Kristin SteinsheimDrilling Fluid Measurements NTNU Norwegian University of Science and Technology Faculty of Engineering Department of Geoscience and Petroleum
Master ’s thesis
Kristin Steinsheim
Drilling Fluid Measurements
Master’s thesis in Petroleum Engineering, MTPETR Supervisor: Alexey Pavlov
June 2020
Kristin Steinsheim
Drilling Fluid Measurements
Master’s thesis in Petroleum Engineering, MTPETR Supervisor: Alexey Pavlov
June 2020
Norwegian University of Science and Technology Faculty of Engineering
Department of Geoscience and Petroleum
Note on Thesis Scope
The original plan for this master’s thesis had to be changed midway through the spring semester of 2020, due to the extraordinary situation with the SARS-CoV-2 virus. The original plan was to build a flow loop and conduct experiments with the flow loop in the laboratory at the Department of Geoscience and Petroleum at the Norwegian University of Science and Technology. As of mid-March the student access to the laboratory was denied, which made it difficult to go through with the original plan. The master’s thesis was then redefined to consist of two parts.
The first part is a literature study on challenges and advances in measurements of drilling fluid and an analysis of measurement accuracy. This is a continuation of the report written in the courseTPG4560 - Petroleum Engineering, Specialization Projectin the fall semester of 2019. The intention behind the TPG4560 project report was to familiarize with the flow measurements conducted during drilling operations and identify possibilities for new and better measurement methods. Chapters 2-6 presented in this thesis are taken directly from the TPG4560 project report. These chapters are included to provide an important founda- tion for the extended literature study conducted in this thesis.
The second part presents the planning and start-up phase of the flow loop project. The early planning of the flow loop was conducted as a part of the courseTPG4565 - Petroleum En- gineering, Specialization Coursein the fall semester of 2019. A report was written as a preparation for an oral presentation on the flow loop project planning. Part II of this thesis is a continuation and extension of this work and parts are taken directly from the TPG4565 report.
The plan forward after this master’s thesis is for another student to continue the work with the flow loop. This report will then function as a background and a guideline to the project.
The report is therefore intended to give the next student valuable information on the topic of flow measurements and an overview of all the work conducted on and plans made for the flow loop so far.
Abstract
Flow measurements are an important part of the drilling process. They are conducted for the purpose of process optimization, operation monitoring, and maintaining safe op- erations. This thesis is divided into two parts. The first part covers flow measurement methods and applications in drilling operations. Measurements of flow rate and drilling fluid properties are presented, as well as acoustic flow measurements and soft sensing for estimation of parameters that are difficult to measure. Utilization of real-time downhole data depends on reliable transmission to surface, which can be performed by mud pulse telemetry and wired drill pipe. The interest of automating the drilling process has led to the development of new solutions for flow measurements and control. An analysis of how certain flow measurement accuracies affect drilling parameters is presented.
The second part presents the planning and start-up phase of building a flow loop. The purpose of the flow loop project is to test the flow measurement abilities of the ClampOn SandQ Monitor for drilling processes. The design of the flow loop is based on resembling a drilling fluid circulation loop. Equipment to be included in the loop and a plan of exper- iments to be run are presented. A cost estimate and a risk analysis have been performed.
The planning process and the start-up of the building phase are described.
Acknowledgements
I would like to thank my supervisor Alexey Pavlov for introducing me to this topic, and for support and great ideas throughout this process. I would also like to thank the Department of Geoscience and Petroleum for granting me the budget and laboratory space needed to initiate the flow loop project. Furthermore, I would like to thank Noralf Vedvik and Steffen Wærnes Moen for their help during both the planning and building phase of the flow loop.
Last but not least I would like to thank my co-students for creating a fun, interesting, and rewarding everyday working environment.
Kristin Steinsheim, Trondheim, Spring 2020
Table of Contents
Note on Thesis Scope i
Abstract iii
Acknowledgements iv
Table of Contents vii
List of Tables x
List of Figures xii
I Challenges and Advances in Measurement of Drilling Fluid 1
1 Introduction 3
2 Reasons for Conducting Flow Measurements 5
3 Flow Rate Measurements 7
3.1 Pump Stroke Counter . . . 7
3.2 Flow Paddle . . . 7
3.3 Pit Volume Totalizer . . . 8
3.4 Coriolis Meter . . . 8
3.5 Venturi Meter . . . 10
3.6 Gamma-Ray Multiphase Flow Meter . . . 10
4 Acoustic Flow Measurement 13 4.1 Clamp-on Acoustic Transit Time Flow Meter . . . 13
4.2 Acoustic Leak Flow Analyzer . . . 14
4.3 Distributed Acoustic Sensing . . . 14
4.4 Multipoint Acoustic Sensing . . . 16
4.5 Acoustic Sand Monitoring . . . 17
5 Other Flow Measurements 19 5.1 Density measurements . . . 19
5.2 Viscosity Measurements . . . 20
5.3 Gas Measurements . . . 21
5.4 Cuttings Measurements . . . 22
6 Soft Sensing 25 7 Real-time Downhole Data 29 7.1 Measurements While Drilling and Logging While Drilling . . . 29
7.2 Telemetry Technologies . . . 32
8 Mud Pulse Telemetry 33 9 Wired Drill Pipe 41 10 Automation of Flow Measurements and Control During Drilling 49 11 Analysis of Measurement Accuracy 55 11.1 Data . . . 55
11.2 Equations . . . 57
11.3 Results . . . 59
11.3.1 Simulation 1 . . . 60
11.3.2 Simulation 2 . . . 61
11.3.3 Simulation 3 . . . 63
11.3.4 Simulation 4 . . . 64
11.4 Discussion . . . 66
12 Discussion 69 12.1 Chapters 2-6 . . . 69
12.2 Chapters 7-11 . . . 71
13 Conclusion 73
