sonic investigations in and around the borehole · 14 oilfield review sonic investigations in and...
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14 Oilfield Review
Sonic Investigations In and Around the Borehole
J.L. Arroyo FrancoM.A. Mercado OrtizPemex Exploración y ProducciónReynosa, Mexico
Gopa S. DeChevron Energy Technology CompanySan Ramon, California, USA
Lasse RenlieStatoil ASAStjørdal, Norway
Stephen WilliamsNorsk Hydro ASABergen, Norway
For help in preparation of this article and in acknowledge-ment of their contributions to the development of the SonicScanner acoustic scanning platform and applications,thanks to Sandip Bose, Jahir Pabon and Ram Shenoy,Cambridge, Massachusetts, USA; Tom Bratton and Adam Donald, Denver, Colorado, USA; Chung Chang, TarekHabashy, Jakob Haldorsen, Chaur-Jian Hsu, Toru Ikegami,David Johnson, Tom Plona, Bikash Sinha and Henri-PierreValero, Ridgefield, Connecticut, USA; Steve Chang, Takeshi Endo, Hiroshi Hori, Hiroshi Inoue, Masaei Ito,Toshihiro Kinoshita, Koichi Naito, Motohiro Nakanouchi,Akira Otsuka, Vivian Pistre, Atsushi Saito, Anthony Smits, Hitoshi Sugiyama, Hitoshi Tashiro and Hiroaki Yamamoto,Sagamihara, Kanagawa, Japan; Rafael Guerra and Jean-Francois Mengual, Rio de Janeiro, Brazil; Dale Julander,Chevron, Bakersfield, California, USA; Larry O’Mahoney,Chevron, New Orleans, Louisiana, USA; Marcelo OsvaldoGennari, Reynosa, Mexico; Pablo Saldungaray, Veracruz,Mexico; Keith Schilling, Bangkok, Thailand; Kwasi Tagborand John Walsh, Houston, Texas; Badarinadh Vissapragada,Stavanger, Norway; Canyun Wang, Beijing, China; Erik Wielemaker, The Hague, The Netherlands; and Smaine Zeroug, Paris, France.Array-Sonic, CBT (Cement Bond Tool), DSI (Dipole ShearSonic Imager), ECS (Elemental Capture Spectroscopy), FMI (Fullbore Formation MicroImager), HRLA (High-Resolution Laterolog Array), LSS (Long-Spaced Sonic Tool),MDT (Modular Formation Dynamics Tester), OBMI (Oil-Base MicroImager), Platform Express, Sonic Scanner, TLC(Tough Logging Conditions) and Variable Density are marks of Schlumberger.
Sonic measurements have come a long way since their introduction 50 years ago.
The latest advancement in sonic technology delivers the highest quality data seen
to date, allowing acoustic measurements to characterize mechanical and fluid
properties around the borehole and tens of feet into the formation.
Finding and producing hydrocarbons efficientlyand effectively require understanding the rocksand fluids of a reservoir and of surroundingformations. Three basic oilfield measurements—electromagnetic, nuclear and acoustic—havebeen devised to achieve this end. With advancesin tool design and in data acquisition, processingand interpretation, each measurement type hasevolved to produce more and different information.None, perhaps, has evolved more than theacoustic, or sonic, measurement.
In their early days, sonic measurements wererelatively simple. They began as a way to matchseismic signals to rock layers.1 Today, sonicmeasurements reveal a multitude of reservoirand wellbore properties. They can be used toinfer primary and secondary porosity, permea-bility, lithology, mineralogy, pore pressure,invasion, anisotropy, fluid type, stress magnitudeand direction, the presence and alignment offractures and the quality of casing-cement bonds.
Improvements in sonic measurements areenhancing our ability to determine some of theseproperties. Accuracy is improving in the basicmeasurements, which consist of estimates ofcompressional- (P-) and shear- (S-) wave slow-nesses.2 Variations in slowness are also becomingmore fully characterized, leading to an improvedunderstanding of how formation propertieschange over distance and with direction.
Formation properties often vary directionally,so to be completely described, they must bemeasured in three dimensions. The borehole hasa natural, cylindrical 3D coordinate system:axial, or along the borehole; radial, or perpen-dicular to the borehole axis; and azimuthal, oraround the borehole. Variations around and awayfrom the borehole depend on many factors,including the angle the borehole makes withsedimentary layering. Axial variations are typicalof vertical boreholes in horizontal layers, and canindicate changes in lithology, fluid content,porosity and permeability. Radial rock- and fluid-property variations arise because of nonuniformstress distributions and mechanical or chemicalnear-wellbore alteration caused by the drillingprocess. Azimuthal variations can indicate aniso-tropy, which is caused by layering of mineralgrains, aligned fractures or differential stresses.
Improved characterization of compressionaland shear slownesses in terms of their radial,azimuthal and axial variations is now possiblewith a new sonic tool, the Sonic Scanner acousticscanning platform. High-quality waveforms andadvanced processing techniques lead to moreaccurate slowness estimates, even in unconsoli-dated sediments and large boreholes, and also toreliable through-casing slowness measurements.These improvements result in better characteri-zation of subsurface rock and fluid properties,meaning more stable wellbores, longer-lastingcompletions and enhanced production.
1. Léonardon EG: “Logging, Sampling, and Testing,” inCarter DV (ed): History of Petroleum Engineering. NewYork City: American Petroleum Institute (1961): 493–578.
2. Slowness, also called interval transit time, is thereciprocal of speed, or velocity. The common unit ofslowness is microseconds per foot (µs/ft).
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This article describes the advances in tooldesign and resulting data quality of the SonicScanner tool. Examples from the USA, Norwayand Mexico highlight applications that includedetermining shear velocities in ultraslowformations, radial profiling for optimizingdrilling, completion and sampling operations,fluid-mobility logging, fracture characterizationand imaging away from the borehole.
Engineering SuccessMore so than electromagnetic and nuclearlogging tools, a sonic tool’s very presence in aborehole can introduce a bias to themeasurements it acquires. The steel tool housingis extremely efficient at propagating sonic waves.Sonic-logging tool designers have minimized thisunwanted effect by isolating the transmittersfrom the receivers with insulating materials or by milling slots and grooves into the steel sonde (see “History of Wireline Sonic Logging,”page 32). These efforts were aimed at delayingundesirable signals and making the tool astransparent to the measurement as possible.
The Sonic Scanner tool is completelydifferent from other tools. Its design, materialcomposition and components were engineered sothat the effects of its presence could be modeled.These effects can then be incorporated intopredicting the complete tool-borehole-formationresponse. These theoretical predictions havebeen verified by experimental results in a testwell having known formation properties. As aresult, tool effects can be predicted accurately inisotropic homogeneous formations, and real-timecorrections can be made at the wellsite.
The transmitter-receiver (TR) geometry andfunctionality of the new tool were carefullydesigned to provide P-, S-, Stoneley- and flexural-wave slowness measurements at varying radialdepths of investigation (for a review see “BoreholeAcoustic Waves,” page 34). These modes areacquired at a logging speed of 1,800 ft/h[549 m/h]. For the typical scenario with formationcompressional and shear speeds increasing withdistance from the borehole, this is achieved byincreasing TR spacing to probe deeper into theformation. The Sonic Scanner tool combines thislong-spaced approach with the close TR spacing ofa borehole-compensated arrangement, and alsoadds azimuthally distributed receivers. The toolfeatures 13 axial stations in a 6-ft [1.8-m] receiverarray. Each station has eight receivers placedevery 45° around the tool, for a total of 104 sensors
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on the tool.3 A monopole transmitter sits on each end of the receiver array, and anothermonopole transmitter and two orthogonallyoriented dipole transmitters are located fartherdown the tool (below).
Each of the three Sonic Scanner monopoletransmitters produces a stronger pressure pulsethan transmitters in previous sonic tools. With asharp “click,” they generate clear P- and S-waves,the low-frequency Stoneley mode and the high-frequency energy needed for cement evaluation.
Each of the two dipole transmitters is ashaking device consisting of an electromagneticmotor mounted in a cylinder suspended in the
tool. This mechanism generates a high-pressuredipole signal without inducing vibration in thetool housing. The shaking source can be driven intwo modes: the traditional dipole source in pulsemode produces a deep “click”; the new sourcealso produces a “chirp” with a frequency sweep(bottom left). The chirp mode sustains eachfrequency for a longer duration than narrow-band dipole sources, providing more dipoleenergy to the formation.
