In hydrocarbon exploration, seismic data collected in the field inevitably encounter noise interference, which subsequently affects the data processing and interpretation. Recently, deep learning methods have gained widespread popularity in seismic denoising. Among these methods, the U-Net has shown some potential, but its performance in complex noise suppression needs further improvement due to the limitations of the U-Net structure. Moreover, the majority of existing noise suppression methods primarily focus on synthetic noises with single characteristics, such as Gaussian random noise and linear interference. To devise methods that can effectively suppress more intricate field noise, this article proposes a novel noise suppression method based on an encoder–decoder architecture called multiscale channel attention Swin Conv U-Net. Notably, it enhances the U-Net through the integration of the following two modules: 1) Swin-Conv block (SCB), which replaces the convolution operation of U-Net and integrates the nonlocal modeling ability of Swin Transformer (SwinT) and the local modeling ability of residual connection convolution layers to achieve multidimensional feature extraction, and 2) multiscale channel attention block (MCAB), which replaces skip connection modules between the encoder and the decoder in the U-Net with multichannel feature fusion to capture more complex channel dependencies. This article evaluates the proposed algorithm on both synthetic and field seismic data and compares the results with several established denoising methods. Our algorithm enhances the network’s noise perception capabilities and improves signal-to-noise ratio (SNR) and structural similarity index measure (SSIM) of seismic data. Finally, a concise discussion on the limitations of our method and potential avenues for enhancement is provided.

Building high-fidelity velocity models for salt structures is a valuable and difficult problem in seismic exploration. Acoustic-based full-waveform inversion (FWI) methods usually produce velocity artifacts around high-contrast interfaces due to the generation of converted waves. Therefore, elastic FWI (EFWI) should be used in salt model velocity building. Two problems that restrict EFWI are: lack of low-frequency seismic data and multiparameter coupling. For the first problem, envelope is a good choice because of its ability to reconstruct low-frequency components independent of the frequency range of seismic data. However, envelope is instantaneous energy flow and lacks polarity information, while the elastic waves are vectors. Thus, the direct use of envelope to reconstruct the low-frequency components of elastic waves causes serious artificial artifacts in envelope inversion. Therefore, we introduce signed demodulation and window average function to obtain the multiscale (MS) envelope with polarity, defined as the MS signed envelope to reconstruct low-frequency elastic data. The reconstructed low-frequency data are then used in EFWI, and an elastic MS signed direct envelope inversion algorithm is proposed. For the second problem, wave mode decomposition and hierarchical inversion strategies are integrated into the inversion to eliminate the multiparameter coupling effect. A salt layer model and BP model are used to verify the effectiveness of the algorithm. Finally, the deficiencies in the research of this article and further improvement plans are also discussed.

For the full‐waveform inversion, obtaining a globally optimal solution is difficult when the seismic data do not contain sufficient low‐frequency information and the inversion object is a salt structure with a large‐scale salt dome. The large salt dome presents difficulty for the inversion of the salt structure; however, it also confers a convenience that can be utilized: A large salt dome makes the events in the seismic record sparse and isolated. We use the envelope to obtain the arrival time of the events in the seismic data and apply multiscale strategies to extract the low‐frequency information of the seismic data that relates to the long‐wavelength components of the subsurface. In calculating the gradient, the envelope Fréchet derivative is used to take advantage of the multiscale envelope for the characteristics of the salt structure. Therefore, the multiscale direct envelope inversion using the window‐averaged envelope and the direct envelope Fréchet derivative is proposed. To further improve the computational efficiency and inversion quality of the multiscale direct envelope inversion, several auxiliary strategies are proposed: A joint misfit function is designed to make the inversion method more adaptable, and an offset weighting factor is introduced to implement the multioffset inversion method to improve the inversion quality of subsalt. We analyze the antinoise performance of the multiscale direct envelope inversion. The SEG/EAGE salt model is used to test the application effect of the multiscale direct envelope inversion. The antinoise ability and insensitivity to low‐frequency data of the method are verified in the numerical experiments.

For full-waveform inversion (FWI), building the salt structure velocity model is a challenging problem. In the absence of a high-fidelity initial model, low-frequency seismic data are indispensable for accurate reconstruction of the long-wavelength components of salt domes, which are often missing in field data. The envelope isolates the amplitude information from the seismic data and has a stronger linear relationship with the velocity than the seismic data. It is used to enhance the convexity of the objective function in an envelope inversion (EI). However, the properties of the envelope are not effectively utilized in EI due to the lack of their proper understanding. In order to solve the problems that EI has in building the salt structure velocity, such as the cycle-skipping problem, the gradient calculation problem caused by the waveform Fréchet derivative, and the multisolution problem caused by the missing polarity information of the envelope, we propose a multiscale direct signed EI (MSDSEI) based on the direct envelope Fréchet derivative and multiscale signed envelope. The development process from EI to MSDSEI also inspired us to understand the physical mechanism involved in the low-frequency components of the envelope: the signed envelope can be regarded as a low-pass filter of the reflection sequences in the subsurface. Thus, we use the smoothness and phase-independent properties of the envelope to propose an envelope-based full-band seismic data reconstruction method for multiscale FWI. Finally, the performance of various EI methods is verified on the Sigsbee2A model.

Full waveform inversion is often troubled by falling into a local minimum due to cycle-skipping problem when missing low-frequency seismic data. According to the dynamics of seismic waves, the travel-time information will not change due to the variation in the frequency band of seismic data, which is the working mechanism of travel-time inversion. However, the current travel-time inversion method often requires various assumptions for the convenience of calculation, resulting in limited inversion effects. We present a novel velocity building method based on travel-time information. First, we use the sparse-constrained deconvolution (SCD) to convert travel-time information of seismic data into reflection sequences, which greatly reduces the complexity of the travel-time inversion. Then, the phase-independent characteristic of the envelope is introduced into the SCD to deal with the phase shift of the seismic wave. The combination of SCD and envelope greatly improves the reconstruction accuracy of the reflection sequences. Finally, the reconstructed reflection sequences are convolved with the full-band source wavelet to obtain full-band seismic data, and thus, the envelope-based SCD (E-SCD) inversion method is proposed. The results of numerical experiments on the partial basic tracking (BP) model and SEG/EAGE overthrust model verify the performance of the E-SCD inversion method. The limitations of the method and the direction of future development are also briefly discussed.