Parallelized with OpenMP. # of threads: 4 DCIP2D - Version 5 (BETA) 20110811: DCINV2D Developed by University of British Columbia Geophysical Inversion Facility (UBC-GIF) (C) Copyright 1992 - 2011, UBC-GIF, Department of Earth and Ocean Sciences, UBC http://www.eos.ubc.ca/research/ubcgif/ Distributed by: Mira Geoscience Ltd. DCINV2D started on:12/11/2015 11:26:38 Reading input file: dcinv2d.inp ---------------------------------------------- OBS LOC_X FWR_3D_2_2D.dat MESH FILE Mesh_2D.msh CHIFACT 1 100.000000 TOPO DEFAULT %s INIT_MOD DEFAULT REF_MOD VALUE 1.000000e-03 ALPHA DEFAULT WEIGHT DEFAULT STORE_ALL_MODELS FALSE INVMODE SVD USE_MREF TRUE ---------------------------------------------- maximum # of iterations: 100 data were read from: FWR_3D_2_2D.dat # of current locations: 9 # of data: 45 chifact: 1.00000E+00 target misfit: 4.50000E+01 mesh was read from: Mesh_2D.msh # of cells: 47 x 30 total # of cells: 1410 # of active cells: 1410 # of unique data locations: 9 # of wave values: 13 2.5000E-04 4.9901E-04 9.9606E-04 1.9882E-03 3.9685E-03 7.9213E-03 1.5811E-02 3.1560E-02 6.2996E-02 1.2574E-01 2.5099E-01 5.0099E-01 1.0000E+00 reference conductivity model is set to a constant: 1.000000E-03 initial model is set to the reference model. using default length scales (Lx, Lz): ( 8.00000E+01, 8.00000E+01) corresponding alpha (a_s, a_x, a_z): ( 1.56250E-04, 1.0000E+00, 1.0000E+00) Using basis vectors and SVD. reference model will be used in the derivative terms. number of basis vectors: 17 + 3 + 1 = 21 init cpu time: 0:00:00.06 initial misfit = 5.86595E+04 init. model norm = 0.00000E+00 norm comp Ws = 0.00000E+00 norm comp Wx = 0.00000E+00 norm comp Wz = 0.00000E+00 Iteration 1 beta vs. misfit: beta misfit 1.14011E+04 1.55434E+04 2.28022E+04 1.97701E+04 5.70054E+04 2.80956E+04 6.37666E+04 2.93408E+04 chosen beta = 6.37044E+04 target misfit = 2.93298E+04 achieved misfit = 2.93298E+04 model norm = 1.78131E-01 misfit change = 4.99999E-01 model norm change = 0.00000E+00 norm comp Ws = 9.36044E-02 norm comp Wx = 5.21598E-02 norm comp Wz = 3.23664E-02 iter cpu time: 0:00:00.54 Iteration 2 beta vs. misfit: beta misfit 1.13370E+04 1.41481E+04 1.59261E+04 1.63158E+04 3.18522E+04 2.20755E+04 chosen beta = 1.23494E+04 target misfit = 1.46649E+04 achieved misfit = 1.46622E+04 model norm = 7.62402E-01 misfit change = 5.00094E-01 model norm change = 3.28002E+00 norm comp Ws = 3.10519E-01 norm comp Wx = 3.26120E-01 norm comp Wz = 1.25764E-01 iter cpu time: 0:00:00.17 Iteration 3 beta vs. misfit: beta misfit 3.08734E+03 7.25168E+03 6.17468E+03 1.04745E+04 chosen beta = 3.15138E+03 target misfit = 7.33109E+03 achieved misfit = 7.33827E+03 model norm = 1.97756E+00 misfit change = 4.99510E-01 model norm change = 1.59385E+00 norm comp Ws = 5.74759E-01 norm comp Wx = 1.07019E+00 norm comp Wz = 3.32607E-01 iter cpu time: 0:00:00.14 Iteration 4 beta vs. misfit: beta misfit 7.87844E+02 2.34933E+03 1.57569E+03 4.17369E+03 chosen beta = 1.34889E+03 target misfit = 3.66914E+03 achieved misfit = 3.69116E+03 model norm = 3.63935E+00 misfit change = 4.96999E-01 model norm change = 8.40325E-01 norm comp Ws = 9.31633E-01 norm comp Wx = 2.00929E+00 norm comp Wz = 6.98426E-01 iter cpu time: 0:00:00.43 Iteration 5 beta vs. misfit: beta misfit 3.37223E+02 1.15980E+03 6.74446E+02 1.95927E+03 chosen beta = 6.23201E+02 target misfit = 1.84558E+03 achieved misfit = 1.83831E+03 model norm = 5.55702E+00 misfit change = 5.01969E-01 model norm change = 5.26927E-01 norm comp Ws = 1.39116E+00 norm comp Wx = 2.97085E+00 norm comp Wz = 1.19501E+00 iter cpu time: 0:00:00.13 Iteration 6 beta vs. misfit: beta misfit 1.55800E+02 