Southwest Petroleum University

China University of Geosciences (wuhan)

Shale Gas Research Institute, Petrochina Southwest Oil and Gas Field Company

Sichuan Hengyi Petroleum Technology Services Co., Ltd

Petrochina Zhejiang Oilfield Company

Sinopec Southwest Petroleum Bureau Co., Ltd

Jiangxi Provincial Shale Gas. Investment Company, Ltd

Yan Song

Lei Chen

Kun Zhang

Xinyang He

Xueying Wang

Fengli Han

Yipeng Liu

Jingru Ruan

Xuefei Yang

Hengfeng Gou

Ping Liu

Hulin Niu

Weishi Tang

Lintao Li

Chengzao Jia

Jiayi Liu

Jia He

Jing Li

Yi Zhang

Shu Jiang

Yi Shu

Xiong Ding

Lu Lu

Cheng Yang

Tian Tang

Yi Xiao

Zeyun Wang

Yiting Qiao

Meijia Wu

Laiting Ye

Xiaoxia Dong

Jun Dong

Zhenxue Jiang

Jiasui Ouyang

Ruisong Li

Tong Wang

Nanxi Zhang

Hanbing Zhang

Pu Huang

Xingmeng Wang

Shoucheng Xu

Yubing Ji

Yongjun Li

Tianyou Zhi

Weiwei Liu

Songyang Wan

Sihong Cheng

Daiyu Wu

Bo Li

Yijia Wu

Yiming Yang

Liang Xu

Zhi Gao

Jiajie Wu

Yongyang Liu

A calculation method for fractal dimensions of shale pores includes steps as follows. S1: multiple shale samples from a target stratum of a study area are obtained, parameter values of geological parameters of each of the multiple shale samples are obtained, followed by dividing the multiple shale samples into target shale samples and experimental shale samples. S2: PCA is performed on the parameter values to obtain principal components representing a variation of the geological parameters. fractal dimensions are calculated based on an existing fractal dimension calculation method. S3: the principal components are used as independent variables and the fractal dimensions are used as dependent variables, followed by performing regression analysis to obtain a quantitative calculation model. S4: the fractal dimensions of the target shale sample are calculated according to the parameter values and the quantitative calculation model for the fractal dimension based on the parameter values.

Calculation method for fractal dimension of shale pores

A quantitative prediction method for gas content of deep marine shale includes: obtaining raw data of known wells; establishing relationship formulas between pore specific surface areas and adsorbed gas contents of a known well in an area as an adsorbed gas content quantitative prediction model; establishing relationship formulas between pore volumes and free gas contents of the known well as a free gas content quantitative prediction model; summing the adsorbed gas contents and corresponding free gas contents to obtain total gas contents; calculating adsorbed gas contents, free gas contents and total gas contents of the known wells; drawing a predicted adsorbed gas content contour map, a predicted free gas content contour map and a predicted total gas content contour map; and reading an adsorbed gas content, a free gas content and a total gas content of an unknown well in the area from the above contour maps.

Quantitative prediction method for gas content of deep marine shale

A method for calculating a surface relaxation rate of a shale includes: a relaxation time T distribution curve and a pore throat radius r distribution curve are obtained through experiments; abscissas of the two distribution curves are standardized, and the abscissa of the relaxation time T distribution curve is expanded or shrunk to ensure an abscissa value corresponding to a maximum ordinate value in the transformed relaxation time T distribution curve is same as an abscissa value corresponding to a maximum ordinate value in the pore throat radius r distribution curve; straight lines with a number of N parallel to a y-axis of a combined curve graph including the two distribution curves are drawn and a ρ value corresponding to each straight line is calculated; and ρ value with the number of N are processed to obtain a final surface relaxation rate ρ'.

Method for calculating surface relaxation rate of shale

Growing community of inventors

Chengdu, China

Yan Song