draft - tspace.library.utoronto.ca€¦ · porosity, rock fluid pressure (dowell et al. 2006)....

Draft

Simulation and Experiment of Vibrational or Acoustic Communication in Mining and Oil-Gas Drill Strings

Journal: Transactions of the Canadian Society for Mechanical Engineering

Manuscript ID TCSME-2018-0227

Manuscript Type: Article

Date Submitted by the Author: 17-Oct-2018

Complete List of Authors: Islam, Md Shahriar; University of Saskatchewan, Mechanical Engineering DepartmentPeter, Nathan; Saskatchewan Research Council, Development Engineering and ManufacturingWiens, Travis; University of Saskatchewan, Mechanical Engineering Department

Keywords: vibration, frequency response, drill pipe, transmission line, tonpilz

Is the invited manuscript for consideration in a Special

Issue? :2018 CSME International Congress

https://mc06.manuscriptcentral.com/tcsme-pubs

Transactions of the Canadian Society for Mechanical Engineering

Draft

1

Simulation and Experiment of Vibrational or Acoustic Communication in

Mining and Oil-Gas Drill Strings

Md Shahriar IslamMechanical Engineering Department,University of Saskatchewan,[email protected], SK, S7N 5A2, CAN

Nathan Peter Development Engineering and Manufacturing,Saskatchewan Research Council, Saskatoon, SK, [email protected]

Travis Wiens Mechanical Engineering Department,University of Saskatchewan, Saskatoon, SK, S7N 5A2, [email protected]

Page 1 of 21



mailto:[email protected]



Draft

2

Simulation and Experiment of Vibrational or Acoustic Communication in

Mining and Oil-Gas Drill Strings

Md Shahriar IslamMechanical Engineering Department,University of Saskatchewan,[email protected], SK, S7N 5A2, CAN

Nathan Peter Development Engineering and Manufacturing,Saskatchewan Research Council, Saskatoon, SK, [email protected]

Travis Wiens Mechanical Engineering Department,University of Saskatchewan, Saskatoon, SK, S7N 5A2, [email protected]

Abstract: Drilling for exploration and mineral extraction purposes is generally an invisible process, that is, there is a lack of real-

time information available from the tool head. The borehole mining and oil-gas drilling industries both face tremendous challenges

because of this invisibility. Lack of data has impacts on extraction quantity and quality, process efficiencies, and is a major factor

in overall program costs. This is why a communication method between the drill head and the surface has been under research.

Different communication methods have enabled industries to establish more control over the drill bit. Low data transmission rate is

one of the most concerning drawbacks of existing communication methods. Acoustic, also known as vibrational telemetry is the

most recent method used in transferring data through drill pipe at the highest data transmission rate. A proper use of acoustic tools

and communication scheme will successfully establish a fast data transmission rate and is expected to become a popular method.

This paper will introduce a simulation model for transmission of data through drill pipes and will extrapolate a practical case of a

large number of pipes that is usual in oil-gas extraction. It will also demonstrate an experimental set-up of a new acoustic transducer.

Keywords-acoustics; vibration; drill pipe; tonpilz; transducer; transmission line; communication; frequency response;

Page 2 of 21






Draft

3

1. INTRODUCTION

It is a major challenge in the drilling industry to explore and extract fossil fuel and minerals, because this is done

underground without knowing the lithography of the earth. So, different sensors are installed at the drill bit to acquire data from

these sensors while drilling. This process is commonly known as measurement while drilling (MWD). This process is mostly favored

when the data is acquired in real time. If it is possible to transmit data to the surface instantaneously then the controller at the surface

gains better control over the drill bit. In the case of borehole mining, it is also favorable to transmit large volumes of data, such as

even video, which will essentially make the drilling process a visible one. In addition, the drilling operation involves large

assemblies of equipment, complex well patterns, long operation times, high costs etc. The initial goal of the communication method

is to determine ore location, drilling orientation, properties of rock, dimensions of cavity and other parameters using sensor data

assembled in the borehole assembly (BHA). This data is then transmitted to the surface from the wellbore. The acquired data will

then be used to plot the three dimensional path in front of the drill bit that will help the operator to measure the trajectory of the hole

as it is drilled. Also, the MWD downhole tools allow the wellbore to be directed in a chosen direction, therefore known as directional

drilling. Using different gamma ray sensors the properties of the rock can be determined that help decide about the drilling direction

(Arps et al. 1964). There are several other sensors installed depending on the drilling application to acquire information on density,

porosity, rock fluid pressure (Dowell et al. 2006).

