An overview of the general oil exploration landscape in Norway with a description of the Horda survey, concentrating on the acquisition, but including references to the complete integrated geoscience package that will eventually be delivered
In the Barents Sea, bright amplitudes on seismic data below the Base Quaternary indicate the presence of hydrocarbon reservoirs. To allow characterization and quantitative interpretation of these potential reservoirs, analysis of amplitude versus reflection angle (AVA) information is crucial. Even with the availability of high-quality Q-Kirchhoff pre-stack depth migration (Q-KPSDM) products, transmission-absorption relating to shallow gas pockets along with residual surface-related and interbed multiples may compromise the imaging of these shallow reservoirs. By using the full wavefield, imaging from full-waveform inversion (FWI Imaging) provides a reflectivity image without the need to perform the usual pre-processing and migration steps, offering the potential for improved handling of multiples and transmission issues. While FWI Imaging has delivered superior results in terms of imaging compared to more conventional migration methods, it has so far only provided a structural image without access to common image gathers used to derive AVA information. In this study, we extract elastic information from acoustic FWI Images generated from impedance updates using angle-restricted raw seismic data. The results of the angle-restricted FWI flow provide comparable AVA products to those obtained from a conventional Q-KPSDM approach, but with an improved signal-to-noise ratio in areas with complex near-surface geology.
We present AI-drive workflow for automatic interpretation of large seismic volumes. The workflow is applied to an offshore Abu Dhabi area of 15000 km2. First, we show the fault detection results for the low-magnitude faults of strike-slip type by the fine-tuning of the DNN.
Since the discovery of pre-salt oil fields offshore Brazil two decades ago, the Santos Basin has transitioned from an exploratory to a development phase. This requires a more comprehensive understanding of the reservoir physical properties. This study aims to demonstrate, on one of the biggest Brazilian oil fields, how five years of technological evolution for OBN processing can improve our understanding of the pre-salt reservoir. The Tupi producing field presents various imaging challenges due to its thick and stratified salt and complex pre-salt layer. The latest technologies, such as elastic Time-Lag FWI, RTM angle gathers using spherical binning and internal multiple attenuation, provide a more accurate velocity model, as well as better fault definition and AVA response. The impact on reservoir-based inversion of the Vp/Vs ratio shows decreased uncertainty at the target level.
Traditional petrographic analysis of rock thin sections is time consuming, it is potentially subjective, may suffer from operator bias, and the results are not necessarily representative of the bulk rock sample. The challenge to automation of petrographic description is the complexity that is inherent to geology; sedimentary rocks often contain many types of grains, cements, and pores. Here, we present a machine learning solution to automatically characterize minerals and grains in rock thin sections on a whole slide basis.
Full-waveform inversion (FWI) is a well-established technology for building high-resolution velocity models over complex areas. Conventional industry implementations of FWI typically use the acoustic approximation, which can break down in the presence of strong velocity contrasts where elastic effects in the recorded data cannot be ignored. These issues are well-known for salt and sub-salt areas, where elastic FWI becomes the recommended solution.
Significant subsurface imaging distortions are frequently encountered in intricate faulted structures below substantial gas accumulations in the overburden. The primary difficulty arises from the absorption of seismic energy by gas bodies, and the presence of complex velocity heterogeneities. In these settings, visco-acoustic Time-lag Full Waveform Inversion (Q-TLFWI) proves to be a valuable tool. Nevertheless, when these complex structures are not well illuminated by the diving waves, Q-TLFWI may struggle to rectify velocity errors. This paper demonstrates the application of Dynamic Resolution Q-TLFWI (DR-Q-TLFWI) for a typical narrow-azimuth streamer survey in offshore Indonesia.
This study demonstrates how a high-end 3D seismic survey can generate new insights within a frontier basin such as the Deepwater Zambezi Delta in Mozambique and uncover hidden facets of basin evolution. Observations from high-resolution seismic imaging integrated with potential fields data have helped demarcate crustal domains of the Northern Beira High and Zambezi Delta Depression.
We describe opportunities and challenges for imaging seismic data acquired using conventional marine sources and receivers located on the seafloor. Opportunities include the promise of greater imaging resolution than sea-surface acquisition and processing can offer, especially using P-wave to S-wave converted reflection energy (PS imaging). Challenges include effects of current seafloor receiver spacing, which can be large enough to negate the promised resolution gains. We use a synthetic dataset to illustrate possible imaging improvements that can result from seafloor acquisition, as well as image degradation that can result when seafloor receivers are separated by typical current distances.