Velocity Model For Full Waveform Inversion Research Articles

Acoustic full-waveform inversion on land surveys: A case study on the Qademah fault, Saudi Arabia

Geophysical methods have been used to map a Qademah fault near a residential area in western Saudi Arabia. However, the location and spatial extension of the fault zone are still uncertain due to the limited resolution and length of geophysical surveys. We apply seismic full-waveform inversion (FWI) to a land survey 2 km in length, the result of which reveals more details of the fault as well as the subsurface. Before inversion, we remove the surface waves, converted waves, and other elastic phenomena in the f- k domain and normalize the trace amplitude to compensate for attenuation, such that wavefield modeling for FWI can be approximated by acoustic propagators with constant density. Due to the large wavefield amplitudes near the source-receiver positions, the FWI velocity gradient presents a singular zone in the near surface, which is muted to stabilize the inversion. We also invert the short-offset traces before the larger-offset traces to avoid cycle skipping at the far offsets and obtain a reasonable data fit despite some mismatches in the near offsets. The final FWI velocity model shows the Qademah fault at approximately 1000 m distance as well as three low-velocity anomalies at 100 m depth, confirmed by first-arrival traveltime tomography. We also observe a potential low-velocity layer at 250–300 m depth, which was not reported in former studies. This model can also be used for geologic interpretation, hazard assessment, and paleoseismology studies of the local area.

Waveform inversion with structural regularizing constraint based on gradient decomposition

Abstract Full waveform inversion (FWI) can simultaneously update low-to-medium wavenumber velocity components and high-wavenumber velocity components. However, if seismic data lack large-offset data and effective low-frequency components, FWI updates will be dominated by high-wavenumber velocity perturbation. Meanwhile, providing that the initial model is inaccurate, inversion will have the problem of local minima. In this study, FWI is developed with structural regularizing constraint based on gradient decomposition (RGDFWI). By correlating the separated forward wavefield and backward wavefield with specific propagating direction, FWI gradient is decomposed into tomography-mode gradient and migration-mode gradient. We propose an optimized strategy taking full advantage of the two modes of FWI gradient. On the one hand, we use tomography-mode gradient to enhance low-to-medium wavenumber updates. On the other hand, we use migration-mode gradient to apply structural regularizing constraint by estimating structure dip and adding sparsity constraint in Seislet domain. During the inversion process, high-wavenumber structural information constrains and guides low-wavenumber model updates. The results of two numerical tests, Marmousi model test and Overthrust model test, validate the optimized strategy, which can produce a better initial velocity model for FWI. The inversion finally generates a high-precision and high-resolution velocity model.

Faster determination of an initial velocity model for full-waveform inversion based on simulated annealing

Full-waveform inversion (FWI) is a prominent method commonly used to create detailed velocity models of the subsurface. However, because it relies on gradient methods, it suffers from the limitation of getting trapped in local minima. To avoid this problem, FWI needs to start from an initial velocity model that lies in the same region of convexity as the global minimum. Global optimization methods, such as simulated annealing, can be used to find such an initial velocity model. However, the iterative process of simulated annealing entails high computational cost, first because of the large number of iterations needed to explore the variables space, and second because of the large number of simulations needed to adjust the simulation parameters. Although the first issue is a common concern of previous work, the second issue is usually neglected, relying on trial and error. We introduce an approach to tackle the issues and then apply it within a simulated annealing framework we create. Our experiments using the Marmousi data yielded promising results when compared with previous work. We find that our approach almost eliminated the computational effort to fine-tune several simulation parameters. In addition, the number of iterations needed to explore the variables space is reduced by two orders of magnitude. FWI is able to find a detailed velocity model with high quality when using the initial velocity model generated by the method.

