Synopsis
		sfvelinvnew < infile.rsf res=fres.rsf vel0=fm.rsf mres=fmres.rsf > outfile.rsf velout=vtr.rsf nv=nhx dv=0.01 ov=1.5 niter=20 savevel=0 flag=0 mflag=0 huber=0 irls=0 nstep=1 rwt=0. mwt=0. srate=0.01 eps=0.01 lamda=1000. delta=0.0001 step=0.000005 alpha=790.635 alpha= lip= reset=

Parameters
		alpha= smoothing parameter, typical value: 1 to 10 times estimated norm(x,inf)   delta=0.0001 delta controls update step and convergent, small delta ensure convergence but with small decrease in data fit error   dv=0.01   eps=0.01   flag=0   huber=0   irls=0   lamda=1000. lamda controls sparsity, bigger lamda, more sparsity   lip= the estimated Lipschitz constrant of the dual objective, default: alpha*normest(A*A',1e-2)   mflag=0   file mres= auxiliary output file name   mwt=0.   niter=20   nstep=1   nv=nhx   ov=1.5   file res= auxiliary output file name   reset= Nesterov's acceleration restart (theta is reset) or skip (theta is not reset)   rwt=0.   savevel=0 Flag to choose the algorithm   srate=0.01   step=0.000005 step is very important in convergence and sparsity   file vel0= auxiliary input file name   file velout= auxiliary output file name