Clustering earthquakes refer to the seismic events that occur closely with each other in time and space.Because their overlapping waveform records make it difficult to pick the first arrivals,the hypocenters of clustering earthquakes cannot be determined accurately by traveltime location methods.Here we apply a reverse-time imaging(RTI) method to map clustering earthquakes.Taking the advantage of directly using waveforms,the RTI method is capable to map either a single small earthquake or some densely distributed clustering earthquakes beneath a 2-D seismic array.In 3-D case the RTI method is successfully applied to locate the long-offset doublet earthquakes using the data from a set of sparsely distributed surface stations.However,for the same acquisition geometry,the RTI encounters challenges in mapping densely distributed clustering earthquakes.While it is obvious that improving the mapping of clustering earthquakes requires a denser receiver network with wider range of illumination angles,it is necessary to verify the actual resolution of the RTI method with synthetic data.In our study area in the Three Gorges region,our tests in 3-D case suggest that some events beneath the linear aligned sub-arrays have reasonable resolution. Clustering earthquakes refer to the seismic events that occur closely with each other in time and space.Because their overlapping waveform records make it difficult to pick the first arrivals, the hypocenters of clustering earthquakes can not be determined accurately by traveltime location methods. Hele we apply a reverse-time imaging (RTI) method to map clustering earthquakes.Taking the advantage of directly using waveforms, the RTI method is capable to map either a single small earthquake or some densely distributed clustering earthquakes beneath a 2-D seismic array .In 3- D case the RTI method is successfully applied to locate the long-offset doublet earthquakes using the data from a set of sparsely distributed surface stations. Still, for the same acquisition geometry, the RTI encounters challenges in mapping densely distributed clustering earthquakes. Whilst it is obviously that improving the mapping of clustering earthquakes requires a denser receiver network with wider range of illumination angles, it is necessary to verify the actual resolution of the RTI method with synthetic data. In our study area in the Three Gorges region, our tests in 3-D case suggest that some events beneath the linear aligned sub-arrays have reasonable resolution.