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Multi String Imaging
EmPulse
White Paper
Andrey Arbuzov, Maxim Volkov,
Sami El Halfawi and Arthur Aslanyan
June 2016
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Contents
1. Physics ......................................................................................................................... 3
1.1. TOOL OPERATING PRINCIPLE AND DESIGN ................................................................................................. 3 1.2. EMPULSE SENSORS .................................................................................................................................. 4
2. Numerical Model and Thickness Calculation ................................................................ 6
2.1. REAL TIME FITTING TECHNIQUE FOR THICKNESS CALCULATION ................................................................... 7 2.2. DELTA PANEL ....................................................................................................................................... 10
3. Laboratory experiments .............................................................................................. 12
3.1. SINGLE-BARRIER CASES ......................................................................................................................... 12 3.2. DUAL-BARRIER CASES ............................................................................................................................ 13 3.3. TRIPLE-BARRIER CASES.......................................................................................................................... 15 3.4. DUAL-STRING CASES .............................................................................................................................. 15 3.5. COLLAR CORROSION EVALUATION ........................................................................................................... 16
4. Well Data Processing and Interpretation .................................................................... 18
4.1. TEMPERATURE DATA CORRECTION ........................................................................................................... 18 4.2. AUTOMATIC COLLAR RECOGNITION ........................................................................................................... 18 4.3. TUBING CORROSION ............................................................................................................................... 19 4.4. CASING CORROSION INSPECTION THROUGH TUBING (2ND METAL BARRIER) ................................................. 21 4.5. SURFACE CASING CORROSION INSPECTION THROUGH TUBING AND PRODUCTION CASING
(3RD METAL BARRIER) ..................................................................................................................................... 21 4.6. INSPECTION OF DUAL-STRING COMPLETION .............................................................................................. 23 4.7. COLLAR CORROSION ............................................................................................................................... 23
5. Well Monitoring ........................................................................................................... 25
5.1. REPEATABILITY ....................................................................................................................................... 25 5.2. CORROSION PROPAGATION ..................................................................................................................... 26
Conclusions ....................................................................................................................... 27
Appendix A. EmPulse technical specifications ................................................................... 28
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1. Physics
1.1. Tool Operating Principle and Design
The Magnetic Imaging Defectoscope EmPulse is a slim downhole tool designed to scan
metal around its sensors. The tools are run through the tubing to detect metal loss due to
corrosion or other factors and to monitor perforation quality.
The downhole EmPulse Defectoscope is currently represented by two modules:
EmPulse-2 for scanning the first two metal barriers of 2 7/8" to 13 3/8" size
EmPulse-3 for scanning up to 18 3/8" casing
Fig. 1. EmPulse-2 and EmPulse-3 modules
Combined toolstring contains three co-axial sensors of different lengths: the short 5" sensor
(EmPulse-2), the medium 13" sensor (EmPulse-2) and the long 19" sensor (EmPulse-3)
(see fig. 1). Each of these sensors is a generating-and-receiving electromagnetic coil wound
on a core. The receiving and generating coils are placed together to avoid ghost effects from
defects and well completion components. Those coils alternately generate electromagnetic
excitation pulses. The speed of decay of a response pulse is governed by the properties of
the tubing and casing surrounding the tool. Metal loss due to corrosion causes a faster
decay.
Fig. 2. Generating and receiving coils
5” Short sensor
13” Medium sensor
19” Long sensor
EmPulse-2 EmPulse-3
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The short receiver coil records a short time response sampled in 42 channels, scanning the
near zone where only one barrier is present, which is normally a tubing string. The medium
coil generates a separate electromagnetic pulse and records a longer response sampled in
51 channels. The long coil records the longtime response sampled in 83 channels. That
coils scan a larger distance of up to 14 inches and up to 20” respectively and capture a
combined response from tubing and casings. Further mathematical processing enables the
identification of an independent casing response. As an example, fig. 3 shows excitation
pulse and decay of response pulse for medium sensor.
