The Research And Application Of Buried Hill's Fracture Prediction With Combining Logging And Seismic Data

One of the key seismic exploration work of buried hill fractured oil and gas reservoirs is the prediction of fracture development zone. How to predict the development of fracture, occurrence and distribution of fractures in the reservoir rock is the most difficult problem in the exploration and development of fractured reservoirs. The fracture distribution is complex and the regularity is poor. It is difficult to identify and forecast the fracture zones in the reservoirs, so the relevant technical research has been being the focus of attention of the industry.Well logging and seismic fracture identification methods are the main geophysical methods to solve the problem of fracture prediction. Among logging methods, imaging logging is still the most reliable basis for crack identification; conventional logging is easy to implement, has certain effect, and is able to be combined with seismic inversion to predict the regional distribution of fractures; shear wave logging and radioactive logging effect is better, but the data are difficult to collect. The fracture identification method related to numerical analysis is confined to the study of the fracture in the well. In seismic method, fracture prediction based on the P-wave anisotropy of is the most widely applied, and the method can obtain spatial distribution of fractures; prestack near and far offset distance attribute difference method, coherency analysis and angle detection method, post stack attribute fusion method, multi-scale edge detection method and seismic inversion method etc. are the main methods of the seismic fracture prediction. Due to the existence of multiple solutions of fracture prediction, it is difficult to accurately describe the fracture distribution, so people expected to use the method which can combine the various kinds of data.According to requirement of exploration of the Bohai Bay buried hill oil and gas reservoir, this thesis proposed to do the fracture prediction of buried hill reservoir focusing on the directional information and density of fracture by combining the seismic and logging data based on the choice of correlation parameters of logging data to seismic data, and optimizing the methods of seismic and logging interpretation. The results showed the improvements on the reliability and accuracy of prediction of fractures in the study area. The established approach and workflow have been applied to the study area. The proposed method has achieved good results in the practical application, which provides a scientific basis for the prediction of reservoir in buried hill reservoir.