Steven D. Glaser,1 John W. Dudley II,2 and Jacob Shlyapobersky2

ACTIVE AND PASSIVE ACOUSTIC IMAGING INSIDE A LARGE-SCALEPOLYAXIAL HYDRAULIC FRACTURE TEST

REFERENCE: Glaser, S.D., Dudley, J.W. II, and Shlyapobersky, J., “Active andPassive Acoustic Imaging Inside a Large-Scale Polyaxial Hydraulic Fracture Test,”Nondestructive and Automated Testing for Soil and Rock Properties, ASTM STP 1350,W.A. Marr and C.E. Fairhurst, Eds., American Society for Testing and Materials, 1998.

ABSTRACT: An automated laboratory hydraulic fracture experiment has beenassembled to determine what rock and treatment parameters are crucial to improving theefficiency and effectiveness of field hydraulic fractures. To this end a large (460 mmcubic sample) polyaxial cell, with servo-controlled X, Y, Z, pore pressure, crack-mouth-opening-displacement, and bottom hole pressure, was built. Active imaging withembedded seismic diffraction arrays images the geometry of the fracture. Preliminarytests indicate fracture extent can be imaged to within 5%. Unique embeddible high-fidelity particle velocity AE sensors were designed and calibrated to allow determinationof fracture source kinematics.

KEYWORDS: acoustic emission, acoustic imaging, hydraulic fracture, polyaxial testing,process zone, sensors

This paper describes an automated polyaxial loading and acoustic imaging systemdesigned for the Hydraulics Fracture Mechanics Project at the Shell Exploration andProduction Laboratories (Shell) under sponsorship of the Gas Research Institute (GRI).The primary goal of the project is to gain new physical insight into hydraulic fracturingwhich will reduce the uncertainties and improve the accuracy of existing pressurecalibrated models and field operational procedures. Toward this end a unique integratedpolyaxial loading, active acoustic imaging, and passive acoustic monitoring system wasdevised and built. This system allows detailed experiments defining fracture growth andcrack-tip processes under conditions very close to in situ for the first time. Insight gainedin acoustic imaging and fracture monitoring of hydraulic fracture mechanisms in thelaboratory will add to the understanding of field seismic monitoring, leading to real-time

1 Assistant professor, Dept. of Civil Engineering, University of California, Berkeley, CA 94720-1710.

2 Senior research physicist, and staff research engineer, respectively, Shell Exploration and Production Co.,P.O. Box 481, Houston, TX 77001.

monitoring of fracture geometry. This knowledge will aid in optimizing fracturingtreatments to improve their effectiveness, resulting in increased well productivity andprofitability.

Description of ExperimentThis project is based on our ability to control the fracturing environment

completely, using realistic field stress conditions, saturated samples with significant porepressure, and low viscosity fluids. To this end emphasis was placed on the design andconstruction of the experimental equipment, especially the polyaxial (true triaxial)loading system. This unique device was designed to test large enough specimens (460mm cube) so that parameters such as grain size, inheterogeneities, anisotropies, and crackgrowth rate could be studied without boundary and size effects. The ability to loadindependently in 3 orthogonal directions allows experimental study of the effects of insitu stresses on fracture propagation in a detail not possible before. The 3-D testing issupported by 2-D pilot testing on plate samples that is used to define polyaxial testconditions and identify various tip mechanisms by direct observation of fracturepropagation. The experimental program consists of three parts:

Task 1: Hydraulic fracturing experiments are being conducted on 460 mmcubes under realistic 3D stress conditions in various saturated rocks to buildhydraulic fracture mechanism maps (Shlyapobersky and Chudnovsky 1994)and investigate the effects of both in-situ and treatment parameters uponfracture tip mechanisms and process zone growth;Task 2: Real-time passive and active acoustic measurements of fracturegeometry and process zone during these tests so that fracture geometry andkinematics can be measured. This allows correlation of fracture tipmechanisms and process zone to the observed microseismic activity and thechanges of dynamic rock properties,Task 3: Post-test microstructure characterization of hydraulically fracturedsamples is used to relate changes in rock texture and morphology to treatmentand in-situ conditions. These changes will also be related to signatures ofacoustic signals recorded during polyaxial tests.