II Flow Loop Project 75
14 Introduction 77
15 Flow Loop Design 79
16 Experiments 81
17 Equipment 83
17.1 ClampOn SandQ Monitor . . . 83
17.2 Fluid Pump . . . 85
17.3 Coriolis Meter . . . 86
17.4 Flow Meter . . . 88
17.5 Gas Controller . . . 88
17.6 Pressure Sensors . . . 89
17.7 Venturi Meter . . . 89
17.8 Differential Pressure Sensor . . . 91
17.9 Pipes . . . 91
17.10Solenoid . . . 94
17.11Tanks . . . 94
17.12Valves . . . 94
17.13Stand . . . 96
17.14Restriction . . . 97
17.15Cuttings . . . 97
17.16Screen . . . 98
17.17LabVIEW . . . 98
18 Cost Estimation 99 19 Risk Analysis 101 20 Project Process 103 20.1 Planning Phase . . . 103
20.2 Building Phase . . . 103
21 Future Work 107 22 Discussion 109 23 Conclusion 111 Nomenclature 113 Bibliography 117 Appendix 125 A MATLAB Functions . . . 126
B Risk Register . . . 135
C Coriolis Technical Information and Simulations . . . 139
List of Tables
9.1 Comparison of different telemetry technologies [41]. . . 46
11.1 Data input of accuracy analysis. . . 57
11.2 Results for the ideal case. . . 60
11.3 Results for viscosity accuracy calculations. . . 61
11.4 Results for density accuracy calculations. . . 62
11.5 Results for flow rate accuracy calculations. . . 64
11.6 Results for viscosity, density, and flow rate accuracy calculations. . . 66
16.1 Overview of the first 12 planned experiments. . . 82
17.1 Key specifications for the ClampOn SandQ Monitor [56]. . . 85
17.2 Key specifications for the Pedrello F50/250B fluid pump [57]. . . 85
17.3 Preferable parameters for a Coriolis meter. . . 87
17.4 Key specifications for the Coriolis meter [59]. . . 87
17.5 Key specifications for the flow meter [60]. . . 88
17.6 Key specifications for the gas controller [61]. . . 88
17.7 Key specifications for the pressure sensors [62]. . . 89
17.8 Venturi dimensions. . . 90
17.9 Key specifications for the differential pressure sensor [64]. . . 91
17.10Key specifications for the stainless steel pipe [65]. . . 92
17.11Key specifications for the transparent PVC pipes [66]. . . 93
17.12Key specifications for the PVC pipes [67]. . . 94
17.13Key specifications for the PVC ball valves [69]. . . 95
17.14Key specifications for the PVC one-way valve [70]. . . 95
17.15Key specifications for the brass ball valve [71]. . . 96
17.16Key specifications for the brass one-way valve [72]. . . 96
17.17Key specifications for the PVC ventilation valve [73]. . . 96
17.18Key specifications for Sponesand [74]. . . 98
18.1 First cost estimate. . . 99
18.2 Updated cost estimate. . . 100 B.1 Risk register. . . 135
List of Figures
3.1 Model showing the principle behind the Coriolis meter [11]. . . 9
3.2 Model of a venturi meter [13]. . . 10
3.3 Schematic of a gamma-ray multiphase flow meter [7]. . . 11
4.1 Example of smart completion including a fiber optic cable [19]. . . 16
4.2 Acoustic sensor mounted close to a 90-degree bend [21]. . . 17
5.1 Schematic of a cuttings flow meter [28]. . . 23
5.2 Overview of the cuttings transfer system using cuttings blowers [31]. . . . 24
6.1 Model of the downhole set-up for a unilateral well [33]. . . 26
7.1 Example of an advanced BHA [38]. . . 29
7.2 Bandwidth distribution of a case investigated by [37]. . . 30
7.3 Common RSS downlink sequence scenarios [39]. . . 31
8.1 The principle of MPT [37]. . . 33
8.2 Types of generated mud pulses: positive (a), negative (b) and continuous (c) [41]. . . 34
8.3 Mathematical model of MPT [38]. . . 34
8.4 Shear valve consisting of a stator and an oscillating rotor [42]. . . 36
8.5 Downhole pulse pressure at the valve with different mud flow areas (sec- ond from right: closed valve, first from right: fully open valve) [37]. . . . 37
8.6 Simple model of the signal flow [42]. . . 37
8.7 Surface signal processing stages [37]. . . 38
8.8 Example of change in signal quality [42]. . . 39
8.9 Changes made to surface signal processing by Emmerich et al. [37]. Light gray: unchanged, gray: adjusted and black: new. . . 40
8.10 Worldwide utilization of MPT [38]. . . 40
9.1 Schematic of a typical WDP system [44]. . . 41
9.2 Example of a drill pipe joint with the micro-repeater system [40]. . . 43
9.3 The combined serial and parallel design of the micro-repeater system [40]. 43 9.4 Example of software display used to monitor ASM [44]. . . 45
9.5 Cross-section of drill pipe with braid and insulator [36]. . . 46
10.1 Instrumented standpipe set-up [47]. . . 50
10.2 Offshore installation of pipe rheometer [46]. . . 51
11.1 Wellbore schematic of the well. . . 56
11.2 The effect of viscosity accuracy on pressure. . . 60
11.3 The effect of viscosity accuracy on ECD. . . 61
11.4 The effect of density accuracy on pressure. . . 62
11.5 The effect of density accuracy on ECD. . . 62
11.6 The effect of flow rate accuracy on pressure. . . 63
11.7 The effect of flow rate accuracy on ECD. . . 64
11.8 The effect of viscosity, density, and flow rate accuracy on pressure. . . 65
11.9 The effect of viscosity, density, and flow rate accuracy on ECD. . . 65
15.1 System drawing of the flow loop base design. . . 80
17.1 System layout for the ClampOn sensor [56]. . . 84
17.2 Tracking the distance a bubble travels by pulsing [56]. . . 84
17.3 Velocity changes inside the centrifugal pump presented as streamlines [58]. 86 17.4 Pressure changes inside the centrifugal pump [58]. . . 86
17.5 Model of venturi meter [13]. . . 90
17.6 Venturi meter design [63]. . . 91
17.7 Schematic of set-up for stand. . . 97
17.8 Schematic of restriction. . . 97
19.1 Risk matrix used to evaluate project risks. . . 102
20.1 Overview of the flow loop area. . . 104
20.2 Overview of the upper left corner of flow loop area. . . 105
Part I
Challenges and Advances in
Measurement of Drilling Fluid
Chapter 1
Introduction
Flow measurements performed during drilling are an important part of drilling operations, both for performance and process control. Correct measurements are important for opti- mizing drilling parameters, keeping track of the operation, and detecting changes. Having the right drilling fluid parameters are crucial for staying within the downhole pressure regimes, which is a necessity for the drilling operation. Monitoring changes requires ac- curate measurements.
