Open AccessHigh resolution analysis based on deconvolution and matching pursuit
Author(s) -
Huajun Sun,
Qiong Li
Publication year - 2021
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/671/1/012020
Subject(s) - deconvolution , matching pursuit , computer science , blind deconvolution , signal (programming language) , matching (statistics) , time–frequency analysis , process (computing) , basis pursuit , reflection (computer programming) , signal processing , algorithm , a priori and a posteriori , data processing , data mining , artificial intelligence , computer vision , mathematics , compressed sensing , statistics , telecommunications , filter (signal processing) , programming language , operating system , radar , philosophy , epistemology
The complexity of seismic exploration targets makes the exploration process more difficult and requires higher resolution of seismic data. Singular Methodology (inverse Q filtering, spectrum shaping, etc.) is limited in improving the resolution of seismic data and cannot meet the requirements of data interpretation. In this regard, combining time-varying frequency division deconvolution and matching pursuit (MP) methods, first perform time varying frequency division deconvolution processing on the original signal, and then use matching pursuit to remove the strong reflection seismic event and reconstruct the signal. Which can reflect the characteristics of reservoirs. By testing analog signals, deconvolution and matching pursuit methods improve the signal resolution. In the actual seismic data analysis, the comprehensive use of several methods can better identify the distribution characteristics of the effective tight carbonate reservoirs, and correspond well with the actual geological structure and drilling data. Which also provides a reference basis for further capacity analysis.