A generic methodology was developed for rapid screening of coal seam gas (CSG) chemicals (drilling, fracturing, and geogenic chemicals) to determine which chemicals are more likely to be hazardous when present in or mobilised from deeper groundwater environments. First, the method adopts existing rules for screening chemicals and lists of chemicals that have previously been rigorously assessed and found to be of low concern to the environment and/or human health. Next, the degree of attenuation (expressed as a dilution attenuation factor) that coal seam gas chemicals would experience prior to potentially reaching receptors was determined using a multiple lines of evidence approach. This involves i) spatial analyses of proximity (horizontal distance) between potential contaminant sources at CSG wells and receptor locations in the vicinity of those wells, including derivation of proximity-frequency relationships for several groups of receptors (ecologic, economic and socio-cultural), ii) chemical and or biological, geological (owing to chemical sorption onto organic and/or mineral phases) and flow-related (dilution/dispersion) attenuation information for CSG chemicals in deep groundwater, iii) conceptual models with plausible fate and transport release pathways, iv) solute particle tracking analysis to identify likely connectivity, travel distance and time between the coal seam formations being hydraulically stimulated and groundwater receptors, and v) simplified calculation tools that combined all the above information. An extensive literature survey provided robust data on chemical and or biological degradation of organic chemicals. Additional particle tracking-based pathway calculations were undertaken with an entire well field to capture possible cumulative effects from mass accumulating for the case of hydraulically stimulated wells. Application of this methodology facilitates prioritisation of chemicals for which more detailed risks assessments associated with potential deeper groundwater contamination are warranted. Our methods further provide a robust approach to inform management decisions around safe setback distances.