One of the major parameters to monitor is the delta flow, which is defined as the return flow from the well, minus the inflow to the well. Unexpected changes in delta flow can be an indication of a developing well control situation, as an increase can be a sign of an occur- ring kick, and a decrease can be a sign of occurring losses. There are several methods for measuring flow rate, ranging from simple, qualitative measurements to highly advanced, quantitative measurements. Acoustic flow measurements are used in many flow segments and could have potential for implementation in the drilling process. Other measurements are performed on drilling fluid properties and include measurements of density, viscosity, gas content, and cuttings parameters. Another interesting aspect is soft sensing, which can be used to estimate parameters that are difficult to measure.
The drilling fluid properties are also important for the power and function of many down- hole tools, in addition to communication of the data acquired by the downhole tools to surface. As of now, mud pulse telemetry (MPT) is the most common telemetry technol- ogy. The low cost and easy implementation are two large advantages, and research and testing has been performed to develop further improvements of the system. Wired drill pipe (WDP) has the potential for replacing MPT. It can deliver more and faster data, and also has the ability to include more measurements, such as along-string measure- ments (ASM).
WDP is a step in the direction of automation of drilling processes. Automation and digital- ization are of high interest in the industry, as it can lead to improved quality, efficiency, and
consistency. Automated measurements and control of flow parameters have been tested and implemented in the drilling industry.
An overview of different flow measurement technologies will be presented, together with reasons for conducting the measurements. Working principles and positive and negative aspects of the different technologies are discussed, as well as the potential for future de- velopments. An analysis of how accuracies of certain flow measurements affect drilling parameters is also included.
Chapter 2
Reasons for Conducting Flow Measurements
Chapter 2 is taken directly from the TPG4560 project report by Steinsheim [1]. This chapter is included to provide an important foundation for the extended literature study conducted in Part I and for the flow loop project in Part II.
Flow measurements are among the most important procedures to perform during drilling operations. The measurements are used to control that processes are going according to plan, optimizing drilling parameters, and to detect and manage unwanted events. Mea- suring flow parameters in and out of the well helps monitor hole cleaning, hole stability, formation integrity, and volume changes. Evaluation of the flow parameters can disclose drilling-related problems, such as kicks, losses, stuck pipe, and equipment failure. Correct flow parameters are crucial for drilling performance and functionality of many bottom hole assembly (BHA) tools. By analyzing the flow parameters information about the formation being drilled can also be acquired.
Severe changes can occur in the physical properties of the drilling mud from the time it is pumped out of the active mud pit until it returns. Measurements such as density and viscosity measurement are done on the drilling fluid both upstream and downstream of the well. The changes can be caused by pressure and temperature effects, but also by interven- tion of downhole formation fluids and solids. The cuttings accumulated during drilling will alter the flow parameters. Discovering unexpected changes can be the first step to identi- fying undesirable situations such as hole instability, insufficient hole cleaning, or kicks [2].
A kick can be defined as an uncontrolled influx of formation fluids into the well. It occurs when the pore pressure of the formation exceeds the pressure in the well. Volume control is required to be able to detect a kick. If not handled correctly the consequence could be a surface blowout or an underground blowout. It is the worst-case scenario during drilling,
as it poses a risk of damage to equipment, personnel, and environment. A kick will almost always lead to increased cost, regardless of the severity of the kick, due to lost time man- aging the situation before normal drilling operations can resume [3]. A kick situation often arises and develops quickly. Two key performance indicators connected to kick situations are how long it takes to detect the kick and how long it takes to respond to it. A kick tolerance is included in well design to reduce the consequence of not detecting a kick fast enough and to increase the probability of getting the kick situation under control [4].
Losses can be defined as uncontrolled flow of well fluids into the formation. It occurs when the pressure in the well exceeds the pore pressure of the formation. Volume control is required to identify losses. The consequence could be lost time and increased cost due to loss of fluids and solids, and mobilization of new fluids and solids from shore [3]. A kick could occur as a secondary consequence of a loss [4].
The preface of fluid losses could be induced fracturing of the formation due to too high density of the drilling fluid. Fractures reduce the integrity of the formation. Decreased well integrity can cause differential sticking during drilling. Too low density could lead to cavings in the well due to reduced stability of the formation. Decreased stability can lead to stuck pipe, especially in combination with inadequate hole cleaning [5].
Hole cleaning is dependent on the ability of the drilling fluids to lift the cuttings out of the well. Insufficient hole cleaning can cause many drilling-related problems, such as stuck pipe, pack-offs, high torque, and large frictional drag forces. It can also lead to difficul- ties when running the casing, making it hard to get the casing to total depth (TD). If the casing is landed off successfully it might still be challenging to get a good cement job. A bad cement job can become an integrity issue, which can have dangerous consequences.
Logging can also become a problem if cuttings removal is inadequate [6].
