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Carbonate velocity model building is challenging due to the complex geometry and sharp velocity contrasts associated with carbonates. Full-waveform inversion (FWI), together with long offsets, wide azimuth and good low frequency data, is known to be a powerful tool to address these challenges. Unfortunately, many vintage streamer datasets are handicapped by limited offsets and azimuth coverage, and a noisy low-frequency component. We used vintage streamer datasets acquired in the South China Sea to demonstrate that Time-lag FWI (TLFWI), together with other tools like dipconstrained tomography and well calibration, can overcome those shortcomings and produce a highresolution velocity field, leading to improved images. TLFWI uses a crosscorrelation cost function to mitigate amplitude mismatch and low signal-to-noise ratio problems. However, the carbonates being out of reach of diving waves can still be challenging to update with FWI, if the starting background velocity is far from the true model. In this case, an iterative FWI flow with well-constrained velocity updates inbetween offers a more reliable solution. The carbonate fracture system poses another challenge for estimating anisotropic parameters inside the carbonate layer. Here we use diffraction imaging to guide the fracture system identification, which helps to estimate an HTI system.

For long in seismic imaging, velocity model building and depth migration/inversion have produced information on the subsurface velocity model with no overlap in terms of resolved vertical wavelengths. The not covered wavelengths, among which the famous mid frequency gap, had then to be recovered in stratigraphic inversion by external information such as borehole data. The progresses in terms of acquisitions (long offset and low frequency) and imaging tools put us now in the situation of an overlap between all these processing/imaging/inversion approaches. FWI provides for example a velocity model building tool that covers potentially the full range of vertical frequencies in the area investigated by recorded diving waves. High resolution tomography from its side reaches vertical resolutions up to 6 Hz overlapping the resolution that can be obtained from depth migration and then stratigraphic inversion with low frequency data (down to 2.5 Hz). This new status has motivated investigations about improved ways of integrating these sources of information. We review here several of these attempts that allow taking advantage of the various approaches for the benefits of reliability and interpretability of the results. The estimation of uncertainties in ray based tomography is for example a precious add on for assessing the reliability of the final result of the imaging/inversion workflow.

Assessing the uncertainty on the structural information contained in seismic images is critical for risk analysis in reservoir delineation, reserve estimation, and well planning. We propose here an original approach aiming at assessing structural uncertainties associated to ray based tomography. While it has similarities with formerly published approaches it is based on the random generation of equi-probable tomographic models rather than on randomly sampling the a posteriori “probability density function”. Moreover it is associated with non-linear slope tomography which allows considering some non-linear aspects of the problem. We think these two aspects offers significant advantages in terms of efficiency and accuracy. In this paper we carefully review the concepts and definitions (in particular the notions of confidence region and error bars), and then present our approach and discuss its advantages. We finally present an application to a North Sea dataset where we estimate errors bars for a target horizon.

Four recent case studies document how an advanced seismic workflow, which integrates geoscience data, enables operators to enhance their reservoir characterization interpretation.

The North West Shelf of Australia is a prolific hydrocarbon province hosting significant volumes of hydrocarbons, primarily derived from Jurassic and Cretaceous targets. A new regional, integrated geoscience study has been undertaken by CGG to develop new insights into the paleogeography and petroleum systems of Late Permian to Triassic successions which have historically been underexplored in favour of Jurassic to Cretaceous targets. This comprehensive analysis from a paleogeographic and petroleum system perspective provides a basin evaluation tool for Triassic prospectivity.

The Campos Basin, offshore Brazil, features complex shallow geology in the forms of pronounced seabed canyons and paleo-canyons. The rapid variations in the velocity field due to these complex shallow geologic features can be difficult for ray-based tomography techniques to resolve, resulting in distorted images in deeper section. Full waveform inversion (FWI) is able to utilize the recorded diving–wave energy to resolve the high-resolution velocity model in these geologically complex areas. Additionally, dip-constrained non-linear slope tomography introduces dip constraints to ray-based residual move-out tomography and is able to capture small-scale velocity anomalies associated with these shallow heterogeneities. A combined workflow of FWI and dip-constrained tomography enabled Chevron to build accurate and detailed velocity models in the Campos Basin, resulting in fewer seismic image distortions. We demonstrate the method using a Campos Basin, Brazil narrow-azimuth streamer dataset.

To help the industry identify new and previously overlooked prospects in Australia’s Gippsland Basin, CGG acquired a new basin-scale 3D seismic multi-client survey in 2020.

A new, proprietary technique that improves production forecasts has been demonstrated on an Asian gas field. Multi-scale ensemble-based history matching (MS-EnOpt) improves production forecasting and reserve estimation, and provides engineers with an understanding of key reservoir uncertainties.

Seismic inversion transforms seismic reflection data into quantitative rock-property descriptions of a reservoir. Seismic data bandwidth is limited by signal-to-noise ratio, absorption, source wavelet, and shot and receiver ghosts. A typical deterministic seismic inversion workflow fills the low frequencies by extrapolating or interpolating existing well logs along stratigraphic layers. The interpolation result is often biased by the well locations and quality of the well logs and can be affected by the interpolation method. We propose a 3-stage method to minimize the dependency of seismic inversion on a well-log based initial model and improving confidence in the final result.