DTS Primer ISRM Paper

download DTS Primer ISRM Paper

of 24

Transcript of DTS Primer ISRM Paper

  • Distributed Temperature Sensing

    A DTS Primer for Oil & Gas Production

    James J. Smolen & Alex van der Spek

    UNCLASSIFIED

    James J. SmolenSmolen Associates2122 N. Fountain ValleyMissouri City, TexasU.S.A. 77459-3647

    T 01 281 438-1141F 01 281 438-8846E [email protected]

    Alex van der SpekShell International Explorationand Production B.V.Postbus 602280 AB RijswijkThe Netherlands

    T 31 70 447 2536E [email protected]

  • Distributed Temperature SensingA DTS Primer for Oil & Gas Production

    James J. Smolen & Alex van der Spek

    UNCLASSIFIED

  • PREFACE AND ACKNOWLEDGEMENTS

    The intent of this endeavor is to have at hand a readable document to conveythe core ideas of DTS technology to the uninitiated reader. DTS stands forDistributed Temperature Sensing. Not only does this technology provide anon-intrusive glimpse of the wells temperature profile, it effectively addsthe dimension of time to temperature logging. Periodic or rapid-firesequences of temperature logs, now possible through DTS technology,suddenly bring clarity to the often murky world of temperature logevaluation and well monitoring. While this technology is seeminglycomplex, it is hoped that this document achieves its goal to be readable,understandable, and to generate interest in a new and effective technique forwell monitoring.

    I would like to thank Shell International Exploration and Production B.V.and my co-author, Alex van der Spek, for the opportunity to participate inthis document. I must also acknowledge my co-authors brilliant expositionof the mathematics of DTS which permeates this document! I would alsolike to thank the various service company and equipment suppliers who havetaken the time to help me understand the various complexities of DTS. Inparticular, my thanks go out to Mahmoud Farhadiroushan and Tom Parkerof Sensornet, to Nigel Leggett, Dennis Carr, and Rodne Setliff of Sensa, toDavid Johnson, Rick Pruett, and John Maida of Halliburton, to MiodragPancic and Kirby Jabusch of Promore, and Doug Norton of Weatherford.

    DTS is an amazing technology whose potential is not yet understood.Hopefully this document will inspire others to champion its application inthe oil and gas industry.

    James J. SmolenMay, 2003

  • Table of Contents; DTS PRIMER ___________________________________________________ i

    DISTRIBUTED TEMPERATURESENSING

    A DTS PRIMER FOR OIL & GAS PRODUCTION

    TABLE OF CONTENTS

    1. INTRODUCTION TO DTS1.1 WHAT IS DTS?1.2 HOW DOES DTS WORK?1.3 WHERE IS DTS USED?1.4 PURPOSE OF THIS MANUAL1.5 SOME UNITS COMMONLY USED IN FIBER OPTICS

    2. FIBER OPTIC TECHNOLOGY FOR DTS MEASUREMENTS2.1 THE LIGHT PULSE

    2.1A VELOCITY OF LIGHT IN GLASS2.1B LENGTH OF THE LIGHT PULSE

    2.2 TRAVEL TIME AND DISTANCE ALONG THE FIBER2.2A DETECTING THE BACKSCATTERED SIGNAL2.2B SPATIAL AND SAMPLING RESOLUTION2.2C DETERMINING THE MAXIMUM LAUNCH RATE2.2D REASONS FOR HIGH PULSE RATE

    2.3 BACKSCATTERED SPECTRUM2.3A THE RAYLEIGH, BRILLOUIN AND RAMAN LINES2.3B TEMPERATURE FROM THE

    ANTI-STOKES/STOKES RATIO2.3C TEMPERATURE CALIBRATION2.3D OPTICAL DISTORTION2.3E TEMPERATURE RESOLUTION

    2.4 THE DTS LOG

  • Table of Contents; DTS PRIMER ___________________________________________________ ii

    3. TYPICAL DTS INSTALLATIONS AND RECORDINGS3.1 INSTRUMENTATION SET-UP3.2 OPTICAL FIBER, CLADDING, AND CONVEYANCE

    3.2A THE OPTICAL FIBER3.2B MECHANICAL FIBER PROTECTION

    3.3 SELECTION OF LASER PULSE WAVELENGTH3.4 ASSESSING CONDITION OF INSTALLED FIBER

    (OTDR)3.5 TYPICAL DTS INSTALLATIONS

    3.5A OIL WELL INSTALLATION3.5B MONITORING PRESSURE VESSELS3.5C MONITORING FOR LEAKS IN A GAS PIPELINE3.5D OTHER DTS APPLICATIONS

    4. OIL WELL INSTALLATIONS AND HARDWARE4.1 TYPES OF OILWELL/GASWELL INSTALLATIONS

    4.1A RETRIEVABLE INSTALLATION4.1B SEMIPERMANENT INSTALLATIONS4.1C PERMANENT INSTALLATIONS

    4.2 SINGLE OR DOUBLE ENDED FIBER LINE4.2A SINGLE ENDED STRAIGHT SYSTEMS4.2B PARTIALLY RETURNED FIBERS4.2C DOUBLE ENDED FIBER INSTALLATIONS4.2D COMPARISON IF FIBER DEPLOYMENT SYSTEMS

    4.3 MECHANICAL DEPTH ISSUESOVERSTUFF

    5. APPLICATION AND INTERPRETATION OF DTS INOIL AND GAS WELLS

    5.1 INTERPRETATION OF TEMPERATURE LOGS5.1A CLASSIC LIQUID ENTRY5.1B CLASSIC GAS ENTRY5.1C SHUT-IN INJECTION WELLS5.1D HORIZONTAL PRODUCTION WELLS

  • Table of Contents; DTS PRIMER ___________________________________________________ iii

    5.2 EXAMPLES OF DTS TEMPERATURE LOGSUSED FOR VARIOUS APPLICATIONS

    5.2A COMPARISON OF CONVENTIONAL WIRELINEAND DTS SURVEYS

    5.2B DETECTION OF A CHANNEL5.2C DTS USED FOR WELL MONITORING5.2D ELECTRIC SUBMERSIBLE PUMPS(ESP), ETC.5.2E STEAM BREAKTHROUGH5.2F VELOCITY INDICATIONS USING DTS5.2G FLUID VELOCITY USING