Fig. 3. Excitation pulse and decay of response for medium sensor
1.2. EmPulse Sensors
The response duration in vacuum defines the tool's dead time and depends on the relaxation
time of the coil. The faster the coil's relaxation, the faster the tool can detect an informative
response of the metal component.
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The relaxation time of the EmPulse coil is approximately 0.1 ms, which is shorten than in
most of conventional defectoscopes. The last one can only start recording after 4 ms from
the start of the decay as it represents the response of the coil but not of the surveyed well.
As a result, the application of conventional defectoscopes is limited and scanning of chrome
pipes is challengeable because the time response of non-magnetic steel equals the typical
coil relaxation time of a conventional defectoscope. Moreover, information about the first
metal barrier will be partially lost.
Fig. 4. Responses detected by EmPulse (blue line) and conventional defectoscope (green line) in vacuum and EmPulse decays in the stainless (black line with red points) and in the ferromagnetic (black line with blue points) steel pipes.
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2. Numerical Model and Thickness Calculation
The EmPulse simulator is a software used for calculating simulated decays of the tool and
the well. Comparison of simulated decays with actual responses enables the calculation of
wall thicknesses of the first, second, third and even fourth barriers independently (see
Section 2.1).
In fact, calculation of the system response to magnetic disturbance is reduced to calculation
of the magnetic field near the receiver coil. The electromagnetic field shape is described by
the following two Maxwell’s equations,
.0)(,)(
,)(,)(
Bdivt
DjHrot
Ddivt
BErot
(1)
Using additional constitutive relations and Ohm`s law:
(2)
The problem can be simplified to a homogeneous piecewise medium with coaxially
cylindrical boundary surfaces, and the receiving coil is mounted concentrically over a core.
It is assumed that electromagnetic parameters (electrical conductivity σ and magnetic
permeability μ) are constant within the same medium. The solutions of Maxwell’s equations
(1) in terms of frequency are reduced to iteration problems of field calculation in each
medium in such case.
Fig. 5. Axially symmetric model of a tripple-barrier completion
Note that response parameters (amplitude and decay time) are usually defined by geometric
parameters (radius and d – wall thickness) and electromagnetic parameters (μ and σ) of
casing and tubing pipes and depend on the parameters of other media. Therefore, decay
.,, 00 EjEDHB
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time can be roughly represented as a d·μ·σ multiplication; the thicker the pipe wall, the
longer the response decay time.
2.1. Real Time Fitting technique for Thickness Calculation
Real Time Fitting (RTF) algorithm has been developed to determine the thicknesses of up
to four coaxial metal barriers. The calculation procedure can be divided into three stages:
Calculation of simulated responses for different parameters of the surrounding
medium;
Estimation of electromagnetic parameters of the surrounding medium;
Estimation of barrier thickness in relation to depth.
The response is a function of electrical conductivity σ, magnetic permeability μ and the
geometric parameters of the surrounding media. It is assumed that the response is entirely
determined by the metal completion components and is almost independent of the
surrounding rocks and fluid. This assumption is confirmed by the great difference between
the electromagnetic characteristics of metals, rocks and fluid. Therefore, electrical
conductivity, magnetic permeability and tubing/casing thickness are the only variables.
Other parameters are assumed to be constant.
The simulated decays are used to calculate tubing/casing parameters (μ and σ) and estimate
their thicknesses. The parameters are being fit to minimize the discrepancy between
simulated and measured responses. For more precise thickness estimation, the simulated
decays are interpolated with the μ and σ values. Then, simulated decays are selected for the
corresponding actual decays at each depth to produce tubing/casing thickness profiles, such
as those shown in fig. 6.
Fig. 6. Comparison of actual and simulated decays
It can be clearly seen in fig. 6 how pipe thickness affects decay time: changes in tubing
thickness affect the total signal, while a change in casing thickness only affects the total
signal at late times.
