Getting closer to deepwater reservoirs with pioneering OBN imaging Benefits of latest OBN imaging technology open door to new era of subsalt imaging

Investment in deepwater exploration and development is on the rise. Although the often prolific subsalt plays offer high rewards for explorers, they can bring potentially higher development costs and risks. For fields and prospects in particularly complex settings, existing towed-streamer data sets are reaching their technical limits. Despite dramatic recent improvements in streamer data processing and velocity models, there can still be considerable uncertainty in the interpretation of these images.

With the resulting growth in large-scale ocean bottom node (OBN) surveys to provide greater interpretation certainty, the industry is entering a new era in subsalt imaging. At this year's SEG Annual Conference in San Antonio, CGG will be presenting a range of papers showcasing the latest OBN imaging technologies and case studies.

Better, data-driven salt velocity models

A common thread in these presentations is the ability to take full advantage of the valuable low-frequency, full-azimuth, ultra-long offset information recorded in OBN surveys to drive full-waveform inversion (FWI) velocity model building. Yao et al. determine that, for the Stampede field in the Gulf of Mexico, lower frequencies and ultra-long offsets from OBN data are key factors for increasing the detail of complex sediment inclusions in the salt velocity model using FWI.

The combination of FWI and OBN data also supports a data-driven approach to velocity model building which can reduce project cycle time. Traditional velocity model building sequences based on manual salt interpretation require an accurate salt model to obtain an image that can be interpreted. Recent developments pioneered by CGG, particularly time-lag FWI, have streamlined the update of salt models, alleviating the manual interpretation bottleneck and bringing a step-change to subsalt imaging in some of the most complex areas.

A case study update from the Santos Basin by Jouno et al. shows that, with a reasonable initial model, time-lag FWI applied to OBN data can recover fine internal detail of the stratified evaporite sequence and the pre-salt sediments.

The use of sparse OBN surveys designed purely to provide information for velocity model building has been proposed and is the focus of a study performed on the Atlantis field (Mei et al.). The study indicates that OBN spacing of 1 km x 1 km can be sufficient to achieve a satisfactory velocity model for subsalt imaging using time-lag FWI. This approach provides one strategy to achieve imaging uplift from existing streamer data sets across large areas.

A bright future for OBN Imaging

OBN imaging and FWI technology will be hot topics in the industry for years to come, particularly in areas with complex salt overburdens which obscure the reservoir. Work continues on improving various aspects of OBN processing, including internal multiple attenuation (Pereira et al.) and application of advanced imaging techniques, such as least-squares reverse time migration (Liu et al.), to deliver more reliable subsalt reservoir images and attributes. For FWI, discussions continue on improving starting models and incorporating 'more physics' into the algorithms to improve accuracy where effects such as anisotropy and absorption are significant.

These ongoing developments promise further improvements in subsalt imaging which will continue to reduce exploration risk. The technical session at this year's, and future, SEG Annual Conferences will be well worth attending!


Time-lag FWI using OBN data in the Gulf of Mexico with a complex sediment-salt interface close to the deep base of salt. Before the FWI update: (a) legacy velocity model without smoothing and (b) OBN RTM stack image produced using the legacy model. After the TL-FWI update: (c) updated velocity model from FWI using OBN data and (d) OBN RTM stack image produced using the FWI-updated velocity model.

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CGG SA published this content on 16 September 2019 and is solely responsible for the information contained therein. Distributed by Public, unedited and unaltered, on 16 September 2019 15:46:01 UTC