4.7 Article

Detecting Shallow Gas Reservoir in the F3 Block, the Netherlands, Using Offshore Seismic Data and High-Resolution Multi-Synchrosqueezing Transform

Journal

NATURAL RESOURCES RESEARCH
Volume 32, Issue 5, Pages 2007-2035

Publisher

SPRINGER
DOI: 10.1007/s11053-023-10229-w

Keywords

Multi-synchrosqueezing transform; Time-frequency analysis; Low-frequency shadow; Seismic data; F3 block

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The presence of natural gas reserves is often associated with the observation of a low-frequency shadow phenomenon in seismic signals. A high-resolution time-frequency transform called multi-synchrosqueezing transform (MSST) is introduced in this research to accurately recover the non-stationary signal and identify low-frequency shadows. Synthetic seismic data and real 3D seismic data from the North Sea were used to demonstrate the effectiveness of the proposed method in locating shallow gas reservoirs accurately.
The presence of natural gas reserves is correlated frequently with the observation of a shadow with low frequency. The phenomenon known as low-frequency shadow describes a decrease in seismic frequencies measured from reflectors located immediately beneath a reservoir horizon. As a result of the non-stationary character of seismic signals, methods of time-frequency (TF) analysis are able to identify low-frequency shadows. This research introduces a recently created high-resolution TF transform that can evaluate a non-stationary signal in a stepwise reassignment operation while recovering the signal with sufficient accuracy. The proposed technique is termed multi-synchrosqueezing transform (MSST), which examines the signal iteratively using the synchrosqueezing transform (SST). To show the utility of the recommended TF analysis approach, we first described its algorithm through the use of various examples and then applied it to synthetic seismic data. The outcomes revealed that it could generate a sparser TF map than other conventional methods. To assess the effectiveness of the proposed MSST method on real seismic data and find shallow gas reservoirs, we applied it to 3D seismic data from the F3 block, which is located in the North Sea in the Netherlands. It is concluded that the proposed method has great potential to discover the precise location of a shallow gas reservoir.

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