The example displayed in fig. 7 shows the application of the algorithm for calculating
thicknesses of both tubing and casing from the recorded data. Average tubing and casing
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thicknesses appeared to be 7.8 mm (13.5 lb/ft) and 12 mm (47 lb/ft), respectively,
corresponding to the nominal pipe thicknesses. It can be seen that the tubing integrity is
good and casing corrosion can be seen at a depth of X118 ft.
Fig. 7. An example of thickness calculation for a two-barrier completion. Nominal thicknesses are shown as dashed lines.
Corrosion detection in multi-barrier wells is time-consuming, and data processing time
increases many-fold with the number of barriers. Thus, the number of modelled decays for
one well in the three-barrier case under study can reach hundreds of thousands. To reduce
the time of processing and interpreting data from a typical three-barrier well to several hours,
a new algorithm has been developed for a supercomputer that can operate remotely and
can be accessed from a normal computer through the Internet.
Fig. 8 presents findings acquired in a 9 5/8″ OD pipe having the wall gradually reduced in
thickness. The raw data distinctly show uniform metal loss. The casing thickness calculated
by the thickness calculation algorithm RTF corresponds strictly to the wall thickness
measured.
Similar results are demonstrated for a 3 ½’’ tubing with gradually reduced wall thickness on
fig. 9.
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Fig. 8. Findings in a 9 ⅝″ pipe gradually reduced in size. From left to right: picture of the pipe, depth scale, pipe schematic, FAR RESPONSE 35 log (27.4 ms), calculated THICKNESS log.
Fig. 9. Findings in a 3 1/2″ pipe gradually reduced in size. From left to right: picture of the pipe, depth scale, pipe schematic, NEAR RESPONSE 27 log (8.66 ms), calculated THICKNESS log.
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2.2. DELTA Panel
The EmPulse set of data can contain more than 176 channels: 42 short sensor logs + 51
medium sensor logs + 83 long sensor logs + logs from auxiliary gauges like temperature,
acceleration etc. It is impossible to visualise and analyse all of those logs simultaneously in
a conventional way. One can visualize logs as coloured DELTA panels, where y-axis is
depth, x-axis is time and colour is amplitude (blue – high amplitude, red – low amplitude).
The informative DELTA panel shows differences between simulated and real responses.
The difference between the Short Sensor recorded and simulated responses called SS
DELTA, for Medium Sensor – MS DELTA and for Long Sensor it is LS DELTA. This panel
provides sharper image contrast and shows metal losses in finer detail.
mod
mod
( ) ( )( )
( )
R el
el
U t U tt
U t
. (3)
Fig. 10. The DELTA panel – basics
The panel shows good match with the model in white and mismatches in colours (see, e.g. fig. 12-17).
The raw response greater than the simulated response is shown in blue. The underrated raw response
is shown in red. At all depths where well completion has a perfect axial-symmetric geometry, the
DELTA panel is white.
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In most cases DELTA panel is white. In other cases, it develops a colour pattern at some
events, for e.g. tubing collars at X600 ft, X632 ft and X662 ft and casing collars at X612 ft
and X650 ft (see fig. 11).
Fig. 11. Colour DELTA panels
The coaxial model does not account for non-coaxial elements, such as tubing/casing holes,
valves, mandrels, perforations, etc, which all appear to be circularly smeared (azimuthally
averaged) and do not indicate real thicknesses.
For example, a 1-inch hole in 3 1/2-inch tubing is not axially symmetric. The coaxial model
does not understand this and reports 1% circumferential metal loss per foot (which is
equivalent in volumes to 1-inch hole in 3 1/2-inch tubing within the sensor length) and thus
can be easily overlooked in the thickness log. But the DELTA panel clearly shows that model
and raw responses do not match.
Note that DELTA panel has nothing to do with the amount of metal loss/gain. Thickness log is the only
curve which relates to the amount of metal loss/gain.
