A5101778437- Seismic Imaging and Inversion Techniques
- Seismic Waves and Analysis
- Hydraulic Fracturing and Reservoir Analysis
- Drilling and Well Engineering
- Geological Modeling and Analysis
- Geophysical Methods and Applications
- Groundwater flow and contamination studies
- Sparse and Compressive Sensing Techniques
- Groundwater and Isotope Geochemistry
- Image and Signal Denoising Methods
China Coal Technology and Engineering Group Corp (China)
2024
Ministry of Ecology and Environment
2021
China University of Geosciences
2021
China University of Petroleum, Beijing
2016
Most existing amplitude variation with offset (AVO) inversion methods are based on the Zoeppritz’s equation or its approximations. These assume that of seismic data depends only reflection coefficients, which means wave-propagation effects, such as geometric spreading, attenuation, transmission loss, and multiples, have been fully corrected attenuated before inversion. However, these requirements very strict can hardly be satisfied. Under a 1D assumption, reflectivity-method-based inversions...
Many oil fields in the world are continental clastic facies lake basins, which develop many thin interbedded reservoirs. Conventional AVO inversion methods based on Zoeppritz equation not suitable for identification and characterisation of such In this study, we propose a new method vectorised reflectivity with blockiness constraint order to obtain results high accuracy resolution. The can provide 1D analytical solution elastic wave equation, simulate full-wave field. Therefore, it overcomes...
The reflection coefficient inversion algorithm based on compressed sensing mainly includes monopole matching pursuit seismic wavelet, bipole inversion, quadrupole and basis L1-2 norm constraints. wavelet requires a long time its resolution is limited, so tracking constraint proposed the of algorithm. reliability advancement are verified by comparing two-dimensional model, applied to processing interpretation data, results show that this method can reverse formation effectively predict...