Consistency of stress state,locations and source mechanisms of events induced by hydraulic fracturing: downhole monitoring

We present results of processed microseismic events induced by hydraulic fracturing and detected using dual downhole monitoring arrays. The results provide valuable insight into hydraulic fracturing. For our study, we detected and located microseismic events and determined their magnitudes, source mechanisms and inverted stress field orientation. Event locations formed a distinct linear trend above the stimulated intervals. Source mechanisms were only computed for high‐quality events detected on a sufficient number of receivers. All the detected source mechanisms were dip‐slip mechanisms with steep and nearly horizontal nodal planes. The source mechanisms represented shear events and the non‐double‐couple components were very small. Such small, non‐double‐couple components are consistent with a noise level in the data and velocity model uncertainties. Strikes of inverted mechanisms corresponding to the nearly vertical fault plane are (within the error of measurements) identical with the strike of the location trend. Ambient principal stress directions were inverted from the source mechanisms. The least principal stress, σ₃, was determined perpendicular to the strike of the trend of the locations, indicating that the hydraulic fracture propagated in the direction of maximum horizontal stress. Our analysis indicated that the source mechanisms observed using downhole instruments are consistent with the source mechanisms observed in microseismic monitoring arrays in other locations. Furthermore, the orientation of the inverted principal components of the ambient stress field is in agreement with the orientation of the known regional stress, implying that microseismic events induced by hydraulic fracturing are controlled by the regional stress field.     

Understanding acquisition and processing error in microseismic data: An example from Pouce Coupe Field,Canada

A challenge in microseismic monitoring is quantification of survey acquisition and processing errors, and how these errors jointly affect estimated locations. Quantifying acquisition and processing errors and uncertainty has multiple benefits, such as more accurate and precise estimation of locations, anisotropy, moment tensor inversion and, potentially, allowing for detection of 4D reservoir changes. Here, we quantify uncertainty due to acquisition, receiver orientation error, and hodogram analysis. Additionally, we illustrate the effects of signal to noise ratio variances upon event detection. We apply processing steps to a downhole microseismic dataset from Pouce Coupe, Alberta, Canada. We use a probabilistic location approach to identify the optimal bottom well location based upon known source locations. Probability density functions are utilized to quantify uncertainty and propagate it through processing, including in source location inversion to describe the three-dimensional event location likelihood. Event locations are calculated and an amplitude stacking approach is used to reduce the error associated with first break picking and the minimization with modelled travel times. Changes in the early processing steps have allowed for understanding of location uncertainty of the mapped microseismic events.     

Cross double‐difference inversion for simultaneous velocity model update and microseismic event location

Microseismic monitoring is an approach for mapping hydraulic fracturing. Detecting the accurate locations of microseismic events relies on an accurate velocity model. The one‐dimensional layered velocity model is generally obtained by model calibration from inverting perforation data. However, perforation shots may only illuminate the layers between the perforation shots and the recording receivers with limited raypath coverage in a downhole monitoring problem. Some of the microseismic events may occur outside of the depth range of these layers. To derive an accurate velocity model covering all of the microseismic events and locating events at the same time, we apply the cross double‐difference method for the simultaneous inversion of a velocity model and event locations using both perforation shots and microseismic data. The cross double‐difference method could provide accurate locations in both the relative and absolute sense, utilizing cross traveltime differences between P and S phases over different events. At the downhole monitoring scale, the number of cross traveltime differences is sufficiently large to constrain events locations and velocity model as well. In this study, we assume that the layer thickness is known, and velocities of P‐ and S‐wave are inverted. Different simultaneous inversion methods based on the Geiger's, double‐difference, and cross double‐difference algorithms have been compared with the same input data. Synthetic and field data experiments suggest that combining both perforation shots and microseismic data for the simultaneous cross double‐difference inversion of the velocity model and event locations is available for overcoming the trade‐offs in solutions and producing reliable results.     