This paper will address work done toward achieving Tasks 1 and 2, especially theintegrated active and passive acoustic methods to image and monitor fracture behaviorwithin the polyaxial cell. The combined methods allow estimation of the damage state,as well as imaging the location and geometry of the fracture. Active imaging is a low-frequency ultrasonic method that utilizes mathematical imaging schemes developed bythe Center for Wave Phenomena (Cohen and Stockwell 1997) for seismic imaging of theearth. Active acoustic monitoring allows internal defects and inhomogeneities to beimaged using reconstruction of acoustic wave propagation.

Passive monitoring uses acoustic emission (AE) to localize and characterizedisplacement sources within the specimen using an approach based on fundamentalphysical principles. Monitored deformations of the rock specimen are associated with

microcracking and microcrack nucleation, at times yielding signal bandwidthsapproaching 1 MHz and displacements less than 10-12 m (e.g. Eitzen et al. 1981).

Purpose of Project

Hydraulic Fracturing and Fracture Mechanics

Significant discrepancies between field observations and conventional hydraulicfracture model predictions were identified in the 1980's, especially concerning fracturegeometry. Fracture job designs based on these models implied pumping very expensiveand conservative treatments. Recognizing the limitations of conventional hydraulicfracture models, various net pressure calibrated models and procedures were introducedinto field practice (e.g. Shlyapobersky 1985; Shlyapobersky et al. 1988; Cleary et al.1991). The economical optimization based on these models results in radically improvedjob designs, but these designs must be calibrated to measure field treatment pressuresusing a variety of fracture “tip effects”.

Several tip processes are currently used to calibrate hydraulic fracture models;among them are apparent fracture toughness, fluid lag, tip dilatancy, and continuumdamage parameters (Shlyapobersky and Chudnovsky 1994). Various fracture tipmechanisms can materialize under different in-situ and treatment conditions since thesetip processes are scale dependent mechanisms which affect fracture growth differentlyunder various conditions (i.e., lithology barriers, stresses, etc.). Generally, the field datacontain limited information about the actual fracture processes and do not provide detailsneeded for calibrating the fracture design models. More important, numerical simulationsusing laboratory-measured rock properties have indicated that these models cannot matchfield net pressure; and therefore, do not have predictive capabilities.

Uncertainties in predicting the actual hydraulic fracture geometry by numericalmodels prompted numerous field fracture monitoring experiments (e.g., Sadra et al. 1988;Vinegar et al. 1992; Sleefe et al. 1993; Block et al. 1994). An objective of theseexperiments is to compare the numerically computed hydraulic fracture geometry withgeometry mapped using geophysical methods. The latter are usually microseismic and/orgeotomography methods. Recorded and located microseismic signals are distributed overa large hydraulically fractured zone. This physical evidence appears in contradiction tothe simple planar fracture geometry predicted by simplified numerical models. Mahrerand Mauk (1987) and Mahrer (1991, 1993) showed that only a wide fractured zone couldaccount for the microseismic character they observed in treatment well post-fracturemicroseismic data. However, rather than improve measurements and the simplifiedmodel, the width of the microseismic zone is often attributed ad hoc to error in sourcelocation or events arising from slippage on existing defects near the fracture rather thanconsidering a diffuse process zone. One faces similar uncertainty with active monitoring:observed changes in signal amplitude and arrival time cannot be uniquely identified withthe wetted fracture geometry, as possible stress-induced velocity perturbations around thefracture (which actually may be a single crack surrounded by multiple microfractures)may affect the seismic waveforms.

New developments in seismic imaging and nondestructive material evaluationoffer a variety of options for imaging the fracture process, which are implemented in theproject here described. In the past, several groups around the world have performedlaboratory hydraulic fracture experiments (e.g. Savic 1992, 1995; Weijers et al. 1992; dePater et al. 1994); Biot et al. 1984; Daneshy 1976). The experimental facilities andavailable data, however, often limited the interpretation of these tests to simplehomogeneous fracture geometries. We are attempting to apply advances in experimentalfacilities and techniques to the hydraulic fracture process in a controlled laboratoryenvironment under more representative in situ conditions including significant porepressure to address recently identified problems.

