{"id":292,"date":"2012-06-02T06:38:32","date_gmt":"2012-06-02T06:38:32","guid":{"rendered":"http:\/\/ahay.org\/blog\/?p=292"},"modified":"2015-09-03T03:19:07","modified_gmt":"2015-09-03T03:19:07","slug":"program-of-the-month-sfdip","status":"publish","type":"post","link":"https:\/\/ahay.org\/blog\/2012\/06\/02\/program-of-the-month-sfdip\/","title":{"rendered":"Program of the month: sfdip"},"content":{"rendered":"

sfdip<\/a> estimates a local slope (dip) using the plane-wave destruction<\/a> algorithm. <\/p>\n

The dip is measured in time samples. If $\\alpha$ is the dip angle, then the output of sfdip corresponds to the dimensionless quantity $p=\\tan{\\alpha}$. <\/p>\n

The following example from jsg\/flat\/flat<\/a> shows an input synthetic dataset and an estimated dip field <\/p>\n

\"\" \"\"<\/p>\n

When applied to 3-D data, sfdip<\/strong> outputs a 4-D file with n4=2<\/strong> and two dips (inline and crossline). To compute only the inline dip, use n4=0<\/strong>. To compute only the crossline dip, use n4=1<\/strong>. The following example from sep\/plane\/qint<\/a> shows an input synthetic 3-D dataset and the two dip components calculated from it. <\/p>\n

\"\" \"\"<\/p>\n

The algorithm consists of a number of non-linear Gauss-Newton iterations (specified by niter=<\/strong>) with a number of linear CG-shaping iterations (specified by liter=<\/strong>) inside each non-linear cycle. The convergence depends on the initial dip values, which can be specified either as constants (p0=<\/strong> and q0=<\/strong>) or as auxiliary input files (idip=<\/strong> and xdip=<\/strong>). If it is necessary to constrain the range of dip values, it can be controlled by specifying minimum or maximum parameters (pmin=<\/strong>, pmax=<\/strong> and qmin=<\/strong>, qmax=<\/strong>). The smoothness of the dip is assured by shaping regularization<\/a> and controled by the smoothing radii rect1=<\/strong>, rect2=<\/strong>, rect3=<\/strong>. <\/p>\n

With default parameters, the dip estimate is accurate only up to 45 degrees. To estimate steeper (aliased) dips, increase the order=<\/strong> parameter. The order of the filter corresponds to the maximum dip. Alternatively, one can use the technique of filter stretching (interlacing), explained by Claerbout<\/a>; the stretching parameters are nj1=<\/strong> and nj2=<\/strong>. The following examples from sep\/pwd\/alias<\/a> show aliased data interpolation using (a) order=12 (b) order=3 nj1=4. <\/p>\n

\"\" \"\"<\/p>\n

For a faster version, with only one non-linear iteration but with fewer options, try sffdip<\/a>. To estimate two interfering dips, try sftwodip2<\/a>. To estimate a number of constant dips, try sfdips<\/a>. <\/p>\n

10 previous programs of the month<\/h3>\n