NSG2020 4th Applied Shallow Marine Geophysics Conference

Marine shallow gas characterization challenges industrial and academic research. Shallow gas are a risk for marine infrastructures and a limit to penetration of seismic methods to retrieve information on geological features and soil properties. Gassy areas cannot be investigated using seismic imaging because of the scattering effect of gas bubbles on the acoustic signal. Therefore, combining seismic imaging and marine electrical resistivity tomography (MERT) is considered. We present new geophysical results from the Bay of Concarneau (Brittany, France). This area includes several gassy zones, mainly observed within paleovalleys. We acquired multichannel ultra-high-resolution seismic imaging jointly with MERT data in order to better describe the geology and characterize the soil in presence of gas. Results show that the gassy areas are characterized by low resistivity values, indicating a high porosity of the sediment where gas has accumulated. P-wave velocity and resistivity globally vary in the same way, with low values in unconsolidated sediment filling and increasing values below the erosional surface. Two different laws depending on the depth of the considered area control the relationship between P-wave velocity and resistivity. Higher porosity and water content of the substrate close to the seabed can explain this result.

The last glacial cycle covers ~128kaBP to present. On the NW Australian shelf extensive seismic coverage has allowed geomorphological interpretation of an evolving coastal and fluvial landscape for an area encompassing the Bonaparte Gulf. It is possible to infer coastal positions and landscapes over the last glacial period denoted by Marine Isotope Stages (MIS) 5e-1. A key focus for the present study is MIS 4 where a lowstand relative sea level minimum of approximately 77-80m below present day developed ~63kaBP based on SE Australia measurements. This time range is consistent with some of the earliest recorded archaeology in Australia supporting human occupation of northern Australia by 65kaBP. In order for human occupation of Australia to have occurred by this time a sea crossing would have been required. The interpretation of geomorphological features from the seismic database has allowed prediction of most likely coastal position and possible tidal ranges during the MIS 4 lowstand in addition to contemporaneous depositional environments associated with reef, beach, estuarine, lagoonal and fluvial facies in an emergent landscape. The predicted palaeocoastline models are now being used to run simulations of tidal and ocean currents to inform possible maritime transit routes from Sunda to Sahul.

Ultra High Frequency-Multi Channel Seismic (UHF-MSC) data is increasingly being implemented in industry and academia to analyse and quantify shallow subsurface (c. <200m) conditions. However, its use is reliant on the production of consistent and reliable imaging or qualitative interpretations and the use of bespoke quantitative methodologies.

The imaging of UHF-MCS data can be cast through the use of either post-stack, pre-stack, time-domain and depth-domain. Traditionally post-stack time migration has been preferred processing methodology due to its low computational costs and relative insensitivity to velocity errors. While pre-stack time migration improves on signal to noise ratios and produces higher fidelity images, it is pre-stack depth imaging (PSDM) which allows for the highest fidelity images, specifically where lateral velocity variations occur and the geology of the near-surface is complex. However, the increased imaging potential of pre-stack depth migration is countered by a greatly increase computational and user cost.

Comparison of these migration strategies gives the opportunity to analyse the image improvements and the robustness of the velocity models used. The initial results show that the improvement in imaging and production of high-fidelity velocity models through the use of PSDM outweigh the increased computational and user cost during the UHF-MCS processing workflow.

The design and installation of offshore infrastructure such as WTG foundations requires a sound knowledge of the geological character of the sub-seafloor. The layout changes undertaken after the geotechnical campaign require the assessment of the geotechnical properties on not directly investigated locations within the windfarm area. In this study, we developed a flow to interpolate the quantitative interpretation from the 1D geotechnical data into a 3D volume. We apply synthetic seismograms calculated from available and interpolated geotechnical information and seismic wavelet derived from the seismic data to quantify the interpolation quality.

We investigate a simple Deep Learning Neural Network architecture to invert High Resolution seismic data for reflectivity and acoustic impedance. We generate synthetic reflectivity model and corresponding seismic traces by a simple convolution with a wavelet for training the machine learning network. Synthetic reflectivity models are correctly recovered when the reflectors separation is in the range of the train set. Noise in the data is correctly handled if the network is trained with adding noise on the data. Finally, we investigate the prediction of the acoustic impedance using the Marmousi model.