基本信息来源于合作网站,原文需代理用户跳转至来源网站获取       
摘要:
Permeability prediction using linear regression of porosity always has poor performance when the reservoir with complex pore structure and large variation of lithofacies.A new method is proposed to predict permeability by comprehensively considering pore structure,porosity and lithofacies.In this method,firstly,the lithofacies classification is carried out using the elastic parameters,porosity and shear frame flexibility factor.Then,for each lithofacies,the elastic parameters,porosity and shear frame flexibility factor are used to obtain permeability from regression.The permeability prediction test by logging data of the study area shows that the shear frame flexibility factor that characterizes the pore structure is more sensitive to permeability than the conventional elastic parameters,so it can predict permeability more accurately.In addition,the permeability prediction is depending on the precision of lithofacies classification,reliable lithofacies classification is the precondition of permeability prediction.The field data application verifies that the proposed permeability prediction method based on pore structure parameters and lithofacies is accurate and effective.This approach provides an effective tool for permeability prediction.
推荐文章
Using Geomechanical Method to Predict Tectonic Fractures in Low-Permeability Sandstone Reservoirs
Low-permeability sandstone reservoir
Fracture parameters
Geomechanical method
Spatial prediction of landslide susceptibility using GIS-based statistical and machine learning mode
Landslide susceptibility mapping
Statistical model
Machine learning model
Four cases
Rapid estimation of soil heavy metal nickel content based on optimized screening of near-infrared sp
Heavy metal
Band extraction
Partial least squares regression
Extreme learning machine
Near infrared spectroscopy
内容分析
关键词云
关键词热度
相关文献总数  
(/次)
(/年)
文献信息
篇名 A permeability prediction method based on pore structure and lithofacies
来源期刊 石油勘探与开发:英文版 学科 工学
关键词 SEISMIC reservoir prediction PORE structure PERMEABILITY lithofacies shear FRAME FLEXIBILITY factor BOOSTING learning
年,卷(期) 2019,(5) 所属期刊栏目
研究方向 页码范围 935-942
页数 8页 分类号 TE311
字数 语种
DOI
五维指标
传播情况
(/次)
(/年)
引文网络
引文网络
二级参考文献  (0)
共引文献  (0)
参考文献  (0)
节点文献
引证文献  (0)
同被引文献  (0)
二级引证文献  (0)
2019(0)
  • 参考文献(0)
  • 二级参考文献(0)
  • 引证文献(0)
  • 二级引证文献(0)
研究主题发展历程
节点文献
SEISMIC
reservoir
prediction
PORE
structure
PERMEABILITY
lithofacies
shear
FRAME
FLEXIBILITY
factor
BOOSTING
learning
研究起点
研究来源
研究分支
研究去脉
引文网络交叉学科
相关学者/机构
期刊影响力
石油勘探与开发:英文版
双月刊
2096-4803
10-1529/TE
北京市海淀区学院路20号
80-232
出版文献量(篇)
331
总下载数(次)
0
总被引数(次)
0
论文1v1指导