Yikang Zheng

Deblending using a high-resolution radon transform in a common midpoint domain

The advantages of simultaneous sources acquisition are weakened by blended noise. Many conventional filtering methods are ineffective due to the existence of coherent blended noise in common shot gather (CSG). However, the coherent interference appears to be incoherent in a common midpoint (CMP) domain. In light of this characteristic, we propose a high-resolution radon transform based deblending approach. There are four steps for the implementation: (1) transform the original data from a CSG domain to a CMP domain; (2) apply the high-resolution radon transform to CMP gather to obtain the radon spectrum; (3) filter the radon spectrum with iterative threshold method; (4) transform the filtered data from the radon domain back to time spatial domain. The key step of the proposed method is to obtain the high-resolution radon spectrum to which the threshold filtering is applied. We give synthetic and field data examples to show the effectiveness of our approach.

Wave-equation traveltime inversion: Comparison of three numerical optimization methods

Compared to traditional traveltime inversion methods, no traveltime picking, high-frequency assumption or ray tracing is necessary in wave-equation traveltime inversion (WT). Another merit of WT is that it is insensitive to the starting model. Although WT offers less detailed parts of velocity model than the full waveform inversion (FWI), it can provide a good initial velocity model for FWI. In this paper, the steepest descent, conjugate gradient and limited-memory BFGS (L-BFGS) optimization methods are used in the implementation of acoustic WT. We use synthetic crosswell data for testing and the numerical results show that L-BFGS has a faster rate of convergence and offers a reconstructed velocity model with better resolution compared to the other two gradient methods.

Full Waveform Inversion Using Free-Surface Related Multiples as Natural Blended Sources

To improve the computational speed of conventional full waveform inversion (FWI), we propose a new FWI method which uses free-surface related multiples as natural blended sources and name it as NBFWI. The proposed method contains four key steps: 1. at selected source locations, forward propagate synthetic wavelet to generate calculated shot records containing both primaries and free-surface related multiples; 2. Compared with recorded field data to obtain waveform residuals; 3. backward propagate waveform residuals and forward propagate recorded field data to produce gradient; 4. use steep descent method or other optimization methods for velocity updating. Compared with other blended sources methods, the NBFWI method has no need of implementing phase encoding algorithms and the free-surface related multiples act as natural blended sources. A Marmousi velocity model is used for numerical tests. The numerical results show how accurate, efficient and stable the proposed approach is when using different number of shot gathers for inversion. Because of the utilization of wide coverage characteristics of free-surface related multiples, the inversion procedure has good convergence even using very few shots. The proposed approach is easy to implement and maybe significant for both fast velocity model building and inversion of sparse acquisition data.

Eliminating artifacts in migration of surface-related multiples: An application to marine data

AbstractMigration of multiples can use surface-related multiples to provide extra illumination of the subsurface; however, the migrated images usually contain many migration artifacts. We have developed an efficient workflow to eliminate the artifacts in migration of surface-related multiples and applied it to marine data. Our workflow was based on the criterion that true seismic events in angle-domain common-image gathers (ADCIGs) should be flat. The ADCIGs were obtained via the one-way wave-equation migration and then processed by high-resolution parabolic Radon transform to separate the artifacts. Using the adjoint Radon transform, the filtered ADCIGs can be stacked to get the final image with a high signal-to-noise ratio. We also discovered that the ADCIGs can be extracted from Fourier finite-difference migration more efficiently than by reverse time migration. In the application to marine data, most noise generated by the crosscorrelation of undesired seismic events was suppressed. This shows that th...

An application of full-waveform inversion to land data using the pseudo-Hessian matrix

AbstractFull-waveform inversion (FWI) is used to estimate the near-surface velocity field by minimizing the difference between synthetic and observed data iteratively. We apply this method to a data set collected on land. A multiscale strategy is used to overcome the local minima problem and the cycle-skipping phenomenon. Another obstacle in this application is the slow convergence rate. The inverse Hessian can enhance the poorly blurred gradient in FWI, but obtaining the full Hessian matrix needs intensive computation cost; thus, we have developed an efficient method aimed at the pseudo-Hessian in the time domain. The gradient in our FWI workflow is preconditioned with the obtained pseudo-Hessian and a synthetic example verifies its effectiveness in reducing computational cost. We then apply the workflow on the land data set, and the inverted velocity model is better resolved compared with traveltime tomography. The image and angle gathers we get from the inversion result indicate more detailed informati...