    SENSA FLO-TRAK SYSTEM

    6. QUALITY CONTROL6.1 OVERVIEW OF QUALITY CONTROL6.2 SOME QUALITY CONTROL TECHNIQUES

    6.2A DEPTH MATCHING6.2B DETERMINING THE END OF THE FIBER

    6.2C FIBER DAMAGE/LINEAR CALIBRATION6.2D DETERMINING DIFFERENTIAL LOSS

    6.3 THE PUMPING PROCESS6.4 DATA GROUPS

    6.4A WELL INSTALLATION DATA GROUP6.4B FIBER DATA GROUP6.4C INSTRUMENT DATA GROUP6.4D PUMPING DATA GROUP6.4E FIBER INSTALLATION SCHEMATIC GROUP

    6.5 QC QUEST TRACK AND CHECK LIST

    7. VENDOR AND PRODUCT SPECIFICATIONS7.1 VENDOR LIST7.2 INSTRUMENT BOX USE7.3 INSTRUMENT BOX SPECIFICATIONS7.4 TEMPERATURE RESOLUTION AND TEST TIME7.5 RELATIVE COST OF DTS

  • Table of Contents; DTS PRIMER ___________________________________________________ iv

    APPENDIX A. DETERMINATION OF TEMPERATUREA1. ATTENUATION IN A GLASS FIBERA2. DETERMINATION OF TEMPERATURE

    APPENDIX B. TEMPERATURE RESOLUTIONB1. HOW DEPTH AFFECTS TEMPERATURE

    RESOLUTIONB2. A QUANTITATIVE LOOK AT TEMPERATURE RESOLUTION

    APPENDIX C. DETERMINING DIFFERENTIAL LOSSC1. DIFFERENTIAL LOSS FOR PARTIAL WRAP SYSTEMSC2. DOUBLE ENDED SYSTEMS/NON-LINEAR LOSSES

    APPENDIX D. GROUP CHECK LISTS

    LIST OF REFERENCES

    BIOGRAPHICAL SKETCH OF AUTHORS

  • Chapter 1: DTS PRIMER ________________________________________________________ 1

    DTSDISTRIBUTED TEMPERATURESENSING

    1. INTRODUCTION TO DTS

    1.1 WHAT IS DTS?

    DTS stands for Distributed Temperature Sensing. DTS is a technologywhich provides the user with a technique to measure the temperaturedistribution along a fiber optic line at any time and to repeat suchmeasurements as required. The fiber optic line can be any length up to about30km (about 18.5 miles). With the exception of the recordinginstrumentation at one or both ends of the fiber, there are no electronics, nosensors, no electrical wires or electrical connections along the line. The linemay be permanent or reinstalled for each use. It is inherently safe to use inenvironments where an electrical spark may pose a fire safety hazard.

    1.2 HOW DOES DTS WORK?

    Once a fiber optic line is installed, that line may be probed by means of ashort laser light pulse. That pulse, lasting 10 nanoseconds or less, travelsalong the fiber. As it does, the light collides with the lattice structure andatoms of the fiber, causing them to emit small bursts of light at slightlyshifted frequencies which travel back to the beginning of the fiber. Thisreturning backscattered light is then analyzed by the instrumentation boxto determine the temperature at the point from which the backscatteroriginated. Since the velocity of light is constant, even in a fiber, the two-way travel time from the launch of the light pulse to the return of thebackscattered light determines the position of the recorded temperaturealong the fiber. Continuous monitoring of such backscattered light allowsthe construction of a continuous temperature profile along the length of thefiber. Such a temperature profile is called a Distributed TemperatureSurvey or DTS (note that S may also refer to Sensing or Sensor).

  • Chapter 1: DTS PRIMER ________________________________________________________ 2

    1.3 WHERE IS DTS USED?

    A DTS has applications wherever the temperature distribution is useful. Forexample, a fiber optic DTS line may be tied to an electrical power line.1 Thetemperature of the power line can indicate overloading or that excesscapacity exists, thereby allowing more power to be conveyed safely over theline. DTS is most often used where temperature changes in time indicate theonset of deviant behavior or imminent failure of some system.2,3 Pressurevessels wrapped with a DTS line can be monitored to detect hot spots whichmay precede catastrophic failure. Oil wells can be monitored periodically todetect the onset and location of anomalous fluid production.4,5 The use ofDTS technology is quite young at this time, and many new and amazingapplications can be expected in future years.

    1.4 PURPOSE OF THIS MANUAL

    This manual is designed to acquaint the engineer with DTS technology,especially its utility in the Petroleum Industry. The emphasis is on theapplications and installations of such technology in oil and gas wells,although other applications will be described from time to time. Thismanual covers the basic fiber optic technology which enables the DTSmeasurement. It shows how such DTS systems are set up in various types ofsettings. Oil/gas well installations are discussed in detail as well as theinterpretation, quality control, and use of such DTS data. Lastly, vendornames, contacts, and product specifications are listed.

    1.5 SOME UNITS COMMONLY USED IN FIBER OPTICS

    When working with optics and the passage of light, the lengths andmagnitudes commonly encountered are quite unusual to most engineeringdisciplines. This section provides a very short overview of some major unitsas well as the prefixes used in the metric system. In the metric system, theLatin prefixes such as deci, centi, milli, and the like are used to indicate adivision of the major unit to which they are applied, while the Greekprefixes such as deka, hecto, kilo, and the like are used to indicate the orderof multiplication by orders of 10. Some units are used so commonly in

  • Chapter 1: DTS PRIMER ________________________________________________________ 3

    certain sciences that they have received special names.6 Some English unitsmay also be used. These are noted below.

