We reanalysed the induced seismicity data from the Groningen gas reservoir. We used the well-maintained induced event catalogue of the KNMI. The distributions of seismic moments and interevent times show a power law behaviour over several decades, and we find that upon increasing the magnitude threshold, these distributions remained scale-invariant. Because of this scale-invariance, we can put a constraint on the average loading of the elastic energy within the reservoir, which upon reaching a critical value gives rise to the seismic events. We find that the elastic energy roughly increases proportional to time. We also propose a new machine learning approach for declustering the seismic events, separating correlated from independent events. We find that only few events are truly independent, i.e. exponentially distributed over time. There are also few aftershocks following an Omori-type power law. The bulk of events presents a Gamma distribution for interevent times. This gives us an indication that the rigidity in the reservoir is high, but whether this results in overall correlated events should be settled with physics-based arguments rather than statistical ones.