A constrained spectral inversion method based on compressive sensing in order to distinguish high-quality shale. Issue 5 (1st October 2018) - Zhang, Hua; He, Zhenhua; Li, Yalin; Li, Rui; He, Guangming
Abstract : Multi-wave exploration has become one of the main means of unconventional shale gas exploration in the Sichuan Basin, China. How to effectively improve the resolution of the shale gas reservoir layer and distinguish high-quality shale has become one of the difficulties for shale gas exploration. The spectral inversion technology can effectively break the resolution limit of the conventional technology and greatly improve the resolution of the thin shale layer; however, it also needs enough prior information to overcome the problem of multiple solutions in the inversion. The compressed sensing (CS) theory has the ability to reconstruct complete data using incomplete data can use less data information to improve the accuracy of spectral inversion. A novel constrained spectral inversion method based on CS is presented to handle these situations. The CS technique is applied to the objective function of spectral inversion, which can improve the accuracy of the spectral inversion algorithm and create profiles with a higher resolution and greater continuity. Applications through theoretical and real data can illustrate very high performance of the presented algorithm. Abstract : Distinguishing high-quality shale effectively is a difficult exploration problem. We propose a constrained spectral inversion method based on compressive sensing to handle this challenge. This method can help us improve the resolution and continuity of the profiles and enhance our ability to discover high-quality shale.