Search

During the past few years, distributed acoustic sensing (DAS) has become an invaluable tool for recording high-fidelity seismic wavefields with great spatiotemporal resolutions. However, the considerable amount of data generated during DAS experiments limits their distribution with the broader scientific community. Such a bottleneck inherently slows down the pursuit of new scientific discoveries in geosciences. Here, we introduce PubDAS—the first large-scale open-source repository where several DAS datasets from multiple experiments are publicly shared. PubDAS currently hosts eight datasets covering a variety of geological settings (e.g., urban centers, underground mines, and seafloor), spanning from several days to several years, offering both continuous and triggered active source recordings, and totaling up to ∼90 TB of data. This article describes these datasets, their metadata, and how to access and download them. Some of these datasets have only been shallowly explored, leaving the door open for new discoveries in Earth sciences and beyond.

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.

While seismic arrays have been in use since the 1950s and are currently a vital part of the IMS, they have fundamentally consisted of single or 3-component seismometers to measure the ground motion at a discrete set of locations known as the array elements. With the advent of Distributed Acoustic Sensing (DAS) within the last two decades, there is currently great interest in exploring the potential seismological applications. In contrast to traditional seismometers, DAS measures the deformation (e.g. strain-rate) along the length of a fibre optic cable with great flexibility in the number of measurements that can be taken and where they are taken along a given cable layout. Applying such technology to seismic arrays offers an exciting opportunity to design array configurations that were previously impractical with individual seismometers. However, the use of DAS requires special consideration of its unique signal characteristics, which include insensitivity of P-waves arriving broadside to the fibre optic cable.In this paper we present a design study for the installation of a new fibre optical cable at the site of the existing NORES seismic array in Norway – a 1.4 km aperture array located within a subarray of IMS station PS27 (NOA). We demonstrate through the modelling of DAS-specific array response functions how to optimize a new seismic array for regional seismic monitoring, highlighting the importance of incorporating DAS directivity effects. The final design will be installed in 2022 supplementing the current NORES array and will provide a unique data set that could lead to a new generation of DAS seismic arrays for both regional and global seismic monitoring.

From June to August 2021, we deployed a dense seismic nodal network across the Hengill geothermal area in southwest Iceland to image and characterize faults and high-temperature zones at high resolution. The nodal network comprised 498 geophone nodes spread across the northern Nesjavellir and southern Hverahlíð geothermal fields and was complemented by an existing permanent and temporary backbone seismic network of a total of 44 short-period and broadband stations. In addition, we recorded distributed acoustic sensing data along two fiber optic telecommunication cables near the Nesjavellir geothermal power plant with commercial interrogators. During the time of deployment, a vibroseis survey took place around the Nesjavellir power plant. Here, we describe the network and the recorded datasets. Furthermore, we show some initial results that indicate a high data quality and highlight the potential of the seismic records for various follow up studies, such as high-resolution event location to delineate faults and body- and surface-wave tomographies to image the subsurface velocity structure in great detail.

Distributed Acoustic Sensing (DAS) involves the transmission of laser pulses along a fiber-optic cable. These pulses are backscattered at fiber inhomogeneities and again detected by the same interrogator unit that emits the pulses. Elastic deformation along the fiber causes phase shifts in the backscattered laser pulses which are converted to spatially averaged strain measurements, typically at regular fiber intervals.DAS systems provide the potential to employ array processing algorithms. However, there are certain differences between DAS and conventional sensors. The current paper is focused on taking these differences into account. While seismic sensors typically record the directional particle displacement, velocity, or acceleration, the DAS axial strain is inherently proportional to the spatial gradient of the axial cable displacement. DAS is therefore insensitive to broadside displacement, e.g., broadside P-waves. In classical delay-and-sum beamforming, the array response function is the far-field response on a horizontal slowness (or wavenumber) grid. However, for geometrically non-linear DAS layouts, the angle between wavefront and cable varies, requiring the analysis of a steered response that varies with the direction of arrival. This contrasts with the traditional array response function which is given in terms of slowness difference between arrival and steering.This paper provides a framework for DAS steered response estimation accounting also for cable directivity and gauge-length averaging – hereby demonstrating the applicability of DAS in array seismology and to assess DAS design aspects. It bridges a gap between DAS and array theory frameworks and communities, facilitating increased employment of DAS as a seismic array.

