can be used to estimate RZSM through various methods. In this study, we tested the utility of an exponential filter (ExpF) using in situ soil moisture by optimizing the optimal characteristic time length T_opt for different soil depths. Furthermore, the parameter analysis showed that T_opt correlated negatively with precipitation and had no significant correlation with selected soil properties. Two approaches were taken to obtain T_opt: (1) optimization of the Nash–Sutcliffe efficiency coefficient (NSE); (2) calculation based on annual average precipitation. The precipitation-based T_pre outperformed the station-specific T_opt and stations-averaged T_opt. To apply the ExpF on grid scale, the precipitation-based T_pre considering spatial variability was adopted in the ExpF to obtain RZSM from a new soil moisture dataset RF_SMAP_L3_P (Random Forest Soil Moisture Active Passive_L3_Passive) continuous in time and space over Huai River Basin. Finally, the performance of RF_SMAP_L3_P RZSM (0–100 cm) was evaluated using in situ measurements and compared with mainstream products, for instance, Soil Moisture Active Passive (SMAP) and Soil Moisture and Ocean Salinity Level 4 (SMOS L4) RZSM. The results indicated that RF_SMAP_L3_P RZSM could captured the temporal variation of measured RZSM best with R value of 0.586, followed by SMAP L4, which had the lowest bias value of 0.03, and SMOS L4 significantly underestimated the measured RZSM with bias value of −0.048 in the basin. Higher accuracy of RF_SMAP_L3_P RZSM was found in the flood period compared with the non-flood period, which indicates a better application for ExpF in wetter weather conditions.This article is published as Liu E, Zhu Y, Lü H, Horton R, Gou Q, Wang X, Ding Z, Xu H, Pan Y. Estimation and Assessment of the Root Zone Soil Moisture from Near-Surface Measurements over Huai River Basin. Atmosphere. 2023; 14(1):124. https://doi.org/10.3390/atmos14010124. Posted with permission.This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/)

Estimation and Assessment of the Root Zone Soil Moisture from Near-Surface Measurements over Huai River Basin

Root zone soil moisture (RZSM) is a vital variable for agricultural production, water resource management and runoff prediction. Satellites provide large-scale and long-term near-surface soil moisture retrievals, which can be used to estimate RZSM through various methods. In this study, we tested the utility of an exponential filter (ExpF) using in situ soil moisture by optimizing the optimal characteristic time length T_opt for different soil depths. Furthermore, the parameter analysis showed that T_opt correlated negatively with precipitation and had no significant correlation with selected soil properties. Two approaches were taken to obtain T_opt: (1) optimization of the Nash–Sutcliffe efficiency coefficient (NSE); (2) calculation based on annual average precipitation. The precipitation-based T_pre outperformed the station-specific T_opt and stations-averaged T_opt. To apply the ExpF on grid scale, the precipitation-based T_pre considering spatial variability was adopted in the ExpF to obtain RZSM from a new soil moisture dataset RF_SMAP_L3_P (Random Forest Soil Moisture Active Passive_L3_Passive) continuous in time and space over Huai River Basin. Finally, the performance of RF_SMAP_L3_P RZSM (0–100 cm) was evaluated using in situ measurements and compared with mainstream products, for instance, Soil Moisture Active Passive (SMAP) and Soil Moisture and Ocean Salinity Level 4 (SMOS L4) RZSM. The results indicated that RF_SMAP_L3_P RZSM could captured the temporal variation of measured RZSM best with R value of 0.586, followed by SMAP L4, which had the lowest bias value of 0.03, and SMOS L4 significantly underestimated the measured RZSM with bias value of −0.048 in the basin. Higher accuracy of RF_SMAP_L3_P RZSM was found in the flood period compared with the non-flood period, which indicates a better application for ExpF in wetter weather conditions

Application of an improved spatio-temporal identification method of flash droughts

Flash droughts are regional phenomena that can manifest in large areas with rapid intensification for a period of time. Few studies have considered the spatial pathways of flash droughts or their drought period. This study uses the five criteria based on the standardized evaporative stress ratio (SESR) method to identify flash droughts, and when a SESR value recovers to the 20th percentile, the flash drought is considered to terminate. To define spatially continuous flash droughts accurately, the usual order of first calculating drought patches and then identifying flash droughts is reversed to first identify flash droughts on the grid and then determine flash drought patches. In addition, this study tracks the spatial paths of flash droughts via centroid transfers of flash drought patches. Using MOD16 data, the methodology is evaluated by analyzing the regional characteristics of flash droughts in the Huaibei Plain of China from 2001 to 2019. The flash droughts in this region most frequently tracked in the northeast and west. The average flash drought duration was 31 days, of which the rapid intensification period was 18 days and drought period was 14 days. Flash drought events in this region mostly occurred in May, August and October, and east to west transition and non-transitions, which accounted for 44% and 22%, respectively, were the main spatial track paths. Only 26% of flash drought events transitioned to long term drought events. This study expands our knowledge of the evolution process of flash droughts to space-time dimensions, which is essential for flash droughts early warning and agricultural water management.This is a manuscript of an article published as Gou, Qiqi, Yonghua Zhu, Haishen Lü, Robert Horton, Xiaohan Yu, Haoqiang Zhang, Xiaoyi Wang et al. "Application of an improved spatio-temporal identification method of flash droughts." Journal of Hydrology (2021): 127224. doi:10.1016/j.jhydrol.2021.127224. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License

