Joint deblending and source time inversion

Abstract

The simultaneous source technique has been widely applied in seismic field acquisition and has achieved great success in the past decade. Many studies have shown that inversion-based source-separation algorithms are more robust than filtering-based methods. However, inversion-based methods depend on accurate shot times. Here, we tackle the long-standing issue of the shot times being inaccurate or unavailable during iterative inversion by proposing a joint inversion framework to simultaneously separate the blended sources and invert for the shot time. We formulate a non-linear inverse problem that contains two unknowns, i.e., the unblended data and the shot time vector, and we propose a Gauss-Newton method to iteratively invert the shot time vector given an estimate of the unblended data. Then, the estimated shot time vector is fixed for iterative source-separation following a traditional deblending framework. The two aforementioned steps are recursively implemented until they converge or reach a maximum number of iterations. We demonstrate the proposed method through several synthetic and field data examples. Results show that the proposed joint inversion framework is effective and the low-frequency component matters during the non-linear inversion of the shot time vector.