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Attention-Based Two-Stage U-Net Horizon Tracking

To reduce the impact of non-target horizon regions and improve horizon tracking precision, we propose an attention-based two-stage U-Net horizon tracking method (ATUM). The ATUM consists of the horizon region label automatic generation and the attention module (AM) based two-stage U-Net (ATUN). Horizon region label automatic generation aims to automatically generate the target horizon region label of the target horizon label. In ATUN, the two stages (stages I and II) consist of the conventional encoder-decoder U-Net, and the two decoder parts are connected by the AM. Stage I treats horizon tracking as an objection detection problem. It takes the seismic data as its input and the automatically generated target horizon region label as its label, and finally obtains the target horizon region. Stage II takes the results of stage I with the corresponding seismic data as its input, and finally obtains the precise horizon. Two field 3-D seismic dataset studies demonstrated the performance of the ATUM for high-precision horizon tracking.