The success of a distributed acoustic sensing (DAS) survey depends on strain energy impeding at favorable angles at most sections of the fiber. Although constrained to the path of the wellbore, there are various design parameters that can influence the recorded DAS amplitude. We present here a method to model the performance of DAS installations. We use precise raypath modeling in complex velocity models to determine ray incidence angles and show variations between different wrapping angles and detection thresholds. We then propose a way to evaluate the performance of the DAS acquisition design, and how to optimize processing, based on the percentage of DAS channels above a chosen amplitude threshold. For microseismic studies, the best wrapping angle of the fiber can be determined, which may be defined as covering the target area most homogeneously. For vertical seismic profiling projects, surface shot positions can be evaluated for their predicted recorded energy.

Summary Equinor in collaboration with Shell and Total is working on maturing the carbon storage project to store industrially produced CO2 into geological subsurface offshore Norway. However, the selected candidates for CO2 storage are part of a region with moderate natural seismicity. In order to assure a safe storage, the background seismicity should be monitored to understand both the nature of natural seismicity and to detect possible events induced by the imposed pressure changes due to CO2 injection. Current existing seismic network onshore is rather sparse and due to the limitation of recording mostly from the Norwegian side, event location uncertainty is rather high which complicates associating individual earthquakes to specific faults. Integration of onshore network with selected offshore PRM stations improved detectability. However, a more local monitoring system is required to improve the detectability and reduce the location uncertainty. We here present a proposal for a seismic monitoring array design for the offshore setting around the Smeaheia and Aurora sites that includes an upgrade of the onshore monitoring network as well as some ocean bottom nodes. We argue that such a network will provide an adequate baseline dataset, which is crucial for understanding the site prior to injection.

Summary We present Nor-FROST, the NORwegian FibRe Optic Sensing Test site in the backyard at NORSAR! 3 parallel trenches of 30m length and 1m depth are filled with concrete, gravel, and sand respectively. Various fiber cables from different vendors have been laid out in 3 depths in each trench. With this site in place, we will be able to do fundamental research on DAS, DSS, and DTS fiber sensing technology, such as transfer functions. We can compare and calibrate different fibers and interrogators. Furthermore, repeat measurements will give a time series for near-surface effects throughout the seasons.

A priori assessment of the expected location accuracy of a sensor network is typically done through inversion of the traveltime spatial gradients. This approach assumes that the applied location algorithm successfully recovers the global minimum of the objective function. However, even for accurate and precise phase picks, complexity in the velocity model and limitations in the network layout may inhibit the finding of a global minimum. The location algorithms may end up in a local minimum instead. We compare the location performance of various objective functions and minimization approaches. Although most of the analyzed location approaches mostly lead to good location results, none of the analyzed approaches recovered the correct location for all event locations. This implies that (microseismic) event locations estimates include an additional inherent error, which is linked to the applied location approach. This aspect is often neglected when interpreting event locations. Our site comprises a sensor network of two vertical strings, in a 1D velocity model of the Groningen gas field (The Netherlands), complicated by two thin, very high-velocity layers. For a series of synthetic event locations, we calculate arrival times, add picking errors, and then feed these synthetic picks into a set of different location routines. We also determine a novel way to analyze this approach-dependent location error of the sensor network for the given velocity model and a set of event locations: We compare the distances between a set of assumed event locations to resulting locations in the target region of the subsurface. From the cumulative distribution function of that mislocation distance, we determine the [Formula: see text] and [Formula: see text] confidence distances for each method. This results in scalar values representing the location confidence distances for a given method. In turn, this can be used to easily compare the location capabilities of different sensor layouts.

