For the purpose of common mid-point bin attribute analysis from high density exploration and three-dimensional seismic geometry,this paper analyzes the calculation characteristics of bin analysis,and proposes an efficient parallel algorithm for bin attribute analysis based on Open Computing Language (OpenCL) heterogeneous programming model.The algorithm divides bin grid into several sub-regions under hardware memory constraint.Tasks of sub-regions are executed with coarse-grained parallelization by assigning task to different devices,whereas pairs of source-receiver in sub-region are executed with fine-grained parallelization.With HP's Z820 desktop workstation,experiment was carried out with high density three-dimensional geometry from seismic exploration.The experimental results show that the parallel algorithm takes full advantage of multiprocessor's parallel processing capability,and the processing speed is about 30 times faster than that on CPU-based implementation (single core) under the condition that the precision is not changed.