Atlantis — 20 years of seismic innovation finally removes the shroud of mystery

The Atlantis Field has gone through more than two decades of continuous seismic imaging efforts, during which time many innovative technologies were incubated, the most recent one being the successful application of full-waveform inversion (FWI) in salt environments. This technique led to a significant improvement in the subsalt image. However, imaging challenges remain for the Atlantis reservoirs, primarily due to the complex overburden salt geometries and the highly compartmentalized reservoir. Even with an improved velocity model from FWI, the conventional reverse time migration (RTM) images still suffer from illumination issues and contain strong migration swings that hinder the subsalt imaging and subsequent interpretations. Furthermore, early versions of FWI employed an acoustic assumption, leading to visible salt halos at the salt boundaries in the velocity model, which adversely impacted the reservoir imaging. In the last 12 months, elastic time-lag FWI (TLFWI) and FWI-derived reflectivity (FDR) imaging using long-offset ocean-bottom node data have minimized these imaging issues at Atlantis, providing another step change in subsalt understanding. Although the 3D RTM images using the elastic FWI velocity model are similar overall to their acoustic counterparts, the 4D time-lapse RTM images at Atlantis show noticeable improvements. Furthermore, FDR images derived from elastic FWI velocities show obvious benefits over the acoustic ones. With a more accurate modeling engine that allows for better match between synthetic and real data, FDR imaging shows improved illumination, higher signal-to-noise ratio, and better reservoir details over acoustic FDR imaging. This recent advancement in using elastic TLFWI has had immediate positive effects in facilitating the Atlantis Field's current and future development.

Insights Into Exhumation and Mantle Hydration Processes at the Deep Galicia Margin From a 3D High‐Resolution Seismic Velocity Model

AbstractHigh‐resolution velocity models developed using full‐waveform inversion (FWI) can image fine details of the nature and structure of the subsurface. Using a 3D FWI velocity model of hyper‐thinned crust at the Deep Galicia Margin (DGM) west of Iberia, we constrain the nature of the crust at this margin by comparing its velocity structure with those in other similar tectonic settings. Velocities representative of both the upper and lower continental crust are present, but there is no clear evidence for distinct upper and lower crustal layers within the hyper‐thinned crust. Our velocity model supports exhumation of the lower crust under the footwalls of fault blocks to accommodate the extension. We used our model to generate a serpentinization map for the uppermost mantle at the DGM, at a depth of 100 ms (∼340 m) below the S‐reflector, a low‐angle detachment that marks the base of the crust at this margin. We find a good alignment between serpentinized areas and the overlying major block bounding faults on our map, suggesting that those faults played an important role in transporting water to the upper mantle. Further, we observe a weak correlation between fault heaves and serpentinization beneath the hanging‐wall blocks, indicating that serpentinization was controlled by complex faulting during rifting. A good match between topographic highs of the S and local highly serpentinized areas of the mantle suggests that the morphology of the S was affected by the volume‐increasing process of serpentinization and deformation of the overlying crust.

3D high-resolution seismic imaging of the iron oxide deposits in Ludvika (Sweden) using full-waveform inversion and reverse time migration

Abstract. A sparse 3D seismic survey was acquired over the Blötberget iron oxide deposits of the Ludvika Mines in south-central Sweden. The main aim of the survey was to delineate the deeper extension of the mineralisation and to better understand its 3D nature and associated fault systems for mine planning purposes. To obtain a high-quality seismic image in depth, we applied time-domain 3D acoustic full-waveform inversion (FWI) to build a high-resolution P-wave velocity model. This model was subsequently used for pre-stack depth imaging with reverse time migration (RTM) to produce the complementary reflectivity section. We developed a data preprocessing workflow and inversion strategy for the successful implementation of FWI in the hardrock environment. We obtained a high-fidelity velocity model using FWI and assessed its robustness. We extensively tested and optimised the parameters associated with the RTM method for subsequent depth imaging using different velocity models: a constant velocity model, a model built using first-arrival travel-time tomography and a velocity model derived by FWI. We compare our RTM results with a priori data available in the area. We conclude that, from all tested velocity models, the FWI velocity model in combination with the subsequent RTM step provided the most focussed image of the mineralisation and we successfully mapped its 3D geometrical nature. In particular, a major reflector interpreted as a cross-cutting fault, which is restricting the deeper extension of the mineralisation with depth, and several other fault structures which were earlier not imaged were also delineated. We believe that a thorough analysis of the depth images derived with the combined FWI–RTM approach that we present here can provide more details which will help with better estimation of areas with high mineralisation, better mine planning and safety measures.

