Abstract

The ongoing transition to nodal seismic systems raises discussions around optimal technologies in seismic exploration. This abstract presents a closed-loop validation framework—essentially a model that enhances a well-known convolutional model and helps to incorporate real-world units, such as meters and volts, into the equations. The signal is modeled to pass through the entire acquisition and processing chain. It is compared with the initial signal to understand what can actually be recovered through acquisition and processing. Unlike finite-difference modeling, which struggles with modeling high frequencies and fine details, the analytical approach captures the complete frequency spectrum and realistic noise characteristics in actual physical units. However, the method is limited by the physics of the convolutional model. The proposed approach was used to evaluate realworld problems to understand the impact of seismic receiver and media parameters on the ability to recover the seismic signal above the noise floor. Modeling presents potential scenarios comparing acceleration sensors with geophones, as well as better nodes with simpler nodes, and discusses the potential impact of additional acquisition system components.