Abstract：The separation of the up-going and down-going wavefields is a key step in the data processing of dual-sensor seismic data.Aiming at the dis-advantage that the up-going wavefield separated by conventional methods contains the down-going wavefield，and the down-going wavefield contains the down-going wavefield，that is，the up-going and the down-going wavefields can not be separated completely,this paper introduces three energy matching factors and four wavefield separation contribution factors.Three energy matching factors are the energy matching factor of dual-sensor data，the up-going wavefield energy matching factor of the down-going wavefield，and the down-going wavefield energy matching factor of the up-going wavefield.Four wavefield separation contribution factors are the up-going wavefield contribution factor of the hydrophone data，down-going wavefield contribution factor of the hydrophone data，the up-going wavefield contribution factor of geophone data，and down-going wavefield contribution factor of the geophone data.The up-going and down-going wavefield separation equations are established.The optimal energy matching factors of the up-going and down-going wavefields of dual-sensor seismic data are computed and determined by an iteration algorithm.Then the wave field separation contribution factors are directly calculated to realize the complete separation of the up-going from down-going wavefields of dual-sensor seismic data.The separated up-going wavefield data not only eliminates the ghost multiple interferences，but also widens the effective frequency band.The signal-to-noise ratio and resolution of the seismic data are improved too,and the high-fidelity up-going and down-going wavefields are provided for subsequent joint deconvolution and migration imaging processing.The effectiveness and practicability of this method are illustrated by synthetic and real data examples.
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