Dip-constrained tomography with weighting flow for paleo-canyons: a case study in Para- Maranhao Basin, Brazil Guang Chen and Lingli Hu, CGG

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1 Dip-constrained tomography with weighting flow for paleo-canyons: a case study in Para- Maranhao Basin, Brazil Guang Chen and Lingli Hu, CGG Summary Para-Maranhao Basin offshore Brazil is well-known for its shallow geological complexities. Rugose topography and complex V-shaped paleo-canyons directly below the water bottom create challenges for ray-based migration velocity analysis from prestack depth imaging. In particular, when using a global grid-based tomography, generating velocity updates at a sufficiently small scale to conform to these shallow structures can be difficult. Image distortions, characterized by non-geologic depth undulations and amplitude variations, are often observed below the shallow structures. These artifacts can affect the accuracy of reservoir interpretation. We propose a weighted, highresolution workflow utilizing dip-constrained, non-linear slope tomography to resolve small scale velocity variations at shallow depths. As a result, image distortions below the near-surface geological complexities are attenuated, and the common image gather flatness is improved. Introduction Extensive small-scale velocity variations in the rugose water bottom (WB) and paleo-canyons lead to two principal challenges in ray-based velocity analysis for prestack depth migration (PSDM). First, it is not uncommon to see far-offset artifacts in PSDM gathers beyond the critical angle (Nolan and Symes, 1996) in complex shallow sediments. After muting these artifacts, far offsets corresponding to shallow events are lost and therefore unavailable for residual curvature velocity analysis (RCA) of common image gathers (CIGs) (Zhou et al., 2003). Second, compared to deep events, shallow events have relatively poor image focus directly below the troughs of the canyons; only a few events can be picked with confidence. Because of the limited far offset information and the lack of reliable events, residual moveout (RMO) picks from shallow CIGs cannot fully reflect high-frequency lateral velocity variations in the velocity inversion. For these reasons, small-scale lateral velocity variations in the shallow canyons can rarely be adequately resolved by shallow-layer RCA tomography. Residual shallow velocity errors are often further emphasized in the CIG moveout of deeper events. We frequently observe stronger residual curvature in deeper sections, and the spatial variation of the moveout clearly exhibits the imprint of the shallower canyons. Further iterations of tomography project this residual curvature onto a local velocity anomaly directly above these deep events. As a consequence of these incorrect velocity updates, non-geologic depth undulations and amplitude variations are introduced, making structure mapping and reservoir interpretation problematic. Recent works have focused on addressing these issues. Graham and Richard (2009) introduced a 3D channel tomography to correctly update low-velocity sedimentary channels in the North Sea. In this method, the velocity inversion is constrained by sub-channel horizons with perceived correct positions. Sun et al. (2011) used highresolution, anisotropic tomography to update the vertical velocity, and in a region with small, shallow geologic structures characterized by rugose WB topography, complex paleo-canyons, and channel fill. Their workflows require well log information to calibrate the anomalous high-frequency local anisotropy along geological structures. Previous studies of high-definition (HD) or high-resolution (HR) tomography (Han and Xu, 2011; Guillaume et al., 2011; Hu and Zhou, 2011) have demonstrated that detailed velocity features can be incorporated via dense CIG picks and a dense tomography inversion grid. However, due to the aforementioned limitations, it remains difficult to fully resolve highfrequency velocity variations in complex shallow structures by conventional layer-constrained HR tomography. Chen and Shen (2012) presented a weighted HR tomography workflow to generate updates that reflect the highfrequency lateral velocity variations in the paleo-canyons. In this approach, the velocity update in the shallow layers is guided by the picks from deeper reflectors, and the output is sensitive to the definition of the update region. However, residual imaging distortions can still be observed if velocity anomalies are very narrow or the image focus of deep events is poor. Guillaume et al. (2013) introduced nonlinear slope tomography in which both the RMO and the offset dependent dip of migrated events are used in velocity inversion. We combined the weighted HR tomographic workflow with dip-constrained, non-linear slope tomography to resolve velocity anomalies in the Para-Maranhao Basin. Using our method, the non-geologic undulations below the rugose WB and paleo-canyons can be successfully removed via accurate updates to shallow velocities. Workflow We first employed the geo-mechanical approach introduced by Birdus (2009) to generate an initial velocity model in which the velocity variations below the rugose seafloor are better estimated.

