Prediction of meandering belt and point-bar recognition based on spectral-decomposed and fused seismic attributes: A case study of the Guantao Formation, Chengdao Oilfield,Bohai Bay Basin
Yue Da-Li1, 2, Li Wei1, 2, Wang Jun3, Wang Wu-Rong1, 2, Li Jian3
1 College of Geosciences,China University of Petroleum(Beijing),Beijing 102249; 2 State Key Laboratory of Petroleum Resources and Prospecting,China University of Petroleum(Beijing),Beijing 102249; 3 Shengli Oil Field Company,SINOPEC,Dongying 257015,Shandong;
Abstract：Sedimentary environment of the Guantao Formation in Chengdao Oilfield is meandering river. With the methods including the extraction and optimization of spectral-decomposed and fused seismic attributes,the guidance of reservoir architecture model,and dynamic response characteristics constraints,meandering belts and point bars under the condition of offshore sparse well network are characterized in detail. The result shows that: (1)the reservoir prediction method of spectral-decomposed seismic attributes improves the prediction accuracy of the meandering belt. The correlation between amplitude properties and sand thickness is the best,especially the maximum peak amplitude. Compared to the original seismic attributes,the maximum peak amplitude derived from the spectral-decomposed seismic attributes can characterize the boundary and thickness of the meandering sand-bodies much better. (2)The three important symbols of point bar are composite positive rhythms,thick sand-bodies,and being adjacent to abandoned channels. Corresponding to these features,point bars show the characteristics of seismic response with high maximum peak amplitude and high inversion properties,while abandoned channels show low amplitude attributes and low inversion properties with the characteristics of flat top and convex bottom. (3)Based on location prediction of the point bar by using seismic attributes,the span of the point bar is calculated through empirical formula,the scale of point bar is recognized,and the identification of subsurface point bar is effectively guided. The constraint of dynamic data also provides a basis for point bar identification. The methods proposed in this paper can provide implications to the oilfield with similar sedimentary characteristics and data condition.
Yue Da-Li,Li Wei,Wang Jun et al. Prediction of meandering belt and point-bar recognition based on spectral-decomposed and fused seismic attributes: A case study of the Guantao Formation, Chengdao Oilfield,Bohai Bay Basin[J]. JOPC, 2018, 20(6): 941-950.
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