These materials are organized in modules, each of which treats the use of a particular geophysical method. Each module is built around a common structure and format so that students can concentrate on exploration processes rather than computing technology. Each module consists of the following sections:

• A summary of the physical principles involved will provide a basis for discussing sources of signals and noise and for estimating the amplitude and frequency content of each source. The exploration process will be reviewed to show how it applies to this method.
  
  
• A Request for Bid will present a geological or engineering problem that can be solved by the use of the method that is the subject of this module.
  
  
• Students will be guided through a survey-design process that includes justifying the choice of method, estimating noise levels, using modeling software to predict signal amplitude and shape, considering acquisition tools and techniques, and using the results of these steps to select optimum field parameters.
  
  
• On the basis of the results of step 3, students will prepare and submit a formal bid that includes an analysis of the cost-benefit trade-offs.
  
  
• Students will enter their proposed survey parameters into a form on the WWW and immediately receive a data set that represents a realistic model of the results that their unique survey design would produce.
  
  
• A discussion of data processing techniques will provide the students with the basis for developing their own algorithms (using hardware-independent, high-level languages) for reducing the noise and enhancing the signal in their survey.
  
  
• A summary of the basic principles and rules involved forward-interpretation methods will allow the students to develop a first-guess model for the interpretation of their processed data.
  
  
• After receiving instruction on the basic concepts of model building for the method under study, and reviewing the concept of a structured approach to data interpretation, students will be able to download modeling algorithms that will allow them to superimpose model results on their data and do a manual inversion.
  
  
• A great deal of emphasis will be placed on having the students codify the rules for manual inversion, then apply those rules in conjunction with the modeling algorithm to quantify the uncertainties in their interpretation, identify other models that fit the data, and estimate the probability that each possible interpretation is correct.
  
  
• Upon completion of data processing and interpretation, students will submit a final report on the project results. When this is received, they will be given the actual source of their data and be asked to evaluate the accuracy of their interpretation and explain any errors in their parameters.