    LATIN BASE GREEK BASE

    Deci 1/10 10-1 Deka 10 10+1

    Centi (c) 1/100 10-2 Hecto 100 10+2

    Milli (m) 1/1000 10-3 Kilo (k) 1,000 10+3

    Micro () 1/1,000,000 10-6 Mega (M) 1,000,000 10+6Nano 10-9

    SPECIAL NAMES

    1 Micron = 1 millionth of a meter (10-6 meter)1 Millimicron = 1 millionth of a millimeter (10-6 millimeter)1 Angstrom = 10-8 centimeter (10-10 meter)1 Nanometer = 10-7 centimeter (10-9 meter)1 Micrometer = 10-6 meter

    OTHER COMMON UNITS

    1 Kilometer = 0.6214 miles1 Meter = 39.37 inches1 Foot = 30.48 cm1 Inch = 2.54 cm1 Atmosphere = 14.696 psiSpeed Of Light in a Vacuum = 3x10+8 meters/sec = 186,000 miles/secAttenuation m-1 = 10-4 x ln(10) dB/km = 2.3026x10-4 dB/km

  • Chapter 2: DTS PRIMER _________________________________________________________ 1

    2. FIBER OPTIC TECHNOLOGY FORDTS MEASUREMENTS

    2.1 THE LIGHT PULSE

    2.1A VELOCITY OF LIGHT IN GLASS

    The light pulse is launched by a laser in the surface instrumentation orinstrument box. This light pulse is typically at a wavelength of betweenabout 800 to 1600 nm, in the infrared and just beyond the visible spectrum.7

    When this light enters the fiber, it is slowed down somewhat. The degree towhich it is slowed is related to the refractive index of the glass in the fiber.The velocity of light in the fiber, v, is related to the speed of light in avacuum, c, and the fiber refractive index through the following equation.

    v = c/n = (3 x 10+8)/1.5 = 2 x 10+8 m/s

    Most glass has a value of n between 1.5 and 1.7. Using a value of n=1.5, thevelocity of light in a glass fiber is determined to be about 2x10+8 m/s. If theglass fiber has a larger refractive index than the surroundings, then lightwithin the fiber may be trapped and forced to propagate through the fiber.This occurs when the angle of incidence between the light ray within thefiber and its interface with the surroundings is less than some critical value.This is the principle of total internal reflection based on Snells Law.8

    2.1B LENGTH OF THE LIGHT PULSE

    The laser light pulse typically has a duration of about 10 ns (nanoseconds) orless. When that pulse enters the fiber, it is said to be launched. The lengthof a 10 ns pulse in the fiber, assuming that the refractive index of the fiber is1.5, is given by multiplying the velocity of light in the fiber, c/n, times thepulse duration of 10ns.

    Light Pulse Length In Fiber = ((3. X 10+8) /1.5)m/s x (10x10-9)s = 2 m

    This light pulse is, in effect, a travelling sensor moving through the fiber lineand relaying back temperature information (See Fig. 2.1). The length of thispulse is one factor in resolution along the fiber length.

  • Chapter 2: DTS PRIMER _________________________________________________________ 2

    FIG. 2.1. Travelling light pulse sending backscattered light back to the instrument box.

    2.2 TRAVEL TIME AND DISTANCE ALONG THE FIBER

    2.2A DETECTING THE BACKSCATTERED SIGNAL

    The refractive index of the fiber is usually well known before installation. Itdetermines the speed of light in the fiber. When the light pulse travels tosome point along the fiber, z, the backscattered light must return along thatsame path, and the total two-way path length for the signal is 2z. If thevelocity of light in the fiber is v, a window can be opened at some time t tocapture that backscattered light. The time t for this window is

    t = 2z/v

    The window size required to achieve a one meter length resolution along thefiber (z = 1m) is

    t = 2z/v = 2x1/(2x10+8) = 10-8 = 10 ns

  • Chapter 2: DTS PRIMER _________________________________________________________ 3

    The instrumentation box must be capable of providing a series of adjacent10 ns windows. Service companies can provide such windows as small as1.0 ns. However, smaller windows can be effective only on shorter fiberlengths and the sampling time would be increased.

    2.2B SPATIAL AND SAMPLING RESOLUTION

    In the previous section it was shown that the samples can be gathered indepth increments of one meter if the backscatter detecting windows are setfor a 10 ns duration. This would be called the sampling resolution, i.e.,the depth increment at which temperature data is gathered. This, however, isnot the same as the depth or spatial resolution of a DTS system. Thedifference is easily illustrated by looking at the systems response to a short(.5m) temperature anomaly.

    In Fig. 2.2 below, the 2 meter light pulse in a fiber is shown moving along in2.5 ns increments. Each of these movements corresponds to .50 meters.

    FIG. 2.2. Response of a 2m light pulse to a .5m x 10 deg temperature anomaly.

    A temperature anomaly of 10 deg along .5 meter of the fiber is shown. Theresponse from the laser pulse is seen to spread the .5 meter step intemperature over about 2.5 meters and reduce the temperature detected toabout 2.5 degrees. The reduction of the temperature anomaly measured isroughly equal to the hot spot width divided by the spatial resolution, i.e.,the 2 meter length of the light pulse. Shorter laser pulses and smaller time

  • Chapter 2: DTS PRIMER _________________________________________________________ 4

    windows are required to better detect short length high temperatureanomalies.

    Spatial Resolution is more or less defined as the distance it takes a systemto fully respond to a sudden or step change in temperature. Considering thecircumstances similar to that of Fig. 2-2, it should be easy for the reader tosee that spatial resolution to a step temperature anomaly would be 2 meters.Of course, in real world conditions, with variations in backscattered light,filtering, and electronics,the actual transitionacross a step would not belinear, but would follow ashape like that shown inFig. 2.3. Under suchcircumstances, the SpatialResolution may bedefined as the distancebetween the 10% and90% points on thetemperature ramp.7,9,10 FIG. 2.3 Spatial resolution (Courtesy Sensa, Ref. 7)This definition is notUniversal and other definitions exist within the industry.

    2.2B DETERMINING THE LAUNCH REPITITION RATE

    Another factor to consider is how often launches should be repeated. Todiscuss this issue, consider a 3000m (about 10,000 ft) fiber optic line. Therecannot be two light pulses in the line at the same time. If this is the case, thebackscattered signals would be mixed and the resulting spectrum extremelydifficult or impossible to analyze. So, the light must travel to the end of thefiber and the backscattered light return before the next launch. Theminimum time between launches is the two-way travel time to the end of thefiber. For a 3000 m line and n=1.5,

    Time between launches = (2 x 3000 m)/(2 x 10+8 m/s) = 3 x 10-5 s

    This corresponds to about 33,000 launches per second. In actual cases, thelaunch rate is less, typically about 4000 to 10,000 pulses per second. This isthe case to allow for necessary data processing between launches.