There have been four major communication methods used until now for data transmission from the drill bit to the surface.

These are cable operated communication, mud pulse telemetry, vibration telemetry and electromagnetic communication (Franconi

et al. 2014). Among these different methods, the most popular is mud pulse telemetry (MPT), which is also the first method to

become formally proposed in the industry from early 1929s (Hughes 1997). The cable operated communication method is not

convenient because it requires customized drill strings where coaxial cables are attached inside the drill strings (Bybee 2008).

Moreover, the coaxial cables block the flow of the drilling fluid which is undesirable. The electromagnetic (EM) communication

method is also not convenient because the earth’s geological properties are unknown that attenuate the signal (Chew 1995; Li 2009).

The EM also consumes a lot of power which is a concern because it has to run on batteries. The MPT is a method of continuous

wave propagation where drilling fluid is the medium of propagation. This method has been popular because of its easy

implementation, however, it has the issue of slow data transmission that raises because of different attenuating factors. The

attenuation occurs mostly due to the medium itself which is a viscous liquid that dampens the pressure wave. The properties of the

drilling fluid or mud change along with the well depths which affects the pressure pulse. The properties of the drilling mud also

change based on the application it is used for. The non-homogeneity of the mud fluid itself affects the wave propagation and

Page 3 of 21



Draft

4

attenuates the signal. Oil based drilling fluids with high plastic viscosity (PV) and high density attenuate the signal more (Shen et

al. 2009). Moreover, high frequency noise is generated because of its vibration that blocks the pressure pulse significantly.

Sometimes buffers and dampeners are used on the surface and inside of the pipes to reduce noise caused by the mud pump and from

other sources. However, while they absorb noise and pressure fluctuations, they also reflect pressure pulses back to the signal

actuator, which can totally damage the signal received by the sensor (Klotz et al. 2008). The location of the sensors at the surface

also attenuates the signal. This is why mounting the sensor at the right location is a very important task. Moreover, this method is

only applicable when the drilling fluid is running. Its data transmission rate is slow on the scale of 1-10 bits per second (Franconi

et al. 2014). This is why exploring other methods such as communication via structural vibration have become necessary, since it

offers a faster data transmission rate (Franconi et al. 2014).

Vibrational or acoustic telemetry uses the drill pipe itself as a medium of wave propagation. It has a similar theoretical

wave propagation concept to that of mud pulse telemetry but uses piezo-electric transducers to generate a stress wave in the pipe

rather than in the fluid within the pipe. This pressure wave can be picked up at the other end of the drill string using any vibrational

sensor. The information picked up by different sensors on the drill head are converted into digital data. The data is then broadcast

by the transducers as vibration or acoustic wave through the drill strings. The transducer generates this vibration within the steel

drill string by means of a high frequency ferroelectric ceramic piezoelectric material with the combination of two different masses

(Islam et al. 2017). This method can give faster data rates up to 100 bits per second (Drumheller et al. 1989). Although the vibrational

method was introduced previously, because of the lack of an efficient transducer the method was not popular. Nowadays, the

piezoelectric ceramic technology has become more advanced so the method of acoustic telemetry is beginning to gain commercial

popularity (Dias et al. 2014; Haddad et al. 2017; and Kreuzer et al. 2014). In acoustic telemetry, the medium of pressure wave

transmission is the solid steel pipe rather than viscous liquid as in mud pulse telemetry, so it has less attenuating factors. For the oil

and gas applications, the attenuation for acoustics systems varies from 2-10 dB/1000 feet and up to 30 dB/1000 feet if the pipe is

badly worn (Cox et al. 1981). Drumheller (1989 and 2003) has done a lot of theoretical and experimental work of wave propagation

through drill strings, concentrating on the effect of the characteristic impedance mismatch at the collars connecting the pieces of

drill pipe.