As in earlier sonic tools, such as the DSIDipole Shear Sonic Imager, the two dipolesources are oriented orthogonally. One vibratesin line with the tool reference axis, and the otherat 90° to the axis. These devices generate strongflexural modes—waves that gently shake theentire borehole the way a person might shake atree from its trunk. Flexural modes propagate upand down the borehole and also into theformation to different depths that depend ontheir frequencies. The frequency content—300 Hz to 8 kHz—of the new chirp dipole sourceexcites flexural modes in all borehole andformation conditions, including slow formations,and ensures maximum signal-to-noise ratio.
The new sonic tool delivers P, S, Stoneley andflexural-mode waveforms with unprecedentedquality. An example from a typical fast formationoffshore Norway shows waveforms acquired fromthe monopole and dipole transmitters (nextpage, top). At high frequencies, the monopolesource generates clear P-, S- and Stoneley waves,while at low frequencies, it generatespredominantly Stoneley waves. The X- and Y-dipole transmitters generate flexural waves. Thedispersion curves show slowness versus frequencyfor the nondispersive shear, slightly dispersiveStoneley and highly dispersive flexural arrivals.The low-frequency limit of the flexural-wavedispersion curve is in line with the slowness ofthe shear head wave and the true shear slownessof the formation. The two flexural curves match,indicating absence of azimuthal anisotropy.
Waveforms from the same sources in a slowformation in the USA display evident differencescompared with fast-formation results (next page,bottom). The high-frequency monopole source
16 Oilfield Review
3. Pistre V, Kinoshita T, Endo T, Schilling K, Pabon J,Sinha B, Plona T, Ikegami T and Johnson D: “A ModularWireline Sonic Tool for Measurements of 3D (Azimuthal,Radial, and Axial) Formation Acoustic Properties,”Transactions of the SPWLA 46th Annual LoggingSymposium, New Orleans, June 26–29, 2005, paper P.Pistre V, Plona T, Sinha B, Kinoshita T, Tashiro H,Ikegami T, Pabon J, Zeroug S, Shenoy R, Habashy T,Sugiyama H, Saito A, Chang C, Johnson D, Valero H-P,Hsu CJ, Bose S, Hori H, Wang C, Endo T, Yamamoto Hand Schilling K: “A New Modular Sonic Tool ProvidesComplete Acoustic Formation Characterization,”Expanded Abstracts, 75th SEG Annual Meeting, Houston (November 6–11, 2005): 368–371.
> The Sonic Scanner tool, with 13 axial stations in a6-ft receiver array. Each station has eight azimuthallydistributed receivers, giving the tool 104 sensors.Three monopole transmitters allow acquisition oflong-spaced and short-spaced data for boreholecompensation at varying depths of investigation.Two orthogonal dipole transmitters generateflexural waves for characterization of shear-waveslowness in slow and anisotropic formations.
10 ft
Isolator Far transmitter section
Uppermonopole
Electronics Receiver section
X and Ydipole
Lowermonopole
Farmonopole
R13 R1
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, Pa
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nitu
de, d
B
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The frequency sweep of the Sonic Scannerdipole transmitter. The strong chirp creates awide-band response (inset) that is flat fromabout 300 Hz to 8 kHz.
>
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>Waveforms (left) from a fast formation offshore Norway. Monopole transmitters (top) at high frequencies (left) generate clearP-, S- and Stoneley waves, and low frequencies (right) generate mostly Stoneley waves. Flexural waveforms generated by thedipole transmitters (bottom) are recorded on the X (left) and Y (right) receivers. Dispersion analysis (right) shows slightly dispersiveStoneley data, highly dispersive flexural data and nondispersive shear data. The compressional wave is excited only at frequencieshigher than 8 kHz in this formation, and is not shown on the dispersion curve. [Modified from Pistre et al, reference 3 (SEG).]
Slow
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>Waveforms (left) from a slow formation in the USA. The high-frequency monopole source (top left) generates no shear waveand smaller Stoneley waves than in the fast-formation case. At low frequency, the monopole source (top right) generatespredominantly Stoneley waves. The X- and Y-dipole transmitters generate low-frequency flexural waves compared with the fastformation. Anisotropy in this formation causes flexural-wave splitting, creating a fast and slow flexural wave (bottom left andright, respectively). The low-frequency dispersion data (right) include the Stoneley mode and two flexural modes. Higherfrequency dispersion analysis of the P-wave data reveals dispersion—labeled leaky compressional—at higher frequencies.[Modified from Pistre et al, reference 3 (SEG).]
0 10Time, ms
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generates no direct shear wave but does generateleaky-compressional waves. At low frequencies,the monopole source again generates Stoneleywaves, but, in addition, there is a strong leaky-compressional wave generated. The X- and Y-dipole transmitters generate flexural waves withthe characteristic low-frequency response of aslow formation. The dispersion data include theslightly dispersive Stoneley mode and the leaky-compressional wave, but no shear head wave, asexpected in a slow formation. In the absence of ashear head wave, the shear slowness is estimatedfrom the low-frequency limit of the flexural mode.
The flexural mode is not as dispersive as in afast formation, but more dispersive than thatexpected from a homogeneous, isotropic forma-tion. At low frequency, the two flexural-wavedispersion curves level off at different slow-nesses, indicating azimuthal anisotropy. Theflexural waveforms have been mathematicallyrotated into fast and slow shear-wave directions.4
Analysis of flexural-wave dispersion curvesfrom the Sonic Scanner tool classifies formationsaccording to anisotropy type by comparingobserved dispersion curves to those modeledassuming a homogeneous isotropic formation(below). In a homogeneous isotropic formation,shear waves do not split into fast and slowcomponents, so the two observed flexural-wavedispersion curves have identical slowness-versus-frequency signatures, and overlie the modeledcurve. In cases of intrinsic anisotropy, such asshales or fractured formations, the fast and slowshear-wave dispersion curves are separateeverywhere and tend to the true slowness at zerofrequency.5 In formations that have undergonedrilling-induced damage and are near failure butare otherwise homogeneous and isotropic, thetwo dispersion curves are identical but showmuch greater slowness at high frequencies thanthe modeled dispersion for a homogeneousisotropic formation. In formations with stress-induced anisotropy, the fast and slow shear-wavedispersion curves cross. This characteristicfeature is caused by near-wellbore stress
concentrations.6 These simplified relationshipsbetween dispersion curves are valid when onlyone physical mechanism controls wave behavior.When multiple mechanisms are involved, such asif both stress-induced and intrinsic anisotropyare present, the curves can be different.
In addition to acquiring openhole measure-ments in isotropic, anisotropic, homogeneous andinhomogeneous formations, the Sonic Scannertool provides high-quality results behind casing.The improved tool design records waveformsthrough casing with high signal-to-noise ratio.Powerful transmitters and large bandwidth allowacquisition of formation slowness data throughcasing and cement of varying thickness.
The ability to measure formation propertiesthrough casing allows companies to monitor themechanical effects of production on the produc-ing formation. Many formations undergo compac-tion, weakening or other changes with time as aresult of pressure depletion or water injection.
In an example from a Statoil well in the NorthSea, Sonic Scanner data were acquired in both8.5-in. open hole and behind 8-in. OD casingbefore any production (next page). The openholelogs in the zone of interest indicate a slower,softer formation between X,296 and X,305 m. The caliper log flags a washout in this interval.When compared with the openhole logs, thecased-hole compressional and shear slownessesare markedly similar, even through the washed-out zone. The dispersion curves in the two casesare also similar.
In the Middle East, the Sonic Scanner toolhas been used multiple times to acquire slownessthrough 133⁄8-in. casing in hole sizes larger than20 inches. In each case, despite poor cement,good shear-wave slowness data were acquiredover the entire interval, and adequatecompressional slowness was recorded over atleast half the interval.
The Sonic Scanner tool not only obtainsslowness results behind casing, but can alsosimultaneously evaluate the quality of thecement bond and the top of cement. Signalsrecorded by receivers 3 and 5 ft [0.9 and 1.5 m]from the two near monopole transmitters areprocessed to produce a discriminated attenua-tion measurement that is free of tool-normalization fluid effects and pressure andtemperature drifts. The results are comparableto those of the CBT Cement Bond Tool, but arealso corrected for casing and cement properties.Evaluation of well integrity and formationproperties in the same tool run can avoidseparate logging runs and reduce rig-time andmobilization costs.