Importance of borehole deviation surveys for monitoring of hydraulic fracturing treatments

During seismic monitoring of hydraulic fracturing treatment, it is very common to ignore the deviations of the monitoring or treatment wells from their assumed positions. For example, a well is assumed to be perfectly vertical, but in fact, it deviates from verticality. This can lead to significant errors in the observed azimuth and other parameters of the monitored fracture‐system geometry derived from microseismic event locations. For common hydraulic fracturing geometries, a 2° deviation uncertainty on the positions of the monitoring or treatment well survey can cause a more than 20° uncertainty of the inverted fracture azimuths. Furthermore, if the positions of both the injection point and the receiver array are not known accurately and the velocity model is adjusted to locate perforations on the assumed positions, several‐millisecond discrepancies between measured and modeled SH‐P traveltime differences may appear along the receiver array. These traveltime discrepancies may then be misinterpreted as an effect of anisotropy, and the use of such anisotropic model may lead to the mislocation of the detected fracture system. The uncertainty of the relative positions between the monitoring and treatment wells can have a cumulative, nonlinear effect on inverted fracture parameters. We show that incorporation of borehole deviation surveys allows reasonably accurate positioning of the microseismic events. In this study, we concentrate on the effects of horizontal uncertainties of receiver and perforation positions. Understanding them is sufficient for treatment of vertical wells, and also necessary for horizontal wells.     

Comparison of migration‐based location and detection methods for microseismic events

Microseismic monitoring in the oil and gas industry commonly uses migration‐based methods to locate very weak microseismic events. The objective of this study is to compare the most popular migration‐based methods on a synthetic dataset that simulates a strike‐slip source mechanism event with a low signal‐to‐noise ratio recorded by surface receivers (vertical components). The results show the significance of accounting for the known source mechanism in the event detection and location procedures. For detection and location without such a correction, the ability to detect weak events is reduced. We show both numerically and theoretically that neglecting the source mechanism by using only absolute values of the amplitudes reduces noise suppression during stacking and, consequently, limits the possibility to retrieve weak microseismic events. On the other hand, even a simple correction to the data polarization used with otherwise ineffective methods can significantly improve detections and locations. A simple stacking of the data with a polarization correction provided clear event detection and location, but even better results were obtained for those data combined with methods that are based on semblance and cross‐correlation.     

Full‐waveform based microseismic event detection and signal enhancement: An application of the subspace approach

Microseismic monitoring has proven invaluable for optimizing hydraulic fracturing stimulations and monitoring reservoir changes. The signal to noise ratio of the recorded microseismic data varies enormously from one dataset to another, and it can often be very low, especially for surface monitoring scenarios. Moreover, the data are often contaminated by correlated noises such as borehole waves in the downhole monitoring case. These issues pose a significant challenge for microseismic event detection. In addition, for downhole monitoring, the location of microseismic events relies on the accurate polarization analysis of the often weak P‐wave to determine the event azimuth. Therefore, enhancing the microseismic signal, especially the low signal to noise ratio P‐wave data, has become an important task. In this study, a statistical approach based on the binary hypothesis test is developed to detect the weak events embedded in high noise. The method constructs a vector space, known as the signal subspace, from previously detected events to represent similar, yet significantly variable microseismic signals from specific source regions. Empirical procedures are presented for building the signal subspace from clusters of events. The distribution of the detection statistics is analysed to determine the parameters of the subspace detector including the signal subspace dimension and detection threshold. The effect of correlated noise is corrected in the statistical analysis. The subspace design and detection approach is illustrated on a dual‐array hydrofracture monitoring dataset. The comparison between the subspace approach, array correlation method, and array short‐time average/long‐time average detector is performed on the data from the far monitoring well. It is shown that, at the same expected false alarm rate, the subspace detector gives fewer false alarms than the array short‐time average/long‐time average detector and more event detections than the array correlation detector. The additionally detected events from the subspace detector are further validated using the data from the nearby monitoring well. The comparison demonstrates the potential benefit of using the subspace approach to improve the microseismic viewing distance. Following event detection, a novel method based on subspace projection is proposed to enhance weak microseismic signals. Examples on field data are presented, indicating the effectiveness of this subspace‐projection‐based signal enhancement procedure.     

Feasibility of joint 1D velocity model and event location inversion by the Neighbourhood algorithm

Using a set of synthetic P‐ and S‐wave onsets, computed in a 1D medium model from sources that mimic a distribution of microseismic events induced by hydrofrac treatment to a monitoring geophone array(s), we test the possibility to invert back jointly the model and events location. We use the Neighbourhood algorithm for data inversion to account for non‐linear effects of velocity model and grid search for event location. The velocity model used is composed of homogeneous layers, derived from sonic logging. Results for the case of one and two monitoring wells are compared. These results show that the velocity model can be obtained in the case of two monitoring wells, if they have optimal relative position. The use of one monitoring well fails due to the trade‐off between the velocity model and event locations.     

