Offshore towed-streamer positioning based on variance component estimation

Abstract

In offshore towed-streamer seismic surveys, fusing observations from diverse navigation sensors to position streamers and hydrophones accurately is essential for high-quality seismic imaging and analysis. However, streamer positioning accuracy can be limited when nominal sensor precisions adopted in observation weighting become unrealistic in complex marine environments. This study used variance component estimation (VCE) to refine the weight determination of heteroscedastic observations involved in streamer positioning. First, a polynomial fitting model for streamer positioning was established. Subsequently, a simplified VCE method was presented in which the observations were classified based on both sensor type and distribution geometry. Finally, a six-streamer survey dataset acquired from the South China Sea was used to investigate the performance of the proposed method. A comparative analysis was performed between conventional empirical weighting methods and VCE methods implemented in various observation classification schemes. The experimental results verified the superiority of the stochastic model refinement in fully exploiting observations from multiple navigation sensors in offshore streamer positioning. Compared with the empirical weighting, VCE method reduced the mean standard deviation of the hydrophone positions by about 0.5 m.