Building a near-surface velocity model in the South Ghadames basin: surface-wave inversion to solve complex statics D. Boiero*, P. Marsden, V. Esaulov, A. Zarkhidze, and P. Vermeer, WesternGeco Summary The South Ghadames basin, Libya, near-surface geology consists of a Tertiary-Cretaceous carbonate layer overlying Jurassic clastics. This leads to a strong velocity inversion in the near surface that, combined with the absence of a stable refractor, generates serious statics issues in an area where low relief structures are expected. We propose to use surface-wave analysis and inversion as a tool to build a geologically consistent near-surface velocity model. The geology makes the surface-wave inversion particularly challenging because of the superposition of different modes (Rayleigh, Lamb, and S-guided). To combat these challenges, a new inversion approach, which is able to deal with different modes, was applied. Introduction The Ghadames basin is one of the five major onshore hydrocarbon basins in Libya. In 2008, BP Exploration began a 3D seismic exploration program that included two different areas located close to the Algerian and Tunisian borders. The near-surface geology consists of a Tertiary- Cretaceous carbonate layer overlying Jurassic clastics (Figure 1). In the south block, denominated South Ghadames and located across the Nalut and Wadi ash - Shati districts, the transitions from thin carbonates to Jurassic clastics is, in general, much shallower (<100 m) than in the north block. Existing wells reveal the presence of a variable anhydrite layer within carbonate (at depths of ~120-150 m off plateau and up to ~230 m on plateau) with potentially regional extent. Consequently, a stable refractor is challenging to identify and model in the South Ghadames area (Figure 1). These near-surface characteristics generate serious statics issues for seismic imaging of the South Ghadames. In an area where low relief structures are expected, proper correction of near surface travel time distortion is the key element for accurate structural interpretation and reservoir analysis. In this respect, we propose surface-wave analysis and inversion as a tool to build a geologically consistent, near-surface velocity model and to provide a robust statics solution to apply to a 3D volume. Surface-wave analysis and inversion Surface waves propagate along the near surface, and their propagation properties depend directly upon the elastic properties of the near surface. They might consist of several modes of Rayleigh waves (Scholte waves in shallow-water environments), Lamb waves (when strong velocity inversions are present), Love waves (on horizontal components when properly excited), Stoneley waves (that typically propagate along a solid-fluid interface, and, more rarely, a solid-solid interface), and guided P- and S-waves. In many cases, some of these modes may be present simultaneously and are superimposed on each other. Different modes may dominate the propagation, depending on local conditions, even within a single survey. The common physical principle of different surface-wave methods is related to the fact that their penetration depends on their wavelengths, which, in turn, causes dispersion (different frequencies have different phase velocity). The dispersion is strictly related to the local properties, and hence, can be inverted to infer a near-surface velocity model (Socco et al., 2010). In the past few years, methods for processing and analyzing surface waves from high-volume production seismic surveys were developed and adopted (Strobbia et al., 2010; Strobbia et al., 2011). Surface-wave inversion for near-surface characterization is of particular interest in the presence of complex nearsurface conditions, such as velocity inversions. Here refraction methods fail and upholes, while providing pointwise measurements, are difficult to collect and expensive, in particular in presence of karst which can cause loss of circulation. Figure 1: Sketch of a simplified near-surface model across the two different areas. It is important to note that most of the surface waves (Rayleigh, Lamb, and guided S-waves) are sensitive to S- SEG Houston 2013 Annual Meeting Page 1811
wave velocity (V S ), while seismic reflection commonly uses P-wave velocity (V P ) for statics computation. The conversion from V S to V P can be relatively straightforward for sediments in arid areas where the Poisson ratio is known to take a very narrow range of values. Otherwise, calibration with refraction data, or uphole data, allows the V S to V P conversion. South Ghadames and Alwafa In Figure 2, the image shows the project area as the result of joining the recently acquired South Ghadames and legacy Alwafa 3D seismic surveys. One of the primary objectives was to seamlessly join the two surveys that were acquired with very different acquisition parameters and with a 10-year time gap, which requires a unique nearsurface modelling approach. Estimation of phase velocities is done here, following the approach proposed by Strobbia et al. (2011), which is based on the use of high-resolution, unevenly spaced F-K transforms to estimate the local properties of surface waves within a patch of receivers. The analysis workflow aims at extracting the local properties of the linear event of interest (surface-wave modes) and makes use of redundancy in the data to remove the effect of the propagation path from the source to the analysis point by extracting the local average phase gradient. The analysis can be run on source and receiver lines for typical 3D acquisition geometries and results are merged into a volume representing the surfacewave properties within a survey. a) (m) Figure 2: South Ghadames and Alwafa area. We describe the statics evaluation process in three steps: 1. Surface wave analysis The objective of the analysis is extraction of the local wavenumber as a function of frequency for different surface-wave modes. It can be observed that, in a gently varying spatial medium, the modal-phase gradient is essentially a surface-consistent parameter. If the waveform is obviously affected by the full propagation path, the kinematic properties of the surface wave, when excluding the near field, can be expressed in terms of local properties. At this stage, each location is considered one-dimensional and the local phase velocity can be inverted to obtain the vertical distribution of the near-surface velocities. Figure 3: Maps of: a) elevation (m) and b) phase velocity at 6.25 Hz (m/s). Ghadames South and Alwafa have different acquisition geometries. This leads us to estimate surface-wave phase velocity using source configurations for Ghadames South SEG Houston 2013 Annual Meeting Page 1812
