Investigation of gas content of organic-rich shale:A case study from Lower Permian shale in southern North China Basin,central China

Measuring gas content is an essential step in estimating the commerciality of gas reserves. In this study,eight shale core samples from the Mouye-1 well were measured using a homemade patented gas desorption apparatus to determine their gas contents. Due to the air contamination that is introduced into the desorption canister, a mathematical method was devised to correct the gas quantity and quality.Compared to the chemical compositions of desorbed gas, the chemical compositions of residual gas are somewhat different. In residual gas, carbon dioxide and nitrogen record a slight increase, and propane is first observed. This phenomenon may be related to the exposure time during the transportation of shale samples from the drilling site to the laboratory, as well as the differences in the mass, size and adsorptivity of different gas molecules. In addition to a series of conventional methods, including the USBM direct method and the Amoco Curve Fit(ACF) method, which were used here for lost gas content estimation, a Modified Curve Fit(MCF) method, based on the 'bidisperse' diffusion model, was established to estimate lost gas content. By fitting the ACF and MCF models to gas desorption data, we determined that the MCF method could reasonably describe the gas desorption data over the entire time period, whereas the ACF method failed. The failure of the ACF method to describe the gas desorption process may be related to its restrictive assumption of a single pore size within shale samples. In comparison to the indirect method, this study demonstrates that none of the three methods studied in this investigation(USBM, ACF and MCF) could individually estimate the lost gas contents of all shale samples and that the proportion of free gas relative to total gas has a significant effect on the estimation accuracy of the selected method. When the ratio of free gas to total gas is lower than 45%, the USBM method is the best for estimating the lost gas content, whereas when the ratio ranges from 45% to 75% or is more than 75%, the ACF and MCF methods, are the best options respectively.     

RS & GIS-based landslide susceptibility mapping of the Balason River basin,Darjeeling Himalaya,using logistic regression (LR) model

The present study deals with the preparation of a landslide susceptibility map of the Balason River basin, Darjeeling Himalaya, using a logistic regression model based on Geographic Information System and Remote Sensing. The landslide inventory map was prepared with a total of 295 landslide locations extracted from various satellite images and intensive field survey. Topographical maps, satellite images, geological, geomorphological, soil, rainfall and seismic data were collected, processed and constructed into a spatial database in a GIS environment. The chosen landslide-conditioning factors were altitude, slope aspect, slope angle, slope curvature, geology, geomorphology, soil, land use/land cover, normalised differential vegetation index, drainage density, lineament number density, distance from lineament, distance to drainage, stream power index, topographic wetted index, rainfall and peak ground acceleration. The produced landslide susceptibility map satisfied the decision rules and ?2 Log likelihood, Cox &; Snell R-Square and Nagelkerke R-Square values proved that all the independent variables were statistically significant. The receiver operating characteristic curve showed that the prediction accuracy of the landslide probability map was 96.10%. The proposed LR method can be used in other hazard/disaster studies and decision-making.     