18 Oilfield Review
> Flexural-wave dispersion curves for classifying formation anisotropy andinhomogeneity. In a homogeneous isotropic medium (top left), observeddispersion curves for flexural waves recorded on orthogonal dipole receivers(red and blue curves) match modeled flexural-wave dispersion (blackcircles). In an inhomogeneous isotropic formation (top right), both observeddispersion curves show greater slowness with increasing frequency than thehomogeneous isotropic model. Greater slowness with increasing frequencyindicates that the near-borehole region has become slower, a sign ofdamage all around the borehole. In a homogeneous anisotropic medium(bottom left), such as one with intrinsic anisotropy, the fast flexural-wavedispersion curve (red) matches the homogeneous isotropic model (to a firstapproximation), while the slow flexural-wave dispersion curve (blue) has thesame shape but is translated to higher slowness. In an inhomogeneousanisotropic medium (bottom right), the two observed flexural-wavedispersion curves cross. This phenomenon is a result of near-wellbore stressconcentration, and indicates stress-induced anisotropy.
Frequency
Slow
ness
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Homogeneous Isotropic
Frequency
Slow
ness
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Inhomogeneous Isotropic
Damaged formation,near failure
Frequency
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Homogeneous Anisotropic
Intrinsic anisotropy:shales, layering, fractures
Frequency
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Inhomogeneous Anisotropic
Stress-inducedanisotropy
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Extreme SlownessSome formations are so slow that not only is theS-wave slowness greater than that of the mud,but the P-wave slowness approaches that of themud. In these circumstances, the P-wave losesenergy to the formation, in what is known as aleaky-P mode, and is dispersive. At the low-
frequency limit, the leaky-P dispersion curvetends toward the P-wave slowness, and at thehigh-frequency limit, it reaches the borehole-fluid slowness.7
The Antelope formation in the Cymric oil fieldin the San Joaquin Valley, California, is such acase, combining extreme slowness with other
complications that make sonic logging chal-lenging.8 The formation lithology is diatomite and cristobalite—forms of opalized silica.Permeability is low, averaging 2 mD. From earlierstudies, compressional-wave slowness in thisformation is known to approach 200 µs/ft, which isnear the slowness of the mud wave, and shear-
4. The X- and Y-dipole sources are separated by 1 ft. Whilethis avoids electrical cross-talk, it also means thatwaveforms must be shifted by 1 ft before Alford rotation.This reduces the number of collocated waveforms from13 to 11.Alford RM: “Shear Data in the Presence of AzimuthalAnisotropy: Dilley, Texas,” Expanded Abstracts, 56th SEGAnnual International Meeting, Houston (November 2–6,1986): 476–479.
5. For anisotropy to be identified in this way, the anisotropysymmetry axis must be perpendicular to the boreholeaxis. For example, crossed-dipole logging tools invertical wells can detect anisotropy caused by alignedvertical fractures, and in horizontal wells can detectanisotropy caused by horizontal laminations.
6. Sinha BK and Kostek S: “Stress-Induced AzimuthalAnisotropy in Borehole Flexural Waves,” Geophysics 61,no. 6 (November-December 1996): 1899–1907.Winkler KW, Sinha BK and Plona TJ, “Effects ofBorehole Stress Concentrations on Dipole AnisotropyMeasurements,” Geophysics 63, no. 1 (January-February1998): 11–17.
7. Valero H-P, Peng L, Yamamoto M, Plona T, Murray D andYamamoto H: “Processing of Monopole Compressional inSlow Formations,” Expanded Abstracts, 74th SEGInternational Meeting, Denver (October 10–15, 2004):318–321.
8. Walsh J, Tagbor K, Plona T, Yamamoto H and De G:“Acoustic Characterization of an Extremely SlowFormation in California,” Transactions of the SPWLA 46thAnnual Logging Symposium, New Orleans, June 26–29,2005, paper U.
> Openhole (left) and cased-hole (right) results in a Statoil North Sea well. The Sonic Scanner tool measures P-, S- and Stoneley-waveslownesses in open hole and behind casing, even where the caliper (Track 1) indicates a washed-out zone (between X,296 and X,305 m)in the openhole logs. Flexural-mode slowness displayed in Track 2 of each set is more sharply defined, with a narrower color band, inthe cased-hole example than in the openhole logs. In the dispersion curves (bottom), compressional-wave slowness is in dashed greenand shear-wave slowness is in dashed blue.
X,290
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0 150gAPI
Gamma Ray6 16in.
Bit Size
Dept
h, m
80 540µs/ft
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µs0 10,000
Arrival Timeµs0 10,000
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µs0 10,000
Arrival Timeµs0 10,000
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20 Oilfield Review
> Shear-wave slownesses computed from flexural-wave logging in the extremely slow Antelope formation, Cymric field, California. In the diatomite zone,down to 1,500 ft, shear slownesses in Track 3 average 700 µs/ft and approach 900 µs/ft in some intervals. Below that, shear slownesses decrease to about400 µs/ft. The large separation between minimum and maximum offline energy in the depth track indicates anisotropy. Track 1 shows gamma ray (green),hole diameter (yellow), hole azimuth (light blue) and azimuth of the continually rotating tool (dark blue). Azimuth of the fast shear wave, shown in Track 2(red), is relatively constant in the anisotropic zone above 1,500 ft, in spite of continual tool rotation. In addition to fast (red) and slow (blue) shear slownessesestimated from dispersion analysis, Track 3 shows Stoneley-wave slowness (black), P-wave slowness (green curve), and slowness-based (left edge oftrack) and time-based (right edge of track) anisotropies. Track 4 shows the waveforms and time windows used for flexural-wave analysis. Slowness-time-coherence projections for fast and slow shear are shown in Track 5 and Track 7, respectively. Slowness-frequency-analysis (SFA) projections for fast andslow shear are shown in Track 6 and Track 8, respectively. (Modified from Walsh et al, reference 8.)
0 gAPI 150
Gamma Ray5 in. 20
Hole Diameter0 deg 360
Total Azimuth0 deg 360
Hole Azimuth-10 deg 90
Sonde Deviation
0 100
0 100
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∆T-Based Fast Shear200 µs/ft 1,200
∆T-Based Slow Shear
0 %
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100 %
Time-Based Anisotropy0
200 µs/ft 1,200
50 µs/ft 360
0 µs 30,000
Window Start0 µs 30,000
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Coherence
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Fast Shear
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Energy2 4 6 160
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MaximumEnergy
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wave slowness exceeds 800 µs/ft in some sections.9
Nine-component vertical seismic profiles andcrossed-dipole sonic logs have detected changinganisotropy magnitude and direction with depthand around the field.10 Knowledge of acousticvelocities and of anisotropy can be important fordesigning fracture stimulations and enhanced oil-recovery operations.
Measurements with the Sonic Scanner toolprovide new insight into the acoustic behavior ofthese complex rocks. Waveforms were recorded inan interval from 972 to 1,650 ft [296 to 503 m] in awell near the crest of the Cymric structure. In thediatomite zone, down to 1,500 ft [457 m], shearslowness estimated from flexural-mode dispersionprocessing is at least as great as that found inearlier logging programs, averaging 700 µs/ft andapproaching 900 µs/ft in some intervals (previouspage). Below that, shear slowness decreases toabout 400 µs/ft in the cristobalite zone.
Much of the logged interval exhibitsazimuthal anisotropy, as indicated by the largeseparation between minimum and maximumoffline energy, and also between the fast and slowshear-wave slownesses. Anisotropy magnituderanges from 4 to 8%, consistent with results ofprevious studies.11 Slowness anisotropy iscalculated by dividing the difference betweenfast and slow shear slownesses by their average.The azimuth of the fast shear direction isbetween N35W and N15W, in general agreementwith previous studies.12
Along with the typical fast and slow shear-slowness curves and slowness-time-coherence(STC) projections seen in many sonic-log plots,displays of Sonic Scanner data include newquality-control tracks showing slowness-frequency analysis (SFA). To create SFA plots, adispersion curve is generated at each depthusing the recorded dipole flexural waveforms(above right).13 The dispersion curve is projectedonto the slowness axis, and this projection is
plotted in a log versus depth presentation,similar to the way an STC projection isconstructed. The estimated slowness log fromdispersive STC processing is overlaid on the SFAprojection, and if the estimated slownessmatches the low-frequency limit of the SFAprojection, the quality of the slowness estimate ishigh. In azimuthally anisotropic formations, SFAprojections may be plotted for both the fast andslow shear directions.
