Well-controlled seismic resolution enhancement technology based on GRNN amplitude spectrum estimation

Resolution enhancement is always an essential process in seismic exploration. Complex geological bodies, such as thin layer and thin interbed, have become the main target of reservoir exploration with the decrease of simple reservoir, and exploration precision is required more higher. The traditional methods of resolution enhancement are mainly based on seismic profile information, tending to be blind and lack of judgment criterion. However, when applying well-controlled seismic processing technology, well data can be used for seismic exploration. This study proposes a method which introduces well information to improve seismic data resolution in combination with generalized regression neural network (GRNN). With strong self-adaptive learning and approaching ability, GRNN can be taken as a means to modify and expand seismic data spectrum, so as to improve the resolution of seismic data under the constraint of well. Model test and actual data processing indicate that the well-controlled seismic resolution enhancement technology based on GRNN amplitude spectrum estimation is effective and feasible. ©, 2015, Shiyou Xuebao/Acta Petrolei Sinica. All right reserved.