Artificial neural network–based time-domain interwell tracer testing for ultralow-permeability fractured reservoirs-Reference-Cited by-同舟云学术

Artificial neural network–based time-domain interwell tracer testing for ultralow-permeability fractured reservoirs

Published:2020-12 Issue: Volume:195 Page:107558
ISSN:0920-4105
Container-title:Journal of Petroleum Science and Engineering
language:en
Short-container-title:Journal of Petroleum Science and Engineering

Author:

Jing Cheng,Dong Xiaowei,Cui Wenhao,Dong Zhenzhen,Ren Long,Gu Xiaoyu,He Yanlong,Pu Chunsheng,Liu Xiaoyu

Funder

National Natural Science Foundation of China

Natural Science Basic Research Plan in Shaanxi Province of China

Young Talent fund of University Association for Science and Technology in Shaanxi

Publisher

Elsevier BV

Subject

Geotechnical Engineering and Engineering Geology,Fuel Technology

Reference35 articles.

1. Application of chemical tracers in IOR: a case history;Asadi,2010

2. Analysis of well-to-well tracer flow to determine reservoir layering;Abbaszadeh;SPE J.,1984

3. Analysis of field tracers for reservoir description;Allison;J. Petrol. Sci. Eng.,1991

4. Design of a partitioning interwell tracer test for a chemical EOR pilot targeting the sabriyah mauddud carbonate reservoir in Kuwait;Al-Murayri,2017

5. Prediction of tracer behavior in five-spots flow;Brigham,1965

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