In this extremely slow formation, themonopole source does not excite a compressionalhead wave, but rather a strong leaky-P mode.Compressional slowness must therefore beestimated from dispersive STC processing,analogous to the technique for determiningshear slowness from flexural modes.Compressional slowness is estimated at 192 µs/ft
9. Hatchell PJ, De GS, Winterstein DF and DeMartini DC:“Quantitative Comparison Between a Dipole Log andVSP in Anisotropic Rocks from Cymric Oil Field,California,” Expanded Abstracts, 65th SEG AnnualInternational Meeting, Houston (October 8–13, 1995):13–16.
10. De GS, Winterstein DF, Johnson SJ, Higgs WG andXiao H: “Predicting Natural or Induced FractureAzimuths from Shear-Wave Anisotropy,” paperSPE 50993-PA, SPE Reservoir Evaluation & Engineering 1,no. 4 (August 1998): 311–318.
11. De et al, reference 10.12. Hatchell et al, reference 9.13. Plona T, Kane M, Alford J, Endo T, Walsh J and Murray D:
“Slowness-Frequency Projection Logs: A New QCMethod for Accurate Sonic Slowness Evaluation,”Transactions of the SPWLA 46th Annual LoggingSymposium, New Orleans, June 26–29, 2005, paper T.
> Construction of a slowness-frequency-analysis (SFA) log for controlling the quality of shear-slownessestimation from flexural waves. Dipole flexural waveforms at each depth (top left) are analyzed fortheir slowness at varying frequencies. Resulting data are plotted on a slowness-frequency plot(bottom left), with circle size indicating amount of energy. Energies are color-coded and projectedonto the slowness axis. The color strip is plotted at the appropriate depth to create a log (right). The slowness estimate from dispersive STC processing is plotted as a black curve. If this matches thezero-frequency limit of the SFA projection, the slowness estimate is good.
13
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58171schD05R1.qxp 5/24/06 2:25 PM Page 21
in the shallow diatomite section and at 175 µs/ftin the cristobalite section (top).
Following on the initial success of the SonicScanner tool, Chevron is planning to run the toolin more wells in this field in 2006. Sonicvelocities will support microseismic fracture-mapping techniques.14
Radial Profiles of Slowness VariationVariations in formation properties may benatural or induced by the drilling process, andmay be beneficial or detrimental to the E&Pactivity at hand. By fully characterizing P- and S-wave slownesses in a large volume around theborehole, the cause of the variation can be
understood, and decisions can be maderegarding how to take advantage of or mitigatethe situation.
In a recent exploration well in the SouthTimbalier area of the Gulf of Mexico, Chevronsuccessfully penetrated a target sandstone. Inother wells, the same formation had presentedcompletion challenges, so the logging program inthis well included measurements to assess itsmechanical properties.
Radial profiles of compressional and shearslownesses can reveal important informationabout the state of the formation near theborehole. Radial variation in compressionalslowness is revealed by examining the differencein P slowness detected by the receiver array fromthe near and far monopole transmitters. Raysfrom the near transmitter sample the alteredzone near the borehole, while rays from the fartransmitter sample the unaltered zone, alsocalled the far field.
A clear picture of radial variation emergeswhen the P-wave data from all three transmittersand 13 receivers undergo tomographic recon-struction.15 This inversion technique uses ray
22 Oilfield Review
> Dispersion curves for compressional arrivals in the upper, diatomite zone (left) and the lower,cristobalite zone (right). Compressional-wave slowness is estimated by the slowness of the leaky-P mode at low frequency. [Modified from Walsh et al, reference 8].
220
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ness
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itude
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> Estimating compressional slowness by processing leaky-P dispersion data in the slow Antelope formation (left). Traditional monopole processing inTrack 2 does not give slowness estimates as reliably as does dispersive STC processing (Track 3). STC plots (right) from two different depths show theimproved coherence delivered by dispersive STC processing (right) compared with traditional STC processing (left). Track 4 shows slowness-frequencyanalysis (SFA) using leaky-P dispersion data, such as those shown in the dispersion curves (below). (Modified from Walsh et al, reference 8.)
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tracing to calculate signal arrival times at all thesensors, and updates an initially homogeneousformation model to create a final model thatsatisfies the observed data. To visualize theresulting compressional-slowness radial profile,the differential percentage between observedslowness and far-field slowness is color-codedand plotted against radial distance from theborehole wall (right).
Data from this Chevron well showed that thesandstones of interest exhibited radial variationsin compressional slowness approaching 15% atthe borehole wall and extending up 1 ft [30 cm]into the formation. However, quantifying theradial P-wave slowness variation alone does notidentify its cause. Compressional-slownessvariations can be caused by fluid changes, suchas invasion of drilling fluid, or by radial changesin stress or formation strength. Additionalinformation from the shear-slowness radialprofile could help distinguish between these.
Shear-slowness radial profiles are constructedin a multistep procedure.16 Semblance processingof flexural waveforms at low frequencies providesan initial estimate of formation elastic param-eters. These parameters are used to model ahomogeneous isotropic formation. Differencesbetween measured and modeled slownesses at alarge selection of frequencies form the input toan inversion procedure that yields the actualflexural-slowness radial profile. The results areplotted with colors that represent the amount ofdifference between observed slowness and theslowness of the unaltered, far-field formation.
In the South Timbalier case, the shear-slowness radial profile shows a large differencein near-wellbore slowness compared with far-field slowness. Flexural-wave dispersion curves
14. Bennett L, Le Calvez J, Sarver DR, Tanner K, Birk WS,Waters G, Drew J, Primiero P, Eisner L, Jones R, Leslie D,Williams MJ, Govenlock J, Klem RC and Tezuka K: “The Source for Hydraulic Fracture Characterization,”Oilfield Review 17, no. 4 (Winter 2005/2006): 42–57.
15. Zeroug S, Valero H-P and Bose S: “Monopole RadialProfiling of Compressional Slowness,” prepared forpresentation at the 76th SEG Annual InternationalMeeting, New Orleans, October 1–3, 2006.Hornby BE: “Tomographic Reconstruction of Near-Borehole Slowness Using Refracted Sonic Arrivals,”Geophysics 58, no. 12 (December 1993): 1726–1738.
16. Sinha BK: “Near-Wellbore Characterization Using RadialProfiles of Shear Slowness,” Expanded Abstracts,74th SEG Annual International Meeting, Denver (October 10–13, 2004): 326–331.
> Compressional and shear radial profiling in a Chevron Gulf of Mexico well. P-wave data from allthree transmitters and 13 receivers are input to tomographic reconstruction based on tracing raysthrough a modeled formation with properties that vary gradually away from the borehole. Thepercentage difference between observed compressional slowness and slowness of the unaltered,far-field formation is plotted on color and distance scales to indicate the extent of difference awayfrom the borehole (Track 6). In these sandstones, compressional slowness near the borehole variesby up to 15% from far-field slowness, and the variation extends to 1 ft from the borehole wall. Shear-wave radial profiles appear in Tracks 3 and 5 for the fast and slow shear differences from far-fieldslowness, respectively. Large differences, attributed to plastic yielding in the near-wellbore region,are shown in red, and extend out to about 10 in. from the borehole wall. These differences occur onlyin the sandstone intervals, identifiable from the gamma ray log in Track 4.
X,480
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1.7 2.7g/cm3
Density9 19in.
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300 100µs/ft
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180 80
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58171schD05R1.qxp 5/22/06 10:46 AM Page 23
also indicate a high degree of near-wellborealteration (above). The analysis is complicatedsomewhat by the addition of anisotropy; the fastshear and slow shear waves exhibit distinctdifferences relative to the unaltered, far-fieldslowness. In the sandstones, both fast and slowshear slownesses are up to 20% greater than thefar-field slowness in a zone roughly 10 in. [25 cm]from the borehole wall.
