The white noise deconvolution problem has important application background in oil seismic exploration. The multisensor optimal weighted measurement fusion white noise deconvolution Wiener filter is presented by using the Kalman filtering method. Compared with centralized and decentralized fusion methods, not only it give the globally optimal white noise fusion estimator, but also it can obviously reduce the computational burden, so that it is suitable for real time applications. A simulation example of weighted measurement fusion estimator for a Bernoulli-Gaussian white noise with four-sensor shows its effectiveness.