7.04026E+02 3.11600E+02 1.03301E+03 chosen beta = 2.52300E+02 target misfit = 9.19156E+02 achieved misfit = 9.06295E+02 model norm = 7.76502E+00 misfit change = 5.06996E-01 model norm change = 3.97336E-01 norm comp Ws = 1.93177E+00 norm comp Wx = 4.15601E+00 norm comp Wz = 1.67723E+00 iter cpu time: 0:00:00.14 Iteration 7 beta vs. misfit: beta misfit 5.45665E+01 4.43592E+02 6.30749E+01 4.61153E+02 1.26150E+02 5.89041E+02 chosen beta = 5.90843E+01 target misfit = 4.53148E+02 achieved misfit = 4.52929E+02 model norm = 1.10434E+01 misfit change = 5.00242E-01 model norm change = 4.22194E-01 norm comp Ws = 2.44126E+00 norm comp Wx = 6.33488E+00 norm comp Wz = 2.26722E+00 iter cpu time: 0:00:00.15 Iteration 8 beta vs. misfit: beta misfit 1.76205E+00 2.33067E+02 3.87651E+00 2.33770E+02 8.52832E+00 2.36313E+02 1.47711E+01 2.41686E+02 2.95422E+01 2.66924E+02 chosen beta = 3.87651E+00 target misfit = 2.26464E+02 achieved misfit = 2.33770E+02 model norm = 1.57679E+01 misfit change = 4.83870E-01 model norm change = 4.27818E-01 norm comp Ws = 3.91956E+00 norm comp Wx = 8.05061E+00 norm comp Wz = 3.79775E+00 iter cpu time: 0:00:00.54 Iteration 9 beta vs. misfit: beta misfit 9.69127E-01 1.25628E+02 1.93825E+00 1.25177E+02 3.87651E+00 1.26747E+02 chosen beta = 1.93825E+00 target misfit = 1.16885E+02 achieved misfit = 1.25177E+02 model norm = 2.02946E+01 misfit change = 4.64529E-01 model norm change = 2.87081E-01 norm comp Ws = 5.14918E+00 norm comp Wx = 1.04854E+01 norm comp Wz = 4.66004E+00 iter cpu time: 0:00:00.14 Iteration 10 beta vs. misfit: beta misfit 4.84563E-01 8.59120E+01 9.69127E-01 8.56434E+01 1.93825E+00 8.63895E+01 chosen beta = 9.69127E-01 target misfit = 6.25885E+01 achieved misfit = 8.56434E+01 model norm = 2.27540E+01 misfit change = 3.15821E-01 model norm change = 1.21187E-01 norm comp Ws = 6.37929E+00 norm comp Wx = 1.05750E+01 norm comp Wz = 5.79974E+00 iter cpu time: 0:00:00.13 Iteration 11 beta vs. misfit: beta misfit 2.67558E-01 5.36200E+01 5.09212E-01 5.36850E+01 chosen beta = 5.09212E-01 target misfit = 4.50000E+01 achieved misfit = 5.36850E+01 model norm = 2.65060E+01 misfit change = 3.73156E-01 model norm change = 1.64894E-01 norm comp Ws = 7.06440E+00 norm comp Wx = 1.17778E+01 norm comp Wz = 7.66382E+00 iter cpu time: 0:00:00.12 Iteration 12 beta vs. misfit: beta misfit 3.57781E-01 4.27021E+01 4.26833E-01 4.27304E+01 1.06708E+00 4.32906E+01 2.66771E+00 4.58497E+01 chosen beta = 1.97938E+00 target misfit = 4.50000E+01 achieved misfit = 4.46230E+01 model norm = 2.75984E+01 misfit change = 1.68800E-01 model norm change = 4.12137E-02 norm comp Ws = 7.60316E+00 norm comp Wx = 1.17705E+01 norm comp Wz = 8.22479E+00 iter cpu time: 0:00:00.51 Target misfit achieved. Minimizing model norm. Iteration 13 beta vs. misfit: beta misfit 1.99610E+00 3.93953E+01 2.01297E+00 3.94209E+01 5.03242E+00 4.59121E+01 chosen beta = 4.46061E+00 target misfit = 4.50000E+01 achieved misfit = 4.44143E+01 model norm = 2.65756E+01 misfit change = 4.67734E-03 model norm change = -3.70618E-02 norm comp Ws = 7.28818E+00 norm comp Wx = 1.16493E+01 norm comp Wz = 7.63807E+00 iter cpu time: 0:00:00.15 Iteration 14 beta vs. misfit: beta misfit 4.51943E+00 4.42228E+01 4.57903E+00 4.43808E+01 4.81808E+00 4.50262E+01 chosen beta = 4.80820E+00 target misfit = 4.50000E+01 achieved misfit = 4.49992E+01 model norm = 2.59337E+01 misfit change = -1.31690E-02 model norm change = -2.41533E-02 norm comp Ws = 7.05571E+00 norm comp Wx = 1.14342E+01 norm comp Wz = 7.44373E+00 iter cpu time: 0:00:00.15 Exit at convergence. Iterations performed: 14 total cpu time: 0:00:03.57 DCINV2D ended on:12/11/2015 11:26:42