Summary The objective of this study is to find an efficient way to measure bedrock depth and geotechnical parameters through the estimation of shear wave velocity, Vs. The Norwegian Geo Test Sites (NGTS) initiative aims to establish five national test sites as field laboratory for testing innovative soil investigation and foundation methods. We have measured ambient seismic noise data as well as Multichannel Analysis of Surface Waves (MASW) data at two NGTS sites, Onsøy and Halden. The results of the shear-wave inversions are compared with ground-truth measurements from the two well-characterized sites. The results obtained with the passive seismic test and the MASW active test are quite similar despite the fact the passive method requires less time and equipment in the field.
Methods based on the seismic P-wave, seismic surface wave, and apparent resistivity are commonly used in the solution of several near-surface problems. However, the solution nonuniqueness and the intrinsic limitations of these methods can cause inconsistency in the final results. Dispersion curves of surface waves, P-wave traveltimes, and apparent-resistivity data were jointly inverted to obtain internally consistent and more reliable final model of P- and S-wave velocities and resistivity. A collection of 1D layered models was obtained by a deterministic joint-inversion algorithm based on the laterally constrained inversion scheme. The three data sets were jointly inverted imposing the same structure and Poisson’s ratio was introduced as a physical link between P- and S-wave velocities to better constrain the inversion. No physical link was imposed between the resistivity and the seismic velocities. The inversion algorithm was tested on synthetic data and then applied to a field case, where benchmark borehole data were available. The synthetic and field examples provided results in agreement with the true model and the existing geologic information, respectively.
An extensive airborne electromagnetic (AEM) survey was carried out in Norway with the primary purpose to obtain information of depth to bedrock in areas with little or no prior geotechnical knowledge. We present different approaches to extract a bedrock model from the high-resolution time-domain AEM data, including both automated and manual procedures. It was found that in the area of investigation a user-driven approach of manual bedrock picking was the most suitable, taking into account the strongest vertical resistivity gradient and geological information as additional information. A semi-automatic, statistical method, called Localized Smart Interpretation (LSI), is also presented and discussed. This method, while not included in the original bedrock model for the entire area, showed promising results while using less time compared to the fully manual approach. It is recommended that LSI be considered in future projects of similar scope.
Abstract. Monitoring microseismic activity provides a window through which to observe reservoir deformation during hydrocarbon and geothermal energy production, or CO2 injection and storage. Specifically, microseismic monitoring may help constrain geomechanical models through an improved understanding of the location and geometry of faults, and the stress conditions local to them. Such techniques can be assessed in the laboratory, where fault geometries and stress conditions are well constrained. We carried out a triaxial test on a sample of Red Wildmoor sandstone, an analogue to a weak North Sea reservoir sandstone. The sample was coupled with an array of piezo-transducers, to measure ultrasonic wave velocities and monitor acoustic emissions (AE) – sample-scale microseismic activity associated with micro-cracking. We calculated the rate of AE, localised the AE events, and inferred their moment tensor from P-wave first motion polarities and amplitudes. We applied a biaxial decomposition to the resulting moment tensors of the high signal-to-noise ratio events, to provide nodal planes, slip vectors, and displacement vectors for each event. These attributes were then used to infer local stress directions and their relative magnitudes. Both the AE fracture mechanisms and the inferred stress conditions correspond to the sample-scale fracturing and applied stresses. This workflow, which considers fracture models relevant to the subsurface, can be applied to large-scale geoengineering applications to obtain fracture mechanisms and in-situ stresses from recorded microseismic data.
Summary In this paper, we present a rock physical model to estimate the porosity from the seismic velocities and compare it with existing rock physical models. A parameter sensitivity analysis is also conducted and the various models are validated with lab data. We also propose a workflow to predict the porosity from seismic velocities at field scale and apply it to a case study.
Summary We present a new 2.5D inversion result of the Sleipner CSEM data that was acquired in 2008 for the purpose of monitoring the injected CO2. The new result shows more details of the CO2 plume in comparison to previous inversion results. In addition, we can identify accumulation of potential free gas in the region. According to the result, 1) there seems no indication of the injected CO2 leaking through the cap rock and overburden, and 2) all the mass of the injected CO2 is within the CO2 plume body detected by the CSEM inversion. The study also confirms that the marine CSEM can be an important and essential tool for offshore CO2 storage monitoring, yet when combined together with seismic and gravity. This study also demonstrates that CSEM can work, even when data interferes with infra-structures e.g. seabed pipeline.
An extensive airborne electromagnetic (AEM) survey was carried out in Norway with the primary purpose to obtain information of depth to bedrock in areas with little or no prior geotechnical knowledge. We present different approaches to extract a bedrock model from the high-resolution time-domain AEM data, including both automated and manual procedures. It is found that in the area of investigation a user-driven approach of manual bedrock picking is most suitable, taking into account the strongest vertical resistivity gradient and geological information as additional information. A semi-automatic, statistical method, called Localized Smart Interpretation (LSI), is presented and discussed in addition. This method, while not included in the original bedrock model for the entire area, proved promising and should thus be implemented in future projects of similar scope.
In this paper, we revisit the marine controlled-source electromagnetic (CSEM) data, acquired above the Sleipner CO2 storage, in order to further study the dataset and conclude the feasibility of marine CSEM for offshore CCS monitoring. There are some challenges with respect to CSEM in this particular area: 1) strong airwave influence (due to regional shallow water depth); 2) potential of weak resistivity anomaly; 3) seabed pipeline network; and 4) rather shallow target depth. We are yet able to extract useful information; interpret further the CSEM inversion results by combining seismic data; and to extract the in situ resistivity and saturation of CO2 in the Utsira formation by applying a rock physics model. In addition, to minimize the influence of the seabed pipeline on the CSEM data, we have muted some of data and receivers near the seabed pipeline network. The results show a good agreement with seismic data, and the estimated total mass of CO2 agrees well with the injection data. This current study confirms that the marine CSEM can be an important and essential tool for offshore CO2 storage monitoring, yet not alone but when combined with both seismic and gravity. Finally, near-future large-scale CCS projects in the North Sea would require extensive infra-structures such as seabed pipeline, etc. This study demonstrates that CSEM may work even with such infra-structures in place.
