Primary cracking of kerogens. Experimenting and modelling C1, C2–C5, C6–C15 and C15+ classes of hydrocarbons formed

Mathematical models of hydrocarbon formation can be used to simulate the natural evolution of different types of organic matter and to make an overall calculation of the amounts of oil and/or gas produced during this evolution. However, such models do not provide any information on the composition of the hydrocarbons formed or on how they evolve during catagenesis.From the kinetic standpoint, the composition of the hydrocarbons formed can be considered to result from the effect of “primary cracking” reactions having a direct effect on kerogen during its evolution as well as from the effect of “secondary cracking” acting on the hydrocarbons formed.This report gives experimental results concerning the “primary cracking” of Types II and III kerogens and their modelling. For this, the hydrocarbons produced have been grouped into four classes (C₁, C₂–C₅, C₆–C₁₅ and C₁₅₊). Experimental data corresponding to these different classes were obtained by the pyrolysis of kerogens with temperature programming of 4°C/min with continuous analysis, during heating, of the amount of hydrocarbons corresponding to each of these classes.The kinetic parameters of the model were optimized on the basis of the results obtained. This model represents the first step in the creation of a more sophisticated mathematical model to be capable of simulating the formation of different hydrocarbon classes during the thermal history of sediments. The second step being the adjustment of the kinetic parameters of “secondary cracking”.     

台网遥测设备管理软件CALI编制与应用

本软件采用Ｆｏｘｐｒｏ２．５新一代数据库管理系统编写，主要用于遥测地震台网的设备管理及常规系统标定参数的计算，并已在１９９５年系统标定中得到了实践检验。     

Cathodoluminescence of authigenic albite

Authigenic albites in carbonate rocks typically grow in a high-grade diagenetic to low-grade metamorphic environment and often show Roc-Tourné-twinning sensu Füchtbauer. Based on an investigation of four Middle to South European occurrences, they show Mn²⁺- and Fe³⁺-activated cathodoluminescence (CL), as revealed by combined high resolution spectroscopy of cathodoluminescence emission (HRS-CL), electron paramagnetic resonance (EPR), and proton-induced X-ray emission (μPIXE).     

微/纳结构的弗雷德盐对铜的絮凝-吸附研究

以含钙聚合铝(PACCa)作为导向剂与铝源,在常温常压下合成了微/纳结构(微米/纳米尺度)的弗雷德盐。当水溶液中的ρ(Cu2+)为4.406 mg/L时,每升含铜溶液投入0.45 g弗雷德盐对Cu2+的去除率为99.02%。背散射(BEI)与二次电子(SEI)的SEM研究表明:微/纳结构的弗雷德盐在水处理中经历了溶解-结晶过程,XRD鉴定证实弗雷德盐分解后形成方解石晶体与无定形氧化铝。微/纳结构的弗雷德盐去除Cu2+的絮凝沉淀机理与吸附反应模式有所不同,弗雷德盐在絮凝过程中与水中CO2作用转变成方解石与无定形氧化铝,同时Cu2+在碱性环境下生成氢氧化物,新生成的无定型氢氧化铝迅速吸附铜的氢氧化物并裹挟方解石沉淀。     

ERS-2 PRI去噪评价及其在土地利用/覆盖分类中的应用

雷达成像原理和回波信号处理的特殊性,使得斑点噪声是雷达数据所固有的。斑点噪声滤除是雷达数据分析、处理不可或缺的工作。针对ERS-2 PRI产品,分别基于传统方法、模型方法、局域统计自适应滤波法和几何滤波法进行滤噪处理及其去噪质量评价,发现几何滤波的Gamma MAP消除雷达噪声效果最佳,并基于去噪后的多时相数据进行土地利用/覆盖分类。     

沁水盆地柿庄北深部煤层水平井CO2注入参数研究

基于CO₂的吸附能力大于CH₄的原理,向深部煤层中注入并封存CO₂同时置换驱替CH₄增加煤层气井产量,具有环境和经济双重效益。研究深部煤储层特征,通过气、水两相多组分,单孔和双孔模型的三维储层数值模拟技术,模拟不同井底压力下,完成注入量所需要的时间。优化后的注入施工参数为井口注入压力低于10MPa,注入速率低于47 L/min。根据数值模拟结果选定注入压力,注入结果与模拟连续注入时间一致,说明该方法可以有效地模拟注入压力和注入量之间的关系,保障CO₂注入施工安全有效。     