42
channels
51
channels
91
channels
Short
Sensor
Middle
Sensor
Long
Sensor
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3. Laboratory experiments
The EmPulse tool sensitivity to different types of wall metal loss (holes, transverse and
longitudinal fractures) was studied using pipes with known dimensions and defects in the
laboratory. This section describes some of the results.
3.1. Single-Barrier Cases
A pipe with an outside diameter of 3 1/2" and a wall thickness of 5.2 mm was surveyed. Two
defects were made in the pipe: a 35-mm longitudinal slot and a 20-mm hole. Fig.12 shows
the survey results. The hole and the longitudinal slot displayed in the DELTA panels of both
the short (SS DELTA) and medium (MS DELTA) sensors as red areas at middle times (3.5–
17.8 ms). The defects are seen in the thickness log, but average metal loss, for example in
the case of a through hole, is only 0.2 mm. For that reason, small defects can be over looked
in the thickness log but will be clearly shown in the DELTA panels.
Fig. 12. The results of a single-barrier laboratory test: picture of the pipe, depth scale, pipe sketch, the DELTA panels of the short (SS DELTA) and medium (MS DELTA) sensors, calculated pipe wall thickness (3 1/2" TUBING Thickness 1) with nominal pipe wall thickness (dashed line)
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Similar findings were recorded for a 2 7/8’’ tubing with flaws shaped as a vertical slot 38 mm
in length and a 38-mm square hole (fig. 13)
Fig. 13. The results of a single-barrier laboratory test: picture of the pipe, depth scale, pipe sketch, the DELTA panels of the short (SS DELTA) and medium (MS DELTA) sensors, calculated pipe wall thickness (2 7/8" TUBING Thickness 1) with nominal pipe wall thickness (dashed line)
3.2. Dual-Barrier Cases
A study of a dual-barrier completion was conducted with the following configuration: the first
pipe has a diameter of 3 1/2" and a wall thickness of 7 mm; the second pipe has a diameter
of 9 5/8" and a wall thickness of 9.5 mm. Two defects were made in the second pipe: a 125-
mm (5-inch) longitudinal slot and a hole of 80-mm (3-inch) diameter. Fig.14 shows the study
results. No defects are displayed in the short sensor panels. The defects are displayed in
MS DELTA panel of the medium sensor as a red area at late times (40–100 ms), marked by
casing corrosion line (CL2). The defects are also seen in the thickness log (see Fig. 14).
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Fig. 14. The results of a dual-barrier laboratory test: pipe picture, depth scale, pipe sketch, the DELTA panels of the short (SS DELTA) and medium (MS DELTA) sensors, calculated pipe wall thickness of the first and second barriers (3 1/2" TUBING Thickness 1 and 9 5/8" CASING Thickness 2) with nominal pipe wall thickness (dashed lines).
Similar results were obtained for a dual-barrier completion: a 2 7/8’’ tubing with a collar and a 5 1/2’’ casing with a 90-mm square hole (Fig. 15)
Fig. 15. The results of a dual-barrier laboratory test: pipe picture, depth scale, pipe sketch, the DELTA panels
of the short (SS DELTA) and medium (MS DELTA) sensors, calculated pipe wall thickness of the first and
second barriers (2 7/8" TUBING Thickness 1 and 5 1/2" CASING Thickness 2) with nominal pipe wall thickness
(dashed line).
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3.3. Triple-Barrier Cases
Fig. 16 shows the results of an EmPulse laboratory test performed to detect defects in the
third barrier. The testing unit simulated a typical well with three metal barriers: 3 1/2" tubing,
9 5/8" production casing and 13 3/8" intermediate casing. An artificial defect in the third
barrier, a 7 1/2" hole, simulated a homogeneous metal loss of 8.8% per foot of pipe. This
laboratory test conducted using the long 19" sensor of the EmPulse-3 tool confirmed the
defect (see the LS DELTA data panel in fig. 16). It is seen that the maximum deviation of
the recorded decay from the modelled one, shown as a red spot, occurred at the defect's
centre and was crossed by the CL3 corrosion line determined by modelling, which
demonstrates the accuracy of this technique. According to the simulation, the defect size
was equivalent to a metal loss of 6.8% per foot, i.e. within 2% error relative to an actual
value of 8.8%.
