Ground Penetrating Radar (GPR) systems with multi-concurrent sampling receivers can rapidly acquire dense multi-offset GPR data, which is not feasible using typical common offset (CO) GPR systems with a single, fixed offset transmitter-receiver pair. Multi-offset GPR data from these new multi-concurrent receiver systems have the potential to be used to create detailed subsurface velocity models and enhanced reflection sections. These are important features that can improve qualitative and quantitative interpretation of GPR data. In order to realize these benefits and to deal with the large amount of multi-offset data generated by these new systems, we have developed an automated and customized data processing workflow. There are three key algorithms that we have developed as part of our workflow, which are crucial for processing large volume, multi-offset GPR data so as: firstly, to efficiently correct and manage time misalignments from multi-concurrent receivers; secondly, to carry out trace balancing of common mid-point (CMP) data for semblance analysis; and thirdly, to automate the velocity analysis step. We showcase our processing workflow using two field datasets acquired using a multi-concurrent sampling receiver GPR system consisting of one transmitter and seven receivers. The field data were collected at two different locations: a site using a system with a 500 MHz center frequency and another site using a system with a 1000 MHz center frequency. We demonstrated, with both datasets, that our processing workflow could produce automated stacking velocity fields and enhanced zero-offset reflection cross-sections. These benefits increase the information that can be used for interpretation (compared to conventional CO data) and can form the basis of further processing steps such as migration. As the cost of these multi-concurrent sampling receiver systems decreases over time, we anticipate their use, and the acquisition of dense multi-offset GPR data, to become much more commonplace.