Registering multiscan terrestrial laser scanning (TLS) data is a prerequisite for applying TLS in precision forestry. Marker-free automatic registration methods based on tree attributes or stem positions have been considered promising solutions. However, tree attribute–based methods rely heavily on accurate data preprocessing, while stem-based methods are often sensitive to parameter settings. We propose an automatic, robust, and efficient marker-free registration method (StemReg). Our approach first extracts stem candidates using a density-adaptive RANSAC algorithm tailored to local point densities, followed by a visibility check to eliminate occluded stems. Stem correspondences between scans are then established based on spatial configuration, and the registration transformation is estimated accordingly. Experiments conducted on multiple plots with diverse vegetation structures demonstrate that StemReg achieves registration accuracy comparable to that of manual methods, with an average mean deviation (MD) difference of only 0.8 cm across all test plots. Compared to state-of-the-art stem-based methods, the proposed approach retains comparable effectiveness while enhancing robustness and extending applicability to more complex forest environments. Our method is expected to provide reliable support for the application of TLS in large-scale forestry research.

Affected by the low-frequency seismic data missing and multiple parameters coupling, elastic full waveform inversion is easy to fall into local minima. This paper attempts to solve the local minima problem from two aspects: low-frequency seismic data reconstruction and wave mode decomposition. First, by introducing the envelope into sparse constrained deconvolution, an envelope-based sparse constrained deconvolution method is proposed to overcome the problem caused by the phase shift and side lobes. However, the resolution of the envelope is insufficient to identify overlapping seismic events, which are generated by velocity models rich in thin layers. Therefore, sparse constrained deconvolution and envelope-based sparse constrained deconvolution are combined, and a dual deconvolution method is proposed: sparse constrained deconvolution is used to improve the resolution of the original seismic data, then envelope-based sparse constrained deconvolution is used to reconstruct high-precision reflection sequence. Convolve the reconstructed reflection sequence with the full-band source wavelet to obtain the full-band seismic data. Secondly, for the multi-parameter coupling problem, we use wave mode decomposition to obtain separated P- and S-wave. Finally, a multi-scale elastic full waveform inversion method based on dual deconvolution and wave mode decomposition is proposed. Numerical experiment results demonstrate the algorithm proposed in the article.

Faults, fractures, karst caves, and other small-scale geological targets are critical for carbonate oil and gas exploration. However, seismic responses of these small-scale geological targets are low-energy diffractions and it is difficult for traditional method to image them with high resolution. To identify these targets, the diffraction separation is a key technology. Based on the difference of diffractions and reflections in both kinematic and dynamic properties, the singular value decomposition (SVD) method can separate diffractions and reflections effectively. However, how to select the appropriate singular value sequence for diffractions and reflections is a key issue in the application. Based on the analysis of the singular value spectrum characteristics, we propose a second-order difference spectrum strategy to improve the SVD method. The improved SVD method can separate the diffractions and reflections with minimal error. It is stable when seismic data contain Gaussian noise. Reverse time migration (RTM) method is used in the diffraction imaging because it can keep the true shape of subsurface scatterers when diffractions information is complete. Synthetic examples demonstrate the effectiveness of this method.

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.

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 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.