In this paper a simulation model will be demonstrated that can account for any types of drill string along with the transmitter

and receiver for wave propagation. The simulation model will be verified by experimental data, which will justify the model. A

simulation model will be a convenient approach to understand the characteristics of the pipelines for different applications, which

include the attenuation and frequency shifting of the system. The drill pipes used in the mining industry are different in sizes than

the pipes used in the oil-gas application along with different drilling fluid, length of the depth of extraction etc. Also, the mining

Page 4 of 21



Draft

5

method is different in that it has a lower noise level than the oil-gas drilling. So, the attenuation will be less in the mining application.

This gives a tremendous opportunity of achieving fast data transmission rate in the mining industry.

The paper will also investigate the cases of a large number of pipes. For future work, this will lead to the optimization and

modification of the transducer and sensors to be used with any specific application. A unique way of characterizing the system will

be demonstrated here. If the frequency response of the system is known then a particular communication scheme can be chosen

beforehand which can employ different frequency contents. The knowledge gained form different tests will help achieve

understanding wave propagation for different cases. This will also help implement sophisticated communication scheme that outputs

fast data transmission.

The paper will also demonstrate the manufacturing and tests of a new transducer. The tests result of the new transducer

will be compared with the existing transducer.

2. SIMULATION MODEL

This section will demonstrate the simulation model and the fundamental theories behind the model.

2.1.Mathematical Model of Transducer

A piezoelectric transducer is an electromechanical device that converts mechanical energy into electrical energy or vice versa.

For this research, a Tonpilz-type sonar transducer is used. A lot of previous research has been performed on the design of an effective

transducer (Baylis 1998).

The governing equations of piezoelectric ceramics are the combination of mechanical and electrical characteristics. The

constitutive relations are usually known as piezoelectric equations that apply the theory of piezoelectricity shown in the equation

(1) and (2). The equations describe the interaction effects of stress, strain, electric displacement, and the electric field. For the case

where the strain and electric fields are approximately uniform, the mass of the piezoelectric material can be assumed negligible, and

the amount of free charge is small. Then the constitutive equations are (Sherman et al. 2007)

(1) S = sE T + dt E(2) D = d T + ε TE

where T is the stress, S is the strain, E is the electric field, and D is the electric displacement. All of these variables are functions of

position and time, where T and S are both symmetric second rank tensors. In these equations, S and T are 6×1 column matrices, E

and D are 3×1 column matrices, sE is a 6×6 matrix of elastic compliance coefficients, d is a 6×3 matrix of piezoelectric coefficients

(dt is the transpose of d), and εT is a 3×3 matrix of permittivity coefficients (Berlincourt et al. 1964).

Page 5 of 21



Draft

6

To create a simple but effective simulation model the constitutive equation of the piezoelectricity is linearized and justified by

Sherman et al. (2007). Equations (1) and (2) may be rewritten in terms of the variables force, , displacement, , charge, , and 𝐹 𝑥 𝑄

voltage, , which models an idealized piezoelectric ceramic bar of area, , and length, , with a voltage across the length. Thus 𝑉 𝐴 𝐿 𝑉

we have , , , and Equations (1) and (2) become 𝑥 = 𝑆 𝐿 𝐹 = 𝑇 𝐴 𝑄 = 𝐷 𝐴 𝑉 = 𝐸 𝐿

(3) 𝑥 = 𝐶𝐸𝐹 + 𝐶𝐸𝑁𝑉(4) 𝑄 = 𝐶0𝑉 + 𝑁𝑥

where the short-circuit compliance is , the clamped (or “blocked”) capacitance is and the electromechanical turns 𝐶𝐸 =𝑠𝐸

33𝐿𝐴 𝐶0 =

𝜀𝑆33𝐴𝐿

ratio is 𝑁 = 𝑑33𝐴𝑠33𝐿

A Tonpilz type transducer is considered as a simple mass-spring-damper model where piezoelectric stack materials are placed

between the head mass and tail mass as shown in Figure 1.