Innovative application of full-waveform inversion applied to extended wide-azimuth marine streamer seismic data in a complex salt environment

We demonstrate the application of full-waveform inversion (FWI) guided velocity model building to an extended wide-azimuth towed streamer (EWATS) seismic data set in the Gulf of Mexico. Field data are collected over a historically challenging imaging area, colloquially called the “grunge zone” due to the formation of a compressional allosuture emplaced between two colliding salt sheets. These data have a poor subsalt image below the suture with conventional narrow-azimuth data. Additional geologic complexities are observed including high-velocity carbonate carapace near the top of salt and multiple intrasalt sedimentary inclusions. As such, improved seismic imaging is required to plan and execute wells targeting subsalt strata. Significant improvements to the velocity model and subsalt image have been evident with wide-azimuth towed streamer and later EWATS data using conventional top-down velocity model building approaches. Subsequently, high-impact improvements have been made using EWATS data with an FWI velocity model building workflow; this study represents an early successful application of FWI used to update salt body geometries from streamer seismic data, wherein many prior applications were limited to improving sedimentary velocities. Later petrophysical data have verified the new FWI-derived model, which has significantly increased confidence in the structural and stratigraphic interpretation of subsalt reservoir systems below the grunge zone.

Improved imaging of gas hydrate reservoirs and their plumbing system using 2D elastic full-waveform inversion

Gas hydrates are ice-like crystalline materials that form under submarine environments of moderate pressure and low temperature. Another key factor to their formation is the abundance in gas supply from depth in addition to local biogenic gas. Detailed imaging and velocity analysis of the plumbing system of gas hydrates can provide confidence that amplitude anomalies in seismic data are related to gas hydrate accumulations. We have conducted 2D elastic full-waveform inversion (FWI) along a 14 km long segment of a 2D multichannel seismic profile to obtain a high-resolution velocity model of a hydrate system on the southern Hikurangi margin. We compare the FWI velocity model to previously published semblance- and tomography-based velocity models from the same data to explore how much more can be gained from the FWI. The FWI yielded a structurally more accurate velocity model that better delineated the low-velocity zone associated with free gas beneath the bottom simulating reflector (BSR) compared to the semblance- and tomography-based velocity models. Our results also find a lateral velocity inversion, that is, a narrow low-velocity zone surrounded by bands of higher velocities at a seaward-verging protothrust fault, which the two other methodologies failed to resolve. The FWI provides an improved lateral resolution making it an important tool when imaging the “plumbing” systems of gas hydrate reservoirs. In the southeastern limb of the anticline, our results find that the closely spaced landward-vergent protothrusts provide gas-charged fluids for hydrate formation above the BSR. Moreover, at the center of the anticline, our results find that a seaward-vergent protothrust fault appears to be acting as a conduit for gas-rich fluids into strata, although there is no accumulation of any significant hydrate above the BSR at the apex of the anticline. Our finding emphasizes the significance of densely spaced faults and fractures for providing gas for hydrate formation in the hydrate stability zone.