Locating microseismic events using borehole data

Constraining microseismic hypocentres in and around hydrocarbon reservoirs and their overburdens is essential for the monitoring of deformation related to hydraulic fracturing, production and injection and the assessment of reservoir security for CO₂ and wastewater storage. Microseismic monitoring in hydrocarbon reservoirs can be achieved via a variety of surface and subsurface acquisition geometries. In this study we use data from a single, subsurface, vertical array of sensors. We test an existing technique that uses a 1D velocity model to constrain locations by minimizing differential S‐to‐P arrival times for individual sensors. We show that small errors in either arrival time picks or the velocity model can lead to large errors in depth, especially near velocity model discontinuities where events tend to cluster. To address this issue we develop two methods that use all available arrival times simultaneously in the inversion, thus maximizing the number of potential constraints from to N, where N is the number of phase picks. The first approach minimizes all available arrival time pairs whilst the second approach, the equal distance time (EDT) method defines the hypocentre as the point where the maximum number of arrival time surfaces intersect. We test and compare the new location procedures with locations using differential S‐to‐P times at each individual sensor on a microseismic data set recorded by a vertical array of sensors at the Ekofisk reservoir in the North Sea. Specifically, we test each procedure's sensitivity to perturbations in measured arrival times and the velocity model using Monte Carlo analysis. In general, location uncertainties increase with increasing raypath length. We show that errors in velocity model estimates are the most significant source of uncertainty in source location with these experiments. Our tests show that hypocentres determined by the new procedures are less sensitive to erroneous measurements and velocity model uncertainties thus reducing the potential for misinterpretation of the results.     

Effective anisotropic velocity model from surface monitoring of microseismic events

We develop a methodology to obtain a consistent velocity model from calibration shots or microseismicity observed on a buried array. Using a layered 1D isotropic model derived from checkshots as an initial velocity model, we invert P‐wave arrival times to obtain effective anisotropic parameters with a vertical axis of symmetry (VTI). The nonlinear inversion uses iteration between linearized inversion for anisotropic parameters and origin times or depths, which is specific to microseismic monitoring. We apply this technique to multiple microseismic events from several treatments within a buried array. The joint inversion of selected events shows a largely reduced RMS error indicating that we can obtain robust estimates of anisotropic parameters, however we do not show improved source locations. For joint inversion of multiple microseismic events we obtained Thomsen anisotropic parameters ε of 0.15 and δ of 0.05, which are consistent with values observed in active seismic surveys. These values allow us to locate microseismic events from multiple hydraulic fracture treatments separated across thousands of metres with a single velocity model. As a result, we invert the effective anisotropy for the buried array region and are able to provide a more consistent microseismicity mapping for past and future hydraulic fracture stimulations.     

邻近算法在微地震震源位置和一维速度模型同时反演中的应用

微地震事件的空间分布可以用来监测水力压裂过程中裂缝的发育情况。因此,震源定位是微震监测中重要的环节。震源定位依赖准确的速度模型,而震源位置和速度模型的耦合易导致线性迭代的同时反演方法陷入局部极小值。邻近算法作为一种非线性全局优化算法,能够最大程度地避免陷入局部最优解。本文将邻近算法应用于单井监测的微震定位和一维速度模型同时反演,首先利用邻近算法搜索一维速度模型,再使用网格搜索方法进行震源定位,并根据定位的走时残差产生新的速度模型,最后通过若干次迭代使其收敛到最优解。理论和实际数据结果均表明该方法能够避免局部最优解,得到较为可靠的震源位置和一维速度模型。     

基于波形相似特征的微地震事件初至拾取及全局校正

微地震事件初至拾取是井下微地震监测数据处理的关键步骤之一.初至误差的存在会使微地震震源定位结果产生较大偏差,进而影响后续的压裂裂缝解释.通常初至拾取过程对所有的微地震事件选择相同的特征函数并采用一致的拾取参数进行统一处理,然而当事件的能量、震源机制、传播路径以及背景噪声等存在明显差异时,所得初至拾取结果差别显著.为了提高微地震事件初至拾取标准一致性,本文提出基于波形相似特征的初至拾取及全局校正方法.该方法首先利用互相关函数对每个事件内的各道记录进行时差校正,得到初始初至信息并形成叠加道,再对所有事件的叠加道进行全局互相关得到事件间初至相对校正量,最终初至结果可以通过各个事件的初始初至信息与其相对校正量相加得到.方法将所有微地震事件初至结果作为一个整体处理,从而能够克服常规方法初至拾取标准一致性差的缺陷.实际资料处理结果表明,相比于常规方法,该方法可以有效提高事件初至拾取和定位结果的一致性.     

