A5101815143- Seismic Imaging and Inversion Techniques
- Drilling and Well Engineering
- Seismic Waves and Analysis
- Image and Signal Denoising Methods
- Hydraulic Fracturing and Reservoir Analysis
- Machine Fault Diagnosis Techniques
China National Petroleum Corporation (China)
2023
Time-frequency analysis (TFA) is widely used to describe local time-frequency (TF) features of seismic data. Among the commonly TFA tools, sparse (STFA) an excellent one, which can obtain a TF spectrum with good readability. However, many STFA algorithms suffer from expensive calculation time and unavoidable prior knowledge, such as iterative shrinkage-thresholding algorithm (ISTA) reconstruction by separable approximation (SpaRSA). Inspired unrolled its successful applications in signal...
The stratigraphic correlation of well logs is crucial for characterizing subsurface reservoirs. However, due to the complexity and huge amount data, manual time- resource-intensive. Hence, various computerized methods have been developed, especially regarding convolutional neural networks (CNNs). Recently, Transformer, a self-attention system that evolved from Natural Language Processing (NLP), has attained state-of-the-art performance over CNNs in variety domains because its ability...
Time-frequency (TF) analysis is commonly used to reveal the local properties of seismic signals, such as frequency and spectral contents varying with time/depth. Aiming realize a highly localized TF representation researchers treated an inverse problem, regularization adopted in objective functions. Traditionally, sparse inversion process solved by Lasso regression. It has been proven that regression needs large number iterations reach high accurate solution for convex problem. Recently,...