Ultrasonic transmission is sensitive to the variation in mechanical properties of materials. Wave propagation through fractured media introduces changes in the frequency content, travel time and transmission coefficient of the wave. A workflow based on physics-driven unsupervised learning is developed to process the transmitted ultrasonic-shear waveforms to non-invasively visualize the geomechanical alterations due to hydraulic fracturing of a tight sandstone. Novelty of the work involves the assignment of physically consistent clusters to the measurements of shear waveforms across the axial and frontal planes by incorporating the travel time of the peak of spectral energy and transmission coefficient. The proposed workflow generates maps of geomechanical alterations across the frontal and axial planes of the sample. The outputs of the workflow are in good agreement with independent techniques viz. acoustic emission and X-ray computed tomography. The proposed workflow can be adapted for improved fracture characterization in the subsurface when processing sonic-logging, cross-wellbore seismic or surface seismic waveform data.

Fracture characterization is essential to hydrocarbon and geothermal exploration and production as well as carbon geo-sequestration. Active and passive measurements have been extensively applied to map fractures across various scales. Active and passive measurements have inherent advantages and limitations that complement each other. In this study, to improve the mapping of embedded fractures and the surrounding geomechanically altered regions, we integrate active shear-wave transmission measurement with passive acoustic-emission measurement collected during a lab-scale hydraulic-fracturing experiment. The proposed approach leverages the advantages of the two modalities of measurements, while minimizing the limitations. Polarized shear-wave transmission (active) measurement was collected before and after the hydraulic fracturing, and the acoustic emission (passive) measurement was collected during hydraulic fracturing. Two sets of two-dimensional maps of fracture and fracture-induced damage in axial, median and frontal planes were obtained by separately processing the physics-informed transformations of active and passive measurements. These 2D maps are then fed to wavelet-based image-fusion technique to integrate the two sources of information for the reliable mapping/imaging of the embedded fractures and the surrounding geomechanically altered regions. Plain word summary Fractures and geomechanical alterations embedded in a solid material can be characterized using active or passive measurements. Signal type, timing, duration and location of the source is controlled during an active measurement to allow optimal interactions of the propagating wave and the fractured material, whereas the signals due to waves generated by the processes of fracturing and geomechanical alterations are captured during a passive measurement. Active and passive measurements have advantages and limitations that complement each other. In this study, physics-informed transformations and wavelet-based image fusion are used to integrate the active and passive measurements to get the best of the two measurement modalities for purposes of reliable imaging of fractures and the surrounding geomechanically altered regions. Key points  Integration of active and passive measurements will leverage their strengths and minimize the limitations of individual measurement techniques.  To the best of authors’ knowledge, no reference exists where the two modalities are combined to characterize the fractures either in the field or laboratory scale.  We integrate active ultrasonic measurements with passive acoustic-emission measurements using physics-informed transformations and data fusion techniques.  The proposed method improves the imaging of embedded fractures and the surrounding geomechanically altered regions.  Two-dimensional maps of fracture and fracturing-induced damage is generated in axial, median and frontal planes.

Enhanced geothermal systems can provide a substantial share of the global energy demand if certain hurdles are overcome. One such hurdle is the accurate imaging of the fracture networks created in subsurface through hydraulic stimulation of these systems. Microseismicity associated with the stimulation is the primary means to locate the event hypocenters for estimating the stimulated rock volume. Using the data from a single three-component accelerometer in a monitoring well, the polarization features viz. azimuth, incidence, rectilinearity, and planarity are used as inputs for the unsupervised manifold approximation followed by clustering. We show that density-based clusters in the projected 3D space correspond to distinct types of hydraulically fractured zones around the injection point, thereby refining the interpretation of the microseismic cloud. The temporal evolution of these clusters can be used to track fracture creation and propagation for the various types of fracture zones.

Fluid injection into subsurface causes rock deformations, which give rise to mechanical waves in the surrounding rock. This article focuses on the infrasound signals (2-80 Hz) recorded by hydrophones during a meso-scale (~10 meter) hydraulic fracturing experiment at depth of 1.5 kilometer. We present a full-waveform-based data-driven workflow to map the spatiotemporal evolution of the infrasound sources produced during hydraulic fracturing. The infrasound source locations are compared against the simultaneously created microseismic source locations. Orientation of the infrasound source point cloud strongly agrees with natural fracture orientation, as inferred from the discrete fracture-network modelling. Finally, we arrive at a conceptual model of fluid-injection driven infrasound generation in subsurface and posit that the reopening of natural fractures is the main mechanism of the infrasound generation. A joint analysis of signals from microseismicity and infrasound sources can improve subsurface fracture imaging.