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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.

In the framework of the multi-disciplinary LIQUEFACT project, funded under the European Commission's Horizon 2020 program, the LIQUEFACT Reference Guide software has been developed, incorporating both data and methodologies collected and elaborated in the project's various work packages. Specifically, this refers to liquefaction hazard maps, methodologies and results of liquefaction vulnerability analysis for both building typologies and critical infrastructures, liquefaction mitigation measures as well as cost-benefit considerations. The software is targeting a wider range of user groups with different levels of technical background as well as requirements (urban planners, facility managers, structural and geotechnical engineers, or risk modelers). In doing so, the LIQUEFACT software shall allow the user assessing the liquefaction-related risk as well as assisting them in liquefaction mitigation planning. Dependent on the user's requirements, the LIQUEFACT software can be used to separately conduct the liquefaction hazard analysis, the risk analysis, and the mitigation analysis. At the stage of liquefaction hazard, the users can geolocate their assets (buildings or infrastructures) against the pre-defined macrozonation and microzonation maps in the software and identify those assets/sites that are potentially susceptible to an earthquake-induced liquefaction damage hazard. For potentially susceptible sites the user is able to commission a detailed ground investigation (e.g. CPT, SPT or V S30 profile) and this data can be used by the software to customise the level of susceptibility to specific site conditions. The users can either use inbuilt earthquake scenarios or enter their own earthquake scenario data. In the Risk Analysis, the user can estimate the level of impact of the potential liquefaction threat on the asset and evaluate the performance. For the Mitigation Analysis, the user can develop a customized mitigation framework based on the outcome of the risk and cost-benefit analysis.

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This paper considers directional sensitivity aspects of distributed fiber-optic acoustic sensing (DAS) cables employed to probe seismic waves. We provide a unified framework that bridges classical array seismology with DAS array processing to be applied by experts as well as novices from these disciplines.Array-based methods have been used in seismology since the late 1950s and were adapted from radio astronomy, radar, acoustics, and sonar (Schweitzer, 2014). Seismic arrays (e.g., Rost & Thomas, 2002Schweitzer et al., 2021) have the benefit of both improving the signal-to-noise ratio (SNR) of a seismic phase onset, whilst also providing information on the direction-of-arrival for an incoming signal. Applications of seismic arrays are wide ranging and include the monitoring of nuclear explosions, analyzing volcanic tremors, determining earth structure, and more recently, monitoring of induced seismicity (Oye et al., 2021).