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ADVANCED PIPELINE MONITORING USING
MULTIPOINT ACOUSTIC DATA
G. Bernasconi, S. Del Giudice, Politecnico di Milano
G. Giunta, F. Dionigi, eni S.p.A. gas & power division
R. Schiavon, F. Zanon, Tecnomare S.p.A
This paper was presented at the 11th Offshore Mediterranean Conference and Exhibition in Ravenna, Italy, March 20-22, 2013.
It was selected for presentation by OMC 2013 Programme Committee following review of information contained in the abstract
submitted by the author(s). The Paper as presented at OMC 2013 has not been reviewed by the Programme Committee.
ABSTRACT
Multi-point Acoustic Sensing (MAS) technology makes use of hydrophone sensors placed at
discrete distances along pipelines in order to detect third party interference (TPI) and leaks.
Leak transients are associated to “rarefaction waves”, and any interaction with the pipe
generates pressure (acoustic) waves that are guided within the fluid for long distances,
carrying information on the source event. Pressure propagation is mainly governed by the
absorption coefficient and the sound speed. These parameters are in turn complicated
functions of the signal frequency, the geometrical and elastic parameters of the pipe shell,
the elastic parameters of the surrounding medium, and the acoustic and thermodynamic
properties of the transported fluid. We have analyzed this last aspect while processing
acoustic data collected on crude oil and natural gas transportation pipelines, in different
operational and flow conditions. In this paper we describe advanced procedures for the
identification and classification of operational situations of the pipeline/fluid system, and the
elaboration steps for the experimental derivation of fluid properties.
INTRODUCTION
Multipoint Acoustic Sensing (MAS) is an emerging technology for pipeline real-time
monitoring. It takes advantage of the fact that any mechanical interaction with the pipeline or
with the flow generates vibroacoustic waves that are transported along the conduit for long
distances. These waves can be sensed along the pipeline, and processed in order to identify,
classify and locate potential anomalies. Eni has developed a proprietary vibroacoustic
system (e-vpms®) for detection of third-party intrusion (TPI) and leaks in fluid filled pipelines
(Fig. 1). It collects, with a discrete number of monitoring stations, the low frequency elastic
waves travelling along the pipe, and the pressure waves travelling into the fluid. The
recorded data is synchronized with a GPS reference, and it is sent to a central unit, thus
permitting real time multichannel processing. Prototypal installations in crude oil and natural
gas transportation pipelines have been tested by simulating an exhaustive set of TPI and
leak trials (Giunta et al. 2011a, 2011b; Bernasconi et al., 2012). We are now designing long
term and advanced monitoring strategies using the collected vibroacoustic data. In fact
pressure waves are always present in the fluid, produced for example by variations of the
pump regime. Pressure propagation is mainly governed by the absorption coefficient and by
the sound speed. These parameters are in turn complicated functions of the signal
frequency, the geometrical and elastic parameters of the pipe shell, the elastic parameters of
the surrounding medium, and the acoustic and thermodynamic properties of the transported
fluid. We propose then to check the variability of sound propagation parameters within the
transported fluid versus experimental and analytical constitutive equations, in order to derive
additional information on fluid thermodynamic properties and/or pipeline infrastructure
operational status.
In this paper we describe two field campaigns of vibroacoustic data collection, one on a
crude oil scenario, the other on natural gas scenario, and we show advanced procedures for
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the identification and classification of operational situations of the pipeline/fluid system, and
the elaboration steps for the experimental derivation of fluid properties. The results are also
used for the validation of mathematical models of pressure waves propagation in fluid filled
pipes.
Fig. 1: e-vpms® multipoint vibroacoustic sensing system
CRUDE OIL PIPELINE
Field test setup
From December 2010 we are running a field test campaign of a MAS monitoring system (Fig.
2) in a controlled scenario, where third party interference and leaks have been artificially
produced on a service oil-line, managed by eni r&m division, in the north of Italy (Giunta et
al., 2011b). The monitoring system is deployed along the 100km pipeline: pipe diameter is
16”, oil pressure varies between 70 bars at the pumping station, down to 4 bars at the
receiving terminal, flow rate is about 400 m3/h. Two vibroacoustic monitoring stations are
located at the pipe ends, and two along the pipeline, at an intermediate distance of around
30km. Recorded signals are vibrations of the pipe shell, and pressure variations within the
fluid.
