The gradient structure tensor (GST) serves as a common attribute to characterize the boundaries of strongly heterogeneous reservoirs, such as fracture-cavity types, playing an important role in research on carbonate reservoirs. However, due to a lack of dimensions and high difficulties in threshold determination, the accuracy of GSI directly affects the precision of reservoir delineation and reserve estimation. Given this, focusing on a fracture-cavity carbonate reservoir model, this study proposed a three-step strategy for threshold selection based on analysis of the GST attribute distribution corresponding to noisy reservoir and non-reservoir regions. First, the distribution of GST attribute values was statistically analyzed. Then, the value distribution of attribute values in the non-reservoir regions was estimated to identify their mean point, left critical point, and right critical point. Finally, the right critical point was selected as the threshold for the GST attribute of noisy reservoirs, thus delineating the boundaries of fracture-cavity bodies. Model tests and practical applications demonstrate the feasibility and effectiveness of this method. The findings provide a foundation for the application and promotion of the GST attribute in geophysics.
He Z L, Jin X H, Wo Y J, et al. Hydrocarbon accumulation characteristics and exploration domains of ultra-deep marine carbonates in China[J]. China Petroleum Exploration, 2016, 21(1):3-14.
Zhang J L, Tian S C, Zheng D M. Characterization and evaluation of fracture-cavity type carbonate reservoir in the western part of Northern Tarim uplift[J]. Geophysical and Geochemical Exploration, 2014, 38(3):497-503.
Li P, Chen J S, Wang Z Y. Study on controlling factors and reservoir types of Ordovician carbonate reservoirs in Tazhong area[J]. Natural Gas Exploraiton & Development, 2003, 26(1):37-42.
Chang S Y, Zeng J H, Xu X H, et al. Identification technology for internal structures of carbonate fault-karst and its application[J]. Oil Geophysical Prospecting, 2022, 57(2):414-422,247.
Zhang M, Li X W, Jin M, et al. Iterative inversion method for ultradeep fault-controlled fracture-vug reservoirs:A case study of the Fuman oilfield,Tarim Basin[J]. Geophysical and Geochemical Exploration, 2023, 47(1):22-30.
[7]
Knutsson H. Representing loca lstructure using tensors[C]// Proceedings of 6th Scandinavian Conference on Image Analysis,1989:545-556.
[8]
Randen T, Monsen E, Signer C, et al. Three-dimensional texture attributes for seismic data analysis[J]. SEG Technical Program Expanded Abstracts, 2000, 19(1):668-671.
[9]
Luo Y, Wang Y E, Albinhassan N M, et al. Computation of dips and azimuths with weighted structural tensor approach[J]. Geophysics, 2006, 71(5):V119-V121.
[10]
Bakker P. Image structure analysis for seismic interpretation[D]. Delft University of Technology,Delft,Netherlands, 2002.
Wang Q Z, Zhang J M, Jiang X D, et al. Salt dome and fault detection based on the gradient-structure tensor[J]. Oil Geophysical Prospecting, 2018, 53(4):826-831,656.
Cui Z W, Cheng B J, Xu T J, et al. Reservoir fracture prediction method and application based on structure-oriented filtering and coherent attributes of gradient structure tensor[J]. Oil Geophysical Prospecting, 2021, 56(3):555-563,413-414.
Liu J, Huang C, Yang L, et al. Quantitative prediction technology for the hydrocarbon production capacity of fractures and vugs in fault-controlled carbonate reservoirs in the Shunbei area[J]. Geophysical and Geochemical Exploration, 2023, 47(3):747-756.
Zhang S, Li Y L, Xiao Y J, et al. Research and application of carbonate fracture-cavity boundary characterization method based on gradient structure-tensor[J]. Oil Geophysical Prospecting, 2022, 57(4):907-915,742.
He Z L, Zhu C H, Xu W Y, et al. Seismic characterization of multi-type deep/ultra-deep carbonate reservoir[J]. Chinese Journal of Geophysics, 2023, 66(1):65-82.
