Description: 本书涉及的研究方法主要应用于油田生产的实际工作中，包括一般储层参数预测、薄互油藏参数预测、火山岩储层参数预测和储层随机模拟等问题，同时还涉及了石油工业中的油管缺损检测、海底输油管道腐蚀检测等应用问题，对污水处理絮凝过程的智能优化控制及移动机器人的全局和局部路径规划等问题的应用也进行了一定的研究。-Book of research methods involved are mainly used in oil field production of practical work, including the general prediction of reservoir parameters, thin reservoir parameter prediction, volcanic prediction of reservoir parameters and reservoir stochastic simulation and other issues, but also involved in the oil industry pipeline defect detection, submarine detection applications such as pipeline corrosion problem of the sewage treatment process of flocculation and optimal control of intelligent mobile robot path planning global and local issues such as the application have also been some study. Platform: |
Size: 15801344 |
Author:cheny |
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Description: 线性预测算法基于遗传算法-支持向量机的水库叶绿素a浓度短期预测非线性时序模型,利学水 报 2009 年 1 月 SHUILI XUEBAO 第第 40 卷 1 期文章编号 :055929350 2009 0120046206 基于遗传算法 -matlab Linear prediction algorithm is based on genetic algorithm- support vector machine reservoir chlorophyll-a concentration of short-term prediction of nonlinear time series model, Lee study of water reported in January 2009 SHUILI XUEBAO No. 40 Volume 1 Article ID: 055929350 20090120046206 based on genetic algorithm Platform: |
Size: 3072 |
Author:微软 |
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Description: 吸收系数是进行储层描述和油气预测时的一个重要参数 ,它对岩性变化具有很高的灵敏性。结合层位解释结果从地震资料中提取该层位地层吸收系数的空间分布对于提高油藏描述及油气预测精度具有重要作用 ,并可与其它地震、测井和地质信息相结合直接用于圈定油气分布范围 ,估算储量-Absorption coefficient is an important parameter in the reservoir description and hydrocarbon prediction. It is very sensitive to the variation of lithology. The spatial distribution of formation absorption coefficients which are estimated from horizon interpretation of seismic data plays an important role in improving accuracy of reservoir description and hydrocarbon prediction , and can be used to delineate hydrocarbon distribution and estimate reserves when combines withother seismic data , log, and geologic data. Platform: |
Size: 1024 |
Author:解建建 |
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Description: 斯坦福大学储层预测中心的FORTRAN3D克里金源代码，该源代码对于初学者学习理解克里金有很大的帮助！-Stanford University Center FORTRAN3D reservoir prediction Kriging source code, the source code for beginners to learn to understand a great help Kerry King! Platform: |
Size: 70656 |
Author:wangwei |
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Description: 斯坦福大学储层预测中心的FORTRAN截断高斯源代码，对于初学者理解截断高斯模拟算法有很大的帮助!-Reservoir Prediction Center at Stanford University truncated Gaussian FORTRAN source code, for the truncated Gaussian simulation algorithm for beginners to understand a great help! Platform: |
Size: 56320 |
Author:wangwei |
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Description: 斯坦福大学储层预测中心的FORTRAN变差函数源代码，该源代码对于初学者学习理解变差函数有很大的帮助！-Reservoir Prediction Center at Stanford University variogram FORTRAN source code, the source code for beginners to learn to understand variation function a great help! Platform: |
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Author:wangwei |
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Description: S-GeMS（Stanford Geostatistical Modeling Software）是Nicolas Remy在斯坦福大学油藏预测中心（SCRF：The Stanford Center for Reservoir Forecasting）开发的一套开源地质建模及地质统计学研究软件。-S-GeMS (Stanford Geostatistical Modeling Software) is Nicolas Remy Reservoir Prediction Center at Stanford University (SCRF: The Stanford Center for Reservoir Forecasting) developed a set of open source geostatistical geological modeling and research software. Platform: |
Size: 10388480 |
Author:徐倩 |
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Description: 该程序为经典的贝叶斯分类源代码，不仅可以应用于地球物理中的岩性和岩相划分，也可以做储层参数预测！-The source code for classic bayesian classification, the program not only can be used in the lithology and lithofacies division in geophysics, reservoir parameter prediction can also do!
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Size: 5120 |
Author:潘杰 |
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Description: 针对采用回声状态网络预测多元混沌时间序列时存在的病态解问题 , 本文建立了因子回声状态网络模型 , 通过因子分析 (Factor analysis, FA) 方法提取高维储备池状态矩阵的公因子 , 去除冗余和噪声成分 .-When an echo state network is used to predict multivariate time series, there may exist ill-posed problem. This pa-
per proposes a novel prediction model, named factor echo state
network, to solve the problem. It uses a factor analysis (FA) algorithm to extract the common factors of the reservoir matrix,and to remove the redundancies and noises. Platform: |
Size: 770048 |
Author:mafeng |
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Description: bp神经网络进行水库出流预测，输入参数有月份，水库坝上水位，水库坝下水位，水库入流量，输入参数为水库下泄流量(Prediction of reservoir outflow based on BP neural network) Platform: |
Size: 648192 |
Author:童彤264
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