A new method of predicting borehole stability while drilling based on seismic attribute technology

Key words:  borehole stability  prediction while drilling  seismic attribute  well log data  genetic algorithm  neural network

Abstract:

A new method of predicting borehole stability while drilling was presented by using seismic attributes and well logs together. This method is based on the close nonlinear relationships between seismic attributes and well logs. Before drilling the optimal attribute combinations which are sensitive to log properties are selected from original seismic attributes by using genetic algorithm and BP neural networic algorithm together. Tlien a series of mapping models which reflect relationships between seismic attributes and well logs of various formation intervals in given area are constructed through neural network. With analysis of cutting logging data, the proper mapping model can be employed to predict acoustic and density log curves of impending drilling formation while drilling. Based on the analysis, the borehole stability of formation under bit can be predicted. The prediction precision and real-time operation ability of the proposed method are satisfactory，which have been proved in the practical application in south-west area of Tarim Oilfield.