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The merits of Total and Effective porosity approaches have always been a source of discussion within the Petrophysical community globally. In general, an operating company adopts a single approach (Total or Effective) in their modelling workflows and ignores the alternative method. This is normally to have a consistent approach across the company so that the end users know what they are receiving into their subsequent workflows. In the proposed method, both Total and Effective Porosity Methods have been applied. The differences are then used to minimise and improve the resulting porosity and saturation calculations such that the results are mutually comparable. Total Porosity based water saturation equations are dependent on the ‘shale/clay’ volume and porosity to compensate for the ‘shale/clay’ bound water resistivity. Effective Porosity is based on water saturation equations on the shale volume and resistivity. The difference is that the Effective Porosity Water Saturation approach is not directly dependent on the ‘shale/clay’ porosity and can be used as a fitting parameter via the dry clay density (that doesn’t exist in-situ) in addition to compensating for the invaded fluid volume. Examples will be presented in a wider range of geological environments will be discussed.

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.

In 4D (time-lapse) imaging, the primary objective is to obtain a 4D image that is sufficiently free of noise associated with acquisition and processing in order to understand the changes at the reservoir interval. To obtain accurate 4D products, all seismic processing steps must effectively mitigate the differences arising from inconsistencies in acquisition setup and recording conditions of the time-lapse surveys. One of the key steps of the 4D processing sequence is deghosting, which is commonly used to remove the ghost variations between the baseline and monitor vintages. Deghosting can eliminate the variations in source and receiver tow depths and produce normalized broadband datasets at the same datum (mean sea level), which serve as input for further co-processing. We present a 4D multi-sensor deghosting algorithm as an extension of recent deghosting technologies and apply it to a deep-tow multi-sensor streamer time-lapse survey acquired over the Liza field located offshore Guyana. The 4D image, which uses the proposed approach, shows significantly reduced 4D noise compared to result obtained with 3D deghosting of each vintage separately.

Geological bodies like sand injectites are found in numerous geodynamic and geological contexts around the world, and they can manifest as low- or high-amplitude seismic responses with complex structures. In this paper, we demonstrated an amplitude preserving DNN-based workflow for injectite detection using customized U-Net. Our workflow addresses the challenges inherent in the limited number of training datasets and produces a pretrained model that delineates injectite events on migrated seismic images. To address the issue of domain shifting, we proposed a transfer learning approach that avoids mis-predicting faults and other diffraction events as injectites. Finally, we discussed how this result could benefit the seismic processing workflow.

Seismic wavefields traveling through the subsurface lose energy due to various phenomena, such as geometric divergence and intrinsic attenuation. Imaging algorithms that account for these effects are well established. However, an often overlooked aspect of seismic imaging is transmission loss, which occurs due to propagating wavefields losing energy to back-scattered reflections. In this study, we examine the impact of transmission loss on various imaging algorithms and argue that it is not compensated for in standard applications of RTM and LS-RTM. Moreover, we find that transmission loss is naturally corrected for in the high-resolution reflectivity models derived from FWI Imaging, in which the effect is automatically encoded via sharp contrasts in velocity or density added to the earth model by the inversion. We assess the significance of transmission loss in different geological scenarios and evaluate the relative importance of this effect compared to other mechanisms that dissipate energy in the subsurface.

In this paper, we present the importance of a regional dataset, acquired and processed with the latest seismic imaging technologies to better understand the depositional environments of one of the main hydrocarbon plays in the Northern North Sea – the Upper Jurassic sandstones. Here we use frequency decomposition colour blending (RGB) to identify depositional pathways of Late Jurassic sands, where they can be seen to feed in from the east extending across to the west through deep water canyon systems, largely controlled by fault systems.

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

Superimposed reservoirs are common in oil and gas production, but they are challenging to monitor with time-lapse seismic imaging. A common seismic attribute used for assessing reservoir evolution during production is the time-shift measurement which is obtained comparing two 3D seismic images. In the case of superimposed reservoirs, computing these time-shifts becomes challenging due to the change at the top reservoir that affects measurements at the lower one. Directly computing the wave propagation velocity variation between the time-lapse seismic data is an alternative solution. These obtained velocities need to reach a sufficiently high frequency to ensure a vertical resolution to correctly separate the reservoirs. On two offshore West-African case-studies, we illustrate how 4D FWI workflow can finely separate superimposed reservoirs, by providing high resolution velocity variations along the monitoring time. The first case study consists of short offset towed streamer acquisition where the challenge of missing low frequency and diving wave penetration is undertaken by a combination of 4D tomography and 4D FWI. For the second case study, long offset node records mean that only the 4D FWI is needed. This time saving allows for prompt delivery of the velocity variation with time without requiring a complex time-lapse processing beforehand.

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.