The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.
The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.
Patent No.:
Date of Patent:
May. 10, 2022
Filed:
Jun. 11, 2021
China University of Petroleum (Beijing), Beijing, CN;
Guancheng Jiang, Beijing, CN;
Xiongjun Wu, Beijing, CN;
Lili Yang, Beijing, CN;
Yinbo He, Beijing, CN;
Tengfei Dong, Beijing, CN;
Xiaohu Quan, Beijing, CN;
Chunyao Peng, Beijing, CN;
Xuwu Luo, Beijing, CN;
Bin Tan, Beijing, CN;
Jun Cai, Beijing, CN;
Xing Liang, Beijing, CN;
Zhiliang You, Beijing, CN;
Yong Wang, Beijing, CN;
Bin Li, Beijing, CN;
Yongbin Guo, Beijing, CN;
Shen Guan, Beijing, CN;
China University of Petroleum (Beijing), Beijing, CN;
Abstract
The embodiments of the invention provide an intelligent prediction method and apparatus for reservoir sensitivity, belonging to the technical field of reservoir sensitivity prediction. The method includes: acquiring a reservoir sensitivity influence factor item related to a reservoir sensitivity result to be predicted and numerical values of corresponding reservoir sensitivity influence factors; determining a corresponding type of database according to the reservoir sensitivity influence factor item; determining whether numerical values of reservoir sensitivity influence factors corresponding to core parameters in the numerical values of the reservoir sensitivity influence factors include a first upper boundary value or a first lower boundary value; and using, according to whether the first upper boundary value or the first lower boundary value is included, different intelligent sensitivity prediction models to calculate the reservoir sensitivity result to be predicted.