Campos Basin hyperModel | Super-Fast Track Delivery
PGS acquired data over part of the deep-water Campos Basin in 2020, covering an area of 14 496 km2. The data includes a complex geological environment with fast carbonates and salt diapirs.
The slider below shows the initial model and migrated Common Image Gathers (CIGs) used as the input for hyperModel (left) and the output overlain on the migrated CIG (right). Ideally, the CIGs would be flat, but the image shows they are not, indicating the starting point for hyperModel was very inaccurate.
In this example, we applied the hyperModel workflow in two passes, the first for the postsalt sediments, and the second for the presalt sequence. After the first pass, a machine-learning algorithm generated a top salt interpretation. The fast carbonates, sitting on the salt, were conditioned and the salt velocities flooded into the model. Following this, a base of salt interpretation was created using the same machine-learning algorithm, and the flooded salt velocity terminated at this horizon. Finally, we captured the presalt section using the hyperModel workflow.
The input model for hyperModel co-rendered with the migrated Common Image Gathers (CIGs). The gathers from both the pre and postsalt section show significant moveout, as the complexity of the earth is not captured in the starting velocity model.
The slider shows an example of the hyperModel results. The CIGs are flat for both the pre and postsalt sequences. The fast carbonate and salt sections also show minimal moveout.
In this example, PGS used hyperModel to build an accurate velocity model for a ‘super fast-track’ product. Including all the interpretation, flooding, and hyperModel work, the model building took less than one month, with the deliverable exceeding expectations of a super fast-track product.