ALBERT

Description: Microseismic monitoring is an essential tool for the characterization of hydraulic fractures. Fast estimation of the parameters that define a microseismic event is relevant to understand and control fracture development. The amount of data contained in the microseismic records however, poses a challenge for fast continuous detection and evaluation of the microseismic source parameters. Work inspired by the emerging field of Compressive Sensing has showed that it is possible to evaluate source parameters in a compressed domain, thereby reducing processing time. This technique performs well in scenarios where the amplitudes of the signal are above the noise level, as is often the case in microseismic monitoring using downhole tools. This paper extends the idea of the compressed domain processing to scenarios of microseismic monitoring using surface arrays, where the signal amplitudes are commonly at the same level as, or below, the noise amplitudes. To achieve this, we resort to the use of an imaging operator, which has previously been found to produce better results in detection and location of microseismic events from surface arrays. The operator in our method is formed by full-waveform elastodynamic Green's functions that are band-limited by a source time function and represented in the frequency domain. Where full-waveform Green's functions are not available, ray tracing can also be used to compute the required Green's functions. Additionally, we introduce the concept of the compressed inverse, which derives directly from the compression of the migration operator using a random matrix. The described methodology reduces processing time at a cost of introducing distortions into the results. However, the amount of distortion can be managed by controlling the level of compression applied to the operator. Numerical experiments using synthetic and real data demonstrate the reductions in processing time that can be achieved and exemplify the process of selecting the compression rate that produces a tolerable amount of distortion into the results.

Description: Microseismic monitoring is an essential tool for the characterization of hydraulic fractures. Fast estimation of the parameters that define a microseismic event is relevant to understand and control fracture development. The amount of data contained in the microseismic records however, poses a challenge for fast continuous detection and evaluation of the microseismic source parameters. Work inspired by the emerging field of Compressive Sensing has showed that it is possible to evaluate source parameters in a compressed domain, thereby reducing processing time. This technique performs well in scenarios where the amplitudes of the signal are above the noise level, as is often the case in microseismic monitoring using downhole tools. This paper extends the idea of the compressed domain processing to scenarios of microseismic monitoring using surface arrays, where the signal amplitudes are commonly at the same level as, or below, the noise amplitudes. To achieve this, we resort to the use of an imaging operator, which has previously been found to produce better results in detection and location of microseismic events from surface arrays. The operator in our method is formed by full-waveform elastodynamic Green's functions that are band-limited by a source time function and represented in the frequency domain. Where full-waveform Green's functions are not available, ray tracing can also be used to compute the required Green's functions. Additionally, we introduce the concept of the compressed inverse, which derives directly from the compression of the migration operator using a random matrix. The described methodology reduces processing time at a cost of introducing distortions into the results. However, the amount of distortion can be managed by controlling the level of compression applied to the operator. Numerical experiments using synthetic and real data demonstrate the reductions in processing time that can be achieved and exemplify the process of selecting the compression rate that produces a tolerable amount of distortion into the results.

Description: Moment tensor inversion techniques are widely used in global and regional seismic applications. When the ray-path trajectories are confined in a single plane (e.g., in isotropic media using a vertical array of receivers or an array that deviates from the vertical in the direction of wave propagation) only five out of six elements of the moment tensor are resolvable. This study investigates the resolvability of the complete seismic moment tensor for single-well monitoring geometries. By analyzing the resolution matrix, we demonstrate that a correct representation of the five resolvable elements of the moment tensor is only possible in a local reference system. For a vertical array of receivers, a suitable choice of condition number can assist the acquisition design. For a non-vertical array, our numerical modeling experiments suggest that the required distance and orientation of receivers for a full moment tensor inversion can be satisfied in a deviated well. In this case, information embedded in the condition number is valuable for determining the required distribution of receivers along the well.

Description: The occurrence of felt earthquakes due to gas production in Groningen has initiated numerous studies and model attempts to understand and quantify induced seismicity in this region. The whole bandwidth of available models spans the range from fully deterministic models to purely empirical and stochastic models. In this article, we summarise the most important model approaches, describing their main achievements and limitations. In addition, we discuss remaining open questions and potential future directions of development.

Description: The interactive web page contains supplementary information to Acoustic signals of a meteoroid recorded on a large-N seismic network and fibre optic cables. It aggregates the probabilistic trajectory inversion results for the observed meteor explosion above south Iceland on July 2, 2022. These inversion results of a hypersonic moving source model (MSM) are based on travel time picks of the first arrival (A1) and the last arrival (LA), both, in homogeneous and layered atmospheric model. Additionally we present the inversion results of a simple point source model (PSM) based on the arrival times of A1 and LA.

Description: We present an outstanding record of local, dense Large-N seismic and distributed acoustic sensor observations of a meteoroid from July 2, 2021 in Iceland. Our dataset includes high-quality observations from seven small aperture arrays of few hundred meters, an infrasound array, and a rotational station, all located within the distance range of 300 km. The high-frequency data show a variety of different phases associated with the source process along the atmospheric trajectory, including impulsive negative 1 first ground motions, a complex coda wave train about 2.5 s long thereafter, an azimuth-dependent stopping phase with reversed polarity between 1-25 s after the first arrival, which is resolved over only a few kilometers. The ground motion amplitude between the first and last arrivals is generally elevated. We associate the waveform in the 2.5 s coda with meteor-atmosphere interactions and nonlinear plasma processes that produce an oscillating shock-wave source pulse. Our data suggest a small azimuth-dependent deflection or dispersion of this source pulse, which may be related to the meteoroid’s deceleration in the atmosphere. We present a finite-length kinematic line-source pulse model that consistently explains the different phases inside and outside the Mach cone segment of our images, their wave amplitude variations, and a polarity change between the first phase and the terminating phase. The previously undiscovered rich directivity effects can also explain seemingly contradictory, time-dependent wave energy beam-directions at the various small aperture arrays and along the DAS cable. A combination of conventional locations and a Bayesian inversion of first and stopping phase arrivals led to a precise localization of the meteor trajectory.

Description: A common challenge in acoustic meteoroid signal analyses is to discriminate whether the observed wavefield can be better described by line-source or point-source models. This challenge typically arises from a sparse availability of observations. In this work, we present an outstanding record of ground-coupled waves from local large-N seismic and distributed acoustic sensing (DAS) observations of a meteoroid in Iceland. Our complete data set includes additional regional stations located within 300 km of the meteoroid’s trajectory. The dense large-N and DAS data allow identification of acoustic phases that are almost impossible to discriminate on sparser networks, including a weak late arrival resolved mostly only by DAS. Using this data set with a new Bayesian inversion model, we estimate the trajectory parameters of one fragment from the meteoroid. With these results we investigate its orbit in the solar system and propose a classification of the Icelandic event as a slow meteoroid of asteroidal origin with an energy on the order of 4–40 GJ, a probable size on the order of centimeters, and an orbit range consistent with the main asteroid belt.