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2 Acta Geophysica

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Combining the synchrosqueezing generalized S-transform of variational mode decomposition with the Teager-Kaiser energy operator to calculate the attenuation gradient for identifying oil and gas reservoirs

Yan Haitao, Zhou Huailai, Wang Yuanjun, Wu Nanke, Zhou Wei, Zhou Jie

Acta Geophysica

2023

Vol. 71, no. 2

795--812

Because of the limited resolution of conventional time–frequency analysis algorithms, they are also limited to calculate attenuation gradients that describe oil and gas reservoirs. We propose an advanced method for calculating the attenuation gradient that combines the synchrosqueezing generalized S-transform of variational mode decomposition with the Teager–Kaiser energy operator. SSVGST takes advantage of the synchrosqueezing generalized S-transform to focus the longitudinal resolution of the time–frequency domain and variational mode decomposition for adaptive signal segmentation in the frequency domain. Thus, SSVGST can be used to improve the time–frequency resolution of seismic signals, and the Teager–Kaiser energy operator is used to enhance the extracted attenuation gradient and highlight oil and gas regions effectively. The time–frequency focusing ability of SSVGST was verified by using a synthetic signal and theoretical model. Experimental results with the model and field data showed that the combination of SSVGST with the Teager–Kaiser energy operator suppressed the fuzzy energy caused by the low resolution of conventional time–frequency analysis algorithms and could locate reservoirs accurately and effectively.

High-resolution reflectivity inversion based on joint sparse representation

Shi Zhanzhan, Zhou Huailai, Wang Yuanjun, Niu Cong, Huang Rao

Acta Geophysica

2019

Vol. 67, no. 6

1535--1550

High-resolution reflectivity inversion is termed as a fundamental yet essential step for the prediction of thin-bedded hydrocarbon reservoirs. However, algorithms suffer from two key issues: (1) seismic inversion is an ill-posed problem that has multiple solutions, and the results of trace-by-trace seismic inversion are quite poor in lateral continuity, and (2) algorithm stability is likely to be decreased owing to the noise and distortion associated with the acquisition and processing flows. In the current article, we formulate a new joint sparse representation through the combination with L2,1- norm misfit function, which possesses superior noise robustness, in particular in the presence of outliers. On the basis of the L2,1- norm regularization, this specific approach enforces a common sparsity profile, together with consistently lowering the multiplicity of solution. Subsequent to that, the resultant algorithm is applied to the multi-trace seismic inversion. Besides, the wedge model trial and practical applications suggest that the proposed inversion algorithm is stable, in addition to having good noise robustness and lateral continuity; moreover, the vertical resolution of λ/8 is realized under the noise and outliers interference. The logging data calibration illustrates that the proposed methodology is accurate and credible.