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With the new broadband acquisitions, allowing to record frequencies down to 2,5 Hz, and the new tomographic tools, allowing to resolve for vertical velocity components up to 6 Hz, we have moved for velocity model building from the situation of a mid-frequency gap to the situation of an overlapping area in terms of resolution we can expect from tomography and migration-inversion. Full waveform inversion-guided migration velocity analysis has been proposed as an approach taking advantage of this new situation. We show here a first real data application of this innovative approach.

This case study highlights how the application of an optimized hydraulic fracture stimulation plan, by honoring lateral well geological heterogeneities measured by RoqSCAN, improved completion efficiency and well production within the Cleveland Sandstone formation, Oklahoma, USA.

In seismic land acquisition, harmonic–noise in vibrator ground-force has always been a major limitation in terms of data quality and productivity. In high productivity acquisition, vibrator distortion is usually prevented by waiting enough time between successive shots. Otherwise, it has to be reduced during seismic data processing. The low-dwell sweeps that are now currently used in production can induce even more important distortion issues. Harmonics from low frequency content can be considerably more spread out over time after correlation. Consequently, the extensive use of the low-frequency bandwidth for vibro-seismic sources prompted the need for improved distortion control, especially at low frequency. This paper describes a method to mitigate the harmonic distortion directly before emission. The output noise is measured and injected adaptively with opposite phase in the source input to converge towards an ideal output. The results show important noise reduction over the full bandwidth, with perfect low-frequency fidelity. A better source signal quality provides better seismic data that is easier to process, and opens new possibilities in terms of acquisition scenarios with possible productivity improvement.

The quality of the seismic data you record depends on the quality of the energy generated by the source, how it interacts with the subsurface and the ability to record all the effects of those interactions. To obtain the required response from the reservoir it is necessary to start with the right sound, at the right level, from the right angle. This requires the use of the right survey design, with the right equipment and the right acquisition methods, as well as preserving all the recorded information through advanced broadband processing and imaging. By integrating all the available geological knowledge with existing gravity and velocity information it is possible to design the optimum acquisition parameters for a survey. This integrated approach was used to design, acquire and process the new 25,000-km2 broadband multi-client 3D survey offshore Gabon, that covers the five blocks on offer in Gabon’s new deepwater license round.

Gulf of Mexico (GOM) subsalt imaging often suffers from poor illumination due to salt-related wavefield distortion, even with full-azimuth (FAZ) acquisition. In order to image the weakly illuminated subsalt plays, isolating the signal from the noise is a crucial component of many depth imaging practices. Reverse Time Migration (RTM) subsurface 3D dip-azimuth gathers, which separate seismic data into different dip/azimuth components, have been utilized to address illumination problems in structure-oriented imaging techniques. We proposed a weighting scheme on RTM 3D dip gathers for imaging enhancement based on a priori structure information targeting the noise which has conflicting dips with the structure. We further discussed and evaluated the sensitivity of the method to the uncertainty of the priori structure dipping information. We applied the method on subsalt structures on a synthetic data set and a real data set with staggered acquisition full azimuth data. The tests demonstrated the necessity of signal-to-noise ratio enhancement in the imaging of FAZ, long-offset data and the effectiveness of RTM 3D dip gathers in unmasking poorly illuminated zones.

In this article, we focus on variable-depth streamer acquisition and propose a full broadband processing solution that involves three important components: (a) 3D deghosting; (b) Q estimation using Q-Tomography; (c) Q application via Q pre-stack depth migration (Q-PSDM).

We have developed a method to jointly depth invert frequency and time domain Airborne EM data in complex topographic and geologic environments, in 2.5D and 3D. Inversion of synthetic and field data show that using AEM data sets with complimentary information (geo-steering) increases the effective resolution of the near-surface significantly.

We present an efficient convex optimization strategy enabling the simultaneous attenuation of random and erratic noise with interpolation in pre-stack seismic data. For a particular analysis window, frequency slice spatial data can be reorganized into a block Toeplitz matrix with Toeplitz blocks in the spirit of Cadzow / Singular Spectrum Analysis (SSA) methods. The signal and erratic noise are respectively modeled as low-rank and sparse components of this matrix, then a Joint Low-Rank and Sparse Inversion (JLRSI) enables us to recover the low-rank signal component from noisy and incomplete data thanks to a joint minimization of a nuclear norm term and a L1 norm term. The convex optimization framework, related to recent developments in the field of compressed sensing, enables the formulation of a well-posed problem as well as the use of state-of-the-art algorithms. We suggest here an Alternating Directions Method of Multipliers (ADMM) scheme associated to an efficient singular value thresholding kernel. Numerical results on field data illustrate the effectiveness of the JLRSI approach at recovering missing data and increasing the signal-to-noise ratio.

Using pre-stack model-based inversion we will analyze the impact of marine seismic acquisition and processing on our ability to predict elastic parameters.