To achieve high recovery rates, modern-day production management can benefit from not only snapshot images of the state of the reservoir at regular time intervals, but also continuous monitoring of the dynamic processes induced by pressure changes and fluid movement during production. Production management using time-lapse 4D snapshots is reactive, i.e., adjustments addressing the sweep efficiency or reservoir integrity can only be instigated once the next snapshot image is available after acquisition, processing and interpretation, often years later. For a more proactive reservoir management, it is important to have dynamic reservoir information in real time between the seismic time-lapse snapshots. Such information is contained in microseismic monitoring data and in surface or borehole deformation measurements. If sensors are permanently installed, this information comes at a negligible additional cost, provided that the data can be transferred to shore in real-time and processed automatically. Time-lapse 4D snapshot images are typically obtained over a period of years and are inadequately sampled for capturing dynamic reservoir changes taking place over much shorter time intervals, from hours to days. Such changes can include variations in the permeability caused by scaling or compaction (Barkved and Kristiansen, 2005), changes of the fluid phase owing to pressure variations (e.g., Osdal et al., 2006), unintended alterations of the flow paths owing to out-of-zone injections and fault reactivation (e.g., Schinelli et al., 2015), or movement in the overburden, potentially compromising the integrity of infrastructure in the form of casing failures or seafloor subsidence (e.g., Yudovich et al., 1989; Hatchell et al., 2017). While 4D seismic data can capture the cumulative effect of such processes by evaluating differences in still images every few years, they provide little information about when exactly the associated dynamic changes occurred and how they relate to changes in flow rate and pressure that may have been captured through continuous measurements in the wellbores accessing the reservoir. Microseismic events from within or around a producing reservoir can be indicative of reservoir fluid pathways and sub-seismic reservoir compartmentalization (e.g., Maxwell and Urbancic, 2001), or stress changes and associated production- related deformations in the vicinity (e.g., Teanby et al., 2004; Zoback and Zinke, 2002; Wuestefeld et al., 2011, 2013). Continuous monitoring of seismicity can also help in assessing deformation-related risks to infrastructure over the life of a field. Combined with pressure and flow rate, such data can provide the necessary information to capture dynamic processes in the reservoir right when they happen. In conjunction with geomechanical flow modelling, production optimization strategies can thus be validated and adjustments can be properly planned at an early stage. The result will be an improved sweep efficiency with a further increased recovery factor, as well as better risk assessment with the avoidance of potentially costly mitigation actions. A better understanding of, and continuous information about, the reservoir dynamics may even help to plan a 4D seismic strategy better. This can include better definition of suitable intervals for the acquisition of time-lapse images. These intervals could be irregular, depending on the state of reservoir development and type of recovery method. Continuous monitoring may also provide a means to high-grade areas of the reservoir for partial 4D imaging at lower cost and faster turnaround in between ‘full’ time-lapse surveys (Hatchell et al., 2013). In this paper we discuss the general ability to monitor microseismic events in an offshore setting and presents results from a real-time monitoring pilot in Norway. We validate the concept of continuous real-time monitoring from a fibre-optic deep-water installation by comparing our automatic detections with data from a regional seismograph network.

DAS continues to be a promising and cost-effective technology for carbon storage monitoring applications including systems that monitor geological changes using active seismics, and also for passive mode operations, e.g. the monitoring of microseismic activity during CO2 injection. The authors have developed a DAS interrogator research platform that has enabled a better understanding of the critical equipment architecture and experimental factors influencing the collection and analysis of DAS data. The authors plan to test this at different CCS pilot installations. In the future, the performance and functionality of the DAS interrogator research platform will be expanded, and techniques for applying it developed further in order to meet CCS specific needs determined from wider collaboration.

The continental crust provides a record of Earth’s evolution. Analysis of the geochemical signature of continental crust formed since the Hadean points to the initiation of plate tectonics about 3 billion years ago.

In outdoor field-tests where a single optical fibre cable is used to make DAS recordings of hammer shots, coherent seismic arrivals are observed at up to 32 m from the hammer points with frequencies up to 600 Hz. Recording at higher sampling rates and decimating is preferable to downsampled data. Time domain SNRs of acquired DAS data at a given distance are ~1/2 those of complimentary geophones while in the frequency domain, the highest ratios are produced between 20 and 200 Hz. An automated STA/LTA trigger algorithm is able to define reasonable seismic onsets but is unable to identify the first-arriving energy on all traces. Shorter pulse widths produce lower RMS amplitudes for the noise windows while longer pulse widths produce higher RMS amplitudes for the signal windows. This means that the selection of optimum pulse width with respect to maximising the SNR is not clear. This work presents the initial results of field-tests that will be used to refine the use of the DAS system in further field and borehole experiments. This will ultimately be used to monitor the seismicity at active CCS injection sites in the future.