  • Chapter 2: DTS PRIMER _________________________________________________________ 5

    2.2C REASONS FOR HIGH PULSE RATE

    Why is more than one pulse required? The reason is that the data returningis weak and noisy, i.e., it has a very poor signal to noise ratio. Hence manysignals must be stacked on one another to achieve statistically significantdata. Typically, a log may take five minutes or longer to run. At 4000pulses per second, this means that 1,200,000 launches have been completed.This many may be required to achieve a certain degree of temperatureresolution, say 1 deg C. To achieve higher temperature resolution wouldrequire more launches. DTS systems in general require longer times (morelaunches) to achieve better temperature resolution. Hence, a DTS systemsresolution should be stated in terms of fiber length and sampling time. Ingeneral, resolution is improved proportionally to n, where n is the numberof samples. For DTS systems, this is equivalent to the sampling time. Toimprove the resolution by a factor or two would require four times longersampling time.

    2.3 BACKSCATTERED SPECTRUM

    2.3A THE RAYLEIGH, BRILLOUIN, AND RAMAN LINES

    As the light pulse propagates along the fiber, it energizes the glass, latticestructure, and molecules. At first glance, the waves which return appear likereflections. They are not. The energized lattice and molecules then give offlight having wavelengths at, just above, and just below the wavelength of theincident wave. The main backscattered wave is at the wavelength of thelaunched wave and is called the Rayleigh peak or band. This is by far thestrongest signal returned. Except for certain special quality control tests, thissignal is usually filtered and suppressed. Those waves associated with thelattice vibrations show up as Brillouin lines or peaks on the backscatterspectrum. The Brillouin lines are very close to and difficult to separate fromthe main Rayleigh band. Finally, the weakest of the backscattered waves,resulting from molecular and atomic vibrations, are the Raman Bands. TheBackscatter Spectrum is shown on Figure 2.4.7,9-12

  • Chapter 2: DTS PRIMER _________________________________________________________ 6

    2.3B TEMPERATURE FROM THE ANTI-STOKES/STOKES RATIO

    The Raman signal is the signal used for evaluation of temperature. It issufficiently strong and has a unique temperature dependence. Its wavelengthis also shifted substantially (about 40/Nm) from the main Rayleigh peak,thereby allowing the dominant Rayleigh and Brillouin peaks to be filteredout.

    FIG. 2.4. Backscatter spectrum with Rayleigh, Brillouin, and Raman bands as well asthe Stokes and anti-Stokes bands. (Courtesy Pruett Industries, now Halliburton, Ref. 11).

    The Raman signal is comprised of the so-called Stokes and anti-Stokesbands. The Stokes band at the higher wavelengths (red shifted) is stablewith little temperature sensitivity. The anti-Stokes band at the lowerwavelengths (blue shifted) exhibits a temperature sensitivity, where thehigher the energy within the band, the higher the temperature and vice versa.A ratio of the energy or area within the Anti-Stokes band to that of theStokes band can be simply related to the temperature of the fiber optic line atthe depth where the signal originated.

    The temperature, T(z) (deg K), can be related to the ratio of anti-Stokes toStokes signals by the equation (This equation is a simplification. SeeAppendix A for the origin of this equation.)

    T(z) = Tref (1+ z/ln(C+/C-) + ln(I+/I-)/ln(C+/C-))

  • 1

    DEEP UNDERGROUND INSTRUMENTATION AND MONITORING H.F. Wang1, J.R. Gage1, D. Fratta2, M. MacLaughlin3, L.C. Murdoch4, and T. Tokunaga5

    1 Department of Geoscience, University of Wisconsi Madison, 1215 W. Dayton Street., Madison WI, 53706 USA 2 Geological Engineering Program, University of WisconsinMadison, 1415 Engineering Drive, Madison, WI 53706 USA 3 Department of Geological Engineering, Montana Tech, 1300 West Park Street, Butte, MT 59701USA 4 Department of Environmental Engineering and Earth Science, Clemson University, 340 Brackett Hall Clemson, SC 29634 USA 5Department of Environmental Systems, University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa-shi, Chiba, 277-8563, Japan INTRODUCTION The structural integrity of deep, large underground facilities such as tunnels, mines, pumped storage facilities, and physics laboratories requires the ability to predict rock mass stability under loading to ensure the safety of human occupants and the longevity of the underground space. Deformation occurs over time scales that range from milliseconds to decades and spatial scales that range from millimeters to facility scale. Beginning with design, prediction is typically based on finite element models using available or estimated properties. As with most geotechnical problems, much of the difficulty of prediction lies in the inability to sufficiently characterize the rock properties, especially discontinuities. As a consequence, semi-quantitative measures, such as Rock Mass Rating (RMR) or the Hoek-Brown Geological Structure Index (GSI) [1], are used to characterize the rock mass together with empirical charts for design criteria such as rock bolt spacing for ground control. During and following construction, validating model predictions is necessary to assess their performance. Parameter adjustment, or even the physics incorporated within the model, can be made using back analysis. This monitoring should be a continuous or periodic process over the life of the facility. For civil structures, the post-construction era will be measured in decades. With the inherent uncertainties and high stresses associated with the deep underground environment, the potential for rock failure must always be borne in mind. Mitigating the risk is prudent, but formal cost-benefit analysis may be precluded by the uncertainties. Keeping abreast of the condition of the facility through Structural Health Monitoring (SHM) is gaining acceptance for underground construction [2]. One reason for the growth in research in monitoring is that maturing technologies, like fiber-optic sensors and associated instrumentation, can collect data that were not previously achievable. They are robust and geometrically flexible, possess long-term stability, are cost effective, and extend coverage in spatial extent with improved resolution or provide data at a higher sampling rate. In addition to fiber-optic technology, a host of new technologies with potential for underground geotechnical applications exist, including LIDAR, wireless smart dust, piezoelectric sensors, and high resolution electrical and seismic imaging [3; 4; 5; 6; 7]. The subject of this paper is mainly to describe preliminary experiments, future needs, and instrumentation and monitoring plans of the authors research activities in the 2400-meter Deep Underground Science and Engineering Laboratory (DUSEL) in the Black Hills of South Dakota, USA, where fiber-optic sensors and water-level tiltmeter arrays have been installed. 1. FIBER-OPTIC SENSING Fiber optic sensors consist of two main types: discrete Fiber Bragg Grating (FBG) sensors and distributed strain and

    HP_AdministratorText BoxH. F. Wang, J. R. Gage, D. Fratta, M. MacLaughlin, L.C. Murdoch, T. Tokunaga (2010), Deep Underground Instrumentation and Monitoring, in ISRM International Symposium 2010 and 6th Asian Rock Mechanics Symposium - Advances in Rock Engineering 23-27 October, 2010, New Delhi, India Proceedings, ed. by K.G. Sharma, T. Ramamurthy, V. K. Kanglia, and A.C. Gupta, pp. KN46 - KN57..

