Determination of reservoir thickness and distribution using improved AFFA and LFCA technology
- Delong Zhang (Bohai Petroleum Research Institute, CNOOC Tianjin Company, Tianjin 300459, China) | Donghong Zhou (Bohai Petroleum Research Institute, CNOOC Tianjin Company, Tianjin 300459, China) | Zhongqiao Zhang (Bohai Petroleum Research Institute, CNOOC Tianjin Company, Tianjin 300459, China) | Shuanshuan Kong (Bohai Petroleum Research Institute, CNOOC Tianjin Company, Tianjin 300459, China) | Zhu Qiao (Bohai Petroleum Research Institute, CNOOC Tianjin Company, Tianjin 300459, China)
- Document ID
- Society of Exploration Geophysicists
- SEG International Exposition and Annual Meeting, 15-20 September, San Antonio, Texas, USA
- Publication Date
- Document Type
- Conference Paper
- 2019. Society of Exploration Geophysicists
- Frequency-domain, Attributes, Bed thickness
- 4 in the last 30 days
- 7 since 2007
- Show more detail
Strong seismic reflection often represents the oil and gas reservoir, or the lithology change, or the tuning caused by thick layer, and weak reflection indicates that the reservoir is not developing. In the process of oil and gas exploration and development, it is very important to accurately and effectively identify the good reservoir. In this paper, in order to identify the good reservoir in the target zone, a new method combination based on AFFA and LFCA is proposed. Firstly, using the advantage feature fusion attribute (AFFA) analysis, we can reduce the effect of thin layer tuning. Then the novel low frequency constraint amplitude (LFCA) analysis, we can also reduce the effect of thick layer tuning. Finally, we can get the reservoir thickness accurately, reducing the response is caused by thin or thick layer tuning as much as possible. The reservoir thickness and distribution predicted by improved AFFA and LFCA analysis before drilling is agree well with the actual drilling result, thereby the distribution range of good reservoir is delineated accurately and effectively, which provides good data support for well optimization. The actual application effect in Bohai oilfield shows that the proposed method is feasible and effective, which has a certain industrial application value.
Presentation Date: Monday, September 16, 2019
Session Start Time: 1:50 PM
Presentation Start Time: 2:40 PM
Location: Poster Station 5
Presentation Type: Poster
|File Size||795 KB||Number of Pages||5|
Meier,U.,A.,Curtis, andJ.,Trampert,2007,Global crustal thickness from neural network inversion of surface wave data:Geophysical Journal International,169,no.2,706–722,doi:10.1111/j.1365-246X.2007.03373.x.
Wang,K.-Y.,Q.-Y.,Xu,G.-F.,Zhang,M.-C.,Cheng, andP.-H.,Li,2013,Summary of seismic attribute analysis(in Chinese):Progress in Geophysics,28,no.2,815–823,doi:10.6038/pg20130231.
Zhang,D.,X.,Liang, andH.,Jiangbo,2017,The application of AFFA and LFCA technology to enhance the accuracy of reservoir prediction in KL16-X oilfield, southern Bohai Sea of China:87th Annual International Meeting, SEG,Expanded Abstracts,3386–3389,doi:10.1190/segam2017-17776691.1.