Fractures and faults within a reservoir can provide important pathways for the movement of reservoir fluids. Understanding the character and properties of these features on a range of length scales can be vital for the efficient exploitation of natural resources, whether it be enhanced oil and gas recovery, the safe storage of CO2 ,o r better exploitation of geothermal heat. The monitoring of microseismicity within a reservoir illuminates active faults, but these events can be also used to characterize fracture networks through measurements of seismic anisotropy. In this study we use microseismic data acquired over an 18-day period in April 1997 at the Ekofisk oil field in the North Sea. Using the analysis of seismic multiplets we delineate a number of sub-vertical tectonic faults, which are consistent with previous core data analysis and seismic reflection work. We use shear wave splitting measurements, which are indicative of fracture-induced seismic anisotropy, to infer the orientation of aligned aseismic fracture sets within the reservoir. The estimated fracture dip and strike from the shear wave splitting analysis are consistent with the active tectonic fractures characterized by the multiplets, but this analysis also illuminates spatial variations in fracture properties. Such monitoring on a longer term and with multiple wells is a promising tool for better understanding fracture and fault-controlled flow within reservoirs.

SUMMARY Hydraulic overpressure can induce fractures and increase permeability in a range of geological settings, including volcanological, glacial and petroleum reservoirs. Here we consider an example of induced hydraulic fracture stimulation in a tight-gas sandstone. Successful exploitation of tight-gas reservoirs requires fracture networks, either naturally occurring, or generated through hydraulic stimulation. The study of seismic anisotropy provides a means to infer properties of fracture networks, such as the dominant orientation of fracture sets and fracture compliances. Shear wave splitting from microseismic data acquired during hydraulic fracture stimulation allows us to not only estimate anisotropy and fracture properties, but also to monitor their evolution through time. Here, we analyse shear wave splitting using microseismic events recorded during a multistage hydraulic fracture stimulation in a tight-gas sandstone reservoir. A substantial rotation in the dominant fast polarization direction (ψ )i s observed between the events of stage 1 and those from later stages. Although large changes in ψ have often been linked to stress-induced changes in crack orientation, here we argue that it can better be explained by a smaller fracture rotation coupled with an increase in the ratio of normal to tangential compliance (ZN/ZT) from 0.3 to 0.6. ZN/ZT is sensitive to elements of the internal architecture of the fracture, as well as fracture connectivity and permeability. Thus, monitoring ZN/ZT with shear wave splitting can potentially allow us to remotely detect changes in permeability caused by hydraulic stimulation in a range of geological settings.

Terra Nova, 25, 57–64, 2013 Abstract Characterizing the interaction of a fault with its surroundings is vital to fully understand the tectonic processes involved and predict future behaviour. Regional and local stress orientations affect different fracture length scales, manifested by numerous associated fault, fracture and crack structures. We use seismic anisotropy to constrain the dominant orientation of aligned rupture planes of various length scales. In particular, we study shear-wave splitting of regional seismic events in Trans-Alboran Shear Zone (TASZ), south-east Spain. The TASZ consists of three major left-lateral strike-slip faults and numerous secondary strike-slip and thrust faults. The observed orientations for S-waves vary from roughly N–S in the northern segment of TASZ, to E–W in the centre, to NNW–SSE and NNE–SSW in the south. We show that the strikes of fast polarizations reflect both structural and lithological differences, indicating complex interactions of principal and secondary faults within the crust to accommodating tectonic stresses.

Monitoring of induced seismicity is gaining importance in a broad range of industrial operations from hydrocarbon reservoirs to mining to geothermal fields. Such passive seismic monitoring mainly aims at identifying fractures, which is of special interest for safety and productivity reasons. By analysing shear-wave splitting it is possible to determine the anisotropy of the rock, which may be caused by sedimentary layering and/or aligned fractures, which in turn offers insight into the state of stress in the reservoir. We present a workflow strategy for automatic and effective processing of passive microseismic data sets, which are ever increasing in size. The automation provides an objective quality control of the shear-wave splitting measurements and is based on characteristic differences between the two independent eigenvalue and cross-correlation splitting techniques. These differences are summarized in a quality index for each measurement, allowing identification of an appropriate quality threshold. Measurements above this threshold are considered to be of good quality and are used in further interpretation. We suggest an automated inversion scheme using rock physics theory to test for best correlation of the data with various combinations of fracture density, its strike and the background anisotropy. This fully automatic workflow is then tested on a synthetic and a real microseismic data set.

