塔里木盆地早二叠世岩浆特征及其对油气成藏关系初探

塔里木盆地早二叠世裂谷盆地阶段有一次强烈的岩浆活动,主要为玄武岩—中酸性凝灰岩喷发和大规模基性岩墙群的侵入,玄武岩K-Ar法同位素年龄为241~278Ma,而辉长岩的Sm-Nd法年龄为259Ma。火山活动产生的能量使得塔里木盆地内的寒武系—奥陶系烃源岩大量生烃并运移,自生伊利石K-Ar年龄测定数据显示哈得4石炭系油藏、塔中4CⅢ油藏油气充注时间为224~275Ma,与上述火成岩的活动时间相当。东河砂岩,一套深埋的优质储层,其形成的原因可能是二叠纪末油气的注入并导致其后期深埋时只有机械压实而无其他成岩作用的缘故。     

库车坳陷西部构造圈闭形成期与烃源岩生烃期匹配关系探讨

根据库车坳陷西部地质剖面分析其构造圈闭类型,利用平衡剖面和生长地层分析构造圈闭形成期次。选取大北1井和一口人工井,应用PRA公司的BasinMod1-D软件,对其进行烃源岩成熟度史模拟,分析烃源岩的主要生烃期。根据构造圈闭形成期与烃源岩主要生烃期的匹配关系,认为西秋里塔格构造带盐下古构造圈闭与拜城凹陷烃源岩生烃期匹配良好,形成的油气藏大部分在后期保存良好,盐上圈闭可能形成油藏,盐层内部圈闭可能形成油藏、气藏或油气藏,在较厚盐层之下的圈闭可能会形成气藏。克拉苏构造带古构造圈闭与克拉苏构造带烃源岩主要生烃期以及拜城凹陷的主要生油期匹配良好,可以形成良好的油气藏,但是库车组沉积末期—第四纪构造破坏严重,油气藏经受构造调整、破坏和再分配形成残余油气藏、次生油气藏,此时正处于侏罗系烃源岩生气期,可以在盐下形成大量气藏。     

攀西地区晚新生代沉积研究回顾与问题讨论

攀西地区晚新生代沉积是研究青藏高原东南缘隆升演化历史及其周缘环境响应、中国第一第二阶梯地貌格局演变和高原东南缘水系变迁的天然地质记录,具有重要科学意义。对该区晚新生代河湖相沉积,尤其是昔格达组和大箐梁子组的研究历史、岩性内涵、形成时代、古地理与古气候意义等进行了较全面的回顾。在此基础上对晚新生代冰碛物记录的冰川发育过程、青藏高原东南缘新构造运动和隆升历史、水系格局变迁等过程进行了评述。针对该区晚新生代沉积研究中存在的问题和分歧,提出了今后研究的方向,认为在详细的地层学和地貌学等综合研究基础上开展高精度的年代学研究是当前攀西地区晚新生代沉积研究的重点。     

基于LSTM的海洋表面短期风速预测研究

为实现对海面风速精确的短期预测,提出了一种基于长短期记忆(LSTM,longshort-termmemory)神经网络的短期风速预测模型,选取OceanSITES数据库中单个浮标站点采集的风速历史数据作为模型输入,经过训练设置最佳参数等步骤,实现了以LSTM方法,对该站点所在海区海面风速在各季节性代表月份海面风速的24 h短期预测。同时通过不同预测时长的实验以及与BP(back propagation)神经网络神经网络和径向基函数神经网络(radialbasisfunctionneuralnetwork,RBF)的预测效果对比实验,证明了LSTM预测方法相比上述两种神经网络预测方法,在海表面风速预测应用中的优越性。最后通过多个海域对应的站点风速数据预测实验,证明了LSTM神经网络模型的普遍适用性,由相关系数和预测误差的分析可知该方法具备应对急剧变化数据的预测稳定性,可以作为海洋表面风速短期预测的一种可靠方法。     

腐解9个月后杉木枯枝落叶化感物质对杉木的化感作用

采用有机溶剂与蒸馏水混和浸提杉木枯枝落叶腐解9个月后化感物质,应用杉木种子发芽试验进行生物检测.结果表明:杉木枯枝落叶腐解9个月后,杉木枯枝落叶中的弱极性化感物质对绝对发芽率、绝对发芽势、胚根长、胚轴长及干物质量等指标表现为抑制作用,对鲜物质量则表现为轻微的促进作用;极性化感物质对杉木种子发芽各指标均等表现为抑制作用.腐解土中的弱极性化感物质对杉木种子发芽各指标均表现为抑制作用,极性化感物质对绝对发芽率、绝对发芽势、胚轴长及干物质量等表现为抑制作用,但对胚根长、鲜物质量表现为促进作用.     