This lab test illustrates that the tested algorithm could provide accurate metal loss estimates
and confirmed the accuracy of the barrier thickness calculation
Fig. 16. The results of a triple-barrier laboratory test: depth scale, the pipe sketch, the DELTA panel of the
long sensor (LS DELTA), calculated pipe wall thickness of the first, second and third barriers (3 1/2" TUBING
Thickness 1, 9 5/8" CASING Thickness 2, 13 3/8" CASING Thickness 3) with nominal pipe wall thickness
(dashed line)
3.4. Dual-String Cases
Described below laboratory test was conducted to examine the performance of the EmPulse
technique in calculating the thickness of the third barrier for wells with parallel tubing strings.
For this purpose, the test unit was equipped with two inner 3 1/2" pipes, I and II, and two
Metal loss detected in
13 3/8” Casing
6.8%
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outer 9 5/8" and 13 3/8" pipes. An artificial defect, a 7 1/2" hole, was made in the third barrier
to simulate a homogeneous metal loss of 8.8% per foot (see fig. 17).
The defect in this 13 3/8" pipe appeared in the LS DELTA data panel and was intersected
by the CL3 corrosion line. Metal loss was calculated at 7.1% per foot of pipe, which agreed
well with an actual value of 8.8% per foot.
It should be noted that this defect in the third barrier did not affect thickness calculations for
the second barrier and inner pipes. This primarily indicates that the tested modelling-based
thickness algorithm performs well even for dual-string wells
Fig. 17. The results of a triple-barrier with dual-string laboratory test: depth scale, the pipe sketch, the DELTA
panel of the long sensor (LS DELTA), calculated pipe wall thickness of the first, second and third barriers (3
1/2" TUBING Thickness 1, 9 5/8" CASING Thickness 2, 13 3/8" CASING Thickness 3) with nominal pipe
wall thickness (dashed line)
3.5. Collar Corrosion Evaluation
EmPulse technique allows an estimation of collar joint corrosion. The 4 1/2” tubing with walls
6.2 mm thick was subjected to inspection. Holes 0.5” in size were drilled around the collar
joint. Fig. 18 depicts logs of the short sensor for different corrosion degrees of the collar
joint. As shown in fig. 18, the amplitude of corroded collar is less than the amplitude of non-
corroded one.
7.1%
Metal loss detected in
the 3rd barrier
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Fig. 18. The results of a collar corrosion laboratory test: depth scale, pipe sketch, and raw logs for different corrosion degrees of the collar joint.
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4. Well Data Processing and Interpretation
Processing and data interpretation of EmPulse data are performed in special software that
implements EmPulse technique algorithms and includes many features to provide Clients
with high-quality row data and final interpretation reports within short time period. This
chapter describes some specific abilities while data processing and interpretation
4.1. Temperature data correction
The response amplitude of the same metal pipe can be different that is can be caused by
temperature variations. The temperature effect on the data should be accounted.
Empulse tools are equipped with temperature sensor and software filters applied allows to
eliminate temperature impact. Fig. 19 shows results of temperature correction. As it can be
observed, response deviation caused by temperature rise is removed.
Fig. 19. Temperature correction. Logs in red are before correction, logs in blue – after.
It is worth to mention, that temperature influence reduces on the logs for channels with later
times.
4.2. Automatic collar recognition
Increase of metal thickness caused by collar joint significantly enlarges a duration of
response decay. As a result, collars are reflected on channel logs as high-amplitude peaks.