Polyaxial Loading System

Design

The hydraulic fracturing experiments are performed in a large true polyaxial loadframe at Shell E&P Technology Company’s Bellaire Technology Center in Houston,Texas. A schematic of the cell and instrumentation is given in Fig. 1. The load frame(1.5 m on a side) accepts a 460 mm cubic rock specimen. Steel flatjacks are used toapply a uniform load to each dimension of the sample through controlled injection ofhydraulic oil. Porous sintered metal can be placed between the flatjacks and the rockspecimen to allow controlled pore fluid flow. For hydraulic fracturing experiments, a 30mm borehole is drilled to the center of the block, and a sharp groove is cut perpendicularto the wellbore to provide a point for fracture initiation. Crack growth inside the rocksample is monitored during fracturing with an array of ultrasonic transducers coupled intothe surface of the block, embedded with their top surfaces flush with the surface of therock. The sample, flatjacks and all instrumentation are contained within an aluminumpore pressure containment box capable of maintaining up to 35 MPa pore pressure. Theability to perform these highly monitored hydraulic fracture tests under realistic stressconditions with significant pore pressure is unique to this apparatus.

Table 1 gives the system specifications. All external stresses, pore pressure andinjection pressure are supplied using PID servo-controlled hydraulic intensifiers. Stresstransfer efficiency from the flat jacks to the specimen was carefully calibrated and istypically 85 to 90%, with load stabilization occurring within 2 minutes. Experimentalcontrol and data acquisition are done using custom software written in LabView runningunder Windows NT on a Pentium Pro computer. Up to 32 channels of parametric dataacquisition are provided, with all channels having a digitization rate greater than 5000samples/s for recording information during rapid pressure decline periods. The injectionsystem is capable of flowing clear fluids from 0.05 – 50 mL/s for continuous volumes upto 1.8 L. The system has been used successfully to initiate and propagate hydraulicfractures in a variety of materials (sandstone, limestone, and diatomite) using low (~1 cP)and moderate (~1000 cP) viscosity fluids in relatively high (several millidarcies)permeability rock. Saturated block tests have been done with brine pore pressures up to517 MPa.

R o c kS a m p l e

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P or o u sP l at e

A ct i ve/ Pas s i ve A cou s t icWavef o r m D ata Acqu i s i t i on

S ys t em

P o l y ax i al

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P r es s u r e I n t en s i f i er s

B o r eh o l e

Ser vo-Hydr aul icContr ol

FIG. 1--Schematic of the polyaxial cell

TABLE 1-- Polyaxial Testing Frame Specifications

Sample size 460 mm x 460 mm x 460 mm

External X, Y, Z stresses 55 MPa

Pore pressure 34.5 MPa

Injection pressure 69 MPa

Injection rate 0.05 – 50 mL/s

Accuracy of stress control ± 7 kPa

A key piece of the monitoring system is the borehole instrumentation apparatus.The device minimizes the borehole volume and uses a precision miniature pressure gauge(stainless steel diaphragm with a compensated full bridge) and high-resolution gage headfor monitoring the bottom hole pressure and crack mouth opening displacement(CMOD), respectively.

Acoustic Imaging Systems

An overview of the entire acoustic data acquisition, imaging, and monitoringsystem is shown in Fig. 2. The acquisition and imaging subsystems will now each bedescribed in detail.

Data Acquisition Subsystem

Most requirements for the acoustic data acquisition system are driven by the needto accurately record waveforms passing through or emanating from within a 460 mm

cube of porous material. Specifications for the various components are determined byconsidering the acoustic properties of such blocks and the information we plan to extractfrom the acoustic signals. For passive (AE) monitoring the system must be able todigitize a set number of data points for a minimum of 8 channels, store the data, andrearm quick enough to ensure no useful data from the sometimes extremely rapid rate ofmicrocrack growth increment are lost before retriggering is enabled. Up to this project,this has not been reasonably possible.

The upper bound for acoustic frequencies we are concerned with is primarilydetermined by the attenuation characteristics of the porous media. Preliminary tests onthese materials indicate frequencies near 1 MHz are extremely attenuated and do notpropagate more than a few tens of mm or so. For imaging or monitoring through 300 mmof material, we are effectively limited to frequencies of several hundred kHz.

