Application of the clustering method in analysing shallow water masses and modified water masses in the Huanghai Sea and East China Sea

1983 ◽  
Vol 1 (3) ◽  
pp. 272-284 ◽  
Author(s):  
Su Yusong ◽  
Yu Zuxiang ◽  
Li Fengqi
2019 ◽  
Vol 38 (8) ◽  
pp. 610-616
Author(s):  
Yun Wei ◽  
Hua Chen ◽  
Senqing Hu ◽  
Peipei Deng ◽  
Yongdeng Xiao ◽  
...  

A new broadband wide-azimuth towed-streamer (WATS) survey was acquired to better resolve reservoir compartments in a shallow-water region of the East China Sea. To offset the shortcomings of narrow-azimuth acquisition along the strike direction, two vessels were added side-by-side as additional source vessels to form the WATS acquisition geometry for this survey. This WATS acquisition was much sparser than typical WATS surveys used in deepwater environments due to its one-sided configuration. The combination of sparse acquisition, shallow water, and deep targets set the challenge of how to optimally reveal the potential of side-gun data to improve the final image. Three-dimensional effects and severe aliasing in the crossline direction pose significant challenges for side-gun data processing. We present a comprehensive workflow to resolve these challenges consisting of 3D deghosting, 3D model-based water-layer demultiple, 3D surface-related multiple elimination, and 4D regularization for sparse and shallow-water wide-azimuth data. A tilted orthorhombic velocity model is built with better constraints from the wide-azimuth data, leading to improved fault positioning and imaging. Side-gun data clearly enhance the final target reservoir image and tie better with well data due to improved illumination. A new channel is discovered based on interpretation from the inverted VP/VS, explaining the previous incorrect prediction for one failed well that was drilled into a thinner and shallower channel unconnected to the main reservoir. An analysis of the impact of side-gun data from different offsets and azimuths shows that better azimuthal distribution within middle offset ranges had a more significant impact than far offsets in the final image of this survey. This information provides valuable reference in similar geologic conditions for future acquisition designs.


2013 ◽  
Vol 31 (2) ◽  
pp. 247-266 ◽  
Author(s):  
Li Zhao ◽  
Yuan Zhao ◽  
Wuchang Zhang ◽  
Feng Zhou ◽  
Cuixia Zhang ◽  
...  

2018 ◽  
Author(s):  
Ling Ding ◽  
Tiantian Ge ◽  
Xuchen Wang

Abstract. Oceanic dissolved organic carbon (DOC) is one of the largest carbon reservoirs on Earth, and its distribution and behavior play important roles in carbon cycling and biogeochemical processes in the ocean. Here, we report distribution and concentrations of DOC for water samples collected from the shelf-edge and slope regions in East China Sea (ECS) and the Kuroshio Extension (KE) in the northwestern North Pacific (NP) during two cruises in 2014–2015. Concentrations of DOC were 45–88 µM in the ECS and 35–65 µM in the KE. In addition to biological processes, the distribution of DOC is largely controlled by hydrodynamic mixing of different water masses. The intrusion of Kuroshio Current could dilute DOC concentrations at stations in the outer shelf and slope ranges of the ECS. The inverse correlation of DOC with apparent oxygen utilization (AOU) suggests that DOC oxidation only contributes 18 % of the oxygen consumption in the ECS slope waters. In contrast, concentrations of DOC in the KE were significantly lower in surface waters, and a relatively low and stable DOC level (~ 40 µM) was found in deep waters. The observed spatial variations of DOC in the upper 700 m among the stations in the KE were largely influenced by the mixing of the two water masses carried by the two major western boundary currents: Kuroshio and Oyashio that mix and form the KE. The hydrodynamic processes play important roles not only in the distribution of DOC but nutrients as well, thus could have major impact to primary production and ecosystems in the KE region.


2021 ◽  
Vol 40 (4) ◽  
pp. 23-31
Author(s):  
Tianwei Shang ◽  
Xueyan Jiang ◽  
Chenqing Yu

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