Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Leiming Cheng"'
Publikováno v:
Frontiers in Energy Research, Vol 10 (2022)
Distributions of pore pressure and water saturation in matrix around fractures after hydraulic fracturing and shut-in period will impact the shale gas well production significantly. However, the influences of hydraulic fracturing and shut-in period o
Externí odkaz:
https://doaj.org/article/5a6f22af975c4b63be6b39dd1f6b9ca8
Publikováno v:
Frontiers in Genetics, Vol 12 (2021)
Long non-coding RNAs (lncRNAs) are widely concerned because of their close associations with many key biological activities. Though precise functions of most lncRNAs are unknown, research works show that lncRNAs usually exert biological function by i
Externí odkaz:
https://doaj.org/article/73cc32f22773426182a1ca3129aef3f9
Autor:
Leiming Cheng, Yingwei Wang, Haiyan Zhao, Jiacheng Li, Xiao Liu, Qiyao Liu, Xingning Huang, Thanapol Singjaroen, Piyanuch Kieduppatum
Publikováno v:
Day 2 Wed, August 10, 2022.
The unconventional oil and gas resources continuously discovered in China are mainly concentrated in the Junggar Basin, Ordos Basin, Sichuan Basin and Songliao Basin. However, the porosity and permeability of its shale reservoirs are extremely low, w
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::205a7119b3b97d5eb1556cf93acb64fa
https://doi.org/10.2118/209847-ms
https://doi.org/10.2118/209847-ms
Publikováno v:
Processes; Volume 10; Issue 8; Pages: 1646
Hydraulic fracture networks, especially fracture geometry, height growth, and proppant transport within the networks, present a critical influence on productivity evaluation and optimization of fracturing parameters. However, information about hydrau
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4ff3fb1315957414ce6770f27fc6836b
https://doi.org/10.3390/pr10081646
https://doi.org/10.3390/pr10081646
Publikováno v:
2021 IEEE 2nd International Conference on Big Data, Artificial Intelligence and Internet of Things Engineering (ICBAIE).
The capsule network is able to divide the data features into different capsules, which express their invariance and covariation by vectors. Aiming at the insufficiency of traditional machine learning methods for the ability in mapping logging paramet
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::da49ceeee300378213ea609fbeb509e1
https://doi.org/10.1109/icbaie52039.2021.9389895
https://doi.org/10.1109/icbaie52039.2021.9389895
Publikováno v:
Fresenius Environmental Bulletin. Oct2020, Vol. 29 Issue 10, p9144-9154. 11p.