Ivan Chikichev

Encoded Simultaneous Source Full-Wavefield Inversion For Spectrally Shaped Marine Streamer Data

In this paper, we apply encoded simultaneous source fullwavefield inversion (FWI) to marine streamer data. FWI of large scale 3D data is a challenging problem, especially constraining the inversion using the high frequencies available in exploration seismic data. Two methodologies that make high-frequency FWI feasible for field data are: (a) applying encoded simultaneous source full-wavefield inversion (ESSFWI) and (b) shaping the data to provide a preferential weighting to the low-frequency components of the data. These two methods in combination provide us with the computational efficiencies needed for large 3D runs. To date, most encoded simultaneous source methods have been applied to fixed-receiver data; i.e., each receiver records data from all shots in the survey. We developed an approach that enables us to apply ESSFWI to marine streamer data that are non-fixed spread. The approach uses a normalized cross-correlation objective function with multiple realizations of the encoded data at each iteration of the nonlinear FWI. The method can be applied to 2D/3D data with any survey geometry. Here we demonstrate the methodology and discuss its details with synthetic examples. Although not presented here our initial investigations on 3D field streamer data look encouraging.

Improving the convergence rate of full wavefield inversion using spectral shaping

The number of iterations required for convergence of Full Wavefield Inversion (FWI) can often be dramatically reduced by appropriately shaping the spectrum of the seismic data and the source wavelet. This shaping is designed such that the inversion generates subsurface models having a desired frequency spectrum, representative of the subsurface. This subsurface spectrum can be estimated by averaging the spectra of log curves (e.g., impedance) recorded in local wells. The spectral shaping method is particularly effective when the wavefield is dominated by primary reflections. In addition to speeding up convergence, spectral shaping preferentially increases the weight of the lower-frequency part of the spectrum, stabilizing the inversion in the presence of local minima. It can thus be used to bypass the need for the commonly-used multi-scale approach.

Wavelet Estimation and Multiple Modeling in Full-Waveform Inversion

Full-waveform inversion (FWI) has the potential to extract information not only from primary reflections, but also from multiples. We show that accurate modeling of multiples provides strong constraints on the amplitude, frequency spectrum and phase of the seismic wavelet. Thus the method presented here leads to a very robust estimation of the wavelet without relying upon well control. As a consequence, it is applicable to and could be particularly beneficial to the early stages of exploration.