Tubing collars forming first barrier can be nearly always identified as it can be observed in
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fig.20. Casing collars of second barrier can be revealed on the logs for channels with later
times.
Automatic collar recognition algorithm allows to define tubing and casing collars with
accuracy of 1% and 5% respectively
Fig. 20. Automatic collar recognition for tubing (blue points) and for casing (green points)
4.3. Tubing Corrosion
Heavy corrosion of the tubing that has created a hole is displayed in the NEAR DELTA panel
in red (see Fig. 21). This is because the corrosion response is of higher amplitude at early
times and of lower amplitude at late times – since smaller amounts of metal allow rapid
signal changing, i.e. corrosion response increases and then decreases sharply – as shown
in an inlay plot in fig.21.
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Fig. 21. Tubing corrosion
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4.4. Casing Corrosion inspection through tubing (2nd metal barrier)
Casing corrosion detected through the tubing is not displayed in the NEAR DELTA panel,
but is displayed in the FAR DELTA panel at late times in red due to its lower amplitude (see
fig. 22). Corrosion is also seen in the thickness log. The spectral noise captured the noise
from channelling and entering the annulus at a corrosion zone of 17% metal loss suggesting
an integrity problem.
Fig. 22. Casing corrosion detected through tubing and confirmed by Spectrum noise logging.
4.5. Surface casing corrosion inspection through tubing and production
casing (3rd metal barrier)
9 5/8” and 13 3/8” casings corrosion zones of 52% and 73% metal loss accordingly were
detected downhole through the tubing and were confirmed by a surface visual inspection.
The corrosion behaviour suggests the external corrosion development due to poor
cementing and aggressive influence of sea water at a splash zone.
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Fig. 23. Severe Corrosion detected in 9 5/8” and 13 3/8” casings at the splash zone depth in offshore oil producer.
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4.6. Inspection of dual-string completion
In general, processing of EmPulse data for dual-string completions is the same as for single
tubing configuration. The presence of second tubing can slightly increase decay time that
should be taken into account while interpretation. Fig. 23 shows the corrosion identified in
second barrier in triple-barrier dual-string completion.
Fig. 24. Casing corrosion in double-string completion
4.7. Collar corrosion
Fig. 25 shows an EmPulse tool-detected corrosion of a collar joint at X592 m with a 53%
corrosion degree. PLT data, along with water holdup, density and high precision temperature
data, reveal inflow from the leaking tubing collar. The result proves that this is a through
corrosion of that collar.
9 5/8” Collar
3 1/2” SS Collar
13 3/8” Collar
13 3/8” Collar
3 1/2” LS Collar
Corrosion Zone
15%
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Fig. 25. Corroded tubing collar confirmed by production logging tool.
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5. Well Monitoring
Corrosion in wells develops over time and affects both their performance and operating
safety. Time-lapse corrosion monitoring data are used to improve pipe material selection
and enhance downhole inhibitors, as well as to find out the causes of corrosion and
understand its mechanisms. Systematic corrosion monitoring minimizes workovers and
extends the life of a completion string and, therefore, improves well and field economics.
This chapter shows that the EmPulse technology can detect corrosion at an early stage.
5.1. Repeatability
The EmPulse technology provides a high signal-to-noise ratio, which makes EmPulse logs
highly repeatable. Fig. 26 shows time lapse analysis of logs of the short and medium sensors
recorded by two EmPulse surveys in one well in 2009 and 2010. After automatic depth data
matching, the two logs appear to be virtually identical even at late times when the signal
decays significantly.
Fig. 26. The 2009 and 2010 logs recorded by the short and long sensors
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5.2. Corrosion Propagation
Fig. 27 shows the corrosion development in the tubing of high rate oil-producer with a
relatively high H2S of more than 10%. Because of the high flow rate, H2S content and
possibility of corrosion, the decision was made to conduct a baseline metal loss survey and
another survey a year later.