The equations to represent the mass spring systems are:

(5) 𝐹𝑠 = 𝐾𝑥(6) 𝐹𝑑 = 𝐷

𝑑𝑥𝑑𝑡

(7) 𝐹𝑡 = 𝑀𝑡 𝑑2𝑥

𝑑𝑡2

(8) 𝐹ℎ = 𝑀ℎ 𝑑2𝑥

𝑑𝑡2

where K is the stiffness coefficient of the threaded rod, D is the overall damping coefficient because of threaded rod and piezo

ceramic stack. The force applied by the piezoelectric material can be found from the equation (3) and (4).

2.2.Simulation Model of Transducers Coneected Face to Face

Figure 2 is the diagram of the of the transducer for a simulation model when they are connected face to face, one being a driver

transducer and another being a receiver transducer. The mathematical model is developed using the fundamental equations shown

in previous section.

The experimental set-up of two transducers connected face to face using two bolts is explained in Section 3.1. The rubber sheet

at the face of the transducers are squeezed one over another which is represented in the model as spring damper connection. A very

small dummy mass (.0003 kg) is imagined in between these two rubber sheets, is for the convenience of calculation. The dummy

mass here is also connected with the ground through a damper which should neutralize any effect that it may have in the system.

The tail mass of the two transducers are imagined to be connected with a reference position through a spring-damper connection.

This is also for the sake of calculation in the simulation. These spring-damper connections do not affect the overall performance of

the transducers, because the tail mass is considerably higher so it works as a reference. The transfer function model of the transducer

Page 6 of 21



Draft

7

connected face to face obtained from the free body diagram of each of the component of this figure and equations, will later be used

for curve fitting to find effective parameters of the transducer.

2.3.Pipeline or Drill-String

To model the drill string, a transmission line model is used in this research which is commonly used in fluid flow applications.

The transmission line model was initially developed by Krus et al. (1994) and is based on the assumption of a four pole equation.

The approximate transfer functions are shown in Figure 3. This model is a compact transfer function model that reduces the

computational effort by only calculating the states at the inlet and outlet.

From analogy, in Krus’s model the pressure P and flow rate, Q, can be replaced with force, F, and velocity u. They are related

by the following equation (Krus et al. 1994)

(9) F1 = C1 + Zcu1(10) F2 = C2 + Zcu2

where, is the characteristic impedance, 𝑐 is the local speed of sound, 𝐴 is the cross-sectional area of the pipe, and is the 𝑍𝑐 = 𝐴𝑐𝜌 𝜌

material density of the drill string.

The transfer functions in Figure 3 are as follows. They are calculated in the laplace domain, 𝑠.

(11) H1(s) =R

kTs + 1(12) H2(s) = Zc

(13) Gf(s) =kTe

-RA2ρc s + 1

kTs + 1

where k is an empirical factor and determined (Krus et al. 1994) that is an acceptable value. The wave propagation time, 𝑘 = 1.25 𝑇 =

, is related to length of the pipe, L, and local speed of sound, c. The distributed line resistance, , assuming ideal laminar 𝐿𝑐 𝑅 =

µπdℎ 𝐿

flow. This model neglects unsteady friction, and assumes a distributed resistance across the transmission line. The term with the 𝑒 ―𝑇𝑠

(𝑠) transfer function is a time delay of , simulating wave propagation.𝑇

2.4.System Simulation Model

A model shown in Figure 3 is the final simulation model of the system that has both transducers and pipeline. The transducers

model are generated based on the model shown in section 2.1 and 2.2, where the dummy mass is replaced by the pipeline mode.

The pipeline model shown in section 2.3 is used here to account for any number of drill strings. For multiple number of drill strings

we can simply increase the number of pipeline blocks. This simulation model is also based on the experimental set-up explained in

Section 3.

