The main difficulty in seismic full waveform inversion (FWI) is the strong nonlinearity, which is caused by the complexity of seismic wave propagation. Different components of elastic parameters result in different characteristics of seismic data. Meanwhile, different inversion accuracy is required in different stages of exploration or exploitation. So, it is really not necessary to pursue matching all the seismic information during the inversion. Some problems can be solved by matching part of seismic information and the strong nonlinearity can also be alleviated by this way. According to this consideration, a generalized FWI strategy and method based on seismic data subsets is presented. For different seismic data subsets, the gradients of the misfits have the same form and can be calculated by two modeling applications just as traditional FWI, and the only difference in calculating the gradients is the adjoint sources. During the waveform inversion based on seismic data subsets, the responses of seismic data to different scales of perturbation on different media parameters should be analyzed intensively. Different seismic data subsets should be used in different stages of full waveform inversion. And then the residual of this seismic data subset is back-projected along the reasonable sub-kernels to decide where and which component of the medium parameter need to be updated. As examples, envelope and reflection data subsets are used in FWI with synthetic and real data to prove the validity and effectiveness of our presented FWI strategy and method. Especially, in the absence of low frequency contents, reasonable misfits can be used to recover the background compressional and shear velocity using these FWI methods.