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Subsurface parameter reconstruction using full waveform inversion is highly nonlinear with nonunique solutions. When the initial model with high precision is missing, the cycle skipping problem will be encountered, especially for the strong scattering media like salt structures. In order to adapt to the inversion of strong scattering media, direct envelope inversion (DEI) using directly the envelope Fréchet derivatives was proposed to avoid the weakly nonlinear assumption for the model updating. In the original DEI method, the envelope polarity is not considered. To further improve the effectiveness of DEI, signed envelope inversion with polarity detection can be used. In this work, we develop a new polarity detection technique on the basis of seismic attributes, which can provide more accurate polarity information for the seismic envelope. Based on the above technique, the new multi-scale signed DEI method is proposed. The new technique is applied to the SEG/EAGE salt model. The numerical examples verified the effectiveness of this method. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Salt structures are high potential targets for oil and gas exploration. However, large-scale salt domes with irregular surfaces pose significant challenges for velocity model building. For full waveform inversion, in the absence of a high-fidelity initial model, the success of the inversion depends on low-frequency seismic data, which are scarce in the exploration data sets. This paper presents a new idea to solve the problem of salt structure velocity modelling. First, we propose an envelope-based full-band seismic data reconstruction algorithm. The smoothness of envelope is used to segment the events in seismic data, and the phase independence of envelope is used for the identification of the seismic event's arrival-time to obtain the apparent reflection sequences of the subsurface. Full-band seismic data are obtained by convolving the apparent reflection sequence with full-band source. Window averaging function and threshold strategy are used to ensure the accuracy of seismic event segmentation and the stability of the algorithm when dealing with noisy data. Then the multiscale reflection waveform inversion based on reconstructed data is proposed for salt structure velocity building. The numerical experiment results of the Sigbee2A model demonstrate the performance of the inversion algorithm in the case where the seismic data lack low-frequency components and contain noise. The limitations of the algorithm have also been analysed and studied. [ABSTRACT FROM AUTHOR]