Page 7 of 21



Draft

8

In Figure 4, v1 is the input forcing voltage, u1 and u2 are the displacement, F1 is the output mechanical force of driver transducer

and also the input of the pipeline. F2 is the input force at the outlet of pipeline and also the output from the receiver transducer. v2

is the output voltage.

3. EXPERIMENTAL SET-UP

An experimental apparatus was assembled for data transmission through drill strings as shown in Figure 5. This experimental

model includes sonar transducers as both the actuator and sensor. It is possible to use any sensor at the receiving end, but in this

research an identical transducer was used as the receiver. This configuration allows for two-way communication to occur if needed.

All control and data measurements are done by a National Instruments data acquisition board (NI-DAQ). A maximum length

sequence (MLS) signal is created. This is a digital pseudorandom binary sequence that has a perfectly white, flat spectrum. This

signal is sent through an amplifier. The MLS is generated using linear feedback shift registers (LFSR) using Matlab® code created

by Wiens (2007) and LSFR feedback values from Koopman (n.d). The output is measured from the receiver transducer through a

voltage divider which is recorded as voltage v2. The voltage divider is used here so that NI-DAQ device stays within the rated range

of ±10V, while the amplifier outputs v1 = 0-100 V. The MLS used has a sampling frequency of 20 kHz.

The measured data was then used to obtain transfer function

(14) ETFE = V2

V1

where V1 and V2 are the fast Fourier transform (FFT) of the measured voltage (v1 and v2) signals. This experimental method works

very well for pressure measurements of fluid transmission line (ven der Buhs et al. 2017) and is also believed to be a good

experimental method for measuring vibration along any pipeline.

3.1.Frequecny Response of the Transducer

First, an experiment was performed attaching the sonar transducers face to face with bolts as shown in Figure 6. This experiment

gave the frequency response of the two transducers shown in Figure 7. This test essentially shows us the forced frequency range of

the transducer is from 4 kHz to 12 kHz. In this range we observe very good gain and three major peaks.

3.2.Curve Fitting for parameter estimation

The initial transducer parameters were found experimentally for the piezo materials in the lab. An ANSYS Simulation model of

the ceramic rings also gives ideas of different parameters of the transducer. However, it is required to know the effective parameters

Page 8 of 21



Draft

9

of the transducer. PZT ceramics' material data are usually defined at low field. In practice, because of application of high electrical

fields cause a nonlinear ferroelectric effect which alters piezoelectric parameters. So, for dynamic cases, the effective parameters

are different (Sherman et al. 2007). These parameters were found using a parameter estimation technique shown in Table 1. The

experimental frequency response data found from previous section is used to fit the curve with the transfer function model of the

transducer. The initial range of the parameters were taken based on the parameters found in experimental tests and ANSYS

simulation. The fitted curve is not exactly same to that of experimental frequency response seen in the Figure 7: the experimental

result shows three dominant peaks, on the other hand the fitted curve shows two dominant frequency. This is most likely due to the

bending frequency of the head mass (Sherman et al. 2007), while the simulation model is created using one dimensional fundamental

equations which does not account for bending frequency. However, the model clearly accounts for the width of the high frequency

range that matches with the experimental data. A model that include bending frequencies will be more exhaustive for calculation

and is a redundant model for this research.

3.3.One, Two and Three Drill Strings

The transducers are connected with one, two and three drill strings through the end caps which are collected from a mine site. The

same driver and receiver transducers are connected with the strings through end caps as shown in Figure 5.

Figure 8 shows the frequency response for different number of pipe arrangements with the transducers. It is clear from the figure

that the frequency response range here is also 4000 Hz to 12000 Hz. As the forced frequency range is observed in this range, we can

only see the response of the pipes in this range. This is essentially a harmonic excitation where all the natural frequencies of the pipes

in this range are excited. It also observed here that, with an increased number of pipes the amplitude decreases, and the number of

peaks increase. This is simply because the mass matrix increases with the number of pipes that increases the natural frequencies.