Soil moisture downscaling using multiple modes of the DISPATCH algorithm in a semi-humid/humid region

International audienc

Global Climate

In 2021, both social and economic activities began to return towards the levels preceding the COVID-19 pandemic for some parts of the globe, with others still experiencing restrictions. Meanwhile, the climate has continued to respond to the ongoing increase in greenhouse gases and resulting warming. La Niña, a phenomenon which tends to depress global temperatures while changing rainfall patterns in many regions, prevailed for all but two months of the year. Despite this, 2021 was one of the six-warmest years on record as measured by global mean surface temperature with an anomaly of between +0.21° and +0.28°C above the 1991–2020 climatology. Lake surface temperatures were their highest on record during 2021. The number of warm days over land also reached a new record high. Exceptional heat waves struck the Pacific Coast of North America, leading to a new Canadian maximum temperature of 49.6°C at Lytton, British Columbia, on 29 June, breaking the previous national record by over 4°C. In Death Valley, California, the peak temperature reached 54.4°C on 9 July, equaling the temperature measured in 2020, and the highest temperature recorded anywhere on the globe since at least the 1930s. Over the Mediterranean, a provisional new European record of 48.8°C was set in Sicily on 11 August. In the atmosphere, the annual mean tropospheric temperature was among the 10 highest on record, while the stratosphere continued to cool. While La Niña was present except for June and July, likely influencing Australia’s coolest year since 2012 and wettest since 2016, other modes of variability played important roles. A negative Indian Ocean dipole event became established during July, associated with a warmer east and cooler west Indian Ocean. Northern Hemisphere winters were affected by a negative phase of the North Atlantic Oscillation at both the beginning and end of 2021. In the Southern Hemisphere, a very strong positive Southern Annular Mode (also known as the Antarctic Oscillation) contributed to New Zealand’s record warm year and to very cold temperatures over Antarctica. Land surface winds continued a slow reversal from the multi-decadal stilling, and over the ocean wind speeds were at their highest in almost a decade. La Niña conditions had a clear influence on the regional patterns of many hydrological variables. Surface specific humidity and total column water vapor over land and ocean were higher than average in almost all datasets. Relative humidity over land reached record or near-record low saturation depending on the dataset, but with mixed signals over the ocean. Satellite measurements showed that 2021 was the third cloudiest in the 19-year record. The story for precipitation was mixed, with just below-average mean precipitation falling over land and below-average mean precipitation falling over the ocean, while extreme precipitation was generally more frequent, but less intense, than average. Differences between means and extremes can be due to several factors, including using different indices, observing periods, climatological base reference periods, and levels of spatial completeness. The sharp increase in global drought area that began in mid-2019 continued in 2021, reaching a peak in August with 32% of global land area experiencing moderate or worse drought, and declining slightly thereafter. Arctic permafrost temperatures continued to rise, reaching record values at many sites, and the thickness of the layer which seasonally thaws and freezes also increased over 2020 values in a number of regions. It was the 34th-consecutive year of mass balance loss for alpine glaciers in mountainous regions, with glaciers on average 25 m thinner than in the late 1970s. And the duration of lake ice in the Northern Hemisphere was the fourth lowest in situ record dating back to 1991. The atmospheric concentrations of the major long-lived greenhouse gases, CO2, CH4, and N2O, all reached levels not seen in at least the last million years and grew at near-record rates in 2021. La Niña conditions did not appear to have any appreciable impact on their growth rates. The growth rate for CH4, of 17 ppb yr−1, was similar to that for 2020 and set yet another record, although the causes for this post-2019 acceleration are unknown presently. Overall, CO2 growth continues to dominate the increase in global radiative forcing, which increased from 3.19 to 3.23 W m−2 (watts per square meter) during the year. In 2021, stratospheric ozone did not exhibit large negative anomalies, especially near the poles, unlike 2020, where large ozone depletions appeared, mainly from dynamical effects. The positive impact of reductions in emissions of ozone depleting substances can be seen most clearly in the upper stratosphere, where such dynamical effects are less pronounced. It was the fourth-lowest fire year since global records began in 2003, though extreme regional fire activity was again seen in North America and also in Siberia; as in 2020, the effects of wildfires in these two regions led to locally large regional positive anomalies in tropospheric aerosol and carbon monoxide abundance. Vegetation is responding to the higher global mean temperatures, with the satellite-derived measures for the Northern Hemisphere for 2021 rated among the earliest starts of the growing season and the latest end of the season on record. The first bloom date for cherry trees in Kyoto, Japan, broke a 600-year record set in 1409. This year we welcome a sidebar on the global distribution of lightning, which has been recently declared an essential climate variable (ECV) by the Global Climate Observing System (GCOS). Time series and anomaly maps from many of the variables described in this chapter can be found in Plates 1.1 and 2.1. As with other chapters, many of the sections have moved from the previous 1981–2010 to the new 1991–2020 climatological reference period, in line with WMO recommendations (see Chapter 1). This is not possible for all datasets, as it is dependent on their length of record or legacy processing methods. While anomalies from the new climatology period are not so easily comparable with previous editions of this report, they more clearly highlight deviations from more recent conditions