Exchanging experience between drilling and production flow measurement can be valu- able. Flow measurements for production purposes are challenged by multiphase flow complexity. To be able to measure the rates of the different phases test separators are often used. A test separator is large and occupies considerable rig space, and for floating platforms, where buoyancy needs to be considered, the heavy weight of the separator can also be an issue. Implementation of non-intrusive meters for flow measurement can re- move many of the problems connected to separators [7]. The non-intrusive mounting of flow meters is also an advantage as any joint can pose a risk for leakage and because any obstacle in the flow can lead to blockage of the pipe, for instance by sand accumulation.
For production flow lines the pressure is often high, and a leak can have dangerous conse- quences. Another advantage is that the non-intrusive meters can be mounted and operated without required stops in production [8]. Multiphase flow meters can also save costs for subsea pipelines as flow from several wells and several fields can be commingled. This can also lead to the development of many small oil and gas fields that would not be economical without the opportunity to be tied back to existing infrastructure [9].
Chapter 3
Flow Rate Measurements
Chapter 3 is taken directly from the TPG4560 project report by Steinsheim [1]. This chapter is included to provide an important foundation for the extended literature study conducted in Part I and for the flow loop project in Part II.
3.1 Pump Stroke Counter
The mud pump stroke counter is the most common method of calculating inflow to the well. For each stroke with the piston, a limit switch opens and closes. The strokes are counted over a time interval. The volume of the pump cylinder is known, together with the efficiency of the pump. The volume pumped into the well can then be calculated [10].
The mud pump stroke counter is widely used and generally works adequately. The pumps have many moving parts that are exposed to wear and tear, but most rigs have several mud pumps. Often they are not all in use, so if one fails another can be started. This way change of worn-out parts is done without slowing down operations. A challenge with this method is that wear will increase gradually, leading to a reduction in pump efficiency which might be hard to detect in early stages. The pump efficiency used in the calculation of mud flow might be wrong [4].
3.2 Flow Paddle
A common method of measuring return flow from the well is by the flow paddle. A single, spring-mounted paddle is pointed down into the flow. The flow exerts a force on the paddle, which is balanced by the force of the spring. Fluid height, density, and velocity affect the degree of deflection [11]. It is calibrated to give the percentage of deflection and is a qualitative measurement of flow. It can indicate if there is no flow, low flow, or high flow, but does not function as a measurement of flow rate. The sensitivity is too low, and
the accuracy is not sufficient. The impact of the fluid density contributes to the flow paddle not being adequate to measure flow rate [10].
3.3 Pit Volume Totalizer
Pit volume totalizer (PVT) uses multiple floats or other sensing techniques to measure the liquid level in a mud pit, which in turn gives the volume of the pit. This is the most com- mon method to detect changes in delta flow, which is defined as the return flow from the well minus the inflow to the well. By recording the change in height over a time interval, the return flow rate can be calculated. This requires that there is no outflow from the tank and is therefore not measured continuously during operations [11].
The surface area of a mud pit is large, around 400 ft2, and the PVT system is not able to detect small changes in delta flow. A small increase in volume in the pit will hardly increase the pit level and is difficult to discover. When the well is not being circulated the return flow is rerouted through a trip tank, which has smaller volume and smaller surface area, making small changes in height easier to detect. At offshore rigs heave caused by waves can lead to challenges with regards to measuring the pit level. Changes in the active volume, such as offloading from a pit, changing pit, or transferring between pits make PVT readings difficult to conduct. Volume changes are usually alarmed by boundary conditions set by the different drill crews. If the operating interval is too small the alarm will go off very often, making it easy to stop the alarm and ignore it. It can also steal focus away from the other important tasks of the driller. Setting a too large operating interval means that a potential kick can develop for a long time period before being detected. The consequences can be catastrophic, especially because there is a delay from when the drilling fluid flows out of the wellbore until it enters the mud pit. The flow line volume can be quite large and lead to several minutes-long delays. For a high-intensity kick, the inflow and pressure build-up could reach dangerous levels by the time it is recorded in the pit [4].
3.4 Coriolis Meter
A Coriolis meter is used to measure mass flow rate, temperature, and density of fluids.
The main components are flow tubes, a sensor, and a transmitter. The two flow tubes are set vibrating at their natural frequency by a driver coil in the central section. This is done by the transmitter sending a signal to the sensor. When flow enters the Coriolis meter it is separated into the two flow tubes, which has a smaller diameter than the flow line on the rig. When gas or liquid flows through the tubes the flow induces a force on the tubes, causing a phase shift in the oscillation. The oscillation is measured by two position detectors mounted at the inlet and outlet section. This information is transferred back to the transmitter, where some calculations are carried out, before it is outputted for further processing [12]. A model showing the principle behind the Coriolis meter is shown inFig.
3.1.
The principle behind the Coriolis is based on Newton’s second law, which states that the
Fig. 3.1– Model showing the principle behind the Coriolis meter [11].
force is equal to mass times acceleration. The phase shift is directly proportional to the mass flow rate of the fluid. An increase in mass flow rate will lead to an increase in phase shift. The frequency of the vibration depends on the density of the fluid. Denser fluids lead to lower frequencies. To calibrate the Coriolis meter fluids with known densities such as water and air is flown through the meter. The frequency will be lower with water than with air. The relationship between frequency and density is linear, and thus the meter can be used to measure the density of any fluid [12].
There are many challenges associated with the Coriolis system. It has proven to be sensi- tive when it comes to multiphase flow. The gas percentage in the drilling mud is often low and multiphase flow measurement is usually not a severe challenge during drilling. The decrease in pipe diameter in the flow tubes can introduce a risk of plugging the system.
Due to this, there is often a by-pass line installed with the Coriolis meter. The surface area needed for the Coriolis system can be large and can pose a challenge with regards to location on the rig, where space is often limited. Maintenance of the meter is important, especially because it is an expensive system, and it needs to be flushed properly after every use. The vibrations on a rig caused by drilling, compressors, and motors can disturb the frequency of the flow tubes and create noise that can be hard to separate from the actual Coriolis readings [3]. Heave caused by waves and standard practices such as turning the mud pumps on and off can affect the output from the system. It is important to have soft- ware that can compensate for these kinds of effects [4].