4. MANUFACTURING OF A PIEZOELECTRIC TRANSDUCER

A new transducer was manufactured for this research and tested successfully at the SRC with both mining pipes and oil-gas

extraction pipes. This will be called as SRC made transducer. The procedure involved computer aided design of the model, materials

selection, some failure analysis calculations, electrical wiring and finally assembly of the transducer. The Figure 9 shown is the

manufactured and assembled transducer.

It has a tail mass that also works as a shell of the transducer and a head mass which vibrates against the tail mass. The tail mass

is designed to work as a reference for the head mass and piezo rings to vibrate against it. The tail mass is a shell structure to protect

Page 9 of 21



Draft

10

the piezoelectric ring materials from touching the environment and any other parts. The flange of the tail mass contains four holes

to connect the piece with pipe using bolts.

The performance of the SRC made transducer was tested by using it as both driver transducer and receiver transducer.

First, it was used as a driver transducer with the same experimental set-up described earlier, replacing the sonar driver transducer.

The test was performed with three mining pipes, also shown in Figure 5. The frequency response found from the test is shown in

the Figure 10. In this figure the test data of sonar driver and sonar receiver is also presented to compare between SRC driver and

Sonar driver. This test data also shows a frequency response dominated between 4 kHz and 12 kHz. The comparison clearly shows

that new SRC made transducer is also working like the sonar transducer as expected. In fact, for lower frequencies the SRC made

transducer outputs more electromechanical energy which is why higher gain is observed.

Secondly, the SRC made transducer was used as a receiver with the same experimental set up where now the sonar transducer

was used as a driver. The frequency response found from this test is shown in Figure 11. It is clear from the comparison that it works

similarly to the sonar receiver transducer.

5. RESULTS OF SIMULATION MODEL AND COMPARISON

The system simulation model shown in Section 2.4 is implemented in the Simulink platform. The parameters taken in the

simulation model are the parameters obtained from curve fitting and from the parameters of the mining pipe. This simulation model

gives frequency response shown in Figure 12 for one, two and three mining pipes and is similar to the experimental results in Figure

8. The simulation model is not exactly representing the experimental data because of possibly using one dimensional fundamental

equations and some unknown parameters that are difficult to obtain because of the non-linearity of the transducer piezo ceramic

materials. However, a clear trend is observed in the simulation model frequency response that follow the experimental frequency

response. Both experimental data and simulation data show increase of number of frequency peaks with the increase of number of

pipes, and the amplitude reduces accordingly.

Figure 13 is the frequency response comparison among one, two, three, 21, and 61 pipes connected in series with the same driver

and receiver transducer. This comparison is shown here to understand the effect of large number of mining pipes for the same

transducers used in the system. Figure 13 clearly shows that the amplitude decreases with the increase in number pipes and also the

dominant natural frequency peaks get narrow. The first expression of this results should not discourage implementation of this kind

of transducer for wave propagation, since the transducer’s electromechanical power can be increased by increasing the electric input

into it. This will depend on the application that will determine the number of pipes. So, there will be always opportunity to modify

Page 10 of 21



Draft

11

the transducers. The noticeable fact here is that the signal is transmitted even for large number of pipes. Moreover, this more narrow

frequency bands can be manipulated for certain types of communications schemes.

6. CONCLUSION

The comparison of results between the simulation model and the experiment indicates that the simulation model is a good model

to characterize any system of such type. This simulation model can also be used for simulating for a sophisticated communication

scheme to actually use in the mining or oil-gas application. Thus this can help with developing a communication scheme for data

communication in drill string using methods that implement wide range of frequency content in a single transmission.

This research also introduces a successfully manufactured transducer. The transducer can be used in any such application for

communication and possibly in other applications too. This also gives the knowledge behind the working principle of transducers that

can be implemented for manufacturing any transducer.

ACKNOWLEDGMENT

The authors would like to acknowledge the help of Douglas V. Bitner, Dallan Muyres, Ken Babich, Steve Kosteniuk and Reid

Patterson. The authors also acknowledge the support given by the Saskatchewan Research Council (SRC), SK, Canada for the

experimental assembly and equipment, as well as financial support of this work.

