INTRODUCTION 



Many of the analytical techniques which are currently in use in geophysics 

 involve some form of mathematical operation on digitized survey data. The two- 

 dimensional character of some of these techniques requires that the survey data, 

 usually collected along tracks, be reduced to values of the surveyed parameters 

 on an equally spaced grid. Examples of these techniques include upward and 

 downward continuation, derivative calculations, regional trend removal, two- 

 dimensional trend filtering, model studies, deflection of the vertical and geoidal 

 undulation calculations, and automated contouring techniques. The interpolation 

 procedures which are discussed in this report are applicable to any measurements 

 obtained by track -type surveys. Emphasis, however, is placed on the problem of 

 gridding gravity survey data and the determination of mean values of the gravity 

 field within specified areas. 



In general there are two approaches available for gridding track -type 

 survey data. One approach is that of fitting a least -squares surface, usually of 

 polynomial form, to all of the available survey data within a predetermined area 

 and using the resulting formula to generate the required grid values. Examples 

 of this procedure, applied to irregularly spaced data, may be found in Crain and 

 Bhattacharyya (1967) and Krumbein (1959). The advantages of this least -squares 

 method are that it tends to operate as a low-pass filter, which reduces the effects 

 of noisy or erroneous data and it can be applied directly to unequally-spaced 

 data points. The chief disadvantages are: 



1 . The wavelengths of the features which will be accurately fit is a 

 function not only of the degree of the polynomial but also of the size of the 

 area which is selected. This causes some difficulty in controlling the technique 

 in a production type operation. 



