Semi-supervised interlayer intelligent recognition method-Reference-Cited by-同舟云学术

Semi-supervised interlayer intelligent recognition method

Published:2023-05-26 Issue:3 Volume:16 Page:2187-2197
ISSN:1865-0473
Container-title:Earth Science Informatics
language:en
Short-container-title:Earth Sci Inform

Author:

Jiao Shixiang,Zhao Jun,He Yufei,Zhao Shixuan,Wu Zhenguan,Zeng Tianyi,Zhang Rui

Funder

CNPC-SWPU Innovation Alliance

Publisher

Springer Science and Business Media LLC

Subject

General Earth and Planetary Sciences

Link

https://link.springer.com/content/pdf/10.1007/s12145-023-01021-8.pdf

Reference23 articles.

1. Deng Y, Guo R, Tian Z, Tan W, Yi Y, Xu Z, Xiao C, Cao X, Chen L (2016) Geological characteristics and genesis of intercalation layer of carbonate reservoirs: taking the west gulna oilfield in iraq a case of the cretaceous mishrif group. Pet Explor Dev 43(01):136–144

2. Fu XF, Lan X, Meng LD et al (2016) Characteristics of fault zones and their control on remaining oil distribution at the fault edge: a case study from the northern Xingshugang Anticline in the Daqing Oilfield, China. Pet Sci 13(3):418–433

3. Guo C, Ni L, Chen J (2020) Characteristics and distribution of interlayer in gravel-bearing sandstone segment in Tazhong area. Sci Technol Eng 20(7):2625–2633

4. Guo J, Wang W, Tan J et al (2019) Fine Characterization Method for Interlayers in Complex Meander River Sandstone Reservoir: A Case Study of Um7 Sand of C Oilfield in Bohai Bay Area. Int J Geosci 10(04):405

5. Han R, Liu Q, Jiang T, Xu H, Xu Z, Zho L, Lei C, Zhang P (2014) Feature, origin and distribution of calcareous interlayers: a case of Carboniferous Donghe sandstone in Hade Oil Field, Tarim Basin, NW China. Pet Explor Dev 41(4):475–484