Multi-Wave Imaging Methods for Distributed Acoustic Sensing Vertical Seismic Profile Assisted by Artificial Intelligence Processing
Objective We investigate intelligent processing and imaging methods for distributed acoustic sensing vertical seismic profile(DAS-VSP)data,focusing on longitudinal waves and converted waves.Meanwhile,we discuss DAS-VSP morphology component analysis for noise reduction,intelligent separation of multiple waves in DAS-VSP data,and regularization methods using deep learning for DAS-VSP data,and study a multi-wave VSP imaging method based on minimum travel time.The proposed method combines the advantages of VSP-CDP conversion and conventional ray-based Kirchhoff migration and utilizes minimum travel time information to determine the reflection wave paths in the VSP data.By controlling the focusing imaging near the reflection paths using travel time tables,this method reduces the curvature compared to traditional seismic migration methods and calculates the coverage during the imaging to resolve uneven imaging amplitudes.By the actual data processing of offshore inclined well DAS-VSP,the DAS-VSP P-P wave and P-S wave imaging profiles are obtained simultaneously for the first time in China.Combining targeted processing,the researchers achieve imaging of both P-P and P-S waves from DAS-VSP data.The results indicate that the DAS-VSP from deviated wells provides conditions for multi-wave imaging and yields higher signal-to-noise ratio(SNR)imaging data for P-P waves and P-S waves.Multi-wave data is more conducive to oil and gas prediction and identification,and artificial intelligence(AI)processing and multi-wave imaging methods provide new technical means for DAS-VSP in oil and gas exploration and development.Methods The process of the proposed VSP imaging method based on minimum travel time is demonstrated,and multi template fast advancement algorithm is employed to calculate the travel time table for each shot and receiver pair.Further,the two travel time tables are summed and sorted from small to large ones by depth.Given the number of grids(migration aperture),the wave field data are projected at the corresponding position according to the travel time and stacked.Meanwhile,we repeat the projection for each location,followed by calculating the coverage folds to average the seismic amplitude anomaly due to uneven coverage.Finally,we stack them all to form an imaging profile.This process is applicable for both the P-wave and converted wave imaging.This method combines the advantages of common depth point conversion and migration and focuses imaging near the reflection path,thus reducing migration artifacts,calculating the number of coverage times during the imaging,and addressing abnormal imaging amplitudes due to uneven coverage.Results and Discussions Our data are located in the Pinghu Oil and Gas Field in the East China Sea,which is excited by air gun source and received by DAS.The converted wave imaging process extracts a shot line in the well trajectory direction for testing(Fig.1).The maximum offset is 4190 m,the shot point distance is 50 m,and the total number of shots is 148,with the measured optical cable depth of 3357 m,and maximum offset of-1533 m,and DAS receiver channel distance of 2 m.Figure 1 shows the upgoing converted wave ray and polarization direction.It indicates that the polarization of the upgoing converted wave in the well trajectory direction is perpendicular to the optical cable,the well trajectory is in the opposite direction,and the upgoing converted wave is parallel to the optical cable.The DAS Walkaway-VSP P-and converted-wave imaging profiles obtained by the grid ray tracing imaging method are shown in Fig.17 respectively.The imaging results indicate that the imaging range of the upgoing converted wave is smaller than that of the upgoing P-wave.Both images have considerable correspondence in the dominant reflectors.Additionally,deeper in the section,the SNR of converted wave imaging is higher than that of P-wave results,which proves that DAS-VSP performs well in converted wave imaging.The current results demonstrate the capability of the proposed grid-based ray tracing imaging method in conducting imaging on both P-and converted waves.Conclusions We study a VSP imaging method based on grid ray tracing,which has the following advantages:1)More focused imaging around the reflectors with significantly reduced migration artifacts is common under a VSP configuration.2)By calculating the coverage folds during the imaging,the proposed method allows for a straightforward solution to solve the problem of abnormal imaging amplitudes due to the uneven coverage.3)The flexibility in choosing the imaging aperture is suitable for imaging structures with variable complexity.The proposed VSP imaging method based on minimum travel time combines the advantages of VSP-CDP transform and migration,which can achieve VSP imaging profiles in complex structural conditions at a cost-efficiency mode,as demonstrated in the numerical example.The field data example further shows the effectiveness of the proposed method in conducting imaging on both the P-and S-wave.
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