Machine learning for pore-water pressure time-series prediction: Application of recurrent neural networks

Knowledge of pore-water pressure(PWP)variation is fundamental for slope stability.A precise prediction of PWP is difficult due to complex physical mechanisms and in situ natural variability.To explore the applicability and advantages of recurrent neural networks(RNNs)on PWP prediction,three variants of RNNs,i.e.,standard RNN,long short-term memory(LSTM)and gated recurrent unit(GRU)are adopted and compared with a traditional static artificial neural network(ANN),i.e.,multi-layer perceptron(MLP).Measurements of rainfall and PWP of representative piezometers from a fully instrumented natural slope in Hong Kong are used to establish the prediction models.The coefficient of determination(R^2)and root mean square error(RMSE)are used for model evaluations.The influence of input time series length on the model performance is investigated.The results reveal that MLP can provide acceptable performance but is not robust.The uncertainty bounds of RMSE of the MLP model range from 0.24 kPa to 1.12 k Pa for the selected two piezometers.The standard RNN can perform better but the robustness is slightly affected when there are significant time lags between PWP changes and rainfall.The GRU and LSTM models can provide more precise and robust predictions than the standard RNN.The effects of the hidden layer structure and the dropout technique are investigated.The single-layer GRU is accurate enough for PWP prediction,whereas a double-layer GRU brings extra time cost with little accuracy improvement.The dropout technique is essential to overfitting prevention and improvement of accuracy.     

Stage level,volume and time‐frequency information content of Lake Tana using stochastic and wavelet analysis methods

Lake Tana is the largest fresh water body situated in the north‐western highlands of Ethiopia. In addition to its ecological services, it serves for local transport, electric power generation, fishing, recreational purposes, and source of dry season irrigation water supply. Evidence shows that the lake has dried at least once at about 15,000–17,000 before present owing to a combination of high evaporation and low precipitation events. Past attempts to understand and simulate historical fluctuation of Lake Tana based on simplistic water balance approach of inflow, outflow, and storage have failed to capture well‐known events of drawdown and rise of the lake that have happened in the last 44 years. This study tested different stochastic methods of lake level and volume simulation for supporting Lake Tana operational planning decision support. Three stochastic methods (perturbations approach, Monte Carlo methods, and wavelet analysis) were employed for lake level and volume simulation, and the results were compared with the stage level measurements. Forty‐four years of daily, monthly, and mean annual lake level data have shown a Gaussian variation with goodness of fit at 0.01 significant levels of the Kolmogorov–Smirnov test. The stochastic simulations predicted the lake stage level of the 1972, 1984, and 2002/2003 historical droughts 99% of the time. The information content (frequency) of fluctuation of Lake Tana for various periods was resolved using Wigner's Time‐Frequency Decomposition method. The wavelet analysis agreed with the perturbations and Monte Carlo simulations resolving the time (1970s, 1980s, and 2000s) in which low frequency and high spectral power fluctuation has occurred. The Monte Carlo method has shown its superiority for risk analysis over perturbation and deterministic method whereas wavelet analysis reconstructed historical record of lake stage level at daily and monthly time scales. Copyright © 2012 John Wiley & Sons, Ltd.     

ON SOME KEY SEDIMENTATION PROBLEMS OF THREE GORGES PROJECT (TGP)

I. INTRODUCTIONThe Three Gorges Project (TGP) being planned is to be located on the Yangtze River at Sandouplug, 44 km upstream of Yichang (Fig. l). A scheme studied in the feasibility stage has the crest ofthe dam placed at 185 m with a maximums height o…     

周期性潮积岩及其研究意义

回顾了最近十余年来国外对周期性潮汐沉积物，特别是潮汐韵律层的研究进展，系统介绍了几种从古代沉积物中识别出来的潮汐周期，包括基本潮汐（半日潮，全日潮和混合潮），大一小潮周期以及一些长周期波动等。最后，对潮汐韵律层在推测地史时期地－月系的演化历史及计算短期沉积速率中的意义作了评述。