Acquisition Footprint Modelling
Stacked 3D volumes can be simulated from either elastically modelled records or 2D data. It is preferable to use the latter, but suitable data may not be available in some cases, for example if a 3D OBC survey is being planned. In such cases, records can be modelled from density and p-wave sonic logs, using estimated shear velocities. Pressure and particle velocity can be output at any point in the model, so that a seafloor record can be modelled at the same time as a towed streamer record and a VSP for calibration purposes. It is important to ensure that the shot-generated noise systems are accurately depicted in the modelled output. 'Random' noise is also added to the modelled records.
Traces are selected from the input data based on the 3D offset distribution across the template being tested. The data must be modelled or recorded at a sufficiently small receiver interval so that the 3D offset distribution can be properly represented. Source and receiver array responses can also be simulated at this stage. The sorted data are then processed and stacked to produce a mini-volume which simulates the signal to noise ratio and acquisition footprint for the template being evaluated. This technique allows alternative templates to be compared, as shown in the following examples.
Extracts from a 3D volume modelled using an 80 fold cross-spread
Extracts from a 3D volume modelled using an 80 fold parallel template
These two templates were evaluated for use on a land survey in an area of high amplitude shot generated noise. The 3D simulations predicted that a parallel template (lower panel) would produce better signal to noise ratio and less acquisition footprint than a cross-spread (upper panel). This is because the parallel template has a better sampled offset distribution. The survey was acquired using a parallel template and comparison with an adjacent survey, previously acquired with the cross-spread, confirmed the modelling prediction.
Survey Design Phase One: Feasibility
Survey Design Phase Two: Optimisation
Survey Design Phase Three: Technical Support
Target Finders