FIG. 2--Polyaxial cell data acquisition system at the Shell Exploration and ProductionBellaire Laboratory

For active imaging, it is desirable to use the highest frequency possible in order togenerate the smallest wavelength and therefore the best resolution. For the porous rocksused in these experiments, velocities are typically in the range 2-5 km/s, which at 250kHz yields wavelengths of 7.5 mm. The RF-tone burst generator we are using is one ofthe few NDT devices available that can produce significant energy at our frequency ofinterest – 50 kHz to 5 MHz. We initially used a single-cycle 250 kHz tone burst as asource but now make use of arbitrary Ricker wavelets generated by a PC-mountedarbitrary waveform generator and amplified to 800 V by the gated amplifier. Since we do not expect signals with frequency content above 500 kHz (Nyquistfrequency), minimum time resolution is controlled by the desired maximum accuracy ofthe source location. Source location accuracy is primarily a function of sensor size. Thehigh-fidelity transducers we have developed will have an active diameter of 1.5 mm,therefore, first arrival time accuracy must provide distance accuracy to less than a mm.Assuming a rock velocity of 5 km/s, a 1 mm distance is equivalent to a 200 ns timeinterval, which equates to a 5 MHz sampling rate. Hence, we need a minimum waveform

sampling rate of 5 MHz to satisfy both the arrival time resolution and signal frequencycontent considerations.

The digitizer amplitude resolution is determined by the expected dynamic rangeof the acoustic signals. For both the active and passive acoustic signals we can expect adynamic bandwidth of at least one order of magnitude, yielding a minimum signal-to-noise ratio of 10. This gives a minimum dynamic range of 1000 discrete amplitudelevels, or ten-bits. These considerations mandate a nominal twelve-bit digitizer, as theminimum resolution needed to obtain the required dynamic range.

We have integrated a fast versatile digitizer custom-made by Hi-Techniques, Inc.3

The new digitizer provides data streaming directly to disk (10 Msamples/s per channel)and continuous waveform time-stamping with an accuracy of up to plus/minus 50 ns.These unique capabilities allow direct digitization of an entire test and calculation ofenergy distribution among the various dislocation sources identified. Triggeringcapabilities include four-channel full and/or logic modes with user configurable timedtrigger windows, which reject trigger from events occurring outside of the predeterminedfracture zone. Each digitizer channel is controlled by its own CPU that oversees memorymanagement, triggering, and data storage to disk. This results in trigger rearming withintens of microseconds and virtually continuous logging to disk. The system has sixteenindependent high-speed data channels, twelve 8-bit and four 14-bit. The data acquisitionsystem is fully integrated into the computer-controlled servo-hydraulic load system, andthe passive and active imaging system, with software integral to the digitizer allowingautomation of much of the post-test data manipulation.

Active Imaging Subsystem

Active imaging provides a method of quantifying crack growth within a specimenentombed inside the polyaxial load frame. The images created can be used to determinefracture geometry and identify fracture mechanisms. The imaging is achieved using low-frequency ultrasound to detect the fracture within the rock, and seismic data processingtechniques to generate images of the fracture in the space domain from the time-domainultrasonic data. Ultrasonic reflection is a suitable method for detecting millimeter scalefeatures within solids, and imaging using acoustic reflection is well developed in seismicprospecting of kilometer scale geologic structures (Tura et al. 1992). However, seismicimaging techniques have not typically been applied to ultrasound data. Some significantwork has been done in this area (e.g. Weijers et al. 1992; de Pater et al. 1994), but notunder significant pore pressure conditions with low viscosity fluids. Active imaging ofthe hydraulic fracture process in polyaxial tests can be performed using variousapproaches, such as transmission (e.g. Savic 1992) reflection, and diffraction. Theselection of a particular method depends on the sensitivity of the method to the acousticchanges occurring in the tested block. Reflection tomography was chosen since using areflection method requires coupling transducers to only one surface of the test block,which greatly simplifies the laboratory configuration for the imaging experiments. Thereflection method is capable of detecting a crack 1/100 of a wavelength in thickness, and

3 Hi-Techniques, Inc., Madison, WI.

allows utilization of the extensive image reconstruction software applications developedby the petroleum exploration industry. To maximize reflection contrasts and to avoid thescattering associated with mode conversions, the SH-wave is used as the active source.

