Issue |
E3S Web Conf.
Volume 478, 2024
6th International Conference on Green Energy and Sustainable Development (GESD 2023)
|
|
---|---|---|
Article Number | 01010 | |
Number of page(s) | 9 | |
DOI | https://doi.org/10.1051/e3sconf/202447801010 | |
Published online | 16 January 2024 |
Application of Seismic Attribute Analysis Technology Guided by Model Forward Modeling in L29 Area
Daqing Oilfield Co., Ltd. No. 9 Oil Production Plant, Daqing City, Heilongjiang Province, China
Taking the SaErTU and Putaohua oil layers in the L29 well area of LHP oilfield in the northern Songliao Basin as the research object, In response to the difficulty of interference between thin interbedded sand and mudstone and strong reflection between strata, which have a significant impact on fine prediction of sand bodies, a stratigraphic model is established based on the geological characteristics of the target layer to eliminate the impact of stratigraphic reflection; Then add a thin layer of sand body to its interior, establish a thin interlayer model, and obtain a geological model that is more in line with the actual situation of the target layer. Using forward simulation, analyze the seismic response characteristics of sand bodies, extract 30 seismic attributes from 4 categories: amplitude statistics, composite seismic trace statistics, sequence and frequency spectrum statistics, and calculate the correlation between cumulative sandstone thickness and seismic attributes, and select a sensitive seismic attribute set;By combining sedimentary and drilling data, the seismic attribute with the highest sensitivity to the target layer is selected. The multi-level dimensionality reduction and gradual improvement of seismic attribute selection methods using “model forward modeling, attribute analysis, relevant optimization, and drilling implementation” can effectively improve the prediction accuracy of thin interbedded sand bodies and greatly reduce the risk of oilfield exploration and development.
Key words: thin interbedded sand body / Seismic attributes / Forward simulation / Attribute optimization / Reservoir prediction
© The Authors, published by EDP Sciences, 2024
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.