Shenzi OBN: An imaging step change

The story of seismic imaging over BHP's Shenzi Gulf of Mexico production field follows the history of offshore seismic imaging, from 2D to 3D narrow-azimuth streamer acquisition and to its leading the wide-azimuth movement with the Shenzi rich-azimuth (RAZ) survey. Each RAZ reprocessing project over the last 15 years applied the latest processing technology, culminating in hundreds of scenario tests to refine the salt model, but eventually the RAZ data reached a technical limit. A new ocean-bottom-node (OBN) survey acquired in 2020 has produced a step-change improvement over the legacy RAZ image. The uplift can be attributed to several factors. First, an OBN feasibility and survey design study demonstrated that a core of dense nodes combined with sparse nodes would improve the accuracy and resolution of the full-waveform inversion (FWI) solution. Second, the OBN data acquired following the survey design and employing FWI as the main model-building tool realized the predicted improvement. The result was a substantial change to the complex salt model, verified by a salt proximity survey as well as other salt markers, and improvement in imaging over the entire field. In addition to the improvement arising from a more accurate FWI velocity model, the steep-dip imaging also benefited from the new full-azimuth and long-offset data. However, the best steep-dip and fault imaging comes from the FWI image, a direct estimation of reflectivity from the FWI velocity. As the maximum frequency used by FWI moves toward the maximum frequency of the final reverse time migration (RTM), the FWI image approaches the resolution necessary to compete as the primary interpretation volume. Its subsalt illumination surpassed that of the RTM and even the least-squares RTM volumes. These imaging improvements are providing a new understanding of the faults and stratigraphic relationships of the field.

Reflection Full Waveform Inversion with Decoupled Elastic-wave Equations in Inhomogeneous Medium

Reflection full-waveform inversion (RFWI) can reduce the nonlinearity of inversion providing an accurate initial velocity model for full-waveform inversion (FWI) through the tomographic components (low-wavenumber). However, elastic-wave reflection full-waveform inversion (ERFWI) is more vulnerable to the problem of local minimum due to the complicated multi-component wavefield. Our algorithm first divides kernels of ERFWI into four subkernels based on the theory of decoupled elastic-wave equations. Then we try to construct the tomographic components of ERFWI with only single-component wavefields, similarly to acoustic inversions. However, the S-wave velocity is still vulnerable to the coupling effects because of P-wave components contained in the S-wavefield in an inhomogeneous medium. Therefore we develop a method for decoupling elastic- wave equations in an inhomogeneous medium, which is applied to the decomposition of kernels in ERFWI. The new decoupled system can improve the accuracy of S-wavefield and hence further reduces the high-wavenumber crosstalk in the subkernel of S-wave velocity after kernels are decomposed. The numerical examples of Sigsbee2A model demonstrate that our ERFWI method with decoupled elastic-wave equations can efficiently recover the low-wavenumber components of the model and improve the precision of the S-wave velocity.

Managing uncertainty to deliver complex development wells

SummaryManaging seismic depth uncertainty is a key consideration in placing horizontal development wells into thin reservoir targets. Seismic depth uncertainty has the potential to erode project value through missed reservoir (late landing or reservoir exits) and/or the cost of corrective actions (e.g. sidetracks). The placement of Laverda Canyon development wells in 2018 utilised a 30 Hz full waveform inversion velocity model and deep directional resistivity data in combination with a near real-time depth update process to optimise well placement.Utilising these methods resulted in a significant reduction in seismic depth uncertainty which culminated in the final Laverda Canyon development well (LAV04WI) being successfully geosteered for ~ 2,200 m within a 10-15 m thick reservoir with only one reservoir exit.

Parametric convolutional neural network-domain full-waveform inversion

Most current full-waveform inversion (FWI) algorithms minimize the data residuals to estimate a velocity model based on the assumption that the updated model is the sum of a background model and an estimated model perturbation. We have performed reparameterization of the initial velocity model, by the weights in a convolutional neural network (CNN), to automatically capture the salient features in the initial model, as a priori information. The prior information in CNN weights is iteratively updated as regularization to constrain the CNN-domain inversion to refine the features captured in CNN pretraining by reducing the data misfit. Synthetic examples using a 1D increasing velocity function v(z) and a 2D smoothed version of the correct Marmousi2 model as initial models indicate that the performance of the CNN-domain FWI depends on the existence and accuracy of the prior information in the initial velocity model (i.e., whether features whose positions, shapes, and values are present in the correct model are approximately included in the initial model). Forty different sets of randomly initialized CNN weights are used to parameterize and test CNN-domain FWI, using a 2D smoothed Sigsbee model as the initial velocity model. All 40 sets invert for the Sigsbee salt body more accurately (with a smaller standard deviation of the final rms model errors), by CNN-domain FWI, than FWI does. Features that are not represented within the CNN hidden layers in the initial velocity model, and so cannot be recovered by CNN-domain FWI, can be recovered using the final CNN-domain FWI velocity model as the starting model in a subsequent conventional FWI.