The reflection method utilizes a line of closely spaced transducers, which caneach act as source or receiver. The acoustic pulse travels from the one source through thematerial until it meets an impedance contrast, which acts as a reflection source, sending anew signal back to the receiver sensors. The number of transducers to be pulsed andscanned determines the resolution of the resulting image based on an analogous“Nyquist” distance. All the data from a complete scan along the line is collected andprocessed to produce a 2-D image through the body along that line. Combining severalarray lines allows construction of a 3-D image of the block interior. Detailed imaging offracture geometry and process requires sophisticated interpretation software. We areusing the Seismic UNIX (SU) package (Cohen and Stockwell 1997), a freely distributedsoftware developed by academic research and principally funded by GRI. As an ongoingopen-architecture code, SU allows for modifications. At present the algorithms areoptimized for large-scale field work and do not take full advantage of the control andrepeatability of laboratory tests.

To provide a “snap shot” image of the fracture, the active imaging system needsto scan through all the transducers and collect the data in a time short compared to thefracture growth rate. An image scan acquisition time of roughly 1-2 seconds is sufficientfor our range of fluids and pump rates. To scan a large number of channels requires avery fast computer controlled switching matrix. The switch matrix, as shown in Fig. 3,operates thusly. At the start of a scan, the control computer disables the passivemonitoring subsystem, generates an imaging wavelet through the onboard arbitrarywaveform generator, and sends a synch pulse to the gated amplifier. The gated amplifieropens a time gate for the source wavelet and sends out an amplified signal. This signal isrouted by the high voltage multiplexer to the proper channel in the A/B switch, whichsends the source impulse to the correct transducer. The remaining channels are set asreceivers, with their output routed through the A/B switch into the low voltagemultiplexer and into the 8 channels of digitization. This action is repeated with the next 8channels of receivers until the output from all 31 channels of receivers has been digitizedand recorded. This sequence is repeated 31 times so that each of the 32 sensors has beena sender with the other 31 receiving the diffracted signal from that source. The entireprocess comprises 1 scan and is done in 1 or 2 seconds under computer control. The datawas then transferred to a Linux workstation for processing and imaging.

Note from the figure the two layers of switching – multiplexers and A/B switch.A single layer of reed relay commonly has a cross-talk rejection of 80 dB, based oncapacitive coupling across the vacuum gap between reeds. Our source signals are as highas 800 V with the receiving sensor output of a few millivolts, which is 5 to 6 orders ofmagnitude or 100 to 120 dB. The two layer design gives an effective isolation of 160 dBas proven by laboratory calibration.

3 2 cabl es

3 2 cabl es

FIG. 3--Schematic of Cytec4 switch matrix.

Passive Imaging Subsystem

By using a wideband sensor having a flat frequency response over severaloctaves, the recorded signal is directly proportional to the actual kinetics at the receiverlocation, enabling researchers to determine not only the time of P-wave arrival, but alsothe arrival times of the S wave, reflections, as well as their relative magnitudes (e.g.Glaser and Nelson 1992). It has been shown that by using a high fidelity sensor, theinverse problem of determining the source function from remote measurements can beachieved (e.g. Eitzen et al. 1981). Full waveform signals also allow use of forwardmodeling to evaluate source kinematics (e.g. Ohtsu 1995; Aizawa et al. 1987).

A high-fidelity wide band particle velocity sensor was designed to be embeddedin the rock specimen. Embeddment is necessary for the polyaxial experiment, avoidsmode conversions at surfaces, and allows the sensor to be placed close the fracture area.The sensor is based on the NIST conical PZT element (e.g. Proctor 1986) and has afinished length of 38 mm and diameter of 16 mm. The sensor is robust enough to workunder 1MPa of brine pressure, and have successfully survived several cycles ofembeddment and retrieval. The design yields sensitivity equal to commercial resonantdevices while maintaining the high-fidelity of the NIST displacement sensors.Comparison with theoretically calculated waveforms for the embedded sensor - surfacestep force Lamb's problem prove the sensor to be an extremely accurate transducer ofparticle velocity, with a sensitivity of 2.34 V output per mm/s. Calibration as a surfacesensor by NIST (Fick 1996) shows the sensor to be an extremely accurate transducer ofsurface displacement with a sensitivity of 2.8 V/nm. Details about the design andconstruction of the sensor (Weiss and Glaser 1998) as well as calibration and verification(Glaser et al. 1998) can be found elsewhere.