The multiphase performance of the Coriolis meter poses a real challenge when it comes to measuring flow in production pipelines from the reservoir. It can measure dry gas or gas-free liquid, but a mixture has proven to be difficult. Gas bubbles in the liquid will reduce the density of the liquid, which can underestimate the water cut and be interpreted as higher flow rate. Another issue is that the gas can absorb vibration energy which leads to false output values [12].
3.5 Venturi Meter
Venturi meters are not commonly used to measure return flow from the well during drilling but are used together with other sensors in multiphase flow measurement for production purposes. The venturi meter consists of a tube with inlet and outlet diameter equal to the flow line, with a gradually decreasing diameter towards the middle of the tube. A model of a venturi meter can be seen inFig. 3.2. The pressure is measured at the maximum and minimum pipe diameter. The restriction in the flow area leads to an increase in flow velocity and a decrease in static pressure in the restricted area. The venturi effect is based on conservation of energy. The potential energy is presented by the static pressure, and the kinetic energy is presented by the flow velocity. When the velocity increases in the re- stricted area, is it caused by the potential energy converting to kinetic energy, which leads to a decrease in pressure. By measuring the differential pressure over the venturi meter, the velocity can be determined, and the flow rate computed [13].
Fig. 3.2– Model of a venturi meter [13].
3.6 Gamma-Ray Multiphase Flow Meter
The gamma-ray multiphase flow meter is used for multiphase flow measurements for pro- duction purposes. It consists of two gamma-ray transmission gauges mounted on the pipelines, as seen inFig. 3.3. It can be used to determine water cut and fluid flow rates.
One of the gauges measures transmitted intensity of 662 keV gamma-ray from 137Cs and the other gauge measures transmitted intensities of 59.5 keV gamma-rays from 241Am and 662 keV gamma-rays from 137Cs [7]. Water cut is determined by dual energy gamma-ray transmission (DUET). There is a difference in the atomic number of formation water and oil. The intensity of the gamma-rays from 241Am relates to both the atomic number and areal density of the fluids. The intensity of gamma-rays from 137Cs only relates to the areal density of the fluids. The water cut can be found by the two measurements combined with the known densities of the fluids at the pressure and temperature of the system [14].
The flow rates can be determined by single energy gamma-ray transmission. The velocity can be computed from cross-correlation of the 137Cs readings, with the time between the
readings and the know distance between the gauges. To find the flow rates of gas and liq- uid the pressure and temperature of the system are needed, together with applicable flow regime models. The calculated water cut can then be used to get water and oil flow rates [7].
Fig. 3.3– Schematic of a gamma-ray multiphase flow meter [7].
The calibration of the gamma-ray multiphase flow meter is trustworthy because the the- ory behind gamma-ray transmission is well known. Another advantage for production measurements is that the meter can function on a large interval of pipe diameters, ap- proximately between 75 and 300 mm. For drilling purposes, the flow line between the bell nipple and the mud pit will often be larger than 300 mm in diameter, and the measurements would not be accurate [7].
Chapter 4
Acoustic Flow Measurement
Chapter 4 is taken directly from the TPG4560 project report by Steinsheim [1]. This chapter is included to provide an important foundation for the extended literature study conducted in Part I and for the flow loop project in Part II.
4.1 Clamp-on Acoustic Transit Time Flow Meter
The clamp-on acoustic transit time (CATT) flow meter is used for measuring flow rates.
The clamp-on feature makes it non-intrusive on the flow, which allows for easy mounting on the rig, no disturbance of the flow, and no stop in operations due to mounting or main- tenance. It consists of three main parts, which are transducers, clamping arrangement, and a unit for processing the signals. Oscillators inside the transducer send acoustic waves through the pipe walls and fluid. The signals are detected by the oppositely mounted trans- ducer. This process is alternating between the two transducers, sending the acoustic waves both upstream and downstream. The transit times are measured and compared to each other. Together with the known geometry and distance between the two transducers, this can be used to calculate the average velocity of the fluid and hence the flow rate [15].
Experiments with a CATT flow meter was carried out at a hydropower plant in Sassello, Italy by Schwery et al. [15]. They found several parameters that affect the resolution, reliability, and accuracy of the measurement. Emitting acoustic waves with high frequency will improve temporal resolution. This is especially important for small diameter pipes.
If the travel length of the acoustic waves is short, the accuracy of the measurement will decrease. Wave signal damping can occur if the flow regime is bubbly, there are solids in the flow, or the pipe walls are too thick. In these cases, emitting a low-frequency wave can work better as it is less affected by damping. Other factors that influenced the results were temperature and the speed of sound in the pipe material. The roughness of the inside pipe surface was used to correct the flow profile and had to be known in order to get accurate
measurements. After the experiments, it was concluded that the CATT flow meter could be used for cooling systems and to detect leak flow in the hydropower plant system. The uncertainty was too high to be used for efficiency and comparative measurements.
4.2 Acoustic Leak Flow Analyzer
Acoustic measurements can be used for leak flow detection. The acoustic leak flow ana- lyzer (ALFA) is based on passive acoustic measurements. During logging a hydrophone measures amplitudes and frequencies caused by vibrations due to fluid movement. From analyzing different amplitudes and frequencies the location of the leaks can be identified, as well as the size of the leaking apertures. It can also give an indication of the type of fluid and qualitative flow rate. Channeling and flow behind pipes can be detected if the signals vary sufficiently from the signals within the pipe. Detecting leaking casings or packers is one of the most important functions of the ALFA, as a pressure build-up in the annulus can lead to severe well control issues. The frequency is dependent on the size of the aper- tures. The tighter the aperture, the higher the frequency. The wellbore stream will lead to low-frequency signals, which appear as noise and should be identified. This will make it easier to separate the continuous noise from the signals caused by irregularities. The amplitude depends on several factors, such as fluid type and flow rate. High amplitudes would indicate gas, but there is no clear measured boundary to distinguish between gas and liquids. The acoustic measurements are often combined with temperature measurements to strengthen the interpretation [16].