We have presented a finite-element based model for simulation of hydraulic fracturing. Each element is assigned strength in terms of a strain limit, and each element may have its individual strength. The element fractures when the strength limit is exceeded. One or more elements may break in one event. We show a 2D example of hydraulic fracturing of a low-permeable rock, where the fracture geometry is obtained. The bottom hole pressure is computed, which shows the pressure drops that follows each event. Finally, the magnitude of the fracture events is plotted in both space and time, which can be compared with the data from micro-seismic monitoring. A calibration of the model may provide effective parameter values for the rock. The presented formalism can also be coupled to reservoir simulators and calibrated against rupture propagation theories.

A method and system for identifying reservoir drainage patterns from microseismic data for illustrating flow paths towards ports. The method includes: determining moment tensor data for each of a plurality of microseismic events in the reservoir; inferring crack formation data in the reservoir in dependence on the moment tensor data; and calculating stream lines that represent predicted flow of fluids through the reservoir in dependence on the inferred crack formation data.

Seismic and microseismic event populations can be characterized by their spatial and magnitude distributions. The magnitude distribution is described by the Gutenberg-Richter b value. The spatial distribution can be described by the two-point correlation coefficient, Dc. We observe spatio-temporal variations in both b and Dc during hydraulic fracture stimulation in the Cotton Valley tight gas reservoir. We find that during the initial stages of the fracture stimulations, b is high while Dc is low, implying that deformation is dominated by smaller events clustered at points near the injection well. As injection progresses, b decreases and Dc increases. We investigate correlation between b values and Dc, which can be indicative of the style of fracturing. Initially, b and Dc are negatively correlated, consistent with mechanical weakening during the early stages of fracturing. As the stimulation progresses, b and Dc become positively correlated, consistent with later stabilization of the fractures and mechanical hardening when the induced fracture intersects a pre-existing fault. The mechanism of hardening may be crack blunting while propagating into a pre-existing fractured or damaged zone.

Over the past decade, microsesimic monitoring has become the approach most often used to gain an in-situ understanding of the rock's response during hydraulic fracture stimulations. From initial monitoring performed in the Barnett Shale to monitoring currently being carried out for example in the Horn River and Marcellus formations, we review the evolution of microseismic monitoring from data collection (single versus multi-well array configurations, utilization of long lateral stimulation wells), to data analysis and the incorporation of microseismic parameters to constrain and validate reservoir models. Furthermore, we discuss the variations in microseismic activity for different stimulation programs (e.g. zipper-fracs) and stimulation fluids. Generally, we have observed that overall fracture height, width and length, orientation, and growth vary from formation to formation and within each formation, thereby highlighting the ongoing necessity for microseismic monitoring. Additionally, through the use of advanced microseismic analysis techniques, such as Seismic Moment Tensor Inversion (SMTI), details on failure mechanisms have been used to assess stimulation effectiveness and define complex Discrete Fracture Networks (DFN). This information provides estimates of Enhanced Fluid Flow (EFF), which assist in calibrating and validating reservoir models. Utilizing spatial and temporal distributions in DFN and EFF, along with estimates of fracture interconnectivity and complexity, the role of pre-existing fractures and fault structures in the rock matrix can be established and used to provide more realistic estimates of stimulation parameters such as Stimulated Reservoir Volume (SRV).

Summary Fracture networks stimulated by hydraulic fracturing follow pre-existing planes of weakness in the rock. We analyze a stimulation program in a tight gas formation in Texas. Microseismic Frequency-Magnitude analysis is used to infer fracture and stress characteristics. Data from a microseismic Shear-Wave Splitting analysis gives dominant fracture orientation. The static stress interaction of the microseismic events on the fracture network are then calculated. The resulting changes in Coulomb Failure Stresses (ΔCFS) thus constrain the zone of stress induced cracks and fissures, which are activated below microseismic detectability.