Imaging the Shallow Subsurface Structure of the North Hikurangi Subduction Zone, New Zealand, Using 2‐D Full‐Waveform Inversion

AbstractThe northern Hikurangi plate boundary fault hosts a range of seismic behaviors, of which the physical mechanisms controlling seismicity are poorly understood, but often related to high pore fluid pressures and conditionally stable frictional conditions. Using 2‐D marine seismic streamer data, we employ full‐waveform inversion (FWI) to obtain a high‐resolution 2‐D P wave velocity model across the Hikurangi margin down to depths of ~2 km. The validity of the FWI velocity model is investigated through comparison with the prestack depth‐migrated seismic reflection image, sonic well data, and the match between observed and synthetic waveforms. Our model reveals the shallow structure of the overriding plate, including the fault plumbing system above the zone of slow‐slip events to theoretical resolution of a half seismic wavelength. We find that the hanging walls of thrust faults often have substantially higher velocities than footwalls, consistent with higher compaction. In some cases, intrawedge faults identified from reflection data are associated with low‐velocity anomalies, which may suggest that they are high‐porosity zones acting as conduits for fluid flow. The continuity of velocity structure away from International Ocean Discovery Program drill site U1520 suggests that lithological variations in the incoming sedimentary stratigraphy observed at this site continue to the deformation front and are likely important in controlling seismic behavior. This investigation provides a high‐resolution insight into the shallow parts of subduction zones, which shows promise for the extension of modeling to 3‐D using a recently acquired, longer‐offset, seismic data set.

Crustal-scale depth imaging via joint full-waveform inversion of ocean-bottom seismometer data and pre-stack depth migration of multichannel seismic data: a case study from the eastern Nankai Trough

Abstract. Imaging via pre-stack depth migration (PSDM) of reflection towed-streamer multichannel seismic (MCS) data at the scale of the whole crust is inherently difficult. This is because the depth penetration of the seismic wavefield is controlled, firstly, by the acquisition design, such as streamer length and air-gun source configuration, and secondly by the complexity of the crustal structure. Indeed, the limited length of the streamer makes the estimation of velocities from deep targets challenging due to the velocity–depth ambiguity. This problem is even more pronounced when processing 2-D seismic data due to the lack of multi-azimuthal coverage. Therefore, in order to broaden our knowledge about the deep crust using seismic methods, we present the development of specific imaging workflows that integrate different seismic data. Here we propose the combination of velocity model building using (i) first-arrival tomography (FAT) and full-waveform inversion (FWI) of wide-angle, long-offset data collected by stationary ocean-bottom seismometers (OBSs) and (ii) PSDM of short-spread towed-streamer MCS data for reflectivity imaging, with the former velocity model as a background model. We present an application of such a workflow to seismic data collected by the Japan Agency for Marine-Earth Science and Technology (JAMSTEC) and the Institut Français de Recherche pour l'Exploitation de la Mer (IFREMER) in the eastern Nankai Trough (Tokai area) during the 2000–2001 Seize France Japan (SFJ) experiment. We show that the FWI model, although derived from OBS data, provides an acceptable background velocity field for the PSDM of the MCS data. From the initial PSDM, we refine the FWI background velocity model by minimizing the residual move-outs (RMOs) picked in the pre-stack-migrated volume through slope tomography (ST), from which we generate a better-focused migrated image. Such integration of different seismic datasets and leading-edge imaging techniques led to greatly improved imaging at different scales. That is, large to intermediate crustal units identified in the high-resolution FWI velocity model extensively complement the short-wavelength reflectivity inferred from the MCS data to better constrain the structural factors controlling the geodynamics of the Nankai Trough.

