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Multi-trace nonstationary sparse inversion with structural constraints

Cheng Liang, Wang Shangxu, Li Shengjun, Ji Yongzhen

Acta Geophysica

2020

Vol. 68, no. 3

675--685

The recorded seismic signals are attenuated and spatially correlated due to their propagation through an elastic earth and the sedimentary rule of strata. This attenuation phenomenon is quantifed by means of the earth quality factor (Q) or the attenuation factor (1∕Q). Nowadays, the related Q-compensation and multi-trace inversion for the seismic data are two challenging problems when used for enhancing the temporal resolution and preserving the spatial continuity. Separately estimating Q and refectivity are difcult and produce the uncertainty or ill-condition problems. To overcome these limitations, we have developed a multi-trace nonstationary sparse inversion with structural constraint. Using prior dipping-angle information and refectivity sparsity property, the proposed method simultaneously estimates equivalent-Q and refectivity with structural constraint. Constructed by the source wavelet and diferent scanned equivalent-Q, a series of time-varying (nonstationary) wavelet matrices are provided for the forward-modeling schemes and the corresponding inversions. When the Q-model is infnitely close to the true attenuation mechanism, the corresponding inverted refectivity is comparatively sparse and quantifed as maximum sparsity or minimum sparse representation. A sparse representation function, such as l0.1-norm, is used for sparsity measurement of the inverted refectivity corresponding to each scanned Q. Through optimizing these sparse representation values, a suitable equivalent-Q, as well as the corresponding inverted refectivity with structural preservation and Q-attenuation, is determined. The synthetic and feld examples both confrmed a substantial improvement on seismic records, especially for Q-estimation, structure preservation and Q-compensation.

Modelling spatial variation of extreme precipitation over Ho Chi Minh City under nonstationary conditio

Binh Le Thi Hoa, Agilan V., Umamahesh N. V., Rathnam E. V.

Acta Geophysica

2019

Vol. 67, no. 3

849--861

Understanding the magnitude and spatial variation of extreme rainfall events are required for decision making and adaptation strategies for flood risk. In Ho Chi Minh City (HCMC), heavy rainfall, which is considered as a main cause of floods, witnessed an increase in frequency and magnitude in last few decades. Although nonstationarity in extreme rainfall has been proved in many places of the world, research into nonstationarity feature in extreme rainfall in HCMC has not been paid attention thoroughly. In this study, the spatial variation of extreme precipitation over Ho Chi Minh City is modelled under nonstationary condition. The generalized extreme value (GEV) distribution with location made a nonlinear function of time is applied to annual maximum daily rainfall. The study results show that the nonstationary GEV model is found to be superior in capturing extreme precipitation events when compared to the stationary GEV model. The extreme rainfall estimates under the stationary condition are lower than those under the nonstationary condition in most stations. Besides, the spatial variation of extreme rainfall under nonstationary condition shows a significant difference in extreme estimates between the periods of 1980–1984 and 2010–2014 in study area.