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P-Impedance and Vp/Vs prediction based on AVO inversion scheme with deep feedforward neural network: a case study from tight sandstone reservoir

Mao Xinjun, Han Xuehui, Wu Baohai, Wang Zhenlin, Zhang Hao, Wang Hongliang

Acta Geophysica

2022

Vol. 70, no 2

563--580

The low-frequency component of seismic data is an inevitable part to obtain absolute P-impedance (Ip) and Vp∕Vs ratio of the subsurface, especially for the reservoir sweet spot. In this work, we train the deep feedforward neural network (DFNN) with band-pass seismic data and well log data to obtain favorable low-frequency components. Specifically, the Bayesian inference strategy is first applied to the pre-stack constrained sparse spike inversion process, obtaining an “initial” inverted band-pass parameters, which are subsequently used as input when applying the DFNN algorithm to predict low- and bandpass parameters. Moreover, the high linear correlation coefficient between the DFNN-based inversion results and the realistic well logging curves of the blind wells demonstrates that the DFNN-based inversion scheme exhibits strong robustness and good generalization ability. Ultimately, we apply the proposed DFNN-based inversion strategy to a tight sandstone reservoir located at the Sichuan basin field from onshore China. Both low- and band-pass Ip and Vp∕Vs inverted for the clastic formation of the Sichuan basin show a strong correlation with the corresponding Ip and Vp∕Vs logs.

An Amplitude-normalized Pseudo Well-log Construction Method and its Application on AVO Inversion in a Well-absent Marine Area

Fan Ch., Song Y., Zhang Y., Jiang Z.

Acta Geophysica

2015

Vol. 63, no. 3

761--775

AVO inversion is hard to be efficiently applied in unexploited fields due to the insufficiency of well information. For the sake of AVO inversion in a well-absent area, the most conventional method is to construct pseudo well-logs by defining seismic processing velocity as the P-velocity and computing S-velocity and density using empirical formulas, yet the resolution of the corresponding earth models and final inverted results could be extremely low, and a rough formula could destroy the inversion thoroughly. To overcome this problem, an amplitudenormalized pseudo well-log construction method that reconstructs pseudo well-logs in accordance with computed P-wave reflection amplitudes and nearby drilling data is proposed in this paper. It enhances the inversion resolution efficiently with respect to the real elastic parameter relationships, so that the corresponding AVO inversion results are reasonably improved. In summary, the proposed method is successfully applied in the AVO inversion of a well-absent marine area, and could be valuable in the early phase, particularly of the offshore hydrocarbon exploration.