4.3 Distributed Acoustic Sensing
Distributed acoustic sensing (DAS) is based on a passive fiber optic sensor. The sensor can detect acoustic fields along the length of the fiber. The measurements are made by pulsing a laser signal down the fiber and record the intensity of the light that is backscattered. The backscattered light is different from the original signal due to vibrations inducing changes in the refractive index. The time it takes before the backscattered light is recorded can be used to find the point along the sensor where the recorded event occurred. Signal phase and frequency can also be computed by doing repeated pulsing of the laser signal. It is important to wait until a backscattered signal has returned before sending a new signal, in order for the system to distinguish between the different pulses. A large amount of data is recorded and needs to be processed and stored. The data is often displayed by a waterfall model, with time and space on the axes and a color scale representing the signal intensity.
DAS is often chosen due to the spatial resolution, responsiveness to high frequency and the signal-to-noise ratio (SNR) it offers [17].
There are several areas where the DAS technology can be utilized. Downhole monitoring during hydraulic fracturing stimulation, flow profiling, and multiphase flow metering are some examples to be described. Further examples are presented in [18], such as well in- tegrity monitoring, vertical seismic profiling, gas-lift optimization, and sand detection.
DAS could be used for downhole monitoring during hydraulic fracturing stimulation of producing wells. This allows for real-time monitoring of the different clusters and could enable immediate and individual adjustments for each cluster. During multistage plug- and-perf completion the real-time monitoring would make it possible to intervene before moving on to fracturing the next stage. Adjustments could include diverter spheres, change in injection rate, or increasing the time spent on hydraulic fracturing for the specific clus- ter. The result would have to be an increase in production that could justify the cost of downhole installation and monitoring. A challenge with real-time monitoring during perforation is not damaging the DAS fiber when setting of the perforation gun. Correct orientation of the perforations is a prerequisite for this to be successful [18]. Looking at DAS in combination with distributed temperature sensing can increase the evaluation of the hydraulic fracturing stimulation when using cold injection fluids. The time it takes for the temperature to return to the geothermal gradient can be correlated to the amount of cold treatment fluid injected into the formation [17].
Flow profiling is possible with DAS. Different fluids are associated with different fre- quency ranges, even though there are no clear cut-off values. Gas is typically presented by high frequency, while water and oil are presented by low frequency, with oil lower than water. When several phases flow together it becomes more complex. One method to overcome the challenges is by having a collection of noises associated with different flow regimes. By comparing the recorded noise to this collection an estimate of the flow regime of the different perforations can be made. Multiphase flow metering could be possible with DAS. The speed of sound varies with different phases, as the sound travels slower through mediums of low density. The speed of sound of the wellbore fluid can be found by tracking the noise along the fiber. By comparing the computed speed of sound in the direction with and against the well stream the Doppler shift and velocity of the fluid can be determined [17].
The DAS system provides many advantages. It can often be used for the whole lifetime of the well and it can be shared with other technologies that utilize optic fibers. The mea- surements can be done continuously or in time laps and can cover the full length of the well. The spatial resolution can be as small as 1 meter and the sample rates as high as 20 kHz. The need for interventions is usually not present due to the robustness of the fiber.
The main parts of the set-up are the cable in the well and an interrogator at the surface.
The interrogator can be connected to cables in different wells, which offers the opportunity to monitor several wells with just one interrogator. The cables are permanently mounted in the wells and only the connection from the interrogator needs to be switched in order to shift between wells. There are different methods of mounting the cable. It can be ce- mented outside the casing, clamped on the outside of the tubing, or lowered into the well for temporary measurements, as done during logging. A cable installed as a part of a smart completion can be seen inFig. 4.1. The most common methods are based on permanent mounting, which means that the cable is ready in the well when data is needed. This saves time by eliminating tripping into and out of the well for every measurement period. The permanent mounting is also non-intrusive, so it does not affect the flow and there is no required stop in production to start the measurements. Eliminating the need for interven-
tions after installation does not only save time but also reduces the health, safety, security and environment (HSSE) risk and cost management [19].
Fig. 4.1– Example of smart completion including a fiber optic cable [19].
There are several reasons why DAS is not widely implemented. Making absolute measures of acoustic signals is generally not possible. To be able to compare results calibration is important. Factors that impact measurements are the characteristics of the fiber cable, the design of the DAS system, location, mounting, and settings on the sensor that are configurable. There is no universal standard for interpreting and comparing DAS data.
This combined with the relatively high installation cost is the reason why many operators have chosen to not implement DAS in their completion design [18].
4.4 Multipoint Acoustic Sensing
Multipoint acoustic sensing (MAS) is used for detection of third-party interference and leaks in pipelines. Several hydrophones are placed along the pipeline and recorded anoma- lies can, together with the GPS position of the hydrophone, give an indication of the lo- cation and cause of the issue. The theory behind the technology is that any interaction with the pipeline will affect the flow by creating acoustic waves or altering existing waves.
Third-party interference can be both by intentional theft or accidental, for instance during service and repair work, or by unrelated work carried out too close to the pipelines. The consequences of third-party interference, or leaks due to other reasons, can be of severe importance. Damage to personnel, civilians, equipment, and environment are possible ef- fects. Damage to business by demolished reputation or economic losses can also occur [20].
