Innovation in Adjustments
The most recent advance in the acquisition of marine gravity data has been the move toward high-resolution computerized instruments which provide higher sample rates and higher precision data. This technology was first spearheaded by the innovation of the SAGE meter which was designed by EDCON-PRJ. The value of acquiring high-resolution gravity can only be realized if high-resolution data processing is applied to the data. To answer this challenge, EDCON-PRJ also invented a number of methods of processing these data to obtain unprecedented detail.
3D seismic surveys and the advent of the high-resolution marine gravity appeared to be the perfect marriage of technologies that provides the user with complementary detailed data. However, the leveling of the shipborne data was problematic because tie-lines normally used in the network adjustment and leveling procedures were not generally required during 3D seismic operations. Hence, it became necessary to invent a new way of leveling data that could deal with the lack of tie-lines and maintain the resolution inherent in the acquired data. The system for doing so is called Virtual Network Adjustment. Virtual because there may be no intersecting lines but the adjustment is done nonetheless.
Conventional adjustment procedures examine the data only at line intersections and then adjust the line levels such that the intersection differences are minimized. This method normally works well, but sometimes introduces anomalies that were not present in the original data. Such anomalies have become more important with the use of techniques to enhance small residual anomalies. Adjustment anomalies can be interpreted as real features if one is not careful.
The new method uses the entire data set in three dimensions to generate corrections to the unadjusted line data. An iterative approach allows problem lines to be retained in the dataset whereas, with the old method, they might have been edited or entirely removed from the network. The VNAtm process produces a dataset that preserves the high-frequency components that are very important in high-resolution surveys. Other systems have relied on filtering to eliminate remaining adjustment problems but, VNAtm does not produce “line or intersection pulls” so less filtering is required.