4 Cytec Corp., Penfield, NY.

Proof of Active Imaging Subsystem

The reliability of the active imaging subsystem was tested in 2 controlled trials.Further details can be found in Hand and Glaser (1998). An initial hydraulic fracturingexperiment was performed on a sample of Torry Buff sandstone (Vs = 2700 m/s) insidethe polyaxial load frame. This scouting test was designed to examine the feasibility ofseeing reflected waves from small internal flaws. The specimen was confined with ahorizontal stress of 6.1 MPa and a vertical stress of 3 MPa and fractured by pumpingcontrolled volumes of hydraulic oil down the borehole in several cycles. The block wasinstrumented with simple piezoelectric shear and compression transducers on foursurfaces in the configuration shown in Fig. 4. A 250 kHz single-cycle tone burst resultedin 10.8 mm interrogating signal wavelength. During the fracturing process, thetransducers alternately were triggered, while the other sensors received signals.

11 PS 18

10 PP 9

17 PS 16

15

S

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13

S

S

12

2

P

P

1

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P

P

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4

P

P

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Cross- sectional View

Fracture T rans ducer T ypes Shear: 1 2- 18 Compress ional : 1- 11

FIG. 4--Active transducer configuration.

Figure 5 presents downhole pressure and CMOD as the fracturing experimentprogresses. The seismogram in Fig. 5 shows data recorded by transmitting with sheartransducer 13 and receiving with shear transducer 15. The horizontal axis represents thetime progression of the experiment; i.e. trace number 10 occurs early in the fracturingexperiment and trace number 120 is at the end of the experiment. The two figures arescaled so the pressure and CMOD shown at a given trace number correspond to thewaveform at the same trace number on the seismogram. The large pressure spikes in Fig.5 correspond to pump-in sequences, where the fracture is being opened and propagatedby injection of hydraulic oil. When the fracture is open at traces 16 through 20, 33-50,66-76 and 91-97, a strong reflection is visible at approximately 0.22 milliseconds on thevertical axis of the seismogram. A smaller amplitude reflection is also observable whenthe fracture is closed. Fracture images were not reconstructed for this test since multiplesource-receiver data are necessary to provide spatial resolution. However, the resultsindicated conclusively that detection of a small, approximately 0.1 mm, fracture waspossible using relatively low frequency ultrasonic transducers.

In order to verify the ultrasonic imaging technique under controlled benchtopconditions, a 228 x 305 x 381 mm test block was constructed from a gypsum cement usedfor making dental molds. The cement has density of 2.3 g/cc, a dry compressive strengthof 2.16 MPa and sets in 10 to 13 minutes with 0.18 to 0.20% expansion. A flawcomposed of two polyethylene sheets (150 mm dia.) with a thin layer of hydraulic oil

between them (1.5 mm thick tot.) was placed at a depth of 180 mm from the top surfaceof the block and 76 mm from the sides. An array of fifteen very resonant SH-wavetransducers were coupled to the top surface of the test block at 2 mm offsets withcyanoacrylate. Image reconstruction involved migration, stacking, various gathers, etc.,producing an image of a “slice” through the test block. Figure 6 is an example of a fullymigrated stacked section, yielding a result in terms of actual depth rather than 2-waytravel time. The flaw is visible at a depth of 180 mm, and the length of the flaw can beestimated at approximately 160 mm. The length of the flaw can be determined bycounting the number of common depth points (CDP) on which the flaw is visible andmultiplying by the offset distance, 10 mm. The flaw is evident on CDP’s 5 through 21,giving a length of 160 mm. The actual length of the flaw was 152 mm, giving a lengtherror of 4.6%. The width of the flaw (1.5 mm), is not resolvable from any of the datacollected. The ringing of the transducers and the long time duration of the signals resultsin an anomalous thick fracture or a smudgy image. Starting at common depth point(CDP) 19 at 0.17 ms, and extending to CDP 27 at approximately 12 ms, a diagonalfeature is evident. This feature is a thin crack that was most likely generated when themold was removed from the test block and is visible where it intersects the surface of theblock near transducer 15 at a depth of 123 mm.