  • 2temperature (DST) cables. FBG sensors consist of a glass filament core contained in protective cladding. A periodic refractive index grating is written into the core of the fiber. Broad-spectrum light is transmitted down the fiber from an optical laser interrogation box. The grating reflects the wavelength of light that matches the Bragg wavelength while all other wavelengths are transmitted through the fiber. Strain and temperature introduce a shift of the Bragg wavelength [8]. The change in the reflected wavelength of light from the FBG sensor directly corresponds to changes in strain and temperature.

    In distributed strain and temperature sensing, the fiber-optic cable itself is the sensor, and measurements are taken along the entire length of the cable. Distributed sensors are based on Raman and Brillouin scattering of light. Raman scattered light is caused by thermally induced molecular vibrations, which are caused by temperature changes along the cable [9]. Brillouin scattering occurs due to the interaction between the propagating light signal and thermally excited acoustic waves present in the silica core of the fiber. This interaction between light and acoustic waves creates a frequency shift in the propagating light signal, which is controlled by strain and temperature [10]. Fiber-optic sensing technologies have been used successfully in civil engineering for Structural Health Monitoring (SHM). SHM provides information over both long and short time periods [11] concerning structural condition and performance based on measurements of load, deformation, and temperature [9]. SHM not only provides a warning of imminent failure of a structure, but in the best case scenario the data from SHM can be used to plan maintenance activities, increase safety, and monitor the performance of a structure to prevent failure from being reached. Duncliffe [12] recognized the potential for fiber-optic sensors for geotechnical monitoring. Currently, fiber optic sensors are used for several geotechnical applications such as monitoring convergence in underground tunnels [13], monitoring temperature and strain at thousands of points over up to 300 km of pipeline [9], or monitoring deformations caused by the construction of tunnels [14]. Most fiber-optic sensors have a conventional counterpart. For example, an FBG patch gage with a size of a couple of centimeters provides data similar to an electrical resistance foil gage. In both cases the key element to their success is packaging the sensing element to protect them for breakage. Distributed fiber sensing, whereby the fiber itself is the sensor, can be considered to be an optical equivalent to convergence tape. In general, fiber-optic sensors can have several advantages over traditional SHM methods, which make them ideal for monitoring intact rock in a subsurface setting. They are relatively inexpensive, lightweight, versatile, and long-lasting [15]. Measurements that are based on frequency-shifts are stable over time. Because glass is an inert substance, fiber-optic sensors are resistant to most chemicals and they are immune to electromagnetic interference, and they show small to no creep deformation. Many types of sensors can be incorporated on a single data-acquisition cable, and the promise is that the methods will become even better, cheaper, and faster in the future. The array of available sizes for fiber-optic sensors also makes them ideal for underground monitoring applications. Sensors range from bare fiber-optic filament (125-500 m in diameter) to gage lengths of 1 cm to 1 m, and distributed cables measure strain or temperature along their lengths continuously for over tens of kilometers. Thus, possibilities exist to instrument a single rock bolt with several gages, a pillar face with tens of centimeter-long gages, and even entire lengths of drifts and shafts in an underground mine. Additionally, once installed, fiber-optic sensors can be monitored remotely, which reduces the number of personnel underground, making any mining operation safer. 2. DEEP UNDERGROUND SCIENCE AND ENGINEERING LABORATORY (DUSEL) DUSEL is being constructed in the former Homestake gold mine in the northern Black Hills of South Dakota (Fig. 1a). The geology of the area contains complex, folded and altered Precambrian metamorphic rock [16]. At ~2438 m (8,000 ft.), Homestake was the deepest mine in North America. Below 2255 m microseismicity induced by mining activities changed stress conditions and created rock burst and collapse hazards [17]. While DUSEL is proposed principally as a physics laboratory, the project scope includes facilities for geoscience and engineering research. The most significant construction for the physics laboratory is the excavation at 1470-m depth of several water Cherenkov detectors, each of which is a cylindrical room 50-m in diameter by 50-m high. In many ways the former mine and new constructions are themselves a geotechnical laboratory. The opportunity presented by DUSEL for understanding rock-mass behavior is access to over 500 km of drifts plus several winzes, and hundreds of boreholes lying within a mine volume of several cubic kilometers of rock of different lithologies. Geotechnical monitoring can be conducted for several decades while both natural and anthropogenic loads are imposed.

  • 3

    3. EXPERIMENTAL INVESTIGATIONS 3.1 Fiber Bragg Grating (FBG) Monitoring at 4100L A multi-faceted underground strain-monitoring network bridges the gap between small-scale and large-scale deformation monitoring techniques. As a part of early science activities at DUSEL, we installed six Micron Optics Inc. OS3600 FBG strain and temperature gages in the 4100 level of the Homestake Mine in July 2009 (Fig. 1b and c) [18]. The six FBG sensors were installed in two sets of three approximately perpendicular gages (triplets) mounted on two perpendicular walls of a 3-m wide, 2-m deep, and 2-m high alcove (Fig. 1d). Each FGB gage is 1 m-long and measures one-dimensional shortening and elongation between the ends of the sensor. Because FBG sensors have not been extensively used for the monitoring of intact rock, there are not established installation methods to ensure that the gages measure rock mass movement and not surface effects. We installed the FBG sensors in two different ways - surface mounted and embedded. The two ends of each surface mounted sensor are welded to the heads of DYWIDAG rock bolts drilled approximately 2-m deep into the rock mass and secured in place with resin epoxy. The embedded sensors were grouted into the rock mass in 2-m deep holes. Strain and temperature data from the six FBG sensors were collected continuously between October 1, 2009 and August 13, 2010 (Fig. 2). We must separate the thermal effects out of the raw strain data before we can examine mechanical strain in the rock mass. The uncorrected strain values of the two vertically oriented sensors were similar for the entire record and they directly correlated to rapid changes in air temperature in the drift of the mine (Fig. 2a). The horizontal sensors showed similar rapid and short-lived spikes in uncorrected strains that correlated with changes in air temperature at the rock surface (Fig. 2b). The embedded sensors, however, did not show the same correlation between uncorrected strain and rapid changes in air temperature. Instead, during sustained temperature anomalies the response of the embedded strain sensor lagged behind the surface sensor and had a longer decay time (e.g., Fig. 2b from Nov. 6 to Dec. 20). We attribute the time lag to thermal diffusion. Matsui et al. [19] circumvented the issue of temperature effects on surface-mounted FBG tube gages by very carefully thermally insulating sensors and produced 0.1 microstrain sensitivity. Because the FBG sensors currently installed on the 4100 (1250 m) level of DUSEL are too far from active deformation in the mine to record significant mechanical strain [18], we plan to perform an active experiment, which will include using hydraulic jacks to load the walls and ceiling of the alcove near the FBG sensors. The data from the active experiment will be combined with 3-D finite element modeling and the results of laboratory measurement

