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Gridding random data with SURFER

Remember: when you grid or contour, you are interpreting your data

SURFER is a grid-based contouring program that uses gridded data to create the images and contour maps we’ve been working with for the past few exercises. Gridding is the process of interpolating irregularly located data onto a regularly spaced array of points. DEMs are gridded data sets. Usually one does not collected geologic data on a regular grid – often some places you wish to sample are simply not accessible. When you have randomly distributed data, they have to be gridded before SURFER can contour them. For some additional reading and background information check out:

  • Davis (1986; in course references) includes a good section on the theory of gridding and contouring.
  • Krajewski, S. A. and B. L. Gibbs, Computer Contouring Generates Artifacts, Geotimes, April 1994, p. 15 - 19.
  • Li, X. and H. Gotze, Comparison of Some Gridding Methods, The Leading Edge, August 1999, p. 898 - 900.

There are many different ways to grid data; SURFER allows a choice from among eight alternative techniques. Two common ways to grid geologic data are by minimum curvature and Kriging; using radial basis functions is often a viable alternative. Minimum Curvature generates smooth surfaces and is fast for most data sets. It has the additional advantage that many geologic data sets (groundwater, stress/strain, heat flow, gravity, magnetics chemical diffusion, etc.) have their mathematical basis in Laplace’s equation as does the minimum curvature method. Minimum curvature commonly produces edge effects (unrealistic highs and lows) beyond the boundaries of the supplied data.

Kriging is one of the more flexible methods and is useful for gridding almost any type of data set. With most data sets, Kriging with a linear variogram is quite effective; it is the default in SURFER and the method most commonly recommended by Golden Graphics. Kriging is the default gridding method because it generates the best overall interpretation of most data sets. For larger data sets, however, Kriging can be rather slow.

Gridding Data with SURFER

To grid randomly distributed data in SURFER, use Grid/Data from the menu bar. SURFER expects ASCII data organized in columns that are either tab or space delimited. You can put data in this format using Excel, a text editor such as Window’s Notepad, or a word processor. You can also type in and organize such data using SURFER’s worksheet capability. When you create a grid file, there are several options to consider. These options, from SURFER’s help files, are:

  • Gridding Methods determine how the original data is interpreted when creating the grid file.
  • Gridding Options control the Anisotropy and Data Treatment during gridding.
  • Grid File Formats are the file formats for grid files.
  • Grid Line Geometry controls the Grid Limits and Grid Density used for the grid file.
  • Search Options control the Search Type, Search Rules and Search Ellipse parameters.

Each of these topics is expanded on in SURFER’s help files.

The general steps are:

  • Select Grid/Data from the menu bar and SURFER presents a text box in which you move through your computer’s directory structure and click the ASCII data file you wish to grid. Presumably the requisite data are in your subdirectory.
  • SURFER then presents its "Scattered Data Interpolation" text box as in the figure above. Indicate which of the columns in your data file has the x, y, and z values you wish to grid, the spacing you wish those data to be gridded at (minimum and maximum values), the gridding method, and the name of the output file. Kriging is not a bad default for gridding most data. Two others that are typically 'geoscience relevant' are minimum curvature (a potential field) and radial basis functions. Click OK and SURFER grids your data; they are ready to contour, etc.
  • Embellish with base maps, county outlines, and the like (example). Here are some tips.

Data:

Think About All This!

OBJECTIVE: What I want you to understand, through your experimentation above, is that sampling, gridding and contouring all affect the results of data presentation and visualization. You need to manipulate and consider your own data to avoid making an unwarranted interpretation. You need to carefully consider anyone’s presentations. Glitzy presentations are not a substitute for critical and careful thinking.




 

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