多层构造油藏纵向细分计算单元对储量参数及结果的影响     

颜冠山  刘宗宾  宋洪亮  韩雪芳  王欣然 《地质与资源》2020,29(4):342-350

为满足油田中后期精细开发及后续调整挖潜的需要，亟需进行更精细的储量研究，其中最重要的一环就是纵向细分计算单元.对于多层构造油藏，纵向细分主要根据油层组内隔夹层分布特征、小层物性特征，细分到以小层或者分布特征和物性相近且纵向上连续分布的小层组合为计算单元.根据纵向细分计算单元前后储量参数选值的理论推导，结合储层的沉积展布特征，认为含油面积范围内无储层尖灭时，仅平面油层厚度差异较大的油藏平均有效厚度变小.含油面积范围内储层尖灭时，正常三角洲沉积储层的油藏各参数一般都变小；而辫状河三角洲沉积储层的油藏一般平均有效厚度变小，平均有效孔隙度和平均含油饱和度变大.这一结论可以有效指导储量评估过程中纵向细分计算单元方案划分，为同类油田的精细储量研究提供技术支撑.  相似文献   

Simulation of landscape spatial layout evolution in rural-urban fringe areas: a case study of Ganjingzi District   总被引：2，自引：0，他引：2  

Jun Yang  Andong Guo  Yonghua Li  Yuqing Zhang  Xueming Li 《地理信息系统科学与遥感》2019,56(3):388-405

In recent years, the rapid expansion of urban spaces has accelerated the mutual evolution of landscape types. Analyzing and simulating spatio-temporal dynamic features of urban landscape can help to reveal its driving mechanisms and facilitate reasonable planning of urban land resources. The purpose of this study was to design a hybrid cellular automata model to simulate dynamic change in urban landscapes. The model consists of four parts: a geospatial partition, a Markov chain (MC), a multi-layer perceptron artificial neural network (MLP-ANN), and cellular automata (CA). This study employed multivariate land use data for the period 2000–2015 to conduct spatial clustering for the Ganjingzi District and to simulate landscape status evolution via a divisional composite cellular automaton model. During the period of 2000–2015, construction land and forest land areas in Ganjingzi District increased by 19.43% and 15.19%, respectively, whereas farmland, garden lands, and other land areas decreased by 43.42%, 52.14%, and 75.97%, respectively. Land use conversion potentials in different sub-regions show different characteristics in space. The overall land-change prediction accuracy for the subarea-composite model is 3% higher than that of the non-partitioned model, and misses are reduced by 3.1%. Therefore, by integrating geospatial zoning and the MLP-ANN hybrid method, the land type conversion rules of different zonings can be obtained, allowing for more effective simulations of future urban land use change. The hybrid cellular automata model developed here will provide a reference for urban planning and policy formulation.  相似文献   

SAR image despeckling with a multilayer perceptron neural network     

Xiao Tang  Lei Zhang  Xiaoli Ding 《International Journal of Digital Earth》2019,12(3):354-374

Speckle noise in synthetic-aperture radar (SAR) images severely hinders remote sensing applications; therefore, the appropriate removal of speckle noise is crucial. This paper elaborates on the multilayer perceptron (MLP) neural-network model for SAR image despeckling by using a time series of SAR images. Unlike other filtering methods that use only a single radar intensity image to derive their parameters and filter that single image, this method can be trained using archived images over an area of interest to self-learn the intensity characteristics of image patches and then adaptively determine the weights and thresholds by using a neural network for image despeckling. Several hidden layers are designed for feedforward network training, and back-propagation stochastic gradient descent is adopted to reduce the error between the target output and neural-network output. The parameters in the network are automatically updated in the training process. The greatest advantage of MLP is that once the despeckling parameters are determined, they can be used to process not only new images in the same area but also images in completely different locations. Tests with images from TerraSAR-X in selected areas indicated that MLP shows satisfactory performance with respect to noise reduction and edge preservation. The overall image quality obtained using MLP was markedly higher than that obtained using numerous other filters. In comparison with other recently developed filters, this method yields a slightly higher image quality, and it demonstrates the powerful capabilities of computer learning using SAR images, which indicate the promising prospect of applying MLP to SAR image despeckling.  相似文献   

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

Xin Wei  Lulu Zhang  Hao-Qing Yang  Limin Zhang  Yang-Ping Yao 《地学前缘(英文版)》2021,12(1):453-467

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.  相似文献   

A neurocomputing approach to the forecasting of monthly maximum temperature over Kolkata, India using total ozone concentration as predictor     

Syam Sundar De  Goutami Chattopadhyay  Bijoy Bandyopadhyay  Suman Paul 《Comptes Rendus Geoscience》2011,343(10):664-676

