AbstractThe small‐scale discontinuous and inhomogeneous geologies, such as tiny faults, cavities and fractures, play an important role in reservoir analysis. However, effectively extracting them from seismic imaging data is a challenging problem, as their seismic responses are much weaker than reflections' from large‐scale structures. On the other hand, this small‐scale information is easily contaminated with noises, which will make their analysis difficult to perform if there is no strategy adopted for improving the signal‐to‐noise ratio (S/N) of their images. By combing a non‐linear filter and a sparsity constraint, a seismic sparse inversion method of imaging data is developed for detecting these small‐scale discontinuous and inhomogeneous geologies.The core of extracting discontinuous and inhomogeneous information lies in removing strong reflections and noises. The plane‐wave destruction method uses a local plane‐wave model for representing seismic structures and thus is appropriate for estimating reflections. Through subtracting the predicted reflections from seismic imaging data, the small‐scale discontinuous and inhomogeneous information will be left into the seismic residual data. Considering the sparsity property of this small‐scale information, a L1 ‐ L2 norm model is built that uses a non‐linear filter for promoting the S/N of the discontinuous and inhomogeneous inversion results. In order to guarantee the computation efficiency in solving this sparsity model, a L1 norm approximation scheme and quasi‐Newton algorithm is introduced.Numerical experiment demonstrates the effectiveness of the proposed method in extracting the small‐scale discontinuous and inhomogeneous geologies. This numerical model is composed of fractures, faults and cavities. The geological targets are four series of cavities in the shallow part and three series of cavities in the deep part. With the proposed seismic sparse inversion method, a profile with reflections eliminated and noises destroyed is obtained and the edges, faults, fractures and cavities are completely resolved. In field application, a carbonate reservoirs analysis is performed. The 3D prestack time migration profile can clearly display large‐scale layers but fails in describing discontinuous and inhomogeneous geologies. Although coherency techniques can reveal discontinuous information, the small‐scale tiny faults, fractures and cavities are beyond its detection. The proposed method succeeds in clarifying and locating the small‐scale discontinuous and inhomogeneous geologies. The seismic attribute analysis based on seismic spares inversion data also provides valuable information about the planar distribution of the tiny faults, cavities and fractures.Based on a sparsity‐constraint model, a seismic sparse inversion method of imaging data is proposed for extracting small‐scale discontinuous and inhomogeneous geologies. The method can achieve a high‐resolution image by removing strong reflections and elimination of noises. In method application, this seismic discontinuous and inhomogeneous information is required to be imaged by seismic data processing. Otherwise, some additional seismic data processing is needed. As an end, we suggest future research on individually extracting discontinuity and inhomogeneity, especially for evaluating the capacity of carbonate reservoirs.