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Summary We present a microseismic location method using genetic algorithm full waveform inversion (GAFWI). This method not only considers the travel time of microseismic wavefield, but also uses full waveform information, such as amplitude, frequency, primaries, multiples, etc. With GAFWI, we do not need to pick up the first arrival time or give a good initial position. We should only provide an approximate velocity model and a time window that contains the microseismic event. We discuss the effects of velocity perturbation and noises on location results. When the source wavelet is uncertain, we try to match the observed wavefields using Ricker wavelet wavefields. We also discuss the calculation efficiency of this method, and find that parallel and FDFD are two potential methods. In a complex numerical example, we obtain an approximate right position using GAFWI, but the starting time is with some error. Overall, our method can give good results for microseismic location. Introduction Until now, most of the methods for microseismic location only use the travel time of microseismic wavefields to calculate the location, such as double difference method (Tian, 2014). We consider the full waveform information of microseismic wavefield, and solve the location and time by Genetic Algorithm Full Waveform Inversion (GAFWI). Full Waveform Inversion (FWI) uses calculated wavefields to match observed wavefields, and updates the model parameters gradually during the matching process (Virieux, 2009; Zhang, 2014). FWI matches not only travel time, amplitude and frequency, but also full waveform information, such as direct waves, primaries and multiples. With GAFWI, we do not need to pick up the first arrival time. What we need are an approximate velocity model and a time window that contains the microseismic event. When considering real microseismic data, we should deal with many problems, such as the inaccuracy of velocity model, noises in original recordings, the unknown of wavelet and the calculation efficiency. After presenting the fundamentals of GAFWI, we discuss the above problems respectively and show the location results using our method. Finally, we test our method in a complex example.
Summary We apply interferometric theory to solve a 3D seismic residual statics problem that helps to improve reflection imaging. The approach can calculate the statics solutions without picking the first arrivals in shot or receiver gathers. The statics accuracy can be improved significantly since we utilize stacked virtual refraction gathers for calculation. Because sources and receivers can be placed at any position in a 3D seismic survey, the arrival times of virtual refractions for a pair of receivers or sources are no longer the same as in a 2D case. To overcome this problem, we apply 3D Super-Virtual Interferometry (SVI) method in the residual statics calculation. The virtual refraction for the stationary source-receiver pair is obtained by an integral along source or receiver line without the requirement of knowing the stationary locations. Picking the maxenergy times on the SVI stacks followed by applying a set of equations is able to derive reliable residual statics solutions. We demonstrate the approach by applying to synthetic data as well as real data. Introduction Rugged topography and complex near surface layers are some of the important challenges that we are facing in seismic data processing today. Residual statics due to near-surface velocity variations may not be able to be resolved through the near-surface model imaging, but critical for seismic data processing. There are many methods to calculate residual statics solutions, such as reflection stack-power maximization method (Ronen and Claerbout, 1985), refraction waveform residual statics (Hatherly et al., 1994), and refraction traveltime residual statics (Zhu and Luo, 2004). For refraction methods, the accuracy of the refraction static correction largely depends on the quality of the first arrival traveltimes. However, seismic amplitudes at far offsets are often too weak to pick. To overcome this problem, the theory of Super-Virtual Interferometry (SVI) is developed to generate headwave arrivals with improved SNR (Bharadwaj and Schuster, 2010). The SVI method is later used to calculate 2D residual statics solutions without picking first arrivals (Zhang et al., 2014). In this study, we follow Lu et al. (2014) to extend SVI to 3D and apply that to solve a 3D residual statics problem.
- Geophysics > Seismic Surveying > Seismic Processing (1.00)
- Geophysics > Seismic Surveying > Seismic Modeling > Velocity Modeling (1.00)