The association between the monthly total ozone concentration and monthly maximum temperature over Kolkata (22.56° N, 88.30° E), India, has been explored in this paper. For this, the predictability of monthly maximum temperature based on the total ozone as predictor is investigated using Artificial Neural Network. The presence of persistence and similar cyclic patterns are revealed through autocorrelation and cross-correlation coefficients. Common cycles of length 12 and 6 have been identified through periodogram. Hence, a predictive model has been generated by Artificial Neural Network in the form of Multi Layer Perceptron (MLP) using scaled conjugate gradient learning with sigmoid non-linearity. After training and testing the network, an MLP with total ozone of month n as predictor and maximum temperature of month (n + 1) as the target output is found as the best model. Performance of the model has been judged statistically. Finally, the MLP model has been compared with linear and non-linear regressions and the efficiency of MLP has been established over the regression models.  相似文献   

用多层感知器模型由吸收光谱反演浮游植物色素   总被引：1，自引：0，他引：1       下载免费PDF全文

周雯  曹文熙  王桂芬  梁少君  赵俊  孙兆华 《热带海洋学报》2010,29(2):46-51

浮游植物吸收光谱已逐渐成为高光谱水色遥感的可获取参量。文章采用了多层感知器模型, 由珠江口担杆群岛附近水体的浮游植物吸收光谱进行了色素浓度的反演, 感知器的输入量是浮游植物吸收光谱, 输出量分别对应叶绿素a、叶绿素b、叶绿素c、光保护类胡萝卜素和非光保护类胡萝卜素五大类主要色素的浓度。分析结果表明, 叶绿素a和叶绿素c估算结果的平均相对偏差比较低, 在测试数据集中两者的偏差分别为19.06%和15.90%; 光保护类胡萝卜素和非光保护类胡萝卜素的估算浓度的相对偏差比较高, 对于测试数据而言, 分别为37.62%和36.96%; 叶绿素b浓度在测试数据集中的估算相对偏差约为27.47%。五大类色素在测试数据集和训练数据集的估算偏差比较接近, 已训练好的多层感知器可用于担杆岛水体中色素信息的反演。同时, 此色素反演方法也为遥感监测水体浮游植物种群动态提供了重要的手段。  相似文献   

非饱和土地基中复合多层波阻板对S波的隔离效应     

舒进辉  马强  常立君 《岩土力学》2023,44(1):217-231

基于弹性波在非饱和多孔介质与单相弹性介质中的传播理论,考虑在非饱和土地基中设置一定厚度的复合多层波阻板（复合多层波阻板以3层为例）,利用Helmholtz矢量分解定理,推导了非饱和土地基中S波通过复合多层波阻板的透射、反射振幅比的解析解。通过数值算例,分析了层间波阻板剪切模量和密度等物理力学参数对非饱和土地基中S波通过复合多层波阻板时传播特性的影响规律。结果表明：复合多层波阻板中层间波阻板材料的剪切模量和密度对透反射系数影响显著。复合多层波阻板是一种有效的隔振屏障,严格控制层间波阻板的剪切模量和密度可以获得最佳隔振效果,这为复合多层波阻板在地基振动控制领域中的应用提供理论指导。  相似文献   

多通道地下水监测技术应用示范          下载免费PDF全文

潘德元 《探矿工程》2014,41(11):1-4

多通道地下水监测技术能够大幅度降低地下水监测成本。多通道监测井成井井管是采用HDPE材质挤出若干通道的连续管材,在每个通道指定位置加工窗口,对应相应的地下水监测层位,并设计合理的填砾止水厚度。根据多通道地下水监测井特点,研制新型的止水材料。采用该种地下水监测技术,先后在北京、天津、甘肃等地建立了地下水监测示范工程。与传统地下水监测技术相比,节约了占地面积、减少了钻探进尺,与国外CMT地下水监测技术对比,适用范围更广,建井成本更低。  相似文献   

从高密度电阻率法数据中抽取电测深曲线进行解释     

李望明  吴述来  易强  叶明金  黎景开 《物探与化探》2014,(3):587-590

对于碳酸盐岩地层中的多层岩溶、溶洞洞高较小或顺层岩溶,直接从高密度电阻率拟断面图和反演电阻率断面图上难以将其区分。通过从高密度电法数据中抽取电测深曲线,对一系列测点的电测深视电阻率曲线进行解释,同时结合其视电阻率拟断面图和反演电阻率断面图作出推断,能有效地将上述岩溶进行区分。在湖南省某高速公路跨线桥墩台桩基工程基础勘探中的实践表明,使用该方法可获得较好的地质解释效果。  相似文献   

卫星遥感接收数据的管理与软件开发          下载免费PDF全文

李军  宋海英  李海滨  郭思海 《海洋测绘》2009,29(4):70-73

卫星遥感接收数据是遥感影像应用的重要数据来源，因此对特殊格式的海量接收数据的存储和管理成为卫星遥感应用的重要环节。采用多层存储模式对数据分类、分级存储，建立空间数据库管理空间数据和属性数据。基于ArcEngine开发技术建立卫星接收数据管理平台，实现空间数据的快速查询和属性数据的自动入库等高效管理功能。  相似文献