Sunwoong Lee

Fast full-wavefield seismic inversion using encoded sources

Full-wavefield seismic inversion (FWI) estimates a subsurface elastic model by iteratively minimizing the difference between observed and simulated data. This process is extremely computationally intensive, with a cost comparable to at least hundreds of prestack reverse-time depth migrations. When FWI is applied using explicit time-domain or frequency-domain iterative-solver-based methods, the seismic simulations are performed for each seismic-source configuration individually. Therefore, the cost of FWI is proportional to the number of sources. We have found that the cost of FWI for fixed-spread data can be significantly reduced by applying it to data formed by encoding and summing data from individual sources. The encoding step forms a single gather from many input source gathers. This gather represents data that would have been acquired from a spatially distributed set of sources operating simultaneously with different source signatures. The computational cost of FWI using encoded simultaneous-source gathers is reduced by a factor roughly equal to the number of sources. Further, this efficiency is gained without significantly reducing the accuracy of the final inverted model. The efficiency gain depends on subsurface complexity and seismic-acquisition parameters. There is potential for even larger improvements of processing speed.

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.

Preconditioning full waveform inversion with phase-encoded Hes sian

Full waveform inversion (FWI) has received an increasing amount of attention thanks to its ability to provide a highresolution velocity model of the subsurface. The computational cost still presents a challenge, however, and the convergence rate of the FWI problem is usually very slow without proper preconditioning of the gradient. While preconditioners based on the Gauss-Newton Hessian matrix can provide significant improvements in the convergence of FWI, computation of the Hessian matrix itself has been considered highly impractical due to its cost in computational time and storage requirements. In this paper, we design preconditioners based on an approximate Gauss-Newton Hessian matrix obtained using the phase-encoding method. The new method requires only 2Ns forward simulations compared to Ns(Nr + 1) forward simulations required in conventional approaches, where Ns and Nr are the numbers of sources and receivers, respectively. We apply the diagonal of the phase-encoded GaussNewton Hessian to both sequential-source FWI and encoded simultaneous-source FWI. Numerical examples using a truncated Marmousi2 model demonstrate that the phase-encoded Gauss-Newton Hessian improves the convergence of the FWI significantly.

Fast Full Wave Seismic Inversion Using Source Encoding

Full Wavefield Seismic Inversion (FWI) estimates a subsurface elastic model by iteratively minimizing the difference between observed and simulated data. This process is extremely compute intensive, with a cost on the order of at least hundreds of prestack reverse time migrations. For time-domain and Krylov-based frequency-domain FWI, the cost of FWI is proportional to the number of seismic sources inverted. We have found that the cost of FWI can be significantly reduced by applying it to data processed by encoding and summing individual source gathers, and by changing the encoding functions between iterations. The encoding step forms a single gather from many input source gathers. This gather represents data that would have been acquired from a spatially distributed set of sources operating simultaneously with different source signatures. We demonstrate, using synthetic data, significant cost reduction by applying FWI to encoded simultaneous-source data.

Subsurface parameter estimation in full wavefield inversio n and reverse time migration

We develop a method for directly estimating subsurface medium parameter updates from the gradient equations in full wavefield inversion. This is achieved by accounting for the effects of source and receiver illuminations, background medium properties, and seismic resolution volume in the gradient equations. Using this method, we directly compute the subsurface seismic parameters needed to minimize the difference between the measured and modeled seismic field. It is shown that this method, when used to precondition the gradients in iterative inversion processes, yields faster convergence than when gradients are used without preconditioning. It is also shown that this method can be used for inversion of amplitudes in reverse time migration into the difference bulk modulus of subsurface.

3-D Mitigation of Surface-wave Noise In Spatially Inhomogeneous Media

A method is developed for 3-D mitigation of surface waves in spatially inhomogeneous media. Mitigation is enabled by modifying conventional phase-matched filtering techniques to dynamically update the phase-velocity estimates based on shot-receiver locations of the record being processed. This update is achieved by first estimating local phase velocities over the survey area, and then by path-averaging the local phase velocities for each shot-receiver pair. It is shown that surface wave mitigation using the new method is superior to conventional methods when there is spatial variation in medium properties.

Characterization of spatially varying surface waves in a land seismic survey

Summary We present several methods for analyzing surface waves in a highly sampled 3-C, 3D survey, and report the most important characteristics derived from those analyses. In particular, we demonstrate the spatial variability of surfacewave velocities and polarization properties. We also show that surface-wave velocities are correlated with other seismic and nonseismic properties of the near surface, such as shear-wave statics and surface texture derived from satellite imagery.

A novel approach to estimating near‐surface S‐wave velocity and converted‐wave receiver statics

Summary We present a workflow for estimating near-surface S-wave velocity and deri ving long- and short-wavelength receiver statics for converted-wave (PS) data. The estimated S-wave velocity can also be used for depth migration of convertedwave data. The novelty of our method lies in detecting refracted S-wave arrivals present in the data, and using a depth-dependent weighting function to combine the S-wave velocities inverted from Scholte-wave and turning-ray tomography, respectively. We note considerable improvement in the quality of time-migrated convertedwave data after applying the receiver statics solution that was derived using our method.

Role of Simultaneous Source Technology in Seismic Industry

Simultaneous source method has been investigated in the past in the context of efficient seismic data acquisition; however recently due to its computational efficiency in imaging, simulation and inversion the momentum in this field has increased. At ExxonMobil, simultaneous source technology has been an active research topic for many years in several areas ranging from acquisition, imaging and recently in full-wavefield inversion (FWI).