Improvements in mining induced microseismic source locations at the Lucky Friday mine using an automated whole-waveform analysis system

For years, severe rockburst problems at the Lucky Friday mine in northern Idaho have been a persistent safety hazard and an impediment to production. An MP250 based microseismic monitoring system, which uses simple voltage threshold picking of first arrivals, has been used in this mine since 1973 to provide source locations and energy estimates of seismic events. Recently, interest has been expressed in developing a whole waveform microseismic monitoring system for the mine to provide more accurate source locations and information about source characteristics. For this study, we have developed a prototype whole-waveform microseismic monitoring system based on a 80386 computer equipped with a 50 kHz analog-digital convertor board. The software developed includes a data collection program, a data analysis program, and an event detection program. Whole-waveform data collected and analyzed using this system during a three-day test have been employed to investigate sources of error in the hypocenter location process and to develop an automatic phase picker appropriate for microseismic events.Comparison of hypocenter estimates produced by the MP250 system to those produced by the whole-waveform system shows that significant timing errors are common in the MP250 system and that these errors caused a large part of the scatter evident in the daily activity plots produced at the mine. Simulations and analysis of blast data show that analytical control over the solutions is strongly influenced by the array geometry. Within the geophone array, large errors in the velocity model or moderate timing errors may result in small changes in the solution, but outside the array, the solution is very sensitive to small changes in the data.Our whole-waveform detection program picks event onset times and determines event durations by analysis of a segmented envelope function (SEF) derived from the microseismic signal. The detection program has been tested by comparing its arrival time picks to those generated by human analysis of the data set. The program picked 87% of the channels that were picked by hand with a standard error of 0.75 milliseconds. Source locations calculated using times provided by our entire waveform detection program were similar to those calculated using hand-picked arrival times. In particular, they show far less scatter than source locations calculated using arrival times based on simple voltage threshold picking of first arrivals.     

A multi-channel approach for automatic microseismic event association using RANSAC-based Arrival Time Event Clustering (RATEC)

In the presence of background noise, arrival times picked from a surface microseismic data set usually include a number of false picks that can lead to uncertainty in location estimation. To eliminate false picks and improve the accuracy of location estimates, we develop an association algorithm termed RANSAC-based Arrival Time Event Clustering (RATEC) that clusters picked arrival times into event groups based on random sampling and fitting moveout curves that approximate hyperbolas. Arrival times far from the fitted hyperbolas are classified as false picks and removed from the data set prior to location estimation. Simulations of synthetic data for a 1-D linear array show that RATEC is robust under different noise conditions and generally applicable to various types of subsurface structures. By generalizing the underlying moveout model, RATEC is extended to the case of a 2-D surface monitoring array. The effectiveness of event location for the 2-D case is demonstrated using a data set collected by the 5200-element dense Long Beach array. The obtained results suggest that RATEC is effective in removing false picks and hence can be used for phase association before location estimates.     

Approximate traveltime inversion in downhole microseismic monitoring

In downhole microseismic monitoring, accurate event location relies on the accuracy of the velocity model. The model can be estimated along with event locations. Anisotropic models are important to get accurate event locations. Taking anisotropy into account makes it possible to use additional data – two S-wave arrivals generated due to shear-wave splitting. However, anisotropic ray tracing requires iterative procedures for computing group velocities, which may become unstable around caustics. As a result, anisotropic kinematic inversion may become time consuming. In this paper, we explore the idea of using simplified ray tracing to locate events and estimate medium parameters. In the simplified ray-tracing algorithm, the group velocity is assumed to be equal to phase velocity in both magnitude and direction. This assumption makes the ray-tracing algorithm five times faster compared to ray tracing based on exact equations. We present a set of tests showing that given perforation-shot data, one can use inversion based on simplified ray-tracing even for moderate-to-strong anisotropic models. When there are no perforation shots, event-location errors may become too large for moderately anisotropic media.     