(with a measurement on a 100 m by 100 m grid), and 2D receiver configurations for Alwafa. a) (m/s) The phase velocity map at 6.25 Hz is shown in Figure 3 and is compared with the elevation map (Figure 3a). The edge between the two surveys is hardly discernable, despite the two very different acquisition configurations. Note the detail that can be observed in defining structures by phase velocity variations, such as the paleo-wadi clearly visible in the west and the paleo-river channel in the south (Figure 2). 2. Surface-wave inversion The surface-wave phase velocities are inverted to give a near-surface velocity model for data processing applications. The geology shown in Figure 1 (strong velocity inversion on the surface) makes the surface-wave inversion particularly challenging because of the superposition of different modes (Rayleigh, Lamb and S- guided). a) (m/s) c) Figure 5: a) S-wave velocity at 28-35 m depth (m/s), b) P-wave velocity at 28-35 m depth (m/s), and c) V P/V S ratio maps. The black asterisks indicate uphole locations. Figure 4: Maps of: a) S-wave velocity at 42-49 m depth (m/s) and b) S-wave velocity at 77-84 m depth (m/s). To address these challenges, we follow the approach proposed by Ernst (2007) that involves minimizing the determinant of the stiffness matrix: an implicit function whose zeros are the solution of the secular function and correspond to modal curves. In particular, we consider the SEG Houston 2013 Annual Meeting Page 1813
misfit function proposed by Maraschini et al. (2010) based on the Haskell-Thomson matrix method adapted to take into account leaking modes (Boiero et al., 2009). This misfit function allows surface modes to be inverted without the need to associate experimental data points to a specific mode, thus avoiding mode identification errors in the retrieved velocity profiles. In Figures 4a and 4b, two S-wave velocity sections (42-49 and 77-84 m depth) are shown. The arrow highlights the low-velocity paleo-river channel that causes structural distortion in the stacked section if not properly identified and corrected. 3. Statics evaluation The conversion from V S to V P is carried out by calibrating the model using information extracted from upholes. In Figure 5, it is possible to note that, even if the uphole coverage is high, the sampling is not enough to describe the complex geology. Incorrect long-wavelength structure can be introduced by the use and interpolation of sparse uphole sampling and leads to derivation of sub-optimal statics solutions. For these reasons, is better to convert the densely sampled S-wave velocity volume (analyzing local V S to V P ratios) and to use the model derived from surface-wave inversion for statics. In Figure 6, a N-S stacked section is shown along with the near-surface velocity models used to evaluate travel time distortions. The model obtained by surface-wave inversion (Figure 6b) is more complex than what was expected integrating surface geology, topography and velocity information (Figure 6a). The statics solution associated to the surface-wave inversion velocity model is able to tilt the Dimbaba horizon (white arrows in Figure 6) to the expected position, matching information available from wells in the area. In Figure 6, the horizontal black line is reported to show the geological trend reconstructed from surface-wave inversion. Conclusions The inversion of data derived from surface waves contributes to robust statics solution estimation even when other techniques (i.e., refraction, upholes), present intrinsic limitations (velocity inversion, first breaks not easy to identify) or cost issues (difficulties in drilling and collecting measurements). The new inversion technology is able to deal with different phase velocity modes and solves the problem of complex near-surface geologies. In addition to the statics solution, the near-surface velocity model can also be used for linear noise modelling and attenuation, as well as depth imaging, or act as a reference model for full-waveform inversion. Acknowledgments We thank the Libyan NOC and BP Exploration for their support and the data used in this paper. In particular Tony Allen and Peter Simpson for their support throughout this project. Thanks also to WesternGeco for permission to publish this work, to our former colleague Claudio Strobbia for valuable discussions and to Emmanuel Saragoussi and Rodwan Swidan for their help in processing the data. a) b) Figure 6: Examples of stacks after static correction: a) simple geological model and b) model from surface-wave inversion. SEG Houston 2013 Annual Meeting Page 1814
EDITED REFERENCES Note: This reference list is a copy-edited version of the reference list submitted by the author. Reference lists for the 2013 SEG Technical Program Expanded Abstracts have been copy edited so that references provided with the online metadata for each paper will achieve a high degree of linking to cited sources that appear on the Web. REFERENCES Boiero, D., M. Maraschini, and L. V. Socco, 2009, P and S wave velocity model retrieved by multi modal surface wave analysis: Presented at the 71 st Annual International Conference and Exhibition, EAGE. Ernst, F., 2007, Long-wavelength statics estimation from guided waves: Presented at the 69 th Annual International Conference and Exhibition, EAGE. Maraschini, M., F. Ernst, S. Foti, and L. V. Socco, 2010, A new misfit function for multimodal inversion of surface waves: Geophysics, 75, no. 4, G31 G43. Socco, L. V., S. Foti, and D. Boiero, 2010, Surface-wave analysis for building near surface velocity models Established approaches and new perspectives: Geophysics, 75, no. 5, A83 A102. Strobbia, C., A. Laake, P. Vermeer, and A. Glushchenko, 2011, Surface waves: Use them then lose them. Surface-wave analysis, inversion and attenuation in land reflection seismic surveying: Near Surface Geophysics, 9, 503 514. Strobbia, C., P. Vermeer, A. Laake, A. Glushchenko, and S. Re, 2010, Surface waves: Processing, inversion, and removal: First Break, 28, no. 8, 85 91. SEG Houston 2013 Annual Meeting Page 1815