Fugro (Netherlands)

Abstract Multi‐channel analysis of surface waves is a seismic method employed to obtain useful information about shear‐wave velocities in the near surface. A fundamental step in this methodology is the extraction of dispersion curves from dispersion spectra, with the latter usually obtained by applying specific processing algorithms onto the recorded shot gathers. Although the extraction process can be automated to some extent, it usually requires extensive quality control, which can be arduous for large datasets. We present a novel approach that leverages deep learning to identify a direct mapping between seismic shot gathers and their associated dispersion curves (both fundamental and first higher order modes), therefore by‐passing the need to compute dispersion spectra. Given a site of interest, a set of 1D compressional and shear velocities and density models are created using prior knowledge of the local geology; pairs of seismic shot gathers and Rayleigh‐wave phase dispersion curves are then numerically modelled and used to train a simplified residual network. The proposed approach is shown to achieve high‐quality predictions of dispersion curves on a synthetic test dataset and is, ultimately, successfully deployed on a field dataset. Various uncertainty quantification and convolutional neural network visualization techniques are also presented to assess the quality of the inference process and better understand the underlying learning process of the network. The predicted dispersion curves are inverted for both the synthetic and field data; in the latter case, the resulting shear‐wave velocity model is plausible and consistent with prior geological knowledge of the area. Finally, a comparison between the manually picked fundamental modes with the predictions from our model allows for a benchmark of the performance of the proposed workflow.

Although the Pannonian Basin in Hungary boasts significant geothermal potential, most geothermal wells in the region suffer from reinjection issues. The aim of this study is to examine the impact of the sedimentary architecture of a paralic lacustrine succession on the static connectivity of a geothermal aquifer. This problem was examined for a case-study geothermal doublet drilled in Mezőberény, southeast Hungary, which experienced injectivity problems shortly after commencing operations in 2012, ultimately leading to shut-in of the wells. A characterization of the architecture of the deltaic aquifer has been undertaken through a novel workflow that combines sedimentological and sequence stratigraphic analysis of the well-doublet and stochastic 3D modelling techniques to assess the likely static connectivity between the production and injection wells. Planform dimension of aquifer-forming mouth-bar elements and fluvial channel bodies were estimated from geological analogues, selected based on the thickness values of such sedimentary bodies interpreted on the gamma-ray logs of the well doublet and nearby hydrocarbon wells. In total five mouth-bar and two fluvial channel input geometry groups were selected, and fifty object-based realizations were constructed to analyse the static connectivity of different geological scenarios. The internal lithology of mouth-bar and fluvial-channel elements were modelled by sequential indicator simulations (ten realizations). Results of connected volume analysis indicate that the sandstone content of the aquifer is located within vertically segmented fluvial-channel and mouth-bar elements separated by mud-prone prodelta and lower delta-front deposits. This architectural configuration, in combination with low net-sandstone content suggests limited connectivity between the wells. Across the set of stochastic realizations, the volume of sandstone connecting the injection and production wells is ∼4% of the total aquifer volume, on average. Results of this study shows that simplified reservoir models can lead to over-estimation of connectivity of geothermal doublets. The proposed workflow combines sedimentological analysis and 3D modelling supported by geological analogues to predict sandstone reservoir connectivity of deltaic geothermal reservoirs. The described workflow can be carried out in target areas using existing boreholes to assist borehole planning.

Free fall penetrometers (FFP) can improve the efficiency of deepwater geotechnical site investigations. This study investigates the derivation of geotechnical properties from piezocone FFP measurements in the upper 4 m of the seabed at a clayey site with water depths of ∼1500 m. Data analysis methods as commonly applied in cone penetration test (CPT) analysis were tested with strain rate normalization methods previously suggested for FFP analysis. The logarithmic, inverse hyperbolic sine, and power law approaches were applied for strain rate normalization. Strain rate effects appeared small for FFP cone resistance (with μ = 0.1 for the logarithmic and β = 0.06 for the power law approach), but were apparent. Undrained shear strength derived from FFP data matched overall the CPT results, using an N factor Nkt = 12. Undrained shear strength derived from excess pore pressure measured at the u1 position also yielded favorable results using N∆u _FFP = 6. Two soil behavior type classifications showed acceptable agreement between strain rate normalized FFP and CPT results.

