Reflection analysis and identification of fracture-cavity body under strong reflection background
Ordovician carbonate fracture-cavity reservoirs are developed in Tarim basin.When the fracture-cavity body is close to the strong reflection horizon named T74,the background strong reflection and the reflection caused by fracture-cavity body are superimposed,leading to difficult identification of fracture-cavity body.In order to solve this problem,this paper studies the strong reflection separation method based on matching pursuit algorithm focused on the optimization of separation coefficient,and proposes a separation coefficient calculation method based on amplitude trend correction,which can identify and separate the overlying strong reflection effectively,highlight the'string beads'reflection characteristics and improve the prediction precision of fracture-cavity body.Firstly,we analyze the seismic reflection mode of fracture-cavity body under the strong reflection background,and clarify the theoretical seismic reflection characteristics of fracture-cavity body,which is the basis for the following studies.Then based on this mode,a geological model is established to carry out seismic forward modeling and feature analysis.By using the separation coefficient calculation method based on amplitude trend correction,the strong reflection can be separated more accurately and the seismic reflection characteristics of the underlying fracture-cavity body are more obvious,which verify the effectiveness and rationality of this method.Finally,we conduct the strong reflection separation and fracture-cavity body identification for actual seismic data in Tarim basin,and achieve good application results.The method proposed in this paper can weaken the influence of the overlying strong reflection more effectively and improve the identification accuracy of the fracture-cavity body,supporting the well location target deployment and hydrocarbon breakthroughs.
Matching pursuitParameter optimizationSeparation coefficientStrong reflection separationFracture-cavity bodyModel test
NETL
NSTL
万方数据