2 In addition to RMO, dip fields were picked on locally coherent events from near, middle, far and full offset stacks, and a reference dip field was generated by editing out all non-geologic distortions on the dip of full stack. The offset-dependent dip differences were used to guide the velocity update. To accurately resolve small scale lateral velocity variations within the canyons, the structurallyguided weighting scheme was applied (Chen and Shen, 2012). A set of geological horizons was picked to define the velocity update layers. In this method, both RMO and dip picks below the canyons were used to guide velocity updates in the shallow canyon regions, and the shallow canyons were more strongly weighted than the deep regions in the inversion. The non-geologic distortions were successfully attenuated by the combined method. 2005) and high-resolution Radon residual multiple attenuation (Hugonnet et al., 2010). Results We began the study by generating an initial tilted transverse isotropic (TTI) velocity model (Thomsen, 1986). The velocity along the symmetry axis, V 0, was derived via the geo-mechanical method in the layer below the WB canyons. Then the ε and δ models were created by 1D η inversion (Alkhalifah and Tsvankin, 1995). The anisotropic models were kept constant throughout the study. The dip and azimuth angles were originally picked based on the depth image migrated using the initial models and were updated after every iteration of tomography. Study area and data preparation The Para-Maranhao Basin is located offshore of the states of Para and Maranhao in northern Brazil. The study area lies in close proximinity to the Amazon estuary (Figure 1). In this region, complex shallow sedimentary structures were generated by the combined impact of sea level changes and the draining of the Amazon River. Water bottom-incised canyons formed through erosion by the river during periods of low sea level; paleo-crayons were created by channel deposits during periods of rising sea levels. High-frequency lateral velocity anomalies are widely observed in these canyons. Figure 1: Location of 3D narrow azimuth data and water bottom (WB) map of the study area. Our focus for this study was a 367 square km 3D narrow azimuth (NAZ) data set, which exhibited the extremely rugose seafloor. The data was acquired from 2007 to 2009, and the shooting direction was along the WB canyons. The nominal fold coverage was 58. Key pre-processing procedures in the sail line domain include noise attenuation, source designature, datum correction, and 3D surface-related multiple elimination (SRME). After binning data into a 25 m x 25 m common offset cube, the data quality was further improved by data regularization and interpolation with anti-leakage Fourier transform (Xu et al., Figure 2: Dip field picking of a (a) dip on near stack, (b) dip on middle stack, and (c) dip on far stack. Stacks are shown with a depth scale of Z:X=2.5:1. Following the aforementioned steps, the offset dependent dip difference was picked for the inversion. We pick the extra dip information on the near, middle and far stacks (Figure 2, red lines) and create the reference dip by editing out the non-geologic distortion on full stack (Figure 2, blue line). In the tomography, not only were RMOs flattened, but the offset-dependent dip differences were minimized as

