Zobrazeno 1 - 10
of 30
pro vyhledávání: '"Renwei Ding"'
Publikováno v:
CT Lilun yu yingyong yanjiu, Vol 33, Iss 6, Pp 761-771 (2024)
In complex geological conditions, especially in the case of small faults and fractures, it is often impossible to use reflected waves for accurate detection. An alternative method is the use of the scattered waves caused by these small structures for
Externí odkaz:
https://doaj.org/article/1971d9d6e7a646e9a0a6cd9b6da5006b
Publikováno v:
IEEE Access, Vol 12, Pp 151728-151736 (2024)
A precise dynamic model and exact statistical information are required in a standard Kalman filter to ensure optimal performance. Without these, degraded performance may be obtained. In this paper, an improved adaptive estimation approach for uncerta
Externí odkaz:
https://doaj.org/article/90cfa60119954630a392d4987f4476f8
Publikováno v:
CT Lilun yu yingyong yanjiu, Vol 33, Iss 1, Pp 105-117 (2023)
In seismic exploration, complex seismic wave fields comprising reflected waves, scattered waves, and other phenomena are formed due to the intricate nature of underground structures. Traditional imaging methods typically focus solely on the reflected
Externí odkaz:
https://doaj.org/article/e0fcab0b05ca4914aebfe72c1ce5ff95
Publikováno v:
CT Lilun yu yingyong yanjiu, Vol 32, Iss 1, Pp 15-25 (2023)
This study applied the cycle-consistent generative adversarial network method to the denoising of shallow profile data to realize intelligent denoising. This could help resolve the problem of noise and low resolution of shallow profile data. To do th
Externí odkaz:
https://doaj.org/article/946a868f94c84cb1864939a1601d6ced
Autor:
Shimin Sun, Guihua Li, Renwei Ding, Lihong Zhao, Yujie Zhang, Shuo Zhao, Jinwei Zhang, Junlin Ye
Publikováno v:
Frontiers in Earth Science, Vol 11 (2023)
Random noise adversely affects the signal-to-noise ratio of complex seismic signals in complex surface conditions and media. The primary challenges related to processing seismic data have always been reducing the random noise and increasing the signa
Externí odkaz:
https://doaj.org/article/79218d4ac1684ceaba68700f51f8be2f
Fault2SeisGAN: A method for the expansion of fault datasets based on generative adversarial networks
Publikováno v:
Frontiers in Earth Science, Vol 11 (2023)
The development of supervised deep learning technology in seismology and related fields has been restricted due to the lack of training sets. A large amount of unlabeled data is recorded in seismic exploration, and their application to network traini
Externí odkaz:
https://doaj.org/article/4fa4380e7e9f495590ce317e093b96ba
Autor:
Yilin Liu, Yi Zhang, Faqiang Zhao, Renwei Ding, Lihong Zhao, Yufen Niu, Feifei Qu, Zilong Ling
Publikováno v:
Remote Sensing, Vol 15, Iss 13, p 3290 (2023)
Land motions are significantly widespread in the Yellow River delta (YRD). There is, however, a lack of understanding of the delta-wide comprehensive deformation mode and its dynamic mechanism, especially triggered by groundwater extraction. This pap
Externí odkaz:
https://doaj.org/article/d8522cdf1bd74fab992c84ceb46ce7c4
Publikováno v:
Journal of Marine Science and Engineering, Vol 11, Iss 2, p 443 (2023)
This study combines surface heat flow, multi-channel seismic reflection profiles, and ocean-bottom seismometer (OBS) profiles to determine the thermo-rheological structure of the Qiongdongnan Basin (QDNB) and Pearl River Mouth Basin (PRMB), with the
Externí odkaz:
https://doaj.org/article/bd44a9bc7ede404b87ff7da858c7bf16
Autor:
Yujie Zhang, Dongdong Wang, Renwei Ding, Jing Yang, Lihong Zhao, Shuo Zhao, Minghao Cai, Tianjiao Han
Publikováno v:
Energies, Vol 15, Iss 21, p 8098 (2022)
Low-grade faults play an important role in controlling oil and gas accumulations, but their fault throw is small and difficult to identify. Traditional low-grade fault recognition methods are time-consuming and inaccurate. Therefore, this study propo
Externí odkaz:
https://doaj.org/article/d076655cc6be46e384bee53bfee59826
Publikováno v:
Journal of Marine Science and Engineering, Vol 10, Iss 2, p 157 (2022)
To understand the tectonic–magmatic history, crustal structure and crustal accretion mode of the Eurasian Basin in the Arctic, we calculated the crustal thickness, residual bathymetry (RB) and non-isostatic topography of the Eurasian Basin by using
Externí odkaz:
https://doaj.org/article/809843f42e7842af978a87b64a7bb561