4.5 Acoustic Sand Monitoring
Acoustic sand monitoring is based on the impingement of solids on the pipe wall. The sensor is usually a clamp-on type and is not invasive on the flow. It does not take up a lot of space on the rig, and mounting does not require a stop in the operation. The sensor is usually mounted downstream and close to a bend, where the solids will hit the pipe wall in the bend. This can be seen in Fig. 4.2. The technology converts the impacts from the solids on the pipe wall to electrical signals. The signals are dependent on the energy associated with the impingement, which can be affected by both the velocity and size of the solids. Velocity can vary during production and the distribution of sand particle size can be large. To be able to get a quantitative reading these variables need to be averaged based on an evaluation of the current state of the wellbore stream [21].
Fig. 4.2– Acoustic sensor mounted close to a 90-degree bend [21].
The long term, qualitative measurement of sand production is more important than the real-time quantitative measurement. The goal of the operator is often to have the maximum inflow from the reservoir to the well without having a harming production of sand. There are several reasons why operators want to avoid sand production. In the near-wellbore area production of sand can lead to formation damage, which could result in decreased permeability and in the worst case plugging off the area around the well. One of the biggest problems with sand in the well stream is the eroding effect. This will lead to wear and tear of equipment and could cause equipment damage and tool failure, both downhole and top site. The presence of sand can contaminate the petroleum products and large amounts can cause plugging of the entire wellbore. Many wells are completed with sand screens to avoid the problem, but if sand production arises it will often escalate by itself, for instance by the decreasing stability of the formation and by erosion of the apertures in the screens. Monitoring of sand production is important so that corrective measures can
be taken to reduce or eliminate it. This is important for the production, lifetime, and cost of the well. It is also a safety measure because sudden tool failures or leaks caused by erosion can have catastrophic effects, and there is always risk involved when performing a workover or an intervention [21].
Chapter 5
Other Flow Measurements
Chapter 5 is taken directly from the TPG4560 project report by Steinsheim [1]. This chapter is included to provide an important foundation for the extended literature study conducted in Part I and for the flow loop project in Part II.
5.1 Density measurements
Density measurements are important for maintaining the fluid column in the well. If the density is too high it will exceed the fracture gradient, resulting in fracturing of the for- mation and fluid losses. If the density is too low the fluid in the well will not be able to withstand the pressure of the fluids in the pores of the formation and uncontrolled flow of formation fluids into the well will occur. The density measurement is done by a member of the drilling crew manually collecting a sample from both mud going into the well and mud coming out of the well, and analyzing the samples in a laboratory at the rig. The sam- pling is usually repeated every 15 to 30 minutes but can be done more frequently when necessary. The density measurement itself can be done using a mud balance. It is often inserted into a pressure chamber to manage potential bubbles in the mud [2]. Another way of measuring the density is by a Coriolis meter, as explained in chapter 3.
There are several issues with the manual sampling of mud. Any short time event that oc- curs between two samples will not be detected. If a serious or dangerous event happens just after a sample is made it might take until the next sample is made before the change is recorded, unless another system on the rig discovers it, and the consequences could be severe. Collecting the samples requires presence in the shaker room, where the drilling crew members are exposed to skin contact with the drilling fluids, inhalation of possible toxic gasses associated with the drilling fluid, and loud noises due to the shale shakers.
The result of the density measurement is often just communicated verbally to the driller, who writes it in the report. Misunderstandings can occur due to bad communication. With
this system only a few members of the drilling crew are aware of the measured values. If the information was recorded, logged, and distributed to more personnel the probability of detecting severe changes would increase, and creation of trend lines and post well analysis would be possible [2].
Additional density measurements of the mud are required during drilling. The equivalent circulating density (ECD) is the actual density the drilling mud exerts on the borehole wall during circulation. It is highly affected by frictional forces. ECD is calculated from measurements of bottom hole pressure (BHP) and computed true vertical depth (TVD) from tracked measured depth (MD). The information obtained by the BHA is continu- ously communicated to surface by mud pulses. ECD values are recorded and monitored during the entire drilling operation to be able to detect changes in ECD. Changes could in worst case be caused by uncontrolled inflow from the formation to the well. Moni- toring ECD is also important for hole cleaning purposes and when drilling in formations with a narrow mud weight window between the pore pressure and the fracture gradient [5].
The equivalent static density (ESD) is also an important parameter. It is recorded when there is no circulation of the drilling mud, which is the case when doing a pipe connection.
The ESD is calculated from BHP and depth, in the same way as the ECD. The difference between the two measurements is the time they are obtained. When the tools in the BHA recognize that there is no circulation, due to mud pumps turned off, the pressure is mea- sured, TVD is computed from tracked MD, and ESD can be calculated. The maximum pressure recorded when the pumps are off can be considered the largest surge pressure when there is no circulation. The minimum pressure recorded can be considered the low- est swab pressure. The ESD is an important value in the equivalent mud weight (EMW), which is the parameter reported from formation integrity tests and leak-off tests [5].
5.2 Viscosity Measurements
The viscosity of the mud is important for the capability of the mud to carry cuttings out of the hole during circulation. Having control of the viscosity of the drilling fluid poses a substantial impact on hole cleaning. Gel strength is connected to viscosity and describes the ability of the mud to keep the cuttings in suspension when there is no circulation. Gel strength is required when making a connection. The cuttings are not circulated out of hole before making a connection, which means that cuttings can be present in the full length of the well. If the gel strength is insufficient the cuttings will quickly segregate towards the low side of the well. If there is a tool or equipment failure that prohibits further movement of the string and circulation, there is a serious risk of packing off the drillstring or BHA.
To restart circulation after a stop hydraulic power is required. If the gel strength is high the power required will be severe. The gel strength is usually not strong enough to keep cuttings suspended for a long time, and a long stop in circulation with cuttings in the hole will always lead to segregation of the cuttings, resulting in pack-offs [6].