不同闪电跃增算法在北京地区应用效果对比

基于S波段多普勒天气雷达基数据、北京闪电定位网全闪定位数据和北京地区降雹的人工观测结果,对比分析Gatlin和σ两种闪电跃增算法在不同配置下对北京地区2015—2018年共177次冰雹天气过程的预警效果。结果表明：不同倍数的σ算法预警结果差别很大,2σ（要求当前闪电频数变化率超过之前平均闪电频数变化率两倍标准差）在σ算法中的预警效果最佳;不同N（总闪频数变化率的数量）配置下的Gatlin算法的预警结果差别不大,其中当N=6时的预警效果最佳。2σ算法的命中率、虚警率和临界成功指数分别为80.2%,41.6%和51.1%,N=6的Gatlin算法的相应结果分别为82.5%,62.0%和35.2%。另外,详细分析了一次多单体雷暴过程和一次飑线过程中两种算法的应用情况,结果也表明Gatlin算法比2σ算法的命中率略高,但虚警率偏高很多,临界成功指数偏低。综合Gatlin算法和σ算法对冰雹预报结果评估情况,发现2σ闪电跃增算法更适于对北京冰雹天气的预警,对提升闪电数据在北京地区冰雹预报业务的可用度有一定参考价值。     

二维地震观测系统合理性的论证方法

已知勘查区深度范围前提下,最大炮检X和道间距ΔX,不可以太大也不可以太小,施工前能够计算出它的允许值范围。     

超临界CO2岩石致裂机制分析

超临界CO2是一种介于气体和液体之间的特殊状态的CO2流体,具有低黏、高扩散性和零表面张力等独特的性质。利用超临界CO2作为压裂液,有助于裂缝的起裂和扩展,同时可避免储层伤害。通过研究超临界CO2射流破岩和压裂特性,分析得到了超临界CO2岩石致裂机制。研究结果表明,超临界CO2低黏等特性使其更容易进入岩石微孔和微缝之中,在岩石内部建立大小不一的流体压力系统,使岩石发生拉伸和剪切破坏;常规流体压裂起裂压力较高,裂缝一般为单条或多条平直裂缝,大多沿着同一方向贯穿强度较高的胶结颗粒,且裂缝断面光滑、平整;超临界CO2压裂起裂压力相比于常规流体压裂低,在岩石中形成的裂缝网络较为复杂,裂缝互相连通,一般沿着强度较低的胶结物开裂,较少贯穿胶结颗粒,裂缝断面较为粗糙。该研究结果可为超临界CO2压裂技术的实施提供理论支撑。     

Determination of the crop row orientations from Formosat-2 multi-temporal and panchromatic images

This paper presents a technique developed for the retrieval of the orientation of crop rows, over anthropic lands dedicated to agriculture in order to further improve estimate of crop production and soil erosion management. Five crop types are considered: wheat, barley, rapeseed, sunflower, corn and hemp. The study is part of the multi-sensor crop-monitoring experiment, conducted in 2010 throughout the agricultural season (MCM’10) over an area located in southwestern France, near Toulouse. The proposed methodology is based on the use of satellite images acquired by Formosat-2, at high spatial resolution in panchromatic and multispectral modes (with spatial resolution of 2 and 8 m, respectively). Orientations are derived and evaluated for each image and for each plot, using directional spatial filters (45° and 135°) and mathematical morphology algorithms. “Single-date” and “multi-temporal” approaches are considered. The single-date analyses confirm the good performances of the proposed method, but emphasize the limitation of the approach for estimating the crop row orientation over the whole landscape with only one date. The multi-date analyses allow (1) determining the most suitable agricultural period for the detection of the row orientations, and (2) extending the estimation to the entire footprint of the study area. For the winter crops (wheat, barley and rapeseed), best results are obtained with images acquired just after harvest, when surfaces are covered by stubbles or during the period of deep tillage (0.27 > R² > 0.99 and 7.15° > RMSE > 43.02°). For the summer crops (sunflower, corn and hemp), results are strongly crop and date dependents (0 > R² > 0.96, 10.22° > RMSE > 80°), with a well-marked impact of flowering, irrigation equipment and/or maximum crop development. Last, the extent of the method to the whole studied zone allows mapping 90% of the crop row orientations (more than 45,000 ha) with an error inferior to 40°, associated to a confidence index ranging from 1 to 5 for each agricultural plot.