A new approach to the acquisition of potential field data

Abstract

Abstract This study presents a new strategy for the design of geophysical surveys based on non-uniform sampling across a survey area. The strategy comprises several stages. The first stage is design and implementation of an initial, large station spacing, survey that defines the geophysical response in areas where there is little variation, and also allows identification of areas of interest where more data are required. The station spacing in this first-stage survey can be selected based on the probability of detecting such areas of interest that are of a given size. Using a gravity survey as an example, areas of interest are identified within the first-stage dataset based on the occurrence of variations likely to be due to source ‘edges’. The data are used to prepare a source edge density map, thus identifying the regions within the study area that require further sampling. The density of edges is used to design the next phase of data acquisition, station/sampling frequency being proportional to edge density. As a result, a non-uniform sampling array is produced. If necessary the process can be repeated based on an edge-density analysis of the combined first- and second-stage data. To improve the logistics of data collection for this non-uniform sampling array, a simulated annealing algorithm is used to determine a close-to-optimal travel path for the collection of the data. This strategy results in data being acquired in areas where it provides the most information, producing an accurate dataset, whilst minimising the cost of collecting the data.