Seismic while drilling （SWD） is an emerging horehole seismic imaging technique that uses the downhole drill-bit vibrations as seismic source. Without interrupting drilling, SWD technique can make near-real-time imag...Seismic while drilling （SWD） is an emerging horehole seismic imaging technique that uses the downhole drill-bit vibrations as seismic source. Without interrupting drilling, SWD technique can make near-real-time images of the rock formations ahead of the bit and optimize drilling operation, with reduction of costs and the risk of drilling. However, the signal to noise ratio （SNR） of surface SWD-data is severely low for the surface acquisition of SWD data. Here, we propose a new method to retrieve the drill-bit signal from the surface data recorded by an array of broadband seismometers. Taking advantages of wavefield analysis, different types of noises are identified and removed from the surface SWD-data, resulting in the significant improvement of SNR. We also optimally synthesize seis- mic response of the bit source, using a statistical cross-coherence analysis to further improve the SNR and retrieve both the drill-bit direct arrivals and reflections which are then used to establish a reverse vertical seismic profile （RVSP） data set for the continuous drilling depth. The subsurface images derived from these data compare well with the corresponding images of the three-dimension surface seismic survey cross the well.展开更多
A new prestack AVA simultaneous inversion using particle swarm optimization algorithm is proposed, which can obtain the elastic parameters such as P-wave and S-wave impedance from P-wave reflection data simultaneously...A new prestack AVA simultaneous inversion using particle swarm optimization algorithm is proposed, which can obtain the elastic parameters such as P-wave and S-wave impedance from P-wave reflection data simultaneously. Compared with the conventional AVA inversion based on generalized linear technique, this method does not depend on the initial model and can reach the global minimum. In order to increase the stability of the inversion, low-frequency trends of P-wave and S-wave impedances are built into the inversion. This method has been successfully applied to synthetic and field data. The estimated P-wave and S-wave impedances can be combined to derive other elastic parameters, which are sensitive for lithology identification and fluid prediction.展开更多
基金supported by the National Natural Science Foundation of China (Nos.41204087,41230318,41204088)the Specialized Research Fund for the Doctoral Program of Higher Education (No.20120132120030)+1 种基金the National High-Tech R & D Program (No.2013AA092501)the Fund of Key Laboratory of Marine Hydrocarbon Resources and Environmental Geology,Ministry of Land and Resources of China (No.MRE201303)
文摘Seismic while drilling （SWD） is an emerging horehole seismic imaging technique that uses the downhole drill-bit vibrations as seismic source. Without interrupting drilling, SWD technique can make near-real-time images of the rock formations ahead of the bit and optimize drilling operation, with reduction of costs and the risk of drilling. However, the signal to noise ratio （SNR） of surface SWD-data is severely low for the surface acquisition of SWD data. Here, we propose a new method to retrieve the drill-bit signal from the surface data recorded by an array of broadband seismometers. Taking advantages of wavefield analysis, different types of noises are identified and removed from the surface SWD-data, resulting in the significant improvement of SNR. We also optimally synthesize seis- mic response of the bit source, using a statistical cross-coherence analysis to further improve the SNR and retrieve both the drill-bit direct arrivals and reflections which are then used to establish a reverse vertical seismic profile （RVSP） data set for the continuous drilling depth. The subsurface images derived from these data compare well with the corresponding images of the three-dimension surface seismic survey cross the well.
基金supported by the National Natural Science Foundation of China(Nos.41004096 and 41230318)
文摘A new prestack AVA simultaneous inversion using particle swarm optimization algorithm is proposed, which can obtain the elastic parameters such as P-wave and S-wave impedance from P-wave reflection data simultaneously. Compared with the conventional AVA inversion based on generalized linear technique, this method does not depend on the initial model and can reach the global minimum. In order to increase the stability of the inversion, low-frequency trends of P-wave and S-wave impedances are built into the inversion. This method has been successfully applied to synthetic and field data. The estimated P-wave and S-wave impedances can be combined to derive other elastic parameters, which are sensitive for lithology identification and fluid prediction.
