Southwest Petroleum University

China University of Geosciences (wuhan)

China University of Petroleum

University of Electronic Science and Technology of China

Sichuan Zhongguang Lightning Protection Technologies Co., Ltd.

Oil & Gas Survey Center, China Geological Survey

Sinopec Exploration Company

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

Xueying Wang

Kun Zhang

Fengli Han

Lei Chen

Xinyang He

Yipeng Liu

Xuefei Yang

Hengfeng Gou

Jingru Ruan

Lintao Li

Weishi Tang

Ping Liu

Hulin Niu

Shu Jiang

Jiayi Liu

Chengzao Jia

Bin Li

Xiong Ding

Jun Peng

Yan Song

Yi Zhang

Yi Shu

Lu Lu

Binsong Zheng

Yi Xiao

Zeyun Wang

Meijia Wu

Pei Liu

Jinhua Liu

Yiting Qiao

Laiting Ye

Xuejiao Yuan

Jia He

Wei Wang

Jing Li

Xiaoming Zhao

Lin Jiang

Zhenxue Jiang

Xuri Huang

Cheng Yang

Tian Tang

Tong Wang

Hu Zhao

Nanxi Zhang

Pu Huang

Guohua Yang

Xingmeng Wang

Shoucheng Xu

Yongjun Li

Tianyou Zhi

Weiwei Liu

Songyang Wan

Zhujiang Liu

Sihong Cheng

Daiyu Wu

Yunbo Zhang

Yanhua Lin

Daojun Wang

Jingyu Hao

Ruisong Li

Hanbing Zhang

Feiran Chen

Ruobing Liu

Bo Li

Fubin Wei

Yubing Ji

Tianmi Li

Liang Xu

Yijia Wu

Yiming Yang

Hong Liu

Zhi Gao

Xiangfeng Wei

Jiajie Wu

Xiangyu Fan

Yongyang Liu

Xiaoxia Dong

Jun Dong

Yi Ren

Jiasui Ouyang

A method for quantitative evaluation of self-sealing property of organic-rich shale includes: S1, selecting geological parameters for evaluating the self-sealing property of the organic-rich shale; S2, taking organic-rich shale samples, and measuring the geological parameters of each sample; S3, calculating a weight coefficient w; of each geological parameter; S4, calculating a self-sealing evaluation coefficient S, and correcting the S to obtain a corrected self-sealing evaluation coefficient S'; S5, establishing a self-sealing evaluation standard of the organic-rich shale according to the S′, wherein if S′≥0.6, the self-sealing grade is excellent, if 0.45≤S′<0.6, the self-sealing grade is good, if 0.3≤S′<0.45, the self-sealing grade is medium, and if S′<0.3, the self-sealing grade is poor. According to the method, the self-sealing property of the shale is quantitatively evaluated, and the preservation condition of the shale gas in the shale formation can be more accurately predicted.

Method for quantitative evaluation of self-sealing property of organic-rich shale

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

A method for combined characterization of pore structure includes steps as follows. Firstly, CO, Nand high-pressure mercury intrusion porosimetry characterization curves are plotted based on actual measurement data, then, average values of the overlapping range of the COand Ncharacterization curves are calculated, and a function y'=ƒ(x) is fitted. Each pore volume y′ corresponding to each pore diameter xis calculated, and a curve is plotted with xas a horizontal coordinate and y′ as a vertical coordinate, thereby obtaining a characterization curve of the overlapping range between COand Nadsorptions. The same data processing is used to process the overlapping range data of the Nand high-pressure mercury intrusion porosimetry characterization curves, to obtain the characterization curve between them. The characterization curves are spliced with the original CO, N, and high-pressure mercury intrusion porosimetry characterization curves to obtain a combined characterization curve.

Method for combined characterization of pore structure

Provided is an analysis method for determining gas-bearing situation of an unknown shale reservoir, includes: S, selecting a shale reservoir of a target interval of a place; and collecting data of parameters of cores of each of a known gas-bearing shale reservoir A and a known water-bearing shale reservoir B; S, calculating average values of the parameters of each of the reservoirs A and B respectively; S, calculating average differences of the parameters of each of the reservoirs; S, calculating covariance values of the parameters of each of the reservoirs; S, establishing, according to the covariance values, an equation group and resolving discriminant coefficients; S, establishing a discriminant equation according to the discriminant coefficients and solving a discriminant index; and S, obtaining values of parameters of cores of a sample of the unknown shale reservoir, calculating a discriminant value, and determining gas-bearing situation of the unknown shale reservoir.

Analysis method for determining gas-bearing situation of unknown shale reservoir

A data processing method includes: collecting test data of a target rock sample in different gas adsorption experiments; the test data including pore sizes and pore volumes corresponding to the pore sizes and including at least two selected from the group consisting of the test data with pore sizes less than 3 nm in COadsorption experiment, the test data with pore sizes in 1.5 nm to 250 nm in Nadsorption experiment and the test data with pore sizes in 10 nm to 1000 &#x3bc;m in high-pressure mercury adsorption experiment; and fitting the test data in overlapping ranges of the pore sizes using a least square method, and obtaining target pore volumes corresponding to the pore sizes respectively. The accuracy of joint characterization of shale pore structures can be improved by using mathematical methods to process the data in overlapping ranges of pore sizes among different characterization methods.

Joint characterization method of pore structures based on least square method and data processing method

The invention relates to a high-safety surge protective device which comprises a casing, at least one overvoltage protection component inside the casing, a release unit used to separate the overvoltage protection component from the AC or DC circuit or the equipment, an arc suppressing apparatus used to suppress electric arc generated while separating the overvoltage protection component from the AC or DC circuit or the equipment, and a box, Wherein: the release unit comprises a compression spring, a metal dome, a slide and a soft conductor; the arc suppressing apparatus comprises an arc chute assembly, a first arc striking sheet, a second arc striking sheet, a turning block and a torsional spring.

High-safety surge protective device

Growing community of inventors

Chengdu, China

Xueying Wang