Multichannel seismic impedance inversion driven by logging–seismic data

• Autorzy: Li Xinyu , Wang Yaojun , Liu Yu , Cai Hanpeng

Identyfikatory

DOI

10.1007/s11600-021-00687-2

• Języki publikacji: EN

Abstrakty

EN

The prior information constrained impedance inversion is an important tool to improve the inversion effect. With the traditional constrained prior information extracted from logging data by the analytic formula, it is difficult to accurately describe the information of a complex reservoir. In addition, the traditional inversion method is trace-by-trace, which ignores the lateral information contained in seismic data. This paper presents a multichannel seismic impedance inversion method combining logging and seismic. In this method, the dictionary learning method is used to extract the vertical prior information of the formation from the logging data. At the same time, we can learn the dip information from seismic data cube. Under the framework of multichannel inversion, regularization and sparse representation technology are used to simultaneously add the vertical and the transverse distribution prior information into the inversion process. Block coordinate descent method is used to solve the multichannel inversion problem, making the seismic inversion efficient. This method excavates the spatial prior information in a data-driven way and is used for constrained inversion, avoiding the false prior cognition caused by manual interpretation. Through the model and field data testing, it is verified that this method is effective.

Słowa kluczowe

EN

well logging; seismic data collaboration; dictionary learning; sparse representation; multichannel impedance inversion; data driven

PL

geofizyka otworowa; współpraca w zakresie danych sejsmicznych; nauka słownika; rzadka reprezentacja sygnału

• Wydawca: Instytut Geofizyki PAN ; Springer
• Czasopismo: Acta Geophysica
• Rocznik: 2021
• Tom: Vol. 69, no. 6
• Strony: 2261--2274
• Opis fizyczny: Bibliogr. 20 poz.

Twórcy

autor

Li Xinyu

• Research Institute of Petroleum Exploration and Development (RIPED), CNPC, Beijing, China

autor

Wang Yaojun

• School of Resources and Environment, University of Electronic Science and Technology of China, Chengdu, China

• https://orcid.org/0000-0001-9079-0840

autor

Liu Yu

• School of Resources and Environment, University of Electronic Science and Technology of China, Chengdu, China

autor

Cai Hanpeng

• School of Computer, Jiangxi University of Traditional Chinese Medicine, Nanchang, China

Bibliografia

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