藏南喜马拉雅造山带造山型马扎拉Au-Sb矿床和沙拉岗Sb矿床流体包裹体He-Ar同位素组成:对成矿流体来源的制约

马扎拉Au-Sb矿床和沙拉岗Sb矿床是藏南金锑成矿带中典型的造山型矿床。马扎拉Au-Sb矿床中矿体以含金辉锑矿石英脉的形式产于下中侏罗统陆热组地层中,主要组成矿物有自然金、辉锑矿、石英和碳酸盐矿物;沙拉岗Sb矿床中矿体主要以辉锑矿石英脉的形式产于下白垩统多久组地层和辉长岩体中,主要组成矿物为辉锑矿、辰砂、锑华、石英和少量碳酸盐矿物。在两个矿床的矿脉石英和辉锑矿中均发现有三类原生和假次生包裹体:水溶液包裹体、CO2-水溶液包裹体和有机包裹体。流体包裹体显微测温结果显示:马扎拉Au-Sb矿床的成矿温度为160～280℃,沙拉岗Sb矿床的成矿温度为140～240℃。He-Ar同位素分析显示马扎拉Au-Sb矿辉锑矿石英脉矿石中辉锑矿和石英以及赋矿地层中沉积层状硫化物中黄铁矿的流体包裹体均具有低的3He/4He比值,分别为0. 01382～0. 05642Ra和0. 03353～0. 08744Ra,40Ar/36Ar比值具有比较大的变化范围,分别为346. 8～4770. 1和349. 4～2689. 1;沙拉岗Sb矿床中辉锑矿样品的3He/4He比值为0. 02385～0. 11488Ra,40Ar/36Ar比值变化小,为300. 6～537. 5。与藏南Au-Sb成矿带中造山型Au矿床成矿流体中含一定量的幔源挥发份相对比,马扎拉AuSb矿床和沙拉岗Sb矿床成矿流体中均无幔源流体的参与,马扎拉Au-Sb矿床成矿流体为壳源变质流体与改造型饱和大气水形成的混合流体;沙拉岗Sb矿床成矿流体以改造型饱和大气水为主,并有壳源变质流体的加入。     

面向矿产资源信息的空间关联性分析

关联性分析是综合多源、多类数据,发现和挖掘数据中潜在的相关关系,提取和挖掘数据之间的关联性。该方法对于充分利用地质大数据、发现地质要素之间的共生组合规律具有重要的意义。本文首先基于数据的空间位置,将不同类型的地质空间数据建立联系,形成空间属性数据库;其次应用统计方法,对不同来源数据中的属性特征进行分析,发现热液型金矿的形成与火山作用存在明显相关性;最后基于Apriori算法提取热液型金矿的伴生矿与侵入岩的频繁项集,发现伴生矿与侵入岩酸碱性二者密切相关。因此,在今后的工作中,有望应用空间关联性的方法对地球物理、地球化学、遥感等多源地质数据开展深入的研究分析。     

An Innovative Bias-Correction Approach to CMA-GD Hourly QuantitativePrecipitation Forecasts

This paper proposes a simple and powerful optimal integration (OPI) method for improving hourly quantitative precipitation forecasts (QPFs, 0-24 h) of a single-model by integrating the benefits of different bias- corrected methods using the high-resolution CMA-GD model from the Guangzhou Institute of Tropical and Marine Meteorology of China Meteorological Administration (CMA). Three techniques are used to generate multi-method calibrated members for OPI: deep neural network (DNN), frequency-matching (FM), and optimal threat score (OTS). The results are as follows: (1) The QPF using DNN follows the basic physical patterns of CMA-GD. Despite providing superior improvements for clear-rainy and weak precipitation, DNN cannot improve the predictions for severe precipitation, while OTS can significantly strengthen these predictions. As a result, DNN and OTS are the optimal members to be incorporated into OPI. (2) Our new approach achieves state-of-the-art performances on a single model for all magnitudes of precipitation. Compared with the CMA-GD, OPI improves the TS by 2.5%, 5.4%, 7.8%, 8.3%, and 6.1% for QPFs from clear-rainy to rainstorms in the verification dataset. Moreover, OPI shows good stability in the test dataset. (3) It is also noted that the rainstorm pattern of OPI relies heavily on the original model and that OPI cannot correct for deviations in the location of severe precipitation. Therefore, improvements in predicting severe precipitation using this method should be further realized by improving the numerical model’s forecasting capability.     

Dynamic land use change simulation using cellular automata with spatially nonstationary transition rules

The dynamic relationships between land use change and its driving forces vary spatially and can be identified by geographically weighted regression (GWR). We present a novel cellular automata (GWR-CA) model that incorporates GWR-derived spatially varying relationships to simulate land use change. Our GWR-CA model is characterized by spatially nonstationary transition rules that fully address local interactions in land use change. More importantly, each driving factor in our GWR model contains effects that both promote and resist land use change. We applied GWR-CA to simulate rapid land use change in Suzhou City on the Yangtze River Delta from 2000 to 2015. The GWR coefficients were visualized to highlight their spatial patterns and local variation, which are closely associated with their effects on land use change. The transition rules indicate low land conversion potential in the city’s center and outer suburbs, but higher land conversion potential in the inner near suburbs along the belt expressway. Residual statistics show that GWR fits the input data better than logistic regression (LR). Compared with an LR-based CA model, GWR-CA improves overall accuracy by 4.1% and captures 5.5% more urban growth, suggesting that GWR-CA may be superior in modeling land use change. Our results demonstrate that the GWR-CA model is effective in capturing spatially varying land transition rules to produce more realistic results, and is suitable for simulating land use change and urban expansion in rapidly urbanizing regions.     

