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Absorption effects in the Earth attenuate high frequency seismic signal progressively with depth, reducing resolution and limiting the interpretability of the data. Conventional post-migration Q compensation methods often rely on artificial mechanisms to limit amplification of noise, at the expense of unintentionally restricting recovery of signal. We propose an amplitude Q compensation technique using 3D sparse inversion. Comparisons with a conventional approach on synthetic and field datasets highlight improved signal recovery and noise suppression with the proposed method.

Time-lapse seismic is now being used more frequently to assist reservoir development, prevent infrastructure damage or monitor geological storage. To better reveal true 4D signals while suppressing acquisition-related noise as a result of, for example, water velocity changes, source positioning errors etc., a new processing flow which focusses on correcting each noise-contributing factor based on its physical characteristics, has been developed to replace the conventional non-deterministic correction approach based on cross-survey matching. Our proposed flow is based on using common water bottom and the water-bottom travel time to invert each factor and correct for it, which allows for processing of each monitor survey independently and the possible acceleration of standard 4D processing timelines. We applied this workflow on two fields offshore Angola, one with strong subsidence and one without, and showed the superiority of this new approach to reveal the true 4D information. The subsidence effect, observable from the reservoir up to the water bottom, now better matches with the model of pressure changes in the new 4D results compared to legacy results. Even for field experiencing no subsidence effect, the time shift and NRMS maps obtained at the reservoir level are cleaner and easier to interpret from new flow.

Successful applications of full waveform inversion (FWI) to land datasets are far less numerous than marine applications, yet the development of dense, long-offset broadband acquisitions has presented promising opportunities. While challenges exist due to elastic effects, acoustic land FWI has been shown to provide accurate velocity models with a level of resolution traditionally seen only with marine data. The first successful land applications in Oman have been obtained on surveys with only minor variations in surface elevation, and have encouraged the development of FWI capabilities to handle more significant topography. We present a boundary-conforming free-surface topography method for FWI, cast in the curvilinear domain. In a synthetic example, we benchmark this approach against the use of an absorbing surface boundary and a replacement velocity in the air layer (the model extension method), and the method of applying statics shifts to compensate for elevation variations. Finally, we show two real data applications from North and South Oman where our free-surface topography tool illustrates imaging uplifts over FWI results obtained with an absorbing surface and legacy tomography.

Spanning decades of exploration and production in the United Kingdom Continental Shelf, many programs of towed streamer data have shaped our knowledge of the Central North Sea. However, the fundamental lack of illumination and azimuth/offset coverage provided by towed streamer geometries, remains a blocker to resolving the imaging challenges associated with many higher-risk Jurassic and Triassic plays. This means that existing streamer data is rapidly approaching the limit in the value it can add to our understanding of this mature basin. The Cornerstone ocean bottom node (OBN) program looks at using the well-known benefits of OBN data; full azimuths, long offsets and rich low frequencies, to provide a step change in imaging of this important region of the North Sea. This is achieved through improved model building, in particular the detail unlocked by full waveform inversion using the latest Time Lag cost function ( Zhang et al.,2018 ).Utilizing TL-FWI on this OBN data aimed at improving the entire section of the velocity model: the complex overburden, intra chalk and sub-chalk layers. In addition to the added illumination achieved from OBN data, the use of the multiples, further illuminates areas of the subsurface not captured in the primary wavefield.

CGG has always been at the forefront of industrial High Perfor­mance Computing (HPC) architectures: we were operating vector supercomputers (Convex, Cray and NEC) in the early 1990s, and large parallel supercomputers (Convex SPP, IBM SP, Sgi Origin) by the end of that decade. At the turn of the millennium, we were pioneering the use of commodity clusters, and started to add accelerators a couple of years later, even before GPGPU programming languages formally emerged.

The optimal transport problem was formulated more than 200 years ago to calculate the optimal way of transporting piles of sand. Due to the interesting properties of its solutions with respect to shifts between the compared distributions, optimal transport has recently been adapted to full-waveform inversion to mitigate the cycle-skipping issue. Various formalisms have been proposed. Here we present an overview of these approaches, emphasizing more specifically the approach based on the bi-dimensional Kantorovich-Rubinstein norm, which has led to numerous successful full-waveform inversion applications. We illustrate these successes with two onshore case studies from the Sultanate of Oman.