Recent advancements in seismic monitoring techniques are poised to enhance the energy sector’s ability to track subsurface changes, particularly in oil and gas reservoirs. A study led by Fengying Chen from the School of Geophysics and Information Technology at the China University of Geosciences (Beijing) has introduced a novel approach to non-repetitive time-shifted seismic monitoring using data from ocean bottom cables (OBC) and towed streamers.
Traditionally, seismic monitoring relied on repeated data collection at the same locations to observe changes in subsurface fluid dynamics during oil and gas extraction. However, this method can be costly and time-consuming. Chen’s study, published in the Journal of Marine Science and Engineering, explores the effectiveness of using two non-repetitive data sets acquired under different conditions, thus offering a more cost-effective alternative for monitoring subsurface changes.
The research focuses on normalizing various seismic attributes such as amplitude, frequency, and wavelet to ensure consistency between the two data sets. This normalization is crucial for accurately comparing seismic data over time, especially when monitoring changes in gas-water interfaces and distribution due to mining activities. Chen notes, “After consistency processing, the OBC and towed streamer data were suitable for time-shifted seismic monitoring research, providing a reliable foundation for future, non-repetitive, time-shifted seismic comparison studies.”
One of the key findings of this research is the superiority of the data reconstruction method in normalizing seismic geometry parameters. This method allows for a more accurate analysis of the changes in subsurface conditions, which can significantly impact reservoir management and optimization. The study demonstrated that the amplitude attribute ratio method offers a more effective means of evaluating time-shifted changes compared to other methods.
For the energy sector, these findings present substantial commercial opportunities. Enhanced seismic monitoring can lead to better reservoir management, improved accuracy in predicting remaining oil and gas reserves, and optimized extraction strategies. Moreover, the methodology developed in this research could also be applied to carbon capture and storage (CCS) technologies, aiding in the monitoring of carbon dioxide injection and storage in geological formations.
As the energy industry continues to seek more efficient and sustainable practices, the insights gained from Chen’s research could play a pivotal role in shaping future seismic monitoring technologies. The ability to effectively monitor subsurface changes without the need for repetitive data acquisition not only reduces costs but also enhances the overall understanding of reservoir dynamics, which is critical for maximizing resource recovery and minimizing environmental impacts.