REFERENCES

Arps, J. J. and Arps, J. L. 1964. The subsurface telemetry problem - a practical solution. Journal of Petroleum Technology. Society

of Petroleum Engineers. Vol. 16, Issue 05. doi.org/10.2118/710-PA

Bayliss, C. 1998. Application and Development of Finite Element Techniques for Transducer Design and Analysis. PhD Thesis,

The University of Birmingham, Birmingham, UK.

Berlincourt D.A., Curran, D.R., and Jaffe, H. 1964. Piezoelectric and piezomagnetic materials and their function in transducers.

Physical Acoustics. Vol. 1, Part A, ed. by W.P. Mason, Academic Press, New York.

Page 11 of 21



Draft

12

Bybee K, 2008. High-Speed Wired-Drillstring Telemetry. Journal of Petroleum Technology, Volume 60, Issue 12, pp: 76-79, 2008.

doi.org/10.2118/1208-0076-jpt

Chew, W. C. 1995. Waves and Fields in Inhomogeneous Media, IEEE Press, New York, USA, 1995

Cox, W., and Chaney, P. 1981. Telemetry system. US Patent 4,293,936..

Dias, F., Marcancola, F., Wakabayashi, D., and Piazza, R. 2014. First real-time drill-stem test in deepwater using fully acoustic

telemetry monitoring and control of the well. Abu Dhabi International Petroleum Exhibition and Conference, Abu Dhabi, United

Arab Emirates, 10-13 November, 2014. Society of Petroleum Engineers.

Dowell, I., Mills A., and Lora M. 2006. Chapter 15 - Drilling-Data Acquisition. In R. F. Mitchell. Petroleum Engineering Handbook.

II - Drilling Engineering. Society of Petroleum Engineers. pp. 647–685, 2006. ISBN 978-1-55563-114-7.

Drumheller, D. S., and Kuszmaul, S. S. 2003. Acoustic Telemetry. Geothermal Research Department Sandia National Laboratories,

Albuquerque. NM 87185-1 033.

Drumheller, D.S. 1989. Acoustical properties of drill strings. The Journal of the Acoustical Society of America. vol. 85, no. 3, pp.

1048-1064.

Franconi, N. G., Bunger, A. P., Sejdic, E., and Mickle, M. H. 2014. Wireless communication in oil and gas wells. Energy

Technology. vol. 2, no. 12, pp. 996-1005.

Haddad, J. R., Salguero, A., and Jaimes, C. 2017. Application of telemetry technology in high-pressure wells to improve data

accuracy in drill stem tests. SPE Oil and Gas India Conference and Exhibition, Mumbai, India, 4-6 April, 2017 Society of Petroleum

Engineers.

Hughes, B. 1997. White Paper. INTEQ’s Guide to Measurement While Drilling. USA.

Islam, M. S., Dolovich, A. T., Peter, N., and Wiens, T. 2017. Acoustic drill pipe communications for mining. Proceeding of the

Maintenance, Engineering and Reliability/Mine Operators Conference, Saskatoon, Sask, Canada, 24-27 September, 2017. Canadian

Institute of Mining, Metallurgy and Petroleum (CIM). http://store.cim.org/en/acoustic-drill-pipe-communications-for-mining

Koopman, P. n.d. Maximal length lfsr feedback terms. https://users.ece.cmu.edu/~koopman/lfsr/index.html.

Kreuzer, E., Krumm, L., and Pick, M. A. 2014. Investigation of the influence of screw connections in drill-strings on the propagation

of torsional waves with respect to advanced stick-slip controllers. 33rd International Conference on Ocean, Offshore and Arctic

Page 12 of 21



https://users.ece.cmu.edu/~koopman/lfsr/index.html

Draft

13

Engineering, 8-13 June, 2014, San Francisco, California, USA. American Society of Mechanical Engineers, pp. V005T11A022-

V005T11A022.

Krus, P., Weddfelt, K., and Palmberg, J.O. 1994. Fast Pipeline Models for Simulation of Hydraulic Systems. Journal of Dynamic

Systems Measurement and Control.

