Application of multi-attribute analysis technology based on FCM algorithm in fine characterization of sedimentary microfacies： take T Gas Field in Xihu Sag as an example

WANG Kai; LIU Dongcheng; LIU Huafeng; HUANG Derong; CHU Feiyue

doi:10.16028/j.1009-2722.2022.103

2023 Vol. 39, No. 9

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Article navigation > Marine Geology Frontiers > 2023 > 39(9): 55-67

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WANG Kai, LIU Dongcheng, LIU Huafeng, HUANG Derong, CHU Feiyue. Application of multi-attribute analysis technology based on FCM algorithm in fine characterization of sedimentary microfacies： take T Gas Field in Xihu Sag as an example[J]. Marine Geology Frontiers, 2023, 39(9): 55-67. doi: 10.16028/j.1009-2722.2022.103

Citation:

WANG Kai, LIU Dongcheng, LIU Huafeng, HUANG Derong, CHU Feiyue. Application of multi-attribute analysis technology based on FCM algorithm in fine characterization of sedimentary microfacies： take T Gas Field in Xihu Sag as an example[J]. Marine Geology Frontiers, 2023, 39(9): 55-67. doi: 10.16028/j.1009-2722.2022.103

Application of multi-attribute analysis technology based on FCM algorithm in fine characterization of sedimentary microfacies： take T Gas Field in Xihu Sag as an example

1.
School of Geosciences, China University of Petroleum (East China), Qingdao 266580, China
2.
Shandong Provincial Key Laboratory of Reservoir Geology, Qingdao 266580, China
3.
Exploration and Development Research Institute of PetroChina Dagang Oilfield, Tianjin 300280, China

Received Date: 06 April 2022

Publish Date: 28 September 2023

Abstract

Abstract

After 10+ years of exploration and development of the T Gas Field in the Xihu Sag in East China Sea, it is urgent to find potential targets in the Oligocene Huagang Formation. To identify channel sand body and its boundary accurately, 3D seismic data were used based on data of several offshore wells. The petrophysical properties of the target stratum were analyzed based on isochronous stratigraphic division, and the sedimentary microfacies were preliminarily specified by seismic sedimentology and logging data. In total, 48 seismic attributes were extracted in six categories. Correlation analysis was conducted on sand thickness and each attribute, from which three most meaningful seismic attributes were determined and selected. The three seismic attributes could well reflect the geological body boundaries and ideal lithology. In addition, multi-attribute clustering analysis based on the FCM (Fuzzy C-Means clustering) algorithm was performed, by which the effect of data dimension and redundancy were reduced. In addition, the distribution of distributary channel depositional system was studied, and RGB fusion display was carried out to highlight channel sand body boundaries. By combining the comprehensive analysis on geological structure and predicted sand body thickness, the favorable target area was proposed, which provides a basis for the subsequent rolling development of oilfield and the well location deployment.
- seismic attribute /
- FCM (Fuzzy C-Means clustering) algorithm /
- multi-attribute clustering /
- sand body prediction /
- Huagang Formation

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References

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