Research on the generation method of seawater sound velocity model based on Perlin noise

Zhimiao Chang; Fuxing Han; Zhangqing Sun; Zhenghui Gao; Xueqiu Wang

doi:10.1007/s13131-023-2230-6

Volume 43 Issue 1

Jan. 2024

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Article Navigation > Acta Oceanologica Sinica > 2024 > 43(1): 99-111

Zhimiao Chang, Fuxing Han, Zhangqing Sun, Zhenghui Gao, Xueqiu Wang. Research on the generation method of seawater sound velocity model based on Perlin noise[J]. Acta Oceanologica Sinica, 2024, 43(1): 99-111. doi: 10.1007/s13131-023-2230-6

Citation:

Zhimiao Chang, Fuxing Han, Zhangqing Sun, Zhenghui Gao, Xueqiu Wang. Research on the generation method of seawater sound velocity model based on Perlin noise[J]. Acta Oceanologica Sinica, 2024, 43(1): 99-111. doi: 10.1007/s13131-023-2230-6

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Research on the generation method of seawater sound velocity model based on Perlin noise

doi: 10.1007/s13131-023-2230-6

College of Geoexploration Science and Technology, Jilin University, Changchun 130026, China

Funds: The General Program of National Natural Science Foundation of China under contract No. 42074150.

More Information

Corresponding author: Email: sun_zhangq@jlu.edu.cn
Received Date: 2023-04-04
Accepted Date: 2023-06-20

Available Online: 2023-12-12

Publish Date: 2024-01-01

Abstract

Abstract

In the processing of conventional marine seismic data, seawater is often assumed to have a constant velocity model. However, due to static pressure, temperature difference and other factors, random disturbances may often frequently in seawater bodies. The impact of such disturbances on data processing results is a topic of theoretical research. Since seawater sound velocity is a difficult physical quantity to measure, there is a need for a method that can generate models conforming to seawater characteristics. This article will combine the Munk model and Perlin noise to propose a two-dimensional dynamic seawater sound velocity model generation method, a method that can generate a dynamic, continuous, random seawater sound velocity model with some regularity at large scales. Moreover, the paper discusses the influence of the inhomogeneity characteristics of seawater on wave field propagation and imaging. The results show that the seawater sound velocity model with random disturbance will have a significant influence on the wave field simulation and imaging results.
- Munk model,
- Perlin noise,
- seawater inhomogeneity

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References(17)

References

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