@article{Wang2026, 
author = {Si-Yuan Wang and Ying Hu and Xu-Ping Chen and Hui Chen},
title = {The energy-concentrated transform for gas-bearing reservoir identification},
year = {2026},
journal = {Petroleum Science},
volume = {23},
number = {10},
pages = {6174-6187},
keywords = {Seismic signal, Time-frequency analysis, Energy-concentrated transform, Gas-bearing reservoirs},
url = {https://www.sciopen.com/article/10.1016/j.petsci.2026.05.013},
doi = {10.1016/j.petsci.2026.05.013},
abstract = {Identifying gas-bearing reservoirs remains challenging in seismic exploration because the time-frequency (TF) response of seismic signals is often complex and difficult to interpret. Newly developed TF post-processing methods enhance the energy concentration of traditional TF spectra, yielding a peak-shaped TF representation. However, such a representation may overlook the inherent time-width and bandwidth of seismic wavelets, limiting a comprehensive characterization of abnormal TF responses. To address this issue, this paper proposes an energy-concentrated transform (ECT) within the Wigner-Ville distribution framework. The ECT uses the second-order central moments of the local energy distribution to concentrate the diffused energy into the relevant TF interval, rather than reassigning the energy to the centroid as existing TF post-processing methods do. This approach not only concentrates the diffuse TF energy but also preserves essential time-width and bandwidth features important for geological interpretation. Its theoretical foundation is validated, demonstrating consistency with the Morlet wavelet spectrum. Numerical tests show that the ECT exhibits low sensitivity to window length and has strong noise robustness. Furthermore, field seismic data indicate that the ECT provides a clearer TF distribution, enabling the reliable identification of gas-bearing reservoirs.}
}