    Fig. 1. a) Map of the western United States with gray box showing the location of the Black Hills in western South Dakota. b) Schematic cross section of DUSEL showing major science levels. c) Map view of experiment alcove on the 4100 (1250 m) level. Array A and Array B denote the two FBG sensor arrays. d) FBG triplet configuration. The two surface mounted gages are oriented vertically and horizontally. They sit in metal u-shaped brackets welded to the heads of two rock bolts. The embedded sensor is grouted into a hole drilled 10-15 downdip. The embedded sensor has 5-cm diameter metal disks on each end.

  • 4

    of rock mechanical properties to examine the variation of mechanical properties from the centimeter to the meter scale. Over longer periods of time (years), deformation due to mine-wide dewatering may produce measurable mechanical strain. 3.2 Raman Distributed Temperature Sensing (DTS) on the 4100 Level Wilson et al. [20] using DTS found that long-baseline temperature monitoring has the potential to yield information about air movement in Carlsbad (NM) Caverns. Recently, Aminossadati et al. [21] installed approximately one-kilometer of DTS cable throughout the University of Queensland Experimental Mine. They quantitatively demonstrated its potential for monitoring ventilation. They also validated that DTS measurements are accurate to better than 1 C with a one meter resolution distance. At DUSEL we unwound approximately 730 m of DTS cable from a spool containing a total length of 2860 m of fiber at the 4100 (1250m) depth level. It was run approximately 300m in the direction of the Ross Shaft along the ceiling in the drift from the alcove in which the FBG sensor arrays were located and then back to the instrument room along the floor (Fig. 1c). The remaining 130 unspooled meters were coiled and placed in calibration baths near the instrument room (Fig 3a). Following installation, initial temperature data were collected (Fig. 3b). Cooler temperatures were seen in the floor where much of the cable lay in a water-filled ditch. Over a two-month period, temperature changes of several degrees occurred with changes in ventilation.

    Fig. 2. Plots showing uncorrected strain data for correlative sensors and surface temperature results from October 1, 2009 through August 13, 2010. Gaps in data are due to power outages when no data was collected. a) Uncorrected strain for the two vertical sensors together with surface temperature. b) Uncorrected strain for the Array A horizontal sensor and the Array B embedded sensor together with surface temperature.

    Fig. 3. a) Layout of the DST sensor array on the 4100 (1250 m) level of DUSEL. b) Temperature data collected immediately following DST sensor array installation.

    Stra

    in (

    m)

    Stra

    in (

    m)

    Temperature (C

    ) Tem

    perature (C)

    a.

    b.

  • 53.3 Tiltmeter Array at Aurora Mine Water-filled tiltmeters installed underground can provide deformation data to complement the fiber-optic data. Budker style tiltmeters were developed by physicists to understand ground motion at particle accelerator sites [22]. The tiltmeter consists of two chambers connected by tubing and separated by tens of meters or more. Precision capacitance or ultrasonic gauges can measure water-level changes with resolutions from 0.2 to 6 m. The tilt resolution of a device with two, micron-scale water-level sensors spaced 10m apart is 10-7 rad, which is finer resolution than the fiber-optic devices. Separating the water-level sensors by 100m sharpens the resolution to 10-8 rad. Fig. 4 shows typical sinusoidal signatures of the M2 solid earth tide, which has a period of about 12 hours 25 minutes. The data were taken by Dr. James Volk of Fermilab at a depth of 100 meters in the Aurora (IL) Mine between May 11 and 20, 2010. The tiltmeter signals captured not only the Earth tides but also a possible indicator of surface loading by the nearby Fox River, which is 0.2 km away from the array. This hypothesis will be tested by mechanical modeling. 4. DISCUSSION At DUSEL we are pursuing three development areas in furthering applications of fiber-optic sensors for underground monitoring. The first is validating sensor installation methods for rock strain. The second is the adaptation of existing strain-monitoring instrumentation to fiber-optic technology through replacement of a conventional sensor such as an electrical resistance strain gage with a FBG gage. And the third is the development of techniques to acquire and monitor rock moduli and fluid-flow properties as they can be indicators of damage. 4.1 Anchoring and Clamping of Fiber Sensors As attractive as fiber-optic technology appears to be for underground monitoring, the data only have value if the sensors are measuring rock-mass behavior. For both surface-mounted and embedded sensors, the coupling of rock bolts to the rock mass needs to be evaluated as it is essential to assure that true strain measurements are being recorded. Rock bolts exist throughout the mine for ground control and could be anchor points for Distributed Strain and Temperature (DST) monitoring. Guided ultrasonic waves can be used to evaluate their integrity [23]. Our goal is to develop a data acquisition procedure and interpretation algorithm to determine the quality of the bond between the rock bolt and the grout or epoxy and to estimate the stiffness of the rock mass around the bolt. Our concept for DST is that the fiber acts essentially as continuous convergence tape pinned periodically to rock bolt anchors. Uniform strain will be recorded from anchor to anchor. The fiber sheathing must not slip relative to the cladding or core and must be firmly clamped to the anchor as well. Preliminary tests using a special cable and clamp

    Differen

    cebetween

    water

    levels

    3and

    4[

    m]

    Differen

    cebetweenwater

    levels

    0and

    5[

    m]

    Stagelevel[ft]Stagelevel[ft]

    Fig. 4 May 11-20, 2100 Aurora mine tiltmeter response (black line) and the stage level at Fox River (smooth black line). The gray-dashed line indicates the low frequency trend.