Proof of Passive Monitoring

A rigorous verification process was undertaken to calibrate the embedded sensorto theoretical particle velocity time histories from predetermined sources and geometries(Glaser et al. 1998). The epicentral geometry was used as the fundamental calibrationcase, with a step force impulse on the surface of the block representing a half space andthe sensor embedded beneath. The sensor response to a 42 N step force input normal tothe top surface directly above the center-line of the embedded sensor is shown in Fig. 7,with output given as absolute particle velocity time history. For comparison, thetheoretical particle velocity time history for this scenario is also shown in Fig. 7. Thesegments of signals shown covers the period from just before the P-wave arrival to justafter the S-wave arrival.

Since this is the first time experimental waveforms for this geometry are given,the only way to calibrate the embedded response of the sensor is to compare experimentalsensitivity to the theoretical sensitivity of the embedded sensor. Comparison oftheoretical particle velocity history and sensor output voltage at the initial P-wave peakyields a particle velocity sensitivity of 2.34 V output per (mm/s), which compares to adisplacement sensitivity of 5.96 V/nm. The calculation was checked against anindependent solution based on a modified Cagniard technique, which yields the samecalibration factor.

The congruence between the measured and calculated particle velocities timehistory gives credence to the calibration of the sensor from theory. The theoreticalsolution accounts for the source kinematics and geometry of the capillary break(Breckenridge et al. 1990); the material was modeled using a Kennett propagator method(Kennett 1983) as a homogeneous half-space with a quality factor of 50. The onlyprocessing of the theoretical waveform is application of a 450 kHz low-pass filter (1-pole

two-way Butterworth) that mimics the filtering of the rock half-space. The experimentaltime history is presented as measured.

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C M O D

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0 . 2

0 . 3

FIG. 5--Results of Torry Buff fracture experiment.

FIG. 6--Migrated stacked section

-0. 5

-0. 4

-0. 3

-0. 2

-0. 1

0.0

Vel

oci

ty (m

m/s

)

302520151050

Tim e (µs)

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FIG. 7--Measured and calculated epicentral response to a 42 N surface step force. Thesensor is embedded 152.4 mm below and is sensitive to velocity normal to top surface.

Conclusion

This paper describes an automated polyaxial loading and acoustic imaging systemdesigned for the Hydraulic Fracture Mechanics Project at the Shell Exploration andProduction Laboratories (Shell) under sponsorship of the Gas Research Institute (GRI).A unique integrated polyaxial loading, active acoustic imaging, and passive acousticmonitoring system has been devised and built. This system allows for the first timedetailed experiments defining fracture growth and crack-tip processes under realisticstress conditions, with significant pore pressures and low-viscosity fluids. Embeddiblehigh-fidelity particle velocity AE sensors have been designed and calibrated to allowdetermination of fracture source kinematics. Active acoustic imaging techniques havebeen investigated in controlled trials. Insight gained in acoustic imaging and fracturemonitoring of hydraulic fracture mechanisms in the laboratory will add to theunderstanding of field seismic monitoring, leading to real-time monitoring of fracturegeometry. This knowledge will aid in optimizing fracturing treatments to improve theireffectiveness, resulting is increased well productivity and profitability.

Acknowledgments

The experiment described here is part of a joint research effort between ShellExploration and Production Technology Co. (Shell), the University of Illinois at Chicago(UIC), and the University of California at Berkeley (UC). The project is partially fundedby the Gas Research Institute under GRI Contract No.5093-221-2611. The principalparticipants at Shell: J. W. Dudley III, M. M. Arasteh, and J. Shlyapobersky; at UIC: A.Chudnovsky and J. Ma; and at UC: S.D. Glaser and his former students at ColoradoSchool of Mines, G. Weiss and M.K. Hand

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