Two EmPulse surveys were conducted to monitor metal loss in the 3-½", 9-5/8" and 13-3/8"
casings: the first survey in 2015 and the second one a year later in 2016. The first survey
was conducted in the newly set strings of a well that was just put on production, and its
results were used as baseline data to highlight the API thickness tolerated joints and to
improve the accuracy of metal-loss determination.
The second survey, conducted a year later, showed no metal loss in both tubing and casing.
This finding suggested good inhibitor selection by the Customer. The 3-½" tubing also
showed good data repeatability in most of the surveyed interval, but three joints lost more
than 20% of metal (see the fig. 27), which indicated problems with the tubing material.
Fig. 27. Corrosion propagation: depth scale, well sketches, the 2009 (red line) and 2010 (blue line) logs recorded by the short sensor, and the NEAR VARIATION colour panel
Based on the survey results, the Customer implemented a time-lapse monitoring plan in the
field to gather information on casing corrosion and monitor inhibitor performance. They also
analysed and changed the tubing metallurgy to avoid premature workovers.
It can thus be concluded that well monitoring significantly improves EmPulse data
interpretation. As a result, even a slight corrosion can be easily detected.
27 % metal loss in 3 ½”
TBG
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Conclusions
The key advantages of the magnetic imaging defectoscopy EmPulse presented in this paper
can be summarised as follows.
1. The EmPulse tool containing three sensitive sensors records responses in a wide time
range digitized by 178 channels. Those characteristics allow the analysis of non-
magnetic chrome alloy steel pipes and detection of corrosion at an early stage.
2. Analysis of the decay pattern in a wide time range can determine metal thickness at
various distances from the tool and, thus, the individual wall thicknesses of the first,
second, third and fourth metal barriers, such as tubing and casings including dual-string
completions.
3. Algorithms developed for EmPulse data processing enable reliable identification of all
completion components as well as automatic location of collars in the barriers. The
software allows fast and reliable interpretation of large well data sets.
4. This technology has been tried and tested in laboratory studies, customer yard tests and
field tests and was proven effective in well data analysis.
5. Good repeatability of data and low data noise together with automatic data correlation
algorithms open up new possibilities for well monitoring using the magnetic imaging
defectoscopes EmPulse.
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Appendix A. EmPulse technical specifications
Pressure rating 14 500 psi (100 MPa)
Temperature rating 302 °F (150 °C)
H2S < 30%*
Maximum wall thickness of single barrier 0.6 in (16 mm)
Maximum total wall thickness of dual barriers 1 in (25 mm)
Maximum total wall thickness of triple barriers 1.5 in (38 mm)
Barrier thickness accuracy
First barrier
±3.5% (±0.01 in or ±0.25 mm for
3 1/2’’ tubing with 7 mm wall
thickness)
Second barrier
±6% (±0.03 in or ±0.75 mm for
9 5/8’’ casing with 12 mm wall
thickness)
Third barrier
±12% (±0.06 in or ±1.5 mm for
13 3/8’’ casing with 12 mm wall
thickness)
Fourth Barrier
±30% (±0.14 in or ±3.6 mm for
13 3/8’’ casing with 12 mm wall
thickness)
Pipe OD range (1st barrier) 2 – 18 5/8 in
Pipe OD range (2nd barrier) 4 1/2 – 18 5/8 in
Pipe OD range (3nd barrier) 7 – 18 5/8 in
Maximum continuous recording time 48 hrs
Recommended logging speed 6.6-19.7 ft/min (2-6 m/min)
OD 1 11/16 in (42 mm)
Length 11.5** ft (3.5** m)
Weight 41** lb (18.5** kg)
* In wells with H2S concentration up to 30%, if O-Rings TFE/P L 1003 (Aflas) Black Duro 90 are
installed.
All materials used in the external parts meet the requirements of NACE TM 0177-2005 and NACE
TM 0284-2011.
** With RC-3 centralisers (2 pcs)
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