A method of utilizing cone penetration tests (CPTs) is presented which gives continuous profiles of both the in situ thermal conductivity and volumetric heat capacity, along with the in situ temperature, for the upper tens of meters of the ground. Correlations from standard CPT results (cone resistance, sleeve friction and pore pressure) are utilized for both thermal conductivity and volumetric heat capacity for saturated soil. These, in conjunction with point-wise thermal conductivity and in situ temperature results using a Thermal CPT (T-CPT), allow accurate continuous profiles to be derived. The CPT-based method is shown via a field investigation supported by laboratory tests to give accurate and robust results.

The Lehane et al. (2017) pile load test (PLT) database (new PLT database) is one of the results of a joint industry project (JIP) to investigate the reliability of (CPT based) axial pile capacity methods for driven piles. The database contains results of high quality axial load tests of piles in sand and clay. This database was used to recalibrate five pile design methods for axial pile capacity of offshore piles. The methods considered were: For sand: Fugro-05 (Kolk et al., 2005) Fugro-05 (ISO, 2016) For clay: Kolk and van der Velde (1996) Centre for Civil Engineering Research and Codes (CUR, 2001) Van Dijk and Kolk (2010) The recalibrated methods obtain a lower coefficient of variation (COV) and a better prediction of the mean of the measured capacity of the PLTs of the new PLT database and hence they can be considered more reliable than the original methods.

Global Navigation Satellite System (GNSS) based Precise Point Positioning (PPP) has become the de facto standard for precise real-time offshore positioning applications. Current precision is of the order of 3−5 cm horizontally and twice this value for the vertical. However, this may not yet be good enough for tidal applications. In this contribution we will discuss new developments at Fugro, one of the world’s main providers of precise offshore real-time GNSS positioning services, to further improve PPP precision to the 2−3 cm level in the vertical component worldwide. For demanding applications, it is possible to even further improve this precision. These developments are based on merging PPP techniques (use of precise satellite orbits and clocks) with Integer Ambiguity Resolution (IAR), known from GNSS Real-Time Kinematic (RTK) positioning techniques. PPP IAR requires the generation and distribution to mobile users of Uncalibrated Phase Delays (UPDs) a network of reference stations. The network can be as small as one station or cover the entire globe. Once applied to the data of a mobile receiver, the carrier ambiguities should be integer. Fixing of these ambiguities to their proper integer value will result in significantly improved positioning performance. The infrastructure used to generate precise orbits, clocks and UPDs will be discussed. PPP IAR results will be shown from regional and global test beds, based on Fugro’s precise orbits and clocks for all currently available GNSSs. In addition, it will be shown that the introduction of new systems and signals, like triple-frequency GPS, Galileo and BeiDou, will help to significantly reduce the time required for PPP IAR solutions to converge to this centimeter level of accuracy.

High-level radioactive waste needs to be isolated from the biosphere for ∼1 million years. This can be achieved by embedding the waste in appropriate sealing material and then burying it within a suitable geological formation at considerable depth. Monitoring of disposed high-level radioactive waste requires non-intrusive methods to be applied. We have investigated the possibilities and limitations of seismic tomography for such a monitoring task. Changes within a repository are expected to produce subtle but measurable variations of the seismic waveforms when a high-quality sparker source and firmly grouted multi-component geophones are employed. Traveltime tomography is not expected to be particularly useful, but full-waveform inversions have the potential of characterizing changes within a repository. Application of the acoustic approximation proved to be unsuitable, but elastic inversions could provide useful diagnostic information.