Channel identification method based on growing neural gas network and spectrum decomposition

Li Wang; Ruizhao Yang

doi:10.1117/12.2668751

23 February 2023 Channel identification method based on growing neural gas network and spectrum decomposition

Li Wang, Ruizhao Yang

Proceedings Volume 12551, Fourth International Conference on Geoscience and Remote Sensing Mapping (GRSM 2022); 125511I (2023) https://doi.org/10.1117/12.2668751
Event: Fourth International Conference on Geoscience and Remote Sensing Mapping (GRSM 2022), 2022, Changchun, China

Abstract

For the complex channel system with multi seismic facies, it is difficult to accurately identify the channel by conventional seismic attributes. In this paper, the channel identification method was applied based on spectrum decomposition and growing neural gas network (GNG). Firstly, the most sensitive frequency components with channel sand were selected through spectrum decomposition and as the input of the growth neural gas network. Then, GNG training was carried out to obtain the target neuron set. Finally, the GNG trained neural network can be used to estimate probabilities for each facies and a facies map is generated with related probability. The method was used in in Jiangqiao area of Songliao Basin, China. The results show that there are three types of channel facies (red, green and blue) in Saertu oil layer. This method can be used as an effective tool for identification of complex channels.

Citation Download Citation

Li Wang and Ruizhao Yang "Channel identification method based on growing neural gas network and spectrum decomposition", Proc. SPIE 12551, Fourth International Conference on Geoscience and Remote Sensing Mapping (GRSM 2022), 125511I (23 February 2023); https://doi.org/10.1117/12.2668751

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