A tight gas case history from the North America Rocky Mountains shows the capability of borehole microseismic and 3D seismic anisotropy to delineate fracture systems induced in a clastic reservoir by hydraulic fracturing of a horizontal well. Dual monitoring of the horizontal well completion indicates improvements in fracture mapping by compressing hypocenters of the microseisms to more linear features that are corroborated by production logging flowmeter. Fracture half-lengths and vertical heights of fractures are indicated for reservoir modelling. Advanced processing of the microseismic 3-component geophone first motions indicates fracture azimuth and dips from a moment tensor inversion and suggests a conjugate set of orthogonal fractures in the reservoir. 3D seismic anisotropy results, using a fast and slow velocity direction calculated from the data, suggest inherent microfractures present in the rock prior to completion. Surface fault mapping in the field supports fractures mapped by both the microseismic and the 3D seismic anisotropy. Multiple regression analysis of drilling, completion and 3D seismic anisotropy parameters versus initial production for 30, 90 and 180 days results show independent contributions to production. A predictive production model based on the multiple regression analysis allows for future well planning and completions to optimise well performance.

SUMMARY Changing stress conditions are well known to cause rupturing of rock. This is well constrained on a small scale from laboratory experiments and inferred on a much larger scale from tectonic earthquakes. Here, we present a study of rock fracturing induced by changes in stress state during block-caving operations in an Australian mine. This intermediate-scale study provides further evidence of the scalability of processes involved in rock fracturing and thus helps to link laboratory and seismological observations. We analyse the temporal evolution of rock fracturing during a production cycle using the analysis of fracture-induced anisotropy. Fracturingoftherockmassismonitoredusingevidenceofseismicanisotropyfromestimates of shear wave splitting and their subsequent inversion for fracture parameters. The data set consists of more than 40 000 three-component seismograms recorded by an array of sensors, which provides excellent ray coverage. We applied a novel automatic quality assessment technique to handle this large data set and find that anisotropy, and thus fracturing, correlates strongly with the excavation process. We then perform a grid search over a series of synthetic models based on rock physics to invert the splitting parameters for fracture orientation and density. Finally, by applying a sliding window on our results, we are able to identify production related fracture evolution. During production the fracture density increases, with horizontal fracture density being stronger than the vertical fracture density. This can be explained by the removal of the supporting rock during caving. During short intervals of reduced production, the horizontal fracture density decreases, whereas vertical fracture density increases. We relate this to change in stress regime with reducing overburden mass during cavity collapse. This scenario is similar to a collapsing caldera or the inverse of an inflating magma chamber.

The success of microseismic monitoring campaign strongly depends on using the correct sensor layout. Detection limit and location accuracy are affected by the capability of a network to uniformly capture the energy emitted by seismic events in the subsurface. We here highlight the importance of using a accurate, 3D velocity model. We compare performance of a hypothetical network design using 1D and 3D velocity models. Our results show that the complexity of the 3D model translates into the key network performance indicators, such as distribution of magnitude of completeness, location accuracy and ground motion amplitudes.

We summarize observations of shear-wave splitting from passive seismic monitoring in a range of petroleum settings. Such measurements are relatively rare, but the emerging picture is one of fracture-induced anisotropy where a number of factors control both spatial and temporal variations. These observations offer insights into the state of stress in a reservoir and can serve as a ground-truth for geomechanical models.

The successful exploitation of tight-gas reservoirs requires fracture networks, sometimes naturally occurring, often hydraulically stimulated. Borehole microseismic data acquired in such environments hold great promise for characterising such fractures or sweet spots. The loci of seismic events delineate active faults and reveal fracture development in response to stimulation. However, a great deal more can be extracted from these microseismic data. For example, inversions of shear-wave splitting data provide a robust means of mapping fracture densities and preferred orientations, useful information for drilling programs. They can also be used to track temporal variations in fracture compliances, which are indicative of fluid flow and enhanced permeability in response to stimulation. Furthermore, the frequency-dependent nature of shear-wave splitting is very sensitive to size of fractures and their fluidfill composition. Here we demonstrate the feasibility of using such analysis of shear-wave splitting measurements on data acquired during hydraulic stimulation of a tight-gas sandstone in the Cotton Valley field in Carthage, West Texas.