三维地震与地面微地震联合校正方法

由于地面微地震监测台站布设在地表,会受到地表起伏、低降速带厚度和速度变化的影响,降低了微地震事件的识别准确度和定位精度,限制了地面微地震监测技术在复杂地表地区的应用.因此,将三维地震勘探技术的思路引入到地面微地震监测中,提出了三维地震与地面微地震联合校正方法,将油气勘探和开发技术更加紧密地结合在一起.根据三维地震数据和低降速带测量数据,通过约束层析反演方法建立精确的近地表速度模型,将地面微地震台站从起伏地表校正到高速层中的平滑基准面上,有效消除复杂近地表的影响.其次,根据射孔数据和声波测井速度信息,通过非线性反演方法建立最优速度模型,由于已经消除复杂近地表的影响,在进行速度模型优化时不需要考虑近地表的影响,因而建立的速度模型更加准确.最后,在精确速度模型的基础上,通过互相关方法求取剩余静校正量,进一步消除了复杂近地表和速度模型近似误差的影响.三维地震与地面微地震联合校正方法采用逐步校正的思路,能够有效消除复杂近地表的影响,提高微地震数据的品质和速度模型的精确度,保证了微地震事件的定位精度,具有良好的应用前景.     

Regional minimum 1-D P-wave velocity model for a new seismicity catalogue with precise and consistent earthquake locations in southern Iran

For faster and more robust ray tracing in 1-D velocity models and also due to the lack of reliable 3-D models, most seismological centers use 1-D models for routine earthquake locations. In this study, as solution to the coupled hypocenter-velocity problem, we compute a regional P-wave velocity model for southern Iran that can be used for routine earthquake location and also a reference initial model for 3-D seismic tomography. The inversion process was based on travel time data from local earthquakes paired reports obtained by merging the catalogues of Iranian Seismic Center (IRSC, 6422 events) and by the Broadband Iranian National Seismic Network (BIN, 4333 events) for southern Iran in the period 2006 through July 2017. After cleaning the data set from large individual reading errors and by identifying event reports from both networks belonging to same earthquake (a process called event pairing), we obtained a data set of 1115 well-locatable events with a total number of 24,606 P-wave observations. This data set was used to calculate a regional minimum 1-D model for southern Iran as result of an extensive model search by trial-and-error process including several dozens of inversions. Significantly different from previous models, we find a smoothly increasing P-velocity by depth with velocities of 5.8 km/s at shallow and velocities of 6.4 km/s at deepest crustal levels. For well-locatable events, location uncertainties are estimated in the order of ±?3 km for epicenter and double this uncertainty for hypocentral depth. The use of the minimum 1-D model with appropriate station delays in routine hypocenter location processing will yield a high-quality seismic catalogue with consistent uncertainty estimates across the region and it will also allow detection of outlier observations. Based on the two catalogues by IRSC and BIN and using the minimum 1-D model and station delays for all stations in the region, we established a new combined earthquake catalogue for southern Iran. While the general distribution of the seismicity corresponds well with that of the two individual catalogues by IRSC and BIN, the new catalogue significantly enhances the correlation of seismicity with the regional fault systems within and between the major crustal blocks that as an assembly build this continental region. Furthermore, the unified seismic catalogue and the minimum 1-D model resulting from this study provide important ingredients for seismic hazard studies.     

Convolutional neural networks for automated microseismic detection in downhole distributed acoustic sensing data and comparison to a surface geophone array

Distributed acoustic sensing is a growing technology that enables affordable downhole recording of strain wavefields from microseismic events with spatial sampling down to ∼1 m. Exploiting this high spatial information density motivates different detection approaches than typically used for downhole geophones. A new machine learning method using convolutional neural networks is described that operates on the full strain wavefield. The method is tested using data recorded in a horizontal observation well during hydraulic fracturing in the Eagle Ford Shale, Texas, and the results are compared to a surface geophone array that simultaneously recorded microseismic activity. The neural network was trained using synthetic microseismic events injected into real ambient noise, and it was applied to detect events in the remaining data. There were 535 detections found and no false positives. In general, the signal-to-noise ratio of events recorded by distributed acoustic sensing was lower than the surface array and 368 of 933 surface array events were found. Despite this, 167 new events were found in distributed acoustic sensing data that had no detected counterpart in the surface array. These differences can be attributed to the different detection threshold that depends on both magnitude and distance to the optical fibre. As distributed acoustic sensing data quality continues to improve, neural networks offer many advantages for automated, real-time microseismic event detection, including low computational cost, minimal data pre-processing, low false trigger rates and continuous performance improvement as more training data are acquired.     