High-resolution impedance estimation using refraction and reflection FWI constraints: the Fortuna region, offshore Equatorial Guinea

Seismic imaging and reservoir characterization in the Fortuna region, offshore Equatorial Guinea, is beset with various geophysical challenges related to the presence of extensive, but small-scale low-velocity gas pockets, which give rise to significant and cumulative image distortion at target level. This distortion had not been resolved in a vintage 2013 broadband pre-stack depth migration project, as the velocity model was not sufficiently well resolved, but was subsequently addressed successfully in a project conducted using high-resolution non-parametric tomography with improved broadband deghosted data. The primary objective of that subsequent project was to improve the understanding of the internal structure of the Viscata and Fortuna reservoirs, and this objective was met via clearer internal imaging of these reservoir intervals and the overlying gas-charged sediments. The follow-on work considered here deals with the use of full waveform inversion to further delineate small-scale velocity anomalies associated with the highly compartmentalized reservoir units, and also to use the full waveform inversion velocity model as a constraint during acoustic impedance inversion. We compare the results of impedance inversion using both a conventional approach (with the well-log velocities to build the background trend), with a new approach using a trend derived from high-resolution waveform inversion velocities.

Two robust imaging methodologies for challenging environments: Wave-equation dispersion inversion of surface waves and guided waves and supervirtual interferometry + tomography for far-offset refractions

Two robust imaging technologies are reviewed that provide subsurface geologic information in challenging environments. The first one is wave-equation dispersion (WD) inversion of surface waves and guided waves (GW) for the shear-velocity (S-wave) and compressional-velocity (P-wave) models, respectively. The other method is traveltime inversion for the velocity model, in which supervirtual refraction interferometry (SVI) is used to enhance the signal-to-noise ratio of far-offset refractions. We have determined the benefits and liabilities of both methods with synthetic seismograms and field data. The benefits of WD are that (1) there is no layered-medium assumption, as there is in conventional inversion of dispersion curves. This means that 2D or 3D velocity models can be accurately estimated from data recorded by seismic surveys over rugged topography, and (2) WD mostly avoids getting stuck in local minima. The liability is that WD for surface waves is almost as expensive as full-waveform inversion (FWI) and, for Rayleigh waves, only recovers the S-velocity distribution to a depth no deeper than approximately 1/2 to 1/3 wavelength of the lowest-frequency surface wave. The limitation for GW is that, for now, it can estimate the P-velocity model by inverting the dispersion curves from GW propagating in near-surface low-velocity zones. Also, WD often requires user intervention to pick reliable dispersion curves. For SVI, the offset of usable refractions can be more than doubled, so that traveltime tomography can be used to estimate a much deeper model of the P-velocity distribution. This can provide a more effective starting velocity model for FWI. The liability is that SVI assumes head-wave first arrivals, not those from strong diving waves.

Full-waveform inversion: The next leap forward in subsalt imaging

Subsalt imaging has been a long-term challenge for the oil and gas industry. The substantial progress made in data acquisition and imaging since the late 1990s has made some subsalt imaging problems tractable, but building earth models that enable imaging under complex salt remains a challenge. Labor-intensive workflows remain industry standard practice. Not only are these costly and time consuming, they have also performed poorly in many areas of economic interest. Various automatic model-building tools have been proposed to overcome these disadvantages. One such tool, full-waveform inversion (FWI), has already revolutionized velocity-model building in areas with shallow gas. Prior to 2006, imaging in these areas had been considered challenging and labor intensive, just as imaging under complex salt remains today. Modeling indicates that low frequencies and wide offsets may be the key to success when building velocity models using FWI. Just how low and how wide that may be required for FWI success depends on the particular problem. At the Atlantis Field in the deepwater Gulf of Mexico we recently acquired wide-offset ocean-bottom-node data with conventional airguns. By taking care during the acquisition, we recorded usable signal down to a lower frequency than previously achieved. We then applied FWI to the resulting data set and used the resulting velocity model, unmodified, to reverse time migrate the seismic data. It produced some of the best subsalt images of the Atlantis reservoir structure ever seen. Furthermore, the FWI velocity model revealed several major interpretation errors in the legacy salt model; thus the FWI result also offered an excellent basis for updating the salt model with the conventional workflow. These results demonstrate that with appropriate seismic data to support it, and with due care taken during processing and inversion, FWI truly offers a paradigm shift in model building and imaging in areas of complex salt.