Mud viscosity requires sampling in the same way as the density measurements. The vis- cosity can be measured using a Marsh funnel. It records the time it takes for a liter to be
discharged. The measurement for drilling mud is an approximation, as the Marsh funnel measurement is only fully correct for simple polymer solutions. The change in funnel viscosity is more informative than the absolute funnel viscosity of the fluid and is used to correlate changes in the viscosity of the drilling fluid [2]. Another method for measuring viscosity is by a rotational viscometer. A spindle is submerged into a sleeve containing the mud sample. The spindle is connected to a rotating motor shaft via a spring. The required force to overcome the resistance to rotation is measured, by recording the devi- ation angle between the spindle and the spring. Several different rotational speeds can be applied. Viscosity values can be read directly off the apparatus [22]. The previously de- scribed disadvantages with manual mud sampling by the drilling crew members also apply for measuring viscosity. The measurements of density and viscosity are often done during the same sampling [2].
5.3 Gas Measurements
In the daily drilling reports, several different gas parameters are reported. Background gas is the average measure of gas entrained in the circulating mud. Connection gas is the influx of gas into the mud during the time a connection is made. Trip gas is the gas entrained in the mud during tripping. Maximum gas is the gas produced from the volume of the cut- tings created during drilling [23]. The main reasons for recording the gas parameters are indicating well behavior as a safety measure and indicating hydrocarbon-bearing zones.
Gas measurements as influenced by the drilling operation and it is important to correlate the ongoing event with the measured gas. That is the reason why it is necessary to record the various gas parameters. Gas measurement is an important part of mud logging [24].
The wellbore is often open to atmospheric pressure. The returning mud goes from the bell nipple at the wellbore, through the flow line, and to the shale shakers. A gas trap is located somewhere along this path, usually in the shaker box, and is used to extract gas from the mud. The extracted gas is transported to the mud logging unit where a detection system is located. To get a representative measurement of the gas in the return mud the gas trap should be located as close to the wellbore as possible in order to limit the amount of gas extracted in the air at the drilling rig [24]. There are many different traps, such as the legacy trap, consistent volume extractor, semipermeable membrane, and the consistent volume and temperature extractor. During drilling, the rate of the return fluid will vary and the mud volume in the trap will change. This will in turn affect the amount of extracted gas and can lead to misinterpretations. Another factor that can influence gas interpretation is the temperature. Higher temperatures will lead to higher gas concentrations. The desire to have constant volume in the extractor can be solved by pumping a specific volume from the flowline into the gas trap. Constant temperature can be solved by heating the fluid to a set temperature before it enters the trap. Higher temperature allows for extraction of heav- ier hydrocarbon components. The complexity of the traps increases by these methods, but the accuracy and repeatability are improved [25].
Gas detection is often done by the use of gas chromatography, mass spectrometers, or a combination of the two [25]. Gas chromatography is a technique based on separating
analytes between two immiscible phases. The first phase is represented by the carrier gas and is a gaseous mobile phase. The second phase is represented by a capillary column, that can be both hollow or packed, and is an immobilized liquid phase or a stationary solid [26]. A mass spectrometer contains four main components. The first one is an ionizing chamber, where the analytes gain a positive or negative charge. The second component is a vacuum. The third component is a mass selector, where the analytes are accelerated through an electric field. The principle is that charge and kinetic energy can be correlated.
The lighter analytes have higher velocities and reach the detector first, which is the fourth main component [27].
5.4 Cuttings Measurements
Measuring the amount of cuttings that are transported out of the well can be used to eval- uate hole cleaning and wellbore conditions. Based on this evaluation drilling parameters can be optimized. As described previously, flow parameters affect the cuttings transport, and measuring cuttings in the return line is therefore used in the evaluation of the flow parameters [28].
There are several methods for measuring the amount of cuttings. Comparing the theoreti- cal and actual decrease in the active volume of drilling fluid is one of them. The increased volume of the borehole due to drilling should lead to a decrease in the active volume as the cuttings are transported out of the well. When the actual decrease in active volume is considerably smaller than the theoretical decrease it is an indication of insufficient hole cleaning [29].
The cuttings flow meter can continuously measure the return of cuttings. A model of a cuttings flow meter can be seen inFig. 5.1. The meter is located at the outlet of the shale shakers. A tray-shaped gutter collects the cuttings and the weight is recorded. Conversion to volume is done by bulk density measurements. After a set time period the gutter is flipped, and the cuttings are dumped into a ditch. A large screw conveyor is located in the ditch, transporting the cuttings further in the rig cuttings collection system. To make the transportation easier lubrication is added [30]. The shaker room is a harsh working environment. Excessive vibrations, corrosive fluids, and erosion from solids lead to high requirements for the equipment. Gas can also be present, and all equipment must be within the safety regulations for equipment exposed to gas, because this presents an environment where explosions are a possibility. Rig space is often a limitation for equipment, and this is usually also the case in the shaker rooms. The cuttings flow meter can not take up too much space, and there also needs to be access for the crew to perform maintenance and repairs of the cuttings flow meter and the other parts of the shale shakers [28].
A new type of cuttings transportation system has been implemented on many rigs. An overview of the system can be seen in Fig. 5.2. After the cuttings have gone over the shale shakers, they are offloaded in the ditch with the screw conveyor. The cuttings are further transported into a pneumatic transfer unit called a cuttings blower. The cuttings are transferred in a dense phase to large tanks on the main deck using pressurized air. The
Fig. 5.1– Schematic of a cuttings flow meter [28].
bulk storage tanks are not pressurized and have a load cell to measure the weight of cut- tings. When the tanks are full another screw conveyor and pneumatic transfer unit are used to transfer the cuttings to similar bulk storage tanks located on supply vessels. There are many advantages to the new system. Offloading cuttings from the rig to supply vessels is usually done by transferring the cuttings in skips by the use of rig lifting cranes. The new system reduces the number of rig crane operations, both internally on the rig and between the rig and the boat. This is a major risk improvement when it comes to HSSE. The time it takes to transfer the cuttings from the rig to the boat is shorter using the pneumatic transfer system