Mining-induced microseismic event location errors: Accuracy and precision of two location systems

The accuracy and precision of microseismic event locations were measured, analyzed, and compared for two types of location systems: anolog and digital. In the first system, relative times of first arrival were estimated from analog signals using automated hardware circuitry; station positions were estimated from mine map coordinates; and event locations were determined using the BLD (Blake, Leighton, and Duvall) direct solution method. In the second system, arrival times were manually measured during interactive displays of digital waveforms; station coordinates were surveyed; and the SW-GBM (Salamon and Wiebols; Godson, Bridges, and McKavanagh) direct basis function was used to solve for locations. Both systems assume constant isotropic seismic velocity of slightly different signals data sets, calibration blast signals with known source site and origin time, and microseismic event signals, were recorded by each location system employing the same array of high-frequency (5 kHz) accelerometers with 150 m maximum dimension. The calibration blast tests indicated a location precision of ±2 m and accuracy of ±10 m for the analog system. Location precision and accuracy for the digital system measured ±1 m and ±8 m, respectively. Numerical experiments were used to assess the contributions of errors in velocity, arrival times, and station positions on the location accuracy and precision for each system. Measured and estimated errors appropriate to each system for microseismic events were simulated in computing source locations for comparison with exact synthetic event locations. Discrepancy vectors between exact locations and locations calculated with known data errors averaged 7.7 and 1.4 m for the analog and digital systems, respectively. These averages are probably more representative of the location precision of microseismic events, since the calibration blast tests produce impulsive seismic arrivals resulting in smaller arrival-time pick errors in the analog system. For both systems, location accuracy is limited by inadequate modeling of the velocity structure. Consequently, when isotropic velocity models are used in the travel-time inversions, the increased effort expended with the digital location system does not, for the particular systems studied, result in increased accuracy.     

Application of microseismic multiplet analysis to the Basel geothermal reservoir stimulation events

The stimulation of a geothermal well in Basel, Switzerland produced a distribution of microseismic event locations with an overall alignment in the direction of the maximum horizontal stress. Fault plane solutions of individual larger events indicated movements on fracture planes at an angle to the maximum horizontal stress that could not be reliably interpreted from the event locations. To obtain higher resolution images of the microseismic event locations, events with similar waveforms have been identified by multiplet analysis. A number of receivers were used in the multiplet processing to ensure each multiplet is represented by a unique group of waveforms. The location accuracy within each multiplet has been significantly improved using cross‐correlation to refine the shear‐wave traveltime picks. The distribution of events within each multiplet can be interpreted as being due to movements on a single fracture or a number of near parallel fractures. It is shown that whilst the overall distribution of events is around the direction of the maximum horizontal stress, the individual multiplets representing fracture planes have a variety of azimuths and dips.     

Microseismic Full Waveform Modeling in Anisotropic Media with Moment Tensor Implementation

Seismic anisotropy which is common in shale and fractured rocks will cause travel-time and amplitude discrepancy in different propagation directions. For microseismic monitoring which is often implemented in shale or fractured rocks, seismic anisotropy needs to be carefully accounted for in source location and mechanism determination. We have developed an efficient finite-difference full waveform modeling tool with an arbitrary moment tensor source. The modeling tool is suitable for simulating wave propagation in anisotropic media for microseismic monitoring. As both dislocation and non-double-couple source are often observed in microseismic monitoring, an arbitrary moment tensor source is implemented in our forward modeling tool. The increments of shear stress are equally distributed on the staggered grid to implement an accurate and symmetric moment tensor source. Our modeling tool provides an efficient way to obtain the Green’s function in anisotropic media, which is the key of anisotropic moment tensor inversion and source mechanism characterization in microseismic monitoring. In our research, wavefields in anisotropic media have been carefully simulated and analyzed in both surface array and downhole array. The variation characteristics of travel-time and amplitude of direct P- and S-wave in vertical transverse isotropic media and horizontal transverse isotropic media are distinct, thus providing a feasible way to distinguish and identify the anisotropic type of the subsurface. Analyzing the travel-times and amplitudes of the microseismic data is a feasible way to estimate the orientation and density of the induced cracks in hydraulic fracturing. Our anisotropic modeling tool can be used to generate and analyze microseismic full wavefield with full moment tensor source in anisotropic media, which can help promote the anisotropic interpretation and inversion of field data.