  • 6manufactured by Brugg AG in Switzerland give confidence that the sheath does not slip between over distances of a few meters. 4.2 Adaptation of Existing Rock Strain Strips Deformation within a rock mass has traditionally been measured with extensometers or instrumented rock or cable bolts [24; 25]. FBG gages could be welded or epoxied to rock or cable bolts before installation with the advantage of long-term stability in obtaining strain versus depth from the opening. At the present time, we are planning to weld FBG patch gages (e.g., Micron Optics 3110) to Rock Strain Strips [26]. These strain strips are compliant (rather than stiff) and serrations ensure they are firmly engaged when grouted into a borehole. We will compare the Micron Optics OS3600 tube gage with strain strips using fiber-optic strain gages. 4.3 Measuring and Monitoring Rock Properties A high resolution, moveable borehole extensometer (Tilt-X) is being developed to evaluate permeability, fracture normal stiffness, and elastic modulus for application at DUSEL and elsewhere [27; 28]. The extensometer lies between packers in a borehole, injecting or removing water using techniques typical of hydraulic well tests, and the transient signals of pressure and displacement are analyzed. [29; 30; 31; 32]. To constrain the interpretation of the data for fractures of arbitrary orientation, both a tiltmeter and an extensometer are incorporated to measure multiple components of displacement. The current generation of Tilt-X is approximately 1.2 m long and has been tested in situ with resolution of 5x10-9 m displacement and 3x10-8 rad tilt. 5. CONCLUSIONS Fiber-optic monitoring of kilometers of drift within the 8000-ft deep Homestake Mine in Lead, SD presents a unique opportunity to address questions regarding the mechanical and hydrologic response of rock masses. Induced loading (dewatering, drift and cavity construction, meter-scale loading) and natural loading (self weight, earth tides, seismicity) will be monitored at spatial scales ranging from centimeters to hundreds of meters and temporal scales ranging from milliseconds to decades. Large-scale deployment of fiber-optic sensors appears to be an ideal technology for multi-spatial and multi-temporal measurements of rock-mass response to loading. 6. ACKNOWLEDGMENTS The authors wish to acknowledge Alan Turner from Micron Optics Inc., Jim Volk from Fermilab, Larry Stetler from South Dakota School of Mines, Steve Gabriel from Spearfish Schools, Neal Lord from U. Wisconsin, and several graduate students working on the project including: Matt Kogle (UW), Andy Leaf (UW), Noni (MT Tech), and Josh Roberts (UW). This work is supported by National Science Foundation Grants to Wang and Fratta (CMMI- 0900351), MacLaughlin (CMMI-0821788 and 0900663), and Murdoch (CMMI-0900163 and EAR-0609960) and by a Japan Science and Technology Agency grant to Tokunaga. 7. REFERENCES

    1. Hudson, J.A. and Harrison, J.P. 1997. Engineering Rock Mechanics: An Introduction to the Principles. Oxford: Pergamon. 444 p.

    2. Bhalla, S., Yang, Y.W., Zhao, J., and Soh, C.K. 2005. Structural health monitoring of underground facilities Technological issues and challenges, Tunneling and Underground Space Technology 20: 487500.

    3. Gochioco, L.M. 2000. High-resolution 3-D seismic survey over a coal mine reserve area in the U.S.A case study. Geophysics. 65(3), 712718.

    4. Warneke, B., Last, M., Liebowitz, B., and Pister, K. 2001. Smart Dust: Communicating with a Cubic-Millimeter. Computer, 34, 44-51.

    5. Haneberg, W.C., Creighton, A.L., Medley, E.W., and Jonas, D.A. 2005. Use of LiDAR to assess slope hazards at Lihir gold mine, Papua New Guinea, in Landslide Risk Management. Conference on Landslide Risk Assessment. Vancouver, Canada, edited by O. Hungr et al., Taylor and Francis, Philadelphia, Pa.

  • 76. Barbosa, G.A., Lanceros-Mendez, S., Campos, J., Pamplona, J., Zamith, M., Almeida, A.M., Cabral, J.M., and

    Rocha, J.G. 2009. Piezoelectric sensor for acoustic wave detection in anisotropic systems. Industrial Electronics, 2009. IECON '09. 35th Annual Conference of IEEE. Nov. 3-5, 1905-1910.

    7. Sloan, S.D., Tsofliasa, G.P., Steeples, D.W., and Vincent, P.D. 2007. High-resolution ultra-shallow subsurface imaging by integrating near-surface seismic reflection and ground-penetrating radar data in the depth domain. Journal of Applied Geophysics. 62(3), 281-286.

    8. Hasse, K. 2007. Strain sensors based on Bragg gratings. In: IMEKO 20th TC3, 3rd TC16 and 1st TC22 International Conference Cultivating metrological knowledge, 27 30 November, 2007.

    9. Glisic, B. and Inaudi, D. 2007. Fibre Optic Methods for Structural Health Monitoring. 1st ed. Sussex: Chichester.

    10. Karashima, T. 1990. Distributed temperature sensing using stimulated Brillouin scattering in optical silica fibers. Optics Letters. 15: 1038.

    11. Kincade, K. 2006. Optoelectric applications: Fiberoptic sensing Fiber sensors lay groundwork for structural health monitoring. Laser Focus World. 42.

    12. Duncliffe, J. 1988. Geotechnical Instrumentation for Monitoring Field Performance. New York: Wiley.

    13. Inaudi, D., Conte, J.P., Perregaux, N., and Vurpillot, S. 1998. Statistical analysis of under-sampled dynamic displacement measurements. SPIE Symposium on Smart Structures and Materials. 3325: 105-110.

    14. Klar, A. and Linker, R. 2010. Feasibility study of automated detection of tunnel excavation by Brillouin optical time domain reflectometry. Tunnelling and Underground Space Technology 25 (2010) 575586.

    15. Zhang, W., Gao, J, Shi, B., Cui, H., and Zhu, H. 2006. Health monitoring of rehabilitated concrete bridges using distributed optical fiber sensing. Computer Aided Civil and Infrastructure Engineering. 21: 411-424.

    16. Friedel, M.J., Scott, D.F., Jackson, M.J., Williams, T.J., and Killen, S.M. 1996. 3-D tomographic imaging of anomalous stress conditions in a deep US gold mine. Journal of Applied Geophysics. 36: 1-17.

    17. Friedel, M.J., Scott, D.F., and Williams, T.J. 1997. Temporal imaging of mine-induced stress change using seismic tomography. Engineering Geology. 46: 131-141.