Toward a robust workflow for deep crustal imaging by FWI of OBS data: The eastern Nankai Trough revisited

AbstractCrustal‐scale imaging by the full‐waveform inversion (FWI) of long‐offset seismic data is inherently difficult because the large number of wavelengths propagating through the crust makes the inversion prone to cycle skipping. Therefore, efficient crustal‐scale FWI requires an accurate starting model and a stable workflow minimizing the nonlinearity of the inversion. Here we attempt to reprocess a challenging 2‐D ocean‐bottom seismometer (OBS) data set from the eastern Nankai Trough. The starting model is built by first‐arrival traveltime tomography (FAT), which is FWI assisted for tracking cycle skipping. We iteratively refine the picked traveltimes and then reiterate the FAT until the traveltime residuals remain below the cycle‐skipping limit. Subsequently, we apply Laplace‐Fourier FWI, in which progressive relaxation of time damping is nested within frequency continuation to hierarchically inject more data into the inversion. These two multiscale levels are complemented by a layer‐stripping approach implemented through offset continuation. The reliability of the FWI velocity model is assessed by means of source wavelet estimation, synthetic seismogram modeling, ray tracing modeling, dynamic warping, and checkerboard tests. Although the viscoacoustic approximation is used for wave modeling, the synthetic seismograms reproduce most of the complexity of the data with a high traveltime accuracy. The revised FWI scheme produces a high‐resolution velocity model of the entire crust that can be jointly interpreted with migrated images derived from multichannel seismic data. This study opens a new perspective on the design of OBS crustal‐scale experiments amenable to FWI; however, a further assessment of the optimal OBS spacing is required for reliable FWI.

An offshore Gabon full-waveform inversion case study

Velocity model building is one of the most difficult aspects of the seismic processing sequence. But it is also one of the most important: an accurate earth model allows an accurate migrated image to be formed, which allows the geologist a better chance at an accurate interpretation of the area. In addition, the velocity model itself can provide complementary information about the geology and geophysics of the region. Full-waveform inversion (FWI) is a popular, high-end velocity model-building tool that can generate high-resolution earth models, especially in regions of the model probed by the transmitted (diving wave) arrivals on the recorded seismic data. The history of the South Gabon Basin is complex, leading to a rich geologic picture today and a very challenging velocity model-building process. We have developed a case study from the offshore Gabon area showing that FWI is able to help with the model-building process, and the resulting velocity model reveals features that improve the migrated image. The application of FWI is made on an extremely large area covering approximately 25,000 [Formula: see text], demonstrating that FWI can be applied to this magnitude of survey in a timely manner. In addition, the detail in the FWI velocity model aids the geologic interpretation by highlighting, among other things, the location of shallow gas pockets, buried channels, and carbonate rafts. The concept of actively using the FWI-derived velocity model to aid the interpretation in areas of complex geology, and/or to identify potential geohazards to avoid in an exploration context, is applicable to many parts of the world.

Analytical approximations of diving-wave imaging in constant-gradient medium

Full-waveform inversion (FWI) in practical applications is currently used to invert the direct arrivals (diving waves, no reflections) using relatively long offsets. This is driven mainly by the high nonlinearity introduced to the inversion problem when reflection data are included, which in some cases require extremely low frequency for convergence. However, analytical insights into diving waves have lagged behind this sudden interest. We use analytical formulas that describe the diving wave’s behavior and traveltime in a constant-gradient medium to develop insights into the traveltime moveout of diving waves and the image (model) point dispersal (residual) when the wrong velocity is used. The explicit formulations that describe these phenomena reveal the high dependence of diving-wave imaging on the gradient and the initial velocity. The analytical image point residual equation can be further used to scan for the best-fit linear velocity model, which is now becoming a common sight as an initial velocity model for FWI. We determined the accuracy and versatility of these analytical formulas through numerical tests.