Li, K. 2009. Electromagnetic Fields in Stratified Media, Springer, Zhejiang University Press, China.

Sherman, C.H., and Butler, J.L. 2007. Transducers and Arrays for Underwater Sound. Springer, New York.

ven der Buhs, J. 2017. Investigation and Optimization of Hydraulic Step-down Switched Inertance Converters with Non-uniform

Inertance Tubes. M.Sc. thesis, Department of Mechanical Engineering, University of Saskatchewan, Saskatoon, Canada.

ven der Buhs, J., and Wiens, T. 2017. Modelling Dynamic Response of Hydraulic Fluid Within Tapered Transmission Lines.

Proceedings of the 15th Scandinavian International Conference on Fluid Power, 7-9 June, Linköping, Sweden.

Wiens, T. 2009. Kasami sequences, m-sequences, linear feedback shift registers.

https://www.mathworks.com/matlabcentral/fileexchange/22716.

Page 13 of 21



https://www.mathworks.com/matlabcentral/fileexchange/22716

Draft

1

Table 1. Effective parameters of the transducer.

m1 = tail mass 1.4862 kg D12 = damping between head and tail mass 9.2166e3 Ns/m

m2 = head mass 1.4480 kg D23 = damping of rubber boot 428.04 Ns/m

k12 = stiffness of bolt 8.3773e8 N/m D3 = damping of dummy mass 3.1345e4 Ns/m

k23 = stiffness of rubber 1.2594e11 N/m N = Electromechanical Turns Ratio 0.4024

= short circuit 𝐶𝐸

compliance

1.9055e-9 (1/N) = Clamped Capacitance𝐶0 1.0526e-10 F

Table 2. The different parameters of the mining rods.

Outer Diameter, OD 155.33 mm

Inner Diameter, ID 108 mm;

Length, L 1.07 m;

Page 14 of 21



Draft

2

List of Tables

Table 1. Effective parameters of the transducer.

Table 2. The different parameters of the mining rods.

List of figures

Figure 1. Mass-spring-damper model of transducer.

Figure 2. Driver and receiver transducers connected face to face.

Figure 3. Block diagram of a fluid transmission line model (Krus et al. 1994).

Figure 4. Simulation model of the system.

Figure 5. Driver and receiver transducers connected with three borehole mining pipes.


Figure 7. Curve fitting for finding effective parameters of the simulation model.

Figure 8. Frequecny response of the transducers connected with one, two and three drill strings.

Figure 9. The SRC made transducer.

Figure 10. Frequency response comparison of SRC driver and sonar driver.

Figure 11. Frequency response comparison of SRC receiver and sonar receiver.

Figure 12. Frequency response of the simulation model of different mining pipes connected with the transducers.

Figure 13. Frequency response of the simulation model of increased number of mining pipes connected with the transducers.

Page 15 of 21



Draft

1

Figure 1. Mass-spring-damper model of transducer.


Figure 4. Simulation model of the system.

Figure 3. Block diagram of a fluid transmission line model (Krus et al. 1994).

Page 16 of 21



Draft

2

Figure 5. Driver and receiver transducers connected with three borehole mining pipes.


Page 17 of 21



Draft

3

Figure 7. Curve fitting for finding effective parameters of the simulation model.

Figure 8. Frequecny response of the transducers connected with one, two and three drill strings.

Page 18 of 21



Draft

4

Figure 9. The SRC made transducer.

Figure 10. Frequency response comparison of SRC driver and sonar driver.

Page 19 of 21



Draft

5

Figure 11. Frequency response comparison of SRC receiver and sonar receiver.

Figure 12. Frequency response of the simulation model of different mining pipes connected with the transducers.

Page 20 of 21



Draft

6

Figure 13. Frequency response of the simulation model of increased number of mining pipes connected with the transducers.

Page 21 of 21



draft - tspace.library.utoronto.ca€¦ · porosity, rock fluid pressure (dowell et al. 2006)....

Documents