The radial heterogeneity in shear slownessrules out invasion or other fluid-related causes ofnear-wellbore alteration, because shear wavesare almost insensitive to changes in pore fluid.Fluid-related changes would cause onlycompressional-slowness radial variation. Themeasurable radial variation in shear slownessindicates that the formation has undergonemechanical damage in the form of plastic
yielding of grain contacts. The caliper shows nowellbore enlargement through this zone, so thedamaged material has not yet fallen into theborehole, but the increase in shear slowness nearthe borehole wall indicates that it is near failure.The Sonic Scanner data indicate a wide zone ofdamage that will require extra care when thetime comes to design a well completion.
Compressional and shear radial profiles bringnew information not previously available fromany logging tool. Borehole imaging tools andcalipers have been able to deliver images orevidence of drilling-induced borehole irregular-ities such as breakouts and fractures, but areuseful only after the borehole shape haschanged. The Sonic Scanner tool probes deepinto the formation to reveal mechanical damagebeyond the borehole wall.
Radial profiling may also help to fine-tuneprograms for acquisition of fluid samples. In anexample from the North Sea, Sonic Scannercompressional radial profiles were computed fortwo intervals from which samples weresubsequently acquired using the MDT ModularFormation Dynamics Tester. Zone A showed littledifference between near-wellbore and far-fieldslowness (next page). Two fluid samples weretaken from this interval after pumping times of75 and 80 minutes and no sampling problems. InZone B, the radial profile indicated formationdamage out to 12 in. from the borehole wall.During the attempt to obtain a fluid sample, theprobe on the sampling tool became plugged, andno sample was obtained.
Formation damage does not necessarily meanthat samples cannot be acquired, but sampling inthese zones may have an increased risk of toolplugging or sticking. To minimize these risks,sampling from potentially damaged zones shouldbe delayed and attempted later in the samplingprogram, so that samples from other intervalscan be collected first with less risk.
Characterizing Permeable Zones and FracturesPetrophysicists and reservoir engineers have longsought a continuous measurement of permeabilityto optimize well completions and productionscenarios, but continuous permeability is one ofthe most difficult properties to measure in an oilwell. Using empirical relationships calibrated tocore measurements, permeability or mobility—the ratio of permeability to viscosity—can beinferred from other measurements such asporosity or nuclear magnetic resonance logs.
24 Oilfield Review
17. Brie A, Endo T, Johnson DL and Pampuri F: “QuantitativeFormation Permeability Evaluation from StoneleyWaves,” paper SPE 49131, presented at the SPE AnnualTechnical Conference and Exhibition, New Orleans,September 27–30, 1998.
18. Kimball CV and Endo T: “Quantitative Stoneley MobilityInversion,” Expanded Abstracts, 68th SEG AnnualInternational Meeting and Exhibition, New Orleans(September 13–15, 1998): 252–255.Liu H-L and Johnson DL: “Effects of an ElasticMembrane on Tube Waves in Permeable Formations,”Journal of the Acoustic Society of America 101, no. 6(June 1997): 3322–3329.
> Comparison of flexural-wave dispersion seen in a South Timbalier wellwith modeled results (top). Observed flexural-wave slownesses (red andblue circles) show much larger dispersion than the model for a homogeneousisotropic formation (blue curve). The large difference at higher frequenciesindicates near-wellbore damage. Stoneley-wave slownesses appear asgreen circles. In the bottom figure, the difference between observed andmodeled flexural slowness is plotted against distance, in borehole-radius ratiounits. The difference between observed and modeled flexural slownessamounts to 20% out to a distance equivalent to about two borehole radii.
Alteration radius/borehole radius
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Spring 2006 25
Direct measurements can be made with wirelineformation testers at isolated points along the well,or on core, but these require additional loggingruns and coring costs. Stoneley-wave analysis is apowerful technique that delivers a direct,continuous measurement of mobility along the well.17
The idea of measuring mobility from theStoneley wave was first expressed in the 1970s,but proved difficult in practice. Many attemptshave been made to develop empirical correla-tions between permeability and Stoneleyattenuation, but these methods requiredcalibration with other information and neglectedseveral important factors, such as mudcakepermeability and the presence of the tool itself.Approaches that simplified the complex behaviorof Stoneley waves were seldom successful, but aninversion method that uses a model derived fromfull Biot poroelastic theory reliably determinespore-fluid mobility from Stoneley waveforms.18
For application with Sonic Scanner data, the fullBiot inversion technique was extended toincorporate tool response.
The full Biot inversion scheme requiresseveral borehole, mudcake and formationparameters to evaluate fluid mobility usingStoneley-wave data. The list includes: holediameter; mud slowness, attenuation anddensity; formation P and S slowness, density andporosity; grain modulus; pore-fluid modulus anddensity; and mudcake density, bulk modulus,shear modulus, thickness and membranestiffness. The computation outputs fluid mobilityand associated error ranges.
This inversion technique has been availablefor several years, but application has not alwaysbeen successful because the inversion requiresextremely low-frequency Stoneley waves—downto 300 Hz. Data with this frequency content havenot been available in the past, because earliersonic tools interacted negatively with low-frequency signals and required filtering toremove frequencies below 1,500 Hz. Now, thewideband sources of the Sonic Scanner toolgenerate strong Stoneley waves with reliable low-frequency content for mobility calculations.
An example from a Statoil well in theHaltenbanken area of the Norwegian Sea showsgood correlation between mobilities calculatedfrom Stoneley waves and those measured by MDT pretests. Input values of formation and fluid properties of a zone near the oil/watercontact were determined with logs from thePlatform Express integrated wireline logging
> A compressional-wave radial profile indicating intervals of successful andrisky fluid sampling. In interval A, the compressional-wave radial profile(Track 3) shows a small differential between near-wellbore slowness and far-field slowness. There is little near-wellbore alteration in the zone wherethe MDT Modular Dynamics Formation Tester successfully collected twoformation-fluid samples. In Track 3, the amount of slowness differencebetween near and far field is indicated by gold and brown color intensity,while depth of alteration is indicated by the horizontal length of the coloredarea. In interval B, the compressional-wave radial profile shows darkercolors, indicating a higher degree of near-wellbore alteration extendingfarther away from the borehole. In this zone, the MDT probe becameplugged and was not able to collect any formation-fluid samples. Track 2displays the slowness gradient obtained from the tomographic reconstruction.The gradient indicates the difference in slowness from one slowness-model cell to the next, moving away from the borehole in small increments.
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58171schD05R1.qxp 5/22/06 10:47 AM Page 25
tool. The MDT results from eight drawdownpretests and one tight pretest correlate closelywith mobilities extracted from Stoneley-waveanalysis (right).
The continuous mobility log exhibits highmobility inside sand packages and low mobilitynear shale streaks and at the depth of the tightMDT pretest. Because the Sonic Scannermobility results are somewhat sensitive to a fewparameters that are not well constrained bylogging measurements, such as mud slowness,mud attenuation and mudcake stiffness, testswere conducted to study the effect of uncertaintyin these parameters on the mobility error bars.The continuous mobility log shown is the onewith the least uncertainty.
When the borehole is in good condition,continuous mobility logs from Stoneley wavescan be used to obtain a quick permeabilityestimate for selecting sampling points andperforation intervals, and may function as asupplement to core or formation-tester permea-bility points over an extended interval.
Stoneley waves can also be used tocharacterize permeability associated with openfractures. In the US Rocky Mountains, forexample, hard-rock reservoirs depend onhydraulically induced fractures for economicproduction. However, the highly unequal in-situstresses in the region give rise to natural fracturestoo. If natural fractures are encountered in a well,cementing and stimulation designs must beadjusted to prevent cement from entering thenatural-fracture system. For example, fiber-basedtreatments for both cementing and stimulationcan be used to reduce fluid losses.19 Stimulationprograms need to take into account themagnitude and direction of the principal stresses.Optimizing the completion design requiresknowledge of the fracture and stresscharacteristics around the wellbore and in the formation.
An open fracture intersecting a boreholecauses Stoneley waves to reflect and attenuate.20
Analysis of Stoneley waveforms quantifies thesechanges, which are input to an inversion forfracture aperture.21 However, washouts, boreholerugosity and abrupt changes in lithology also cancause Stoneley reflections, and should beconsidered in the analysis.22
An example of successful application of thismethod comes from Colorado, USA.23 In this gasreservoir, porosity ranges from 3 to 7% andpermeability is in the microdarcies. Stoneley-wave analysis quantified the aperture andpermeability of fractures that were also seen on
26 Oilfield Review
> Comparing fluid-mobility values from MDT pretests with those fromStoneley-wave processing in a Statoil well in the Haltenbanken area of theNorwegian Sea. In Track 3, continuous fluid-mobility values (blue curve)and uncertainties (gray shading) estimated from Stoneley-wave analysiscorrelate well with discrete mobility values obtained from MDT drawdownpretests (red dots). The two measures of mobility match even at the tightMDT pretest at X,X42.15 m, where the Stoneley mobility also shows anextremely low value. Porosity, gamma ray, density, caliper and shale volumeare plotted in Track 1. Track 2 shows acoustic slownesses. Track 4 displaysrelative volumes of lithology and fluids.
Mobility Error Bar
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FMI Fullbore Formation MicroImager images(above). With the broad range of Stoneley-modefrequencies acquired by the Sonic Scanner tool, these open natural fractures can be reliably characterized.
Shear-Wave Directions in MexicoSmall directional variations in formationproperties can have a major impact on drillingand completion strategies, but these may bedifficult to measure. For example, sonic velocities
may be different in one horizontal directioncompared with the orthogonal horizontaldirection. This phenomenon, called elasticanisotropy, occurs in most sedimentary rocks andis caused by layering, aligned fractures or stress
19. Bivins CH, Boney C, Fredd C, Lassek J, Sullivan P,Engels J, Fielder EO, Gorham T, Judd T,Sanchez Mogollon AE, Tabor L, Valenzuela Muñoz A and Willberg D: “New Fibers for Hydraulic Fracturing,”Oilfield Review 17, no. 2 (Summer 2005): 34–43.Abbas R, Jaroug H, Dole S, Effendhy, Junaidi H, El-Hassan H, Francis L, Hornsby L, McCraith S,Shuttleworth N, van der Plas K, Messier E, Munk T,Nødland N, Svendsen RK, Therond E and Taoutaou S: “A Safety Net for Controlling Lost Circulation,” OilfieldReview 15, no. 4 (Winter 2003/2004): 20–27.
20. Hornby BE, Johnson DL, Winkler KH and Plumb RA:“Fracture Evaluation Using Reflected Stoneley WaveArrivals,” Geophysics 54, no. 10 (October 1989):1274–1288.Brie A, Hsu K and Eckersley C: “Using the StoneleyNormalized Differential Energies for Fractured ReservoirEvaluation,” Transactions of the SPWLA 29th AnnualLogging Symposium, San Antonio, Texas, June 5–8, 1988,paper XX.
21. Endo T, Tezuka K, Fukushima T, Brie A, Mikada H andMiyairi M: “Fracture Evaluation from Inversion ofStoneley Transmission and Reflections,” Proceedings of the 4th SEGJ International Symposium, Tokyo(December 10–12, 1998): 389–394.
22. Tezuka K, Cheng CH and Tang XM: “Modeling of Low-Frequency Stoneley-Wave Propagation in an IrregularBorehole,” Geophysics 62, no. 4 (July-August 1997):1047–1058.
23. Donald A and Bratton T: “Advancements in AcousticTechniques for Evaluating Open Natural Fractures,”prepared for presentation at the SPWLA 47th AnnualLogging Symposium, Veracruz, Mexico, June 4–7, 2006.
> Identifying permeable fractures in Colorado using Stoneley waves. The fracture aperture, or amountof opening, computed from Stoneley-wave reflection and transmission is displayed in Track 2. Track 3shows fracture permeability computed from the Track 2 apertures. Zones containing permeablefractures correlate with zones in which the FMI logs (Track 6) show fractures. The same zones appearas anisotropic, with large offline energy differences (depth track), and also show large differencesbetween measured Stoneley slowness and slowness modeled for an elastic, impermeable formation(orange shading, Track 1). Track 4 shows measured Stoneley waveforms, with amplitude reduction inthe fractured zones. Track 5 shows waveforms generated by the Tezuka model of reference 22.(Modified from Donald and Bratton, reference 23.)
X,100
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58171schD05R1.qxp 5/22/06 10:47 AM Page 27
imbalance.24 Until now, wireline sonic tools havebeen able to quantify the magnitude andorientation of elastic anisotropy only if thedifference in velocities was at least 5%. The highquality of data provided by the Sonic Scannertool allows reliable measurement of anisotropyas small as 1%, and also helps interpretersdetermine the cause of the anisotropy.
Pemex Exploración y Producción wanted toevaluate the amount and direction of anisotropyin tight gas-producing sandstone formations inthe Burgos basin of northern Mexico. Theseformations have low permeabilities and must bestimulated to produce gas in commercialquantities. Optimal development depends oncorrectly orienting hydraulic fractures in thelocal stress field so that each vertical well drains
its designated volume. Knowledge of elasticanisotropy orientation and magnitude would helpin the design and application of oriented-perforating techniques prior to fracturetreatments and would also improve the success ofinfill-drilling campaigns.25
28 Oilfield Review
> A crossed-dipole log (left) from the Pemex Cuitlahuac-832 well, showing zones with isotropy and with differing amountsof anisotropy. Zone A, an isotropic zone, has low offline energy (depth track) and equal fast and slow shear-waveslownesses (Track 3). Anisotropic Zones B and C have nonzero offline energies and different fast and slow shear-waveslownesses. Anisotropy magnitude, either slowness-based or time-based (edges of Track 3), is about 8% in Zone B andabout 2% in Zone C. The azimuth of the fast shear wave (Track 2) remains constant through the anisotropic intervals,even though the tool is rotating (Track 1), giving confidence in the anisotropy values. Dispersion curves from the threeintervals (right) show characteristic relationships. In Zone A (top), as in other isotropic formations, the dispersion curvesfor flexural waves recorded in the two dipole directions (red and blue circles) overlie each other. At the bottom of ZoneB (bottom), the dispersion curves cross each other. The flexural wave that is fast near the borehole, at low frequencies(red dots), becomes the slower wave with distance from the borehole (blue dots). This indicates that stress-inducedanisotropy is the dominant mechanism of anisotropy in this section. Shallower in Zone B (middle), the dispersion curveslook as though they could cross, but the high-frequency components of the fast shear wave are lost. At this depth, open,induced fractures were visible in OBMI Oil-Base MicroImager logs. (Modified from Wielemaker et al, reference 25.)
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When the vertical stress is the maximumstress, hydraulic fractures propagate in thedirection of the maximum horizontal stress andthey open in the direction of minimum horizontalstress. Shear waves travel fastest when polarizedin the direction of maximum horizontal stress(SH) and slowest when polarized in the directionof minimum horizontal stress (Sh). This isbecause additional stress stiffens the formation,increasing velocity, and reduced stress converselydecreases velocity. Measuring the direction ofthe fast shear waves yields the preferreddirection of fracture propagation.
The directions, or azimuths, of fast and slowshear waves can be seen in a crossed-dipole log.A crossed-dipole log from the Cuitlahuac-832well shows both isotropic and anisotropic zones(previous page). Zone A, an isotropic zone, isidentified by near-zero offline energies and equal fast and slow shear-wave slownesses.26
Anisotropic Zones B and C are identified bynonzero offline energies and diverging fast andslow shear-wave slownesses.
The two anisotropic zones have differentamounts of anisotropy. In Zone B, anisotropymagnitude is about 8%. In Zone C, the amount ofanisotropy is about 2%. Although 2% is lower thanhas been reliably detected by other tools,interpreters have confidence in the valuebecause the waveforms are so clear and becausethe fast shear azimuth remains constant,between 30° and 40° over the interval, even withthe tool continually rotating.
Knowing the magnitude and azimuth ofanisotropy is vital, but this does not identify thecause. The anisotropy may be intrinsic to the rockor may be stress-induced; identifying the cause isimportant for understanding how stable thedrilling process will be and how a borehole willrespond to stress. Usually, additional information,such as borehole images or core analysis, isrequired to pinpoint the cause of anisotropy.
Analysis of flexural-wave dispersion curvesprovided by the Sonic Scanner tool helps toidentify anisotropy mechanisms at three depthsin the Cuitlahuac-832 well using only sonicmeasurements. Dispersion curves at 1,593.04 m,within Zone A, overlie each other closely andmatch the model for a homogeneous isotropicformation. Curves from 1,665.27 m, one of themost anisotropic intervals near the bottom ofZone B, show the crossover characteristic ofstress-induced anisotropy. Slightly shallower, at1,658.87 m, the fast and slow shear dispersioncurves are separated at low frequencies, but the
high-frequency data are missing, so it isimpossible to determine the curve trend or theanisotropy type. OBMI Oil-Base MicroImagerimages at this depth indicate the presence ofopen, induced fractures, which are the likelycause of the loss of high-frequency data and also strongly suggest stress-induced anisotropy.The 45° azimuth of fractures seen in OBMIimages correlates well with the 40° azimuth ofmaximum horizontal stress inferred from the fastshear direction.
In the Burgos basin, maximum horizontalstress has traditionally been taken to be parallelto the strike of the nearest faults. The resultsfrom Sonic Scanner logging in five wells in thisbasin indicate that local stress direction can vary significantly—up to 20° from the strike ofnearby faults—accentuating the importance ofmaking localized sonic measurements beforedesigning perforation, stimulation and infill-drilling operations.
Imaging Well Beyond the WellboreThe superior quality of waveforms acquired withthe Sonic Scanner tool allows for improvedimaging away from the borehole. Sonic imaginguses reflected P-waves to detect reflectors that are subparallel or at low angle relative to the borehole.
Norsk Hydro has used the imaging capabilityof the Sonic Scanner tool in a highly deviatedwell in the Norwegian Sea (above). Followingacquisition of standard sonic waveforms in oneTLC Tough Logging Conditions wireline pass, aseparate TLC imaging pass recorded waveformsevery 0.5 ft [15 cm] from the three monopolesources firing sequentially to the 104 receivers
24. Elastic anisotropy is sometimes called acousticanisotropy or velocity anisotropy. It can be expressed interms of a difference of velocities, slownesses, stressesor elastic parameters.Armstrong P, Ireson D, Chmela B, Dodds K, Esmersoy C,Miller D, Hornby B, Sayers C, Schoenberg M, Leaney Sand Lynn H: “The Promise of Elastic Anisotropy,” OilfieldReview 6, no. 4 (October 1994): 36–56
25. Arroyo Franco JL, Gonzalez de la Torre H, Mercado Ortiz MA, Weilemaker E, Plona TJ,Saldungaray P and Mikhaltzeva I: “Using Shear-WaveAnisotropy to Optimize Reservoir Drainage and ImproveProduction in Low-Permeability Formations in the Northof Mexico,” paper SPE 96808, presented at the SPEAnnual Conference and Technical Exhibition, Dallas,October 9–12, 2005.Wielemaker E, Saldungaray P, Sanguinetti M, Plona T,Yamamoto H, Arroyo JL and Mercado Ortiz MA: “Shear-Wave Anisotropy Evaluation in Mexico’s Cuitlahuac FieldUsing a New Modular Sonic Tool,” Transactions of theSPWLA 46th Annual Logging Symposium, New Orleans,June 26–29, 2005, paper V.
26. The difference between slownesses is called slownessanisotropy, and the difference between arrival times iscalled time-based anisotropy.
> Geologic cross section with trajectory of a deviated well in which Norsk Hydro acquiredSonic Scanner imaging data. The high deviation angle required TLC Tough LoggingConditions wireline logging.
Wellbore
Interval logged
with Sonic Scanner tool
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over a distance of 330 m [1,100 ft]. Waveformsfrom each source were processed in a sequencethat started with separating reflected P-wavesfrom Stoneley and refracted P-waves. Theazimuthal distribution of sensors at eachreceiver station allows identification of thedirection to the reflector. Then, traces from eachreceiver station were depth-migrated usingformation velocities measured by the SonicScanner logs from the earlier logging pass.27 Toaccount for tool rotation and the azimuthaldistribution of sensors, the image at eachreceiver station was reconstructed by depth-shifting and stacking images from eachazimuthal channel. Finally, the depth-migratedimages were stacked. Images were obtainedwithin 48 hours.
The results show a 5-degree dipping eventthat extends at least 13 m [43 ft] into theformation (right). The dip of the event is inagreement with the expected geology at the welllocation. The high-resolution event can becorrelated with a 1-m [3.3-ft] coal bed at thesame depth position indicated by petrophysicallogs (next page). The identification of a 1-m coalbed indicates the potential to obtain high-resolution images from a sonic-imaging survey.The resolution is far better than can be obtainedfrom any surface or borehole seismic survey(below right).
Another potential application of sonicimaging is the detection of vertical fracturesnear but not intersecting vertical boreholes.Current techniques such as borehole imagelogging and fracture identification from Stoneleyreflections work only if a fracture intersects theborehole. In many cases, a vertical well will missvertical fractures. Deep imaging with the SonicScanner tool expands the volume of investigationto enable the identification of features that maydelineate reservoir extent or the state of stressaway from the borehole.
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27. Migration is a data-processing step that aims to sharpen,shift and relocate reflectors to their true locations.
> A gently dipping reflector imaged far from the borehole. The boreholetrajectory is shown in red. The high-resolution event detected by sonicimaging can be seen above and to the right of the borehole, near the centerof the image. The reflector correlates with a coal bed at the same depthposition indicated by petrophysical logs.
Verti
cal d
epth
, ft
X,240
X,260
X,280
X,300
X,320
X,340
X,360
X,380
X,460 X,480 X,500 X,520 X,540 X,560 X,580
Source-receiver midpoint, ft
> Comparing high-resolution sonic-imaging data with a surface seismic survey. The 1-m coal bedresolved by Sonic Scanner imaging (inset) cannot be seen in the surface seismic survey.
Sonic-imaging results on seismic scale
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Scanning the Horizon The Sonic Scanner tool is a new development,and engineers, geologists and petrophysicists arestill finding new ways to use its data. By addingthe radial dimension and multiple depths ofinvestigation to the well-known axial andazimuthal sonic measurements, the SonicScanner tool performs enhanced characteri-zation of acoustic properties in inhomogeneousand anisotropic formations. With this infor-mation, customers are able to predict howformations and fluids will behave during drilling,stimulation and production.
The innovative tool design with predictableacoustics delivers waveforms of excellent qualityand at a wide frequency range. These capabilitiesallow slowness estimation in extremely slowformations, measuring azimuthal anisotropy assmall as 1 to 2%, and reliable application of low-frequency Stoneley modes for fluid-mobilityestimation and evaluation of natural fractures.Advanced quality control with slowness-frequency analysis adds confidence to slownessestimates obtained by dispersion analysis.
Complete recording of all data frommonopole and dipole sources to 104 receiversdistributed azimuthally around the tool removesuncertainties about formation geometry andstructure and improves through-casing andcement evaluation. Current capabilities obtainonly monopole compressional and shear data incased hole. One area of future advancement willbe to extend current openhole applications to cased wells.
Additional applications will arise as morecompanies gain experience with the SonicScanner tool and the high-quality data itproduces. While it is difficult to predict how therest of the oil and gas industry will evolve, sonic-logging enthusiasts anticipate another 50 years ofinvestigations in and around the borehole. —LS
> Petrophysical logs from the Norsk Hydro well in the Haltenbanken area of the Norwegian Sea,showing the 1-m coal bed delineated by sonic imaging. Platform Express resistivity logs (Track 2) anddensity and porosity logs (Track 3) are input, along with ECS Elemental Capture Spectroscopy data to derive mineralogy (Track 4). Nuclear magnetic resonance data appear in Track 5.
X,900
X,925
Caving
ECS Sigma
cu60 0
Caliper
in .6 16
Depth,m ohm-m0.2 200
Porosity
m3/m30.45 -0.15
Density
g/cm31.95 2.95
Density
g/cm32.5 3.0
Coal
Siderite
T2 Distribution
Log T2 Mean
ms0.3 3,000
ms0.3 3,000
T2 Cutoff
ms0.3 3,000
1- mcoal bed
HRLA1 Resistivity
HRLA2 Resistivity
HRLA3 Resistivity
HRLA4 Resistivity
HRLA5 Resistivity
Quartz
Clay
Carbonate
Pyrite
Gamma Ray
gAPI0 200
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32 Oilfield Review
In a patent awarded in 1935, ConradSchlumberger specified how a transmitterand two receivers might be used to measurethe speed of sound in a short interval of rockpenetrated by a borehole (right).1 He claimedthat the speed and attenuation of soundwould characterize lithology. His inventionfailed because neither logging engineers nor the technology of the time was able todetect the short time difference—tens ofmicroseconds (µs)—between signals travelingat the speed of sound to receivers separatedby just inches.
During World War II, the necessaryelectronics emerged, making sonic loggingpossible.2 According to one account, the firstoilfield application of sonic logging was forcasing-collar location, in 1946.3 Most otherhistorical accounts state that the first sonicapplications appeared after the 1948experiments by Humble Oil Research,followed by Magnolia Petroleum Company andShell.4 These companies designed devices tocollect sonic-velocity information for time-depth conversion of surface seismic sectionsand for correlating seismic reflections tolithologic interfaces. The tools featured onetransmitter and one or two receiversseparated from the transmitter by isolatingmaterial. By the mid-1950s, service companiesand oil companies were acquiring sonic-logging data to generate synthetic seismogramsfor comparison with surface seismic sections.5
In 1957, having licensed the Humble patent,Schlumberger introduced its first sonic tool,the velocity logging tool (VLT), for improvingseismic interpretation.
The early Magnolia Petroleum paper hadhinted at the additional possibility of usingsonic velocities to determine porosity andlithology, but it was scientists in the researchdivision of Gulf Oil Corporation who firstpublished experimental observationsconfirming the link.6 Within a short time,demand for sonic porosity-logging applicationsovertook that for seismic applications.
In 1960, field crews testing the VLTresponse in cased holes in Venezuela noticedthat certain zones caused unreadable, low-amplitude signals. They correctly concludedthat the anomalous signals could be attributedonly to cement condition. Measuring andrecording signal amplitude in addition toarrival time gave birth to an unexpectedapplication, and CBT Cement Bond Tool logssoon replaced the temperature survey fordetecting top of cement.
By the early 1960s, the first sonic tools hadacquired tens of thousands of logs, andengineers set about designing a second-generation tool to address three problems: tooldurability, and poor signal in the presence of
borehole irregularities and near-wellborealteration. The tool-durability problem arosebecause early tools used rubber to isolatereceivers from transmitters, therebypreventing undesirable sound waves frompropagating within the tool and overwhelmingdesired signals. However, rubber tended toabsorb gas from gas-rich formations, causingthe tool to expand and break apart as it wasbrought to surface. The tool was strengthenedby replacing the rubber with steel, but thenthe tool housing had to be shaped so that thepath of sonic waves traveling through the steelwould be longer than the paths through theformation and back to the receivers. (nextpage). Many modern sonic tools continue to
History of Wireline Sonic Logging
> Illustration from the 1935 patenton acoustic logging by ConradSchlumberger. The field engineer(13) was supposed to slide a sleeve(17) until sound coming fromreceivers (3 and 4) appeared toarrive simultaneously at each ear.
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feature slots and grooves to slow down thearrival of signals—known as tool arrivals—that travel purely through the tool.
A way around the second problem, poor logs in bad hole, came from the Shell engineerresponsible for that company’s first sonictool.7 His borehole-compensating arrangementof receivers and transmitters not onlyeliminated the problem of poor signal inwashed-out zones, but also removed theeffects of tool tilt and eccentering on logresponse. Solving two of the three problemsthat plagued the earlier tools, Schlumbergerincorporated this idea into the all-steel designof the borehole-compensated (BHC) sonic toolthat was introduced in 1964. The BHC toolcontained two transmitters and four receivers.
Along with BHC technology came theability to view registered waveforms on an
oscilloscope in the logging truck. Appearingon the screen were not only the primary (P-)arrivals, or compressional waves, but alsosecondary (S-), or shear waves and laterarrivals. Recognizing the importance of shearwaves made the mid-1960s a time of intenseactivity in expanding sonic applications.Specialists at Shell proposed using the ratioof P to S velocity as a lithology indicator, andalso used sonic logs to predict overpressuredzones.8 Schlumberger engineers andresearchers evaluated use of P and Samplitudes to locate fractures. Althoughthese and other shear-wave applications hadbeen proposed, the acquisition systems of thetime recorded only the arrival time of the P-wave. The waveform itself, including P, S andlater arrivals, was not recorded.
Another drawback of the BHC tool was itsinability to accurately measure the trueformation interval transit time in zones ofinvasion, shale alteration and drilling-induceddamage. The 3- to 5-ft [0.9- to 1.5-m]
transmitter-receiver (TR) spacing capturedonly waves that propagated in the alteredzone, leaving the unaltered zone away fromthe borehole unexplored. By increasing thespacing to 8 to 12 ft [2.4 to 3.7 m], the LSSLong-Spaced Sonic Tool improved logresponse in altered shales. Sonic velocities ofthe unaltered formation are morerepresentative of the reservoir in its naturalstate and yield synthetic seismograms thatbetter match surface seismic traces.
The long TR spacing also stretched thereceived wavetrain, separating the P-, S- andother waves into recognizable packets ofenergy. Efforts intensified to capture the fullwaveform, leading to the development of toolsthat recorded digital waveforms from an arrayof receivers. The first commercial Schlumbergerversion of this technology, introduced in the1980s, was called the Array-Sonic full-waveformsonic velocity tool. Full-waveform logging gaverise to a host of new processing techniques.
The late 1980s saw research experimentswith a second-generation digital sonic tool.The DSI Dipole Shear Sonic Imager tool hadeight sets of four monopole receivers thatcould function as orthogonal dipole receivers,and carried one monopole source and twoorthogonally oriented dipole sources. Thedipole sources generated flexural waves,allowing characterization of formationanisotropy and shear slowness in slow as wellas fast formations.
Also in the late 1980s, Schlumbergerresearchers tested a variety of multireceiveracoustic tools for their ability to acquire sonicimages—seismic-like images far from theborehole.9 The first commercial sonic-imagingservice was run in 1996, but processing wastime- and personnel-intensive.
In 2005, the Sonic Scanner acousticscanning platform combined manyinnovations of the past and added radialmeasurements to simultaneously probe theformation for near-wellbore and far-fieldslownesses.10 The tool itself is fullycharacterized, with predictable acoustics. The wide frequency range of the monopoleand dipole transmitters delivers excellentwaveform quality in all formation types.
1. Schlumberger C: “Procédé et Appareillage pour laReconnaissance de Terrains Traversés par unSondage.” République Française Brevet d’Inventionnuméro 786,863 (June 17, 1935). Also Doll L: “Methodof and Apparatus for Surveying the FormationsTraversed by a Borehole,” US Patent No. 2,191,119(February 20, 1940) (submitted by the estate of ConradSchlumberger).
2. The terms “sonic” and “acoustic” are usedinterchangeably.
3. Pike B and Duey R: “Logging History Rich withInnovation,” Hart’s E&P (September 2002): 52–55,http://www.spwla.org/about/Logging-history.pdf(accessed April 28, 2006).
4. From Humble Oil: Mounce WD: “Measurement ofAcoustical Properties of Materials,” US PatentNo. 2,200,476 (May 14, 1940).From Magnolia Petroleum Company: Summers GC and Broding RA: “Continuous Velocity Logging,”Geophysics 17, no. 3 (July 1952): 598–614.From Shell: Vogel CB: “A Seismic Velocity LoggingMethod,” Geophysics 17, no. 3 (July 1952): 586–597.Léonardon, reference 1, main text.
5. Breck HR, Schoellhorn SW and Baum RB: “VelocityLogging and Its Geological and GeophysicalApplications,” Bulletin of the American Associationof Petroleum Geologists 41, no. 8 (August 1957):1667–1682.
6. Wyllie MRJ, Gregory AR and Gardner LW: “ElasticWave Velocities in Heterogeneous and PorousMedia,” Geophysics 21, no. 1 (January 1956): 41–70.Tixier MP, Alger RP and Doh CA: “Sonic Logging,”Journal of Petroleum Technology 11, no. 5 (May 1959):106–114.
7. Vogel CB: “Well Logging,” US Patent No. 2,708,485(May 17, 1955).
8. Hottman CE and Johnson RK: “Estimation ofFormation Pressures from Log-Derived ShaleProperties,” Journal of Petroleum Technology 17, no.6 (June 1965): 717–722.
9. Hornby BE: “Imaging of Near-Borehole StructureUsing Full-Waveform Sonic Data,” Geophysics 54, no.6 (June 1989): 747–757.
10. Pistre et al, reference 3, main text.
> A sonic-logging sonde with slots to slowdown tool arrivals.
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