3 well. However, in the shallow canyons, the far offsets were very limited, and picking the reference dip was impractical. In this study, the dependability of deep picks were used to update the shallow layer. Figure 3 compares the RMO-only tomography and dip-constrained tomography. Both results were from one update iteration for a velocity above 3100 m with the weighted HR tomography flow. The weighting was defined to emphasize the layer above 2300 m. Figures 3c and 3d present the stack and the corresponding CIGs generated using regular tomography. Compared to the stack indicated by red arrows in Figure 3e were successfully removed with the extra dip information. The yellow arrow points to a location where the image focus of deep events was too poor to be used in the initial stack. Therefore, the update from RMO-only tomography was inferior to the update from dip-constrained tomography because of the deficient RMO picking. The dip difference can provide extra information for the update at this location. Moreover, both the focus and flatness of the CIGs were notably improved according to the comparison between Figure 3d and Figure 3f. We also compared the corresponding shallow velocity from RMO-only tomography to that from dip-constrained tomography (Figure 4). The inversion without dip information tended to emphasize the deep locations where reflectors were more laterally consistent (Figure 4a). However, the velocity perturbation generated via the dipconstrained method was stronger and exhibited a greater level of geologic detail both laterally and vertically. The velocity at the troughs of paleo-canyons was also properly updated (Figure 4b). Conclusions In this study, the weighted HR workflow with dipconstrained, non-linear tomography was used to resolve the velocity update in the Para-Maranho Basin, offshore Brazil. The non-geologic distortions associated with the rugose WB and complex paleo-canyons were greatly alleviated. The velocity update was not sensitive to the definition of the updated region because both RMO and dip information were involved. This improved weighted HR workflow was an efficient and effective approach for the resolution of small scale velocity updates in the presence of complex geologic structures. Figure 3: Migrated image and gathers in an area with WB canyons and paleo-canyons. (a) Migrated image with initial model. There are obvious image distorions below the canyons. (b) Gathers with initial model. (c) Migrated image without dip-constrained tomography. There are residual image distorions below the canyons. (d) Gathers without dip-constrained tomography. (e) Migrated image with dipconstrained tomography. The image distortions are reduced. (f) Gathers with dip-constrained tomography. Stacks are shown with a depth scale of Z:X=3:1.. with initial model (Figure 3a), the most obvious nongeologic distortions were attenuated, and CIGs were flattened. However, small residual distortions were still observed (Figure 3, red arrows) due to the failed update of the small-scale velocity variations in the shallow canyons (up to 200 m). The stack and CIGs at the same location generated through the use of dip-constrained inversion are displayed in Figures 3e and 3f. The residual undulations Acknowledgments We thank Tony Huang and Yan Huang for providing constructive suggestions and discussions. We are grateful to Tianjiang Li for his contribution to tomography testing as well as Li Lu, Hao Shen, Amy Martin, and Kamal Siddiqui for help with input data preparation. We thank Patrice Guillaume for reviewing the abstract.

4 Figure 4: Shallow velocity model (a) without dip-constrained tomography and (b) with dip-constrained tomography.

5 References Alkhalifah, T., and Tsvankin, I., 1995, Velocity analysis for transversely isotropic media: Geophysics, 60, Zhou, H., Gray, S., Young, J., Pham, D. and Zhang, Y., 2003, Tomographic residual curvature analysis: The process and its components, 73rd Ann. Internat. Mtg.: Soc. of Expl. Geophys., Birdus, S., 2009, Geomechanical modeling to solve velocity anomalies and image distortions below seafloor with complex topography, 71 st EAGE Conference and Exhibition. Chen, G., and Shen, H., 2012, High-resolution tomography for paleo-canyons: a case study in Para-Maranhao Basin, Brazil, SEG Expanded Abstracts, Guillaume, P., Reinier, M., Lambaré, G., Cavalié, A., Adamsen, M., Bruun, B., 2013, Dip constrained non-linear slope tomography, SEG Expanded Abstract, Graham, C., and Richard, L., 2009, Channel tomography, 71 st EAGE Conference and Exhibition. Guillaume, P., Lambare, G., Sioni, S., Carotti, D., Depre, P., Culianez, G., Montel, J., Mitouard, P., Depagne, S., Frehers, S., Vosberg, H., and Vigneaux B., 2011, Geologically consistent velocities obtained by high definition tomography, SEG Expanded Abstracts, 30, Han, W., Xu, S., 2011, High resolution velocity model for imaging complex structures, 73 rd EAGE Conference and Exhibition. Hu, L. and Zhou, J., 2011, Velocity update using high resolution tomography in Santos Basin, Brazil, SEG Expanded Abstracts, 30, Hugonnet, P., Mihoub, M., and Herrmann, P., 2010, 3D High resolution parabolic Radon filtering, GEO Nolan, C., and Symes W., 1996, Imaging in complex velocities with general acquisition geometry: in Annual Report: TRIP, The Rice Inversion Project, Rice university. Sun, Y., Guo, Q., Carroll, S., Chen, J., and Liebes, E., 2011, A high-resolution velocity anisotropy case study, SEG Expaned Abstracts, 30, Thomsen, L. 1986, Weak elastic anisotropy, Geophysics, 51, Xu, S., Zhang, Y., Pham, D., Lambare, G., 2005, Antileakage Fourier transform for seismic data regularization: Geophysics, 70, No.4,