The Cornerstone OBN data set delivers subsurface images of unprecedented quality in the most challenging areas of the UK Central North Sea, de-risking field development and near-field exploration.
Screen opportunities using the latest North Sea seepage data results, which comprise more than 5,000 interpreted satellite-borne radar scenes to provide unrivalled insight into the nature and locations of hydrocarbon seepage across the entire North Sea.
Understand and de-risk geothermal energy prospects, from exploration to production, with multidisciplinary
geoscience data, technology and expertise.
In this paper, we show, first, how a high-resolution 65 Hz Vp model, obtained using Time-Lag FWI, can improve the imaging from the shallow to the deep. Similar improvements are then shown for PS data using a 30 Hz Vs model obtained from PS reflection-FWI. The most remarkable achievement is the flattening of the undulating chalk and top reservoir surfaces on both the Vp and Vs FWI Images, obtained from PP and PS data, respectively, which was confirmed by drilling observations.
A major challenge in the US Gulf of Mexico is transforming disparate public datasets into a quality-controlled database. CGG has successfully created and used the database for its Storage Play Quality Index (SPQI) carbon storage screening methodology and applied its latest imaging technologies to rejuvenate the legacy seismic data.
This article discusses how machine learning and artificial intelligence methods can screen a large corpus of unstructured documents, locating and analysing core and thin section images for the purposes of porosity quantification, assignment of core and thin section scale sedimentary facies and the detection of hydrocarbon shows.
Dynamic Resolution Time-Lag FWI (DR-TLFWI) aims to use both diving waves and reflections for velocity update with optimized low- and high-wavenumber components from shallow to deep section. The proposed method builds contrast into the velocity model, enabling the simulation of reflections. The iterative velocity update scheme of DR-TLFWI handles multiples hence it can work with raw seismic data. The tomographic term of the velocity gradient from the reflection energy (lowwavenumber components) is typically much weaker than other components, due to additional reflections taking place during wave propagation. We propose to compensate these additional reflections by the corresponding illumination volume derived in each iteration of the FWI scheme. As such, a dynamic weighting can be devised for the different components in the FWI kernel to optimize the contributions across low- and high-wavenumber components of the velocity model. We use the time-lag objective function to avoid the dominance of strong amplitudes. Both synthetic and field dataset applications show that DR-TLFWI can reasonably update the velocity models from shallow section to deep beyond the reach of diving waves, especially when input data has a limited offset range. The images are improved accordingly with reduced structural undulations.
The Nordkapp Basin is a large under-explored salt basin of the Barents Sea. Despite several exploration campaigns over the past decades, no successful drilling was achieved. A new hybrid survey combining streamers and nodes was acquired in 2021 to unlock this new play. Sparse nodes recording continuously during a 3 months period, with a nominal spacing of 1200m in both inline and crossline directions, supplemented a natively dense source over streamer data acquired with 7 simultaneous sources and 18 cables. We present here a fully data-driven FWI flow designed to exploit and combine the different types of data recorded by this survey to obtain optimal velocity model. The flow combines the ultra-low frequencies diving waves obtained from node interferometry and the ultra-wide offsets of node active seismic gathers to obtain a background velocity model for accurately imaging salt flanks. For higher frequency FWI, the streamers dataset with its dense spatial sampling including more near offsets traces complemented the sparse OBN data. The final 200Hz FWI product allows to directly distinguish in the velocity model the Carnian sands target and reveals details in shallow as small as 3 to 4m, which opens up new possibilities for hydrocarbon and shallow hazard detections
The salars of the Lithium Triangle in South America contain approximately 55% of the world’s lithium resources (Cabello, 2021; Schulz et al., 2017). The source, transportation and concentration of the lithium-brines involves a complex mineral system that is dependent upon climate, weathering, basin closure, surface drainage, hydrothermal and groundwater systems, lithium-bearing rock distribution and geological structural control. A suite of satellite platforms, geological datasets, advanced data analytics and automated workflows has enabled the delineation and targeting of potential lithium-rich salars and paleosalars buried beneath recent sediments and volcanics.