《petrel建模培训2上课讲义》由会员分享，可在线阅读，更多相关《petrel建模培训2上课讲义（124页珍藏版）》请在金锄头文库上搜索。
1、2. Fault framework modeling2.1 添加断层到断层格架模型,2. Fault framework modeling2.2 确定断层间关系,2. Fault framework modeling2.3 断层参数设置,Demo select zone to model from drop-down list.,Facies If conditioning to a previous facies model, click also the Facies button.,Method Select appropriate method from the drop-down
2、list for the zone to be modeled.,Lock Leave zone unchanged; unlock to activate zone settings.,3.3 相模拟参数设置,1. Select an upscaled property: (U) as suffix.,4. Select the Facies from the template. Use the blue arrow to insert them into the model.,5. Variogram: A. Specify Range, Nugget and Type manually
3、B. or get a variogram from Data Analysis,6. Fraction: A. Use Global fraction from Upscaled cells. B. or use probabilities (property/trend). C. Use attribute probability curves or vertical proportion curves from Data analysis.,SIS is a pixel based modeling algorithm, using upscaled cells as basis for
4、 fraction of facies types to be modeled. The variogram constrains the distribution and connectedness of each facies.,3. Select SIS as the Method for one zone.,2. Select the zone to model and unlock it.,3.3 相模拟参数设置,八、属性建模与数据分析,基于Studio知识库的Petrel一体化研究流程,测井曲线粗化,测井曲线粗化 QC,N,Y,三维网 格QC,N,Y,层位编辑,断层建模,构造格架
5、网格化,建立地层格架,地层格架垂向网格化,纵向网格化,地层厚度 网格化,井点地层厚度计算,网格几何属性建模,网格体 积 QC,N,Y,网格 正交性QC,N,地层格架QC,N,Y,构造 解释,Y,岩相解释,岩相建模,属性建模,数据分析,储量计算,模型粗化,岩相QC,N,Y,属性QC,N,Y,地层划分与对比,合成地震记录,速度建模,时深转换,油藏数模模型,历史拟合,方案调整、加密井网,预测模拟,经济评价,油田动态管理,井历史生 产数据吻合,储量吻合,Y,N,Y,N,地震属性分析,数据查询与研究工区生成,七、属性建模与数据分析,2. 属性数据分析 2.1 数据变换 2.2 变程分析,1. 基本概念,
6、3. 属性建模 3.1 属性建模输入数据类型 3.2 Common和Zone Setting 3.3 相模拟参数设置 3.4 属性质量控制 3.5 属性计算器,1. 基本概念Overview,Key Issues Different petrophysical property distributions in different facies Various trends Spatial variation for each petrophysical parameter Correlation between parameters,Identify petrophysical featur
7、es critical to production,1. 基本概念Petrophysical modeling methods,1. 基本概念Petrophysical modeling methods,1. 基本概念Petrophysical modeling methods,1. 基本概念Petrophysical modeling methods,七、属性建模与数据分析,2. 属性数据分析 2.1 数据变换 2.2 变程分析,1. 基本概念,3. 属性建模 3.1 属性建模输入数据类型 3.2 Common和Zone Setting 3.3 相模拟参数设置 3.4 属性质量控制 3.5
8、属性计算器,连续属性数据分析,In Data analysis process for continuous properties the following functionalities are available: Data transformation: data distribution and spatial trends Variogram analysis: spatial variation Correlation: relationship between parameters By interval (zone) and by facies: maintain heter
9、ogeneity and difference.,Data analysis is a process of data QC, understanding the data and preparing inputs for Property modeling.,Histogram for different Facies: Is the histogram natural or does it need to be edited?,Input distribution for one facies type,Lobe Phi = 0.10,Shale Phi = 0.02,Channel Ph
10、i =0.22,2.1 数据变换Data Analysis Process: Distribution (by Individual Facies),2.1 数据变换What is a Transformation?,Input distribution (well logs),Transformation is the preparation of a real data set into an internal data set. Several transformations can be run in sequence. Before a simulation algorithm is
11、 run, a final Normal Score transformation is used (standard normal distribution: Mean =0, Std.dev=1).,Back-transformation will automatically be performed in the reverse order of the initial transformations to preserve the spatial trends and original data distribution in the resulting property.,2.1 数
12、据变换Data Analysis Process: Transformation (Distribution),2.1 数据变换Data Analysis Process: Transformation (Shape and Scale),2.1 数据变换Data Analysis Process: Transformation (Distribution Shift/Scale/Shape),2.1 数据变换Data Analysis Process: Transformation (Distribution Scale/Shape),Before modeling, Petrel will
13、 perform the following transformations: Truncate the input distribution (i.e. eliminate outliers) Remove the 1D trend (vertical compaction) Normal score the data (mean of 0, std of 1),Perform modeling based on the transformed data set. Then back-transform the data: Remove the Normal score transform
14、Add the 1D trend that was removed Truncate the output distribution (using set Max. and Min. values),2.2 变程分析Example of a Transformation Sequence (Porosity Modeling),2.2 变程分析,Points = Sample variogram Line = Regression line Line = Model Variogram Histogram = Number of pairs,The variogram is calculate
15、d on upscaled transformed data in simbox mode. It measures variability with distance. Calculated in 3 directions: Horizontal Major Horizontal Minor Vertical A search cone must be set to capture data within lags.,2.2 变程分析Data Analysis Process: Variogram Analysis,3. 属性建模 3.1 属性建模输入数据类型 3.2 Common和Zone
16、 Setting 3.3 相模拟参数设置 3.4 属性质量控制 3.5 属性计算器,七、属性建模与数据分析,2. 属性数据分析 2.1 数据变换 2.2 变程分析,1. 基本概念,3.1 属性建模输入数据类型,Well data: upscaled/blocked well logs Distribution: histogram Variogram (spatial model): - Direction, model type, nugget and sill - Correlation lengths in 3 directions (range) Facies model: Conditioning Spatial trends: From seismic /analogs etc. Secondary parameter: with a correlation,3.2 Common和Zone Setting,Two Main Modeling Settings buttons are available (Comm