Reducing wind power curtailment in China: comparing the roles of coal power flexibility and improved dispatch

Renewable energy curtailment is a critical issue in China, impeding the country’s transition to clean energy and its ability to meet its climate goals. This paper analyzes the impacts of more flexible coal-fired power generation and improved power dispatch towards reducing wind power curtailment. A unit commitment model for power dispatch is used to conduct the analysis, with different scenarios demonstrating the relative impacts of more flexible coal-fired generation and improved power dispatch. Overall, while we find both options are effective in reducing wind power curtailment, we find that improved power dispatch is more effective: (1) the effect of ramping down coal-fired generators to reduce wind power curtailment lessens as the minimum output of coal-fired generation is decreased; and (2) as a result, at higher wind capacity levels, wind curtailment is much more significantly reduced with improved power dispatch than with decreased minimum output of coal-fired generation.

Key policy insights

• China should emphasize both coal power flexibility and dispatch in its policies to minimize renewable power curtailment and promote clean energy transition.

• China should accelerate the process of implementing spot market and marginal cost-based economic dispatch, while making incremental improvements to the existing equal share dispatch in places not ready for spot market.

• A key step in improving of dispatch is incorporating renewable power forecasts into the unit commitment process and updating the daily unit commitment based on the latest forecast result.

• China should expand the coal power flexibility retrofit programme and promote the further development of the ancillary service market to encourage more flexibility from coal-fired generation.

     

《巴黎协定》实施细则适应议题焦点解析及后续中国应对措施

适应是《联合国气候变化框架公约》及其《巴黎协定》下的重要谈判内容。2018年12月举行的第24次缔约方大会（COP24）就适应议题后续实施方案达成了共识,为全球气候治理带来新的机遇和挑战。中国在未来全球气候治理中,如何借助新成果推动国内适应工作稳步发展,积极发挥中国作用,是新形势下亟需考虑的重要问题。基于此,本文梳理了适应议题的焦点问题、各集团和缔约方的立场观点,展望了2019—2025年适应相关议题主要工作安排,并对此提出了中国未来适应领域完成相关工作需要考虑的应对措施建议,包括：(1)深入分析国际信息报告体系与国内信息的联系,梳理国内适应工作亮点,为构建高质量报告奠定基础;(2)构建跨部门跨地区协作机制,加强信息搜集与完善,有效提高数据和信息统计功能;(3)强化气候变化适应技术、规范、标准等科学研究的作用,为制定政策规定时纳入相应技术要求、提高政策规定等需求提供科学性和可操作性的服务。     

四川地区多模式2m温度预报性能分析及集成方法研究

本文通过分析2017年9~12月四川地区ECMWF(European Centre for Medium-Range Weather Forecasting)细网格模式、GRAPES_GFS(Global and Regional Assimilation and Prediction System)全球模式和西南区域模式(South West Center-WRF ADAS Real-time Modeling System, SWCWARMS)2m温度168h预报时效内的系统性偏差特征,采用滑动双权重平均法分别对三种模式温度预报产品进行偏差订正,并集成得到各时效2m温度的订正场,结果表明:(1)三种模式的预报存在明显的日变化,整体上EC模式的预报最优。(2)三种模式对于低温和高温的预报,在全省均大致呈现负的系统性误差,特别在高原及过渡区表现的尤为明显。(3)订正后三种模式的预报准确率显著提高,均方根误差减小1.4~2.5℃,大部分地区平均误差维持在±0.5℃之间,在系统性偏差较大的地区,订正效果更好。(4)两种集成方案预报结果接近,且均优于三种模式的订正预报。