    18. Gage, J.R., Noni, N., Turner, A., MacLaughlin, M., and Wang, H.F. 2010. Fiber optic strain and temperature monitoring in crystalline rock at the Sanford Underground Science and Engineering Laboratory (SUSEL), Lead, South Dakota, 44th U. S. Rock Mechanics Symposium and 5th U.S- Canada Rock Mechanics Symposium, Salt Lake City, Utah, June 27-30, 2010, 8 pp.

    19. Matsui, H., Kashiwai, Y., Sano, O., Tokunaga, T., He, Z., Mogi, K. and Wang, H.F. 2009. Evaluation of the applicability of optical fiber strain sensors for monitoring rock deformation caused by ocean tide A case study at the Aburatsubo site, Japan. EOS Trans. AGU. 90: Fall Meet. Suppl., Abstract H23E-1010.

    20. Wilson, J.L., Tyler, S.W., Jorgensen, A.M., Dwivedi, R., Boston, P., Burger, P. 2008. Sensing turbulent flow and heat transport in a cave conduit. Eos Trans. AGU, 89(53), Fall Meet. Supplement. Abstract #H32A-06

    21. Aminossadati, S.M., Nayeemuddin, M.M., and Shemshad, J. 2010. Distributed temperature measurements using optical fibre technology in an underground mine environment, Tunnelling and Underground Space Technology 25 (2010) 220229.

    22. Volk, J.T., LeBrun, P., Shiltsev, V. , & Singatulin, S. 2007. Ground motion data for International Collider models. Proc. Interational Linear Collider Workshop, May 30 June 3, 2007, Hamburg, Germany.

    23. Beard, M.D. and Lowe, M.J.S. 2003. Non-Destructive Testing of Rock Bolts Using Guided Ultrasonic Waves. International Journal of Rock Mechanics and Mining Sciences, 40, 527-536.

    24. http://www.geokon.com/products/datasheets/4910.pdf

    25. Hyett, A.J., Bawden, W.F., Lausch, P., Moosavi, M., Ruest, M., and Pahkala, M. 1997. The S.M.A.R.T. cable bolt: an instrument for the determination of tension in 7-wire strand cable bolts. In Proceedings of International

  • 8

    Symposium on Rock Support Applied Solutions for Underground Structures. Lillehammer, Norway, June. Pp 25 40.

    26. Signer, S. and Sunderman, C. 2003. New Tools for rook Support Evaluation and Design. 22nd International Conference on Ground Control in Mining. Aug. 5-7, 2003; Morgantown WV), Dept. of Mining Engineering, West Virginia University, 114-118.

    27. Murdoch, LC., Schweisinger, T., and Huey Jr., C.O. 2005. Device to measure axial displacement in a borehole, US Patent Application 20050120576, filed June 9, 2005.

    28. Schweisinger, T., Murdoch, L.C., and Huey, C.O. 2007. Design of a removable borehole extensometer. Journal of Geotechnical Measurement, 30: 202-211.

    29. Cappa, F., Guglielmi, Y., Fenart, P., Merrien-Soukatchoff, V., and Thoraval, A. (2005). Hydromechanical interactions in a fractured carbonate reservoir inferred from hydraulic and mechanical measurements. International Journal of Rock Mechanics and Mining Sciences, 42: 287-306.

    30. Svenson, E., Schweisinger, T., and Murdoch, L.C., 2007.Analysis of the hydromechanical response of a flat-lying fracture to a slug test. Journal of Hydrology, 347: 35 47.

    31. Svenson, E, Schweisinger, T., and Murdoch, L.C. 2008. Field evaluation of the hydromechanical behavior of flat-lying fractures during slug tests. Journal of Hydrology, 359: 30-45.

    32. Schweisinger, T., Svenson, E.J., and Murdoch, L.C. 2009. Introduction to hydromechanical well tests in fractured rock aquifers. Ground Water, 47: 69-79.

    BIO-DATA Herb Wang graduated in Physics from the University of Wisconsin-Madison in 1966. He obtained an A.M. in Physics from Harvard University and a Ph.D. in Geophysics at the Massachusetts Institute of Technology. Since 1972 he has been Assistant, Associate, and Professor of Geophysics at the University of Wisconsin-Madison, where he specializes in poroelastic behavior of rock masses. JoAnn Gage graduated with an A.B. in geology from Bryn Mawr College in 2005. She obtained a M.S. in structural geology from the University of Wisconsin-Madison in 2007. She is currently working on her PhD at UW-Madison studying the effect of scale on the mechanical properties of rock. Dante Fratta received a Civil Engineering diploma from Universidad Nacional de Cordoba, Argentina in 1993, a M.A.Sc. in Civil Engineering from University in Waterloo, Canada in 1995, and a Ph.D. in Civil and Environmental Engineering from Georgia Institute of Technology, USA in 1999. He was an assistant professor at Louisiana State University before joining the University of Wisconsin-Madison in 2004. He is now an associate professor in Geological Engineering. His research interests include near surface geophysics and wave propagation in geomaterials. Mary MacLaughlin received her bachelor's degree in Geo-Engineering from the University of Minnesota in 1988. She obtained M.S. and PhD degrees in Civil (Geotechnical) Engineering from the University of California at Berkeley in 1989 and 1997. She joined the faculty in the Geological Engineering department at Montana Tech in fall, 1996, where she specializes in engineering geology, slope stability, rock mechanics and numerical modeling. She is now a full professor, holding the Goldcorp Professorship and serving as head of the department. Larry Murdoch received a B.S. in Geology from Penn State University in 1980, M.S. in Geology and Environmental Science, and Ph.D. in Geology from University in Cincinnati in 1991. He was associate research professor at the Univesrity of Cincinnati before joining Clemson University in 2001. He is now Professor of Environmental Engineering and Earth Science at Clemson University, where he specializes in hydromechanics. Tomochika Tokunaga received his B.S. in Geology in 1989, M.Sc. in Structural Geology in 1992, and a Ph.D. in 1996 in Applied Earth Sciences all from the University of Tokyo. After several years as a Research Associate, he was Associate Professor of Geosystem Engineering from 1999-2005 and Associate Professor of Environment Systems at the University of Tokyo since 2005, where he specializes in hydrogeology.

    DTS_Primer.pdfISRM_Paper_Aug14_final2