Fig. 2: Satellite map of the oil pipeline route (red line)
and measurement stations (yellow pins)
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Acoustic data analysis
Variations of the pump regime and/or valve regulations produce pressure transients that
travel within the oil. Their propagation is mainly governed by the absorption coefficient and
the sound speed. These parameter are in turn functions of the frequency, the geometrical
and elastic parameters of the pipe shell, the elastic parameters of the surrounding medium,
and the acoustic and thermodynamic properties of the transported fluid. During the
monitoring campaign the pipeline has transported different oils, whose properties are
reported in Tab. 1.
Tab. 1: Oil properties
Property Lower Higher
Density [kg/m3] 750 850
Dyn. Viscosity [cPs] at 15°C 2.00 20.00
We have run a cross-correlation analysis between the pressure variations at the monitoring
stations, and we have obtained the sound velocity within the oil in a six month interval of year
2011: Fig. 3 is the result: it is interesting to notice a clusterization of the measured values
mainly in three operational status, that we relate to three different oil types. Tab. 2 collects
the average numerical values.
Fig. 3: Sound speed (top left) and pressure (bottom left) within the oil in the different
pipe sections. Pressure/speed histogram in the first section (right)
Tab. 2: Measured sound speed and pressure
Pipeline
section
Section
length [km]
Avg. pressure
[bar]
OIL A sound
speed [m/s]
OIL B sound
speed [m/s]
OIL C sound
speed [m/s]
Section 1 27.3 63 1256 1223 1193
Section 2 32 46 1245 1213 1181
Section 3 41 17 1236 1203 1174
We obtain the oil free medium sound speed V0 from the experimental in-pipe velocity V by
inverting the equation (Liu, 2003),
Eh
B2a
1
V
V0
+
=,(1)
where
a: pipe internal radius;
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B: oil bulk modulus;
E: pipe Young modulus;
h: pipe thickness.
Then, we compare the measured acoustic properties with the Batzle and Wang (1992) model
for dead oil at 15°C, and different oil densities
PT1)API(0.360.0115P4.64T3.7API)(77.115450V 0.50.5
0⋅⋅−⋅⋅+⋅+⋅−+⋅= −,(2)
where
API: oil grade;
P: pressure [MPa];
T: temperature [°C].
Fig. 4 is the result: the agreement is very good.
Fig. 4: Pressure-sound speed relation.
Experimental data (dots) and Batzle and Wang 1992 model (B-W).
NATURAL GAS PIPELINE
Natural gas thermodynamic parameters
The wave propagation characteristics for a fluid-guided acoustic wave mainly depend on a
set of physical properties that vary with fluid temperature and pressure. While for a pure
substance it is easy to find in databases all relevant properties at any condition, this can be
difficult for mixtures.
Acoustic wave propagation in pipes filled with gaseous fluids can be modeled with the wide-
tube approximation (Blackstock, 2000). In this case the absorption coefficient α and the
phase velocity cph are provided as functions of the angular frequency ω, the pipe radius a,
and the fluid physical properties (density ρf, speed of sound cf, dynamic viscosity η, specific
heats ratio γ and Prandtl number Pr).
⎟
⎠
⎞
⎜
⎝
⎛−
+= Pr
1γ
1
c2ρ
ωη
a
1
α2
ff
(3)
5
⎟
⎠
⎞
⎜
⎝
⎛−
++
=
+
=
Pr
1γ
1
ω2ρ
η
a
1
1
c
/ωαc1
c
c
f
f
f
f
ph (4)
We compare the properties of pure methane and of two natural gas mixtures (GAS1 and
GAS2), borrowed from laboratory test on gas pipelines transportation (Tab. 3). Both mixtures
are composed of methane for nearly 90%. The principal other components are ethane,
nitrogen, carbon dioxide, propane, and traces of other hydrocarbons.
Tab. 3: GAS1 and GAS2 compositions
Component GAS 1
Vol (%)
GAS 2
Vol (%)
N2 2.2 0.85
C4 88.7 87.5
CO2 1.24 1.96
C2 6.2 8.34
C3 1.3 1.16
i-C4 0.13 0.075
n-C4 0.19 0.093
i-C5 0.038 0.014
n-C5 0.033 0.013
n-C6 0.008
Fig. 5 to Fig. 7 compare the physical properties of the gas mixtures with those of pure
methane as a function of pressure, at a fixed temperature of 10° C. Properties of pure
methane are taken from the NIST database (www.nist.gov), whereas mixtures properties are
computed with the GERG standard equations of state (Kunz et al., 2007).
Fig. 5: Density of pure methane and of natural gas mixtures at 10° C
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Fig. 6: Viscosity of pure methane and of natural gas mixtures at 10° C
Fig. 7: Specific heats ratio of pure methane and of natural gas mixtures at 10° C
We are interested in comparing the propagation parameters, namely the speed of sound and
the attenuation factor, for the various mixtures, at different pressures. We define a new
variable α*, normalizing the wide-tube attenuation coefficient α of Eq. (3) for the pipe internal
radius a, and the frequency f:
⎟
⎟
⎠
⎞
⎜
⎜
⎝
⎛−
+=
⋅
=Pr
1γ
1
cρ
πη
f
aα
α2
ff
* (5)
Measurement unit for α* is HzNp /.
The sound speed in the mixtures is significantly lower than in the pure methane, although the
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pressure where the minimum occurs is approximately the same (Fig. 8).
Sound attenuation (Fig. 9) decreases with pressure mainly due to density increase, but the
difference between pure methane and both mixtures is not relevant.
Fig. 8: Speed of sound in pure methane and in natural gas mixtures at 10° C
Fig. 9: Attenuation constant of pure methane and natural gas mixtures at 10° C
Field test setup at Centro Sviluppo Materiali (CSM)
In this section we analyze experimental measurements collected at Centro Sviluppo Materiali
(CSM) in Sardinia with the aim of estimating the propagation characteristics of acoustic
waves in high pressure gas-filled pipes.
CSM is a full-scale test site endowed with a 535 m long steel pipeline (48” diameter) which
simulates a portion of a natural gas pipeline, in order to study the mechanical properties of
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shell materials in extreme conditions (Demofonti et al., 2005). During one of these tests it
was possible to install on the pipe a set of vibroacoustic monitoring stations and to produce
controlled pressure waves. In particular, together with other sensors, three hydrophones
were placed at the two ends and approximately in the middle of the pipeline (Fig. 10). The
pipe was filled with natural gas with increasing pressure up to almost 130 bars, and pressure
transients were provided by gas spills and hammer strikes on the pipe.
We describe here the experimental estimation of the sound speed at different gas pressures.
Fig. 10: CSM full-scale test pipeline map.
Acoustic wave speed estimation
The speed of sound in the gas was estimated from the hydrophones pressure measurements
during the spilling transients. Spillings were executed at different gas pressure conditions, so
that a trend can be identified in the wave speed-pressure experimental function.
The wave speed estimate is performed in the frequency domain by considering a single
receiver and looking for the resonant frequencies fr. In fact, for a closed pipe of length L,
internal diameter d, filled with a fluid with propagation velocity c, resonance occurs at
frequencies
()
dL
nc
fr6.02 +
=
where n is a positive integer. Identifying the resonance frequencies and inserting the pipe
geometrical parameters we obtain Tab. 4.
Tab. 4: Experimental speed of sound
Spill test Resonant
frequency [Hz]
Wave speed
[m/s]
Gas pressure
[bar]
1 0.365 391 32
2 0.360 386 66
3 0.364 390 89
4 0.373 400 111
5 0.375 402 117
6 0.376 403 120
It is interesting to note that the speed-pressure function is not monotonic, but it has a
minimum at around 60bars. This behavior is in very good agreement with the theoretical
speed of sound computed from the laboratory mixture composition (Fig. 11).
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Fig. 11: Experimental and theoretical speed of sound in natural gas
CONCLUSIONS
Multipoint acoustic/pressure sensing is an emerging technology for pipeline monitoring, for
the remote detection of leaks and third party interference. As a side product, sound
propagation parameters within the transported fluid can be checked versus experimental
constitutive equations, to derive additional information on fluid thermodynamic properties
and/or pipeline infrastructure operational status. We have shown some examples of this
approach on natural gas and crude oil pipelines.
ACKNOWLEDGEMENTS
This research was carried out in the framework of the Project DIONISIO, founded by eni
SpA. The authors are grateful to eni r&m division of Genoa and Ferrera Refinery, to Solgeo
and Centro Sviluppo Materiali team project for technical assistance on pipeline test sites.
REFERENCES
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Resistance of X100 Pipes for Long Distance High Pressure Pipelines” PRCI/EPRG/APIA
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