84th EAGE Annual Conference & Exhibition Workshop Programme

The deformation or collapse of tracks, due to sinkhole formation beneath railway platforms, is a natural hazard that affects train traffic regularity, causes extra maintenance costs, but also leads to crucial safety issues.

This paper illustrates an innovative seismic monitoring workflow that uses trains as seismic sources. Thanks to dense networks of seismic sensors (geophones, accelerometers or DAS), continuous data are acquired and processed on-site or remotely. The opportunistic surface waves emitted by passing trains are processed using a dedicated workflow, based on a “Double Matched Field Processing” methodology. This allows to inverse dispersion curves on a daily basis, and provides high-resolution (∼1–2 m) seismic imaging of the near surface beneath railway platforms (from 0 to 50 m in depth).

We look for spatial and temporal anomalies in the velocity models, in order to reveal soil de-compaction and/or genesis and growth of cavities.

This method has been successfully deployed for short or long term missions on different case studies and has shown evidences of cavities or slow de-compaction area.

Creating images from high-resolution FWI models by taking some form of the spatial derivative of the velocity has quickly become a popular way to generate reflectivity images, typically called FWI Imaging. FWI imaging offers the possibility of high-quality and high-resolution in a more simplified workflow compared to the conventional processing, model building and imaging workflow. Such images are being increasingly used as alternatives or even replacements of the conventional, or least-squares, Kirchhoff and RTM products.

Using data examples of FWI imaging we demonstrate its benefits; after drawing conclusions we consider some of the challenges of working with FWI imaging that have formed the basis of ongoing or recently completed work.

Access to ultra-low frequencies is key for full waveform inversion (FWI) in under-explored areas where the knowledge of initial velocity model is limited. While acquisition efforts are heading towards development of low frequency sources, interferometry is providing a way to reconstruct ultra-low frequencies down to 0.5Hz from continuous recordings of ambient noise ( Le Meur et al, 2020 ). We review here a case study from the Nordkapp salt Basin, a challenging exploration area for velocity model building and imaging. OBN interferometry applied on 3 months records from a 2021 hybrid acquisition combining streamers and sparse nodes allowed to properly reconstruct surface and diving waves. This opened the way to stable low frequency FWI updates able to properly resolve salt bodies delineation, which couldn’t be captured with active seismic FWI only. In addition to the use of reconstructed diving waves via FWI, surfaces waves in virtual source gathers were also exploited through the picking of dispersion curves. The use of multi-wave inversion (MWI) combining first-break and surface-wave dispersion curve picks information ( Bardainne, 2018 ) then led to an initial Vp/Vs estimation.

Applying reactive flow simulators to de-risk mineral exploration projects require the correct and accurate modelling of the water chemistry and the related rock-water interaction (reactive flow) in a way that is commercially feasible. The largest obstacle is the computational effort for the water chemistry modeling, resulting in long simulation times. Fast and fit for purpose solutions are needed. To address this challenge, we have combined TerrantaFlow (www.terranta.de) for the fluid flow modeling and Reaktoro (www.reaktoro.org) for the geochemical calculations.

The fluid flow simulator solves a coupled thermal and mechanical (pore fluid pressure, rock compaction and stress) problem, while the chemical equilibrium and kinetics solvers provides the reactive part for our simulations.

Based on a case study from Silvermines, Ireland, we illustrate how reactive flow modeling can be made fast enough to become a routine application in de-risking mineral exploration projects. The same technological approach can be used for other subsurface geo-modeling applications and assessments such as Geothermal, CCUS or radioactive waste disposal.

Depending on the hydrocarbon source and CO2 capture processes, flue gas from boilers may be accompanied by impurities that can be co-injected into a geological storage. These gases (SOx, NOx, oxygen…), can interact with reservoir fluids, rocks and well materials and could affect the safety of the storage. However, there is currently little data on the behaviour of such gas mixtures and their chemical reactivity, particularly in the presence of water. One reason for this lack is the difficulty of handling them due to their hazardous nature and high chemical reactivity.

The aim of this study is to couple Raman spectrometry and Monte Carlo simulations to acquire new thermodynamic data for NOx/SOx/water systems in deep storage conditions. An innovative experimental setup is coupled with Raman microspectrometry to identify and quantify molecular species in the fluid phases. Silica micro-capillaries are loaded with NO(g) or SO2(g) and water. Micro-capillaries are transparent and allow visualisation of the different phases, quantification of their volume and analysis of their chemical composition by Raman spectrometry. These micro-reactors allow the investigation of temperatures from −180° to 600°C and pressures up to 1.5 kbar. This method allows to work safely with micro-volumes of dangerous gases.

Kyparissiakos concession block is located offshore western Greece to the south of Zakynthos Island and is a frontier area. Presence of source rock has been verified, but there is absence of outcrops and deep wells around Kyparissiakos Block. This study is focused on the derisking of source-rock presence, based on a H/C seepage study.

Thermogenic gas seepages at the Katakolo Peninsula, accompanied with the West Katakolo offshore discovery is the first evidence of a working petroleum system in the vicinity of Kyparissiakos Block.

Rock Volatiles Stratigraphy (RVS) is a unique technology based on a novel cryo-trap mass spectrometer system developed by Advanced Hydrocarbon Stratigraphy. With direct measurements of 40+ volatile compounds the analysis of subsurface fluids entrained in rock samples, a comprehensive and unique understanding of the subsurface is possible even if only a few grams of several decades old materials are all that is available. While developed for oil and gas applications, the technology has subsequently been applied to a variety of fields including carbon capture and storage site assessments, helium and hydrogen exploration and subsurface system assessments, and enhanced geothermal systems. The workshop presentation will focus on the technology and several key oil and gas studies in 2019 that led to the eventual application of RVS to these non-oil and gas field as well as a survey of work being done in them. A focus will be how learnings in one field with RVS can be transferred to others given the large available datasets of measured compounds and related rock properties generated from the analysis.

Seismic interferometry (SI) retrieves new seismic responses between receivers or sources using, e.g., cross-correlation. Applying SI to a reflection survey with active sources and receivers at the surface, one retrieves ghost reflections besides the physical reflections. Ghost reflections are retrieved from the correlation of two primary reflections or multiples from two different depth levels. They are only sensitive to the changes in the layer that cause them to appear in the result of SI.

Using ghost reflections from SI, we investigate the possibility of monitoring pore-pressure depletion due to gas extraction in the Groningen gas field, Netherlands. We performed an active-source transmission laboratory experiment to measure S-wave velocities at pore pressures of 50, 80, 100, 200, and 300 bar. Using these values; we numerically model scalar reflection data with sources and receivers at the surface for the Groningen subsurface model. Applying SI by auto-correlation to these datasets, we retrieve zero-offset ghost reflections. We show that using only the reflections from the top and the bottom of the reservoir is essential for retrieving a specific ghost reflection from inside the reservoir. The retrieved ghost reflections showed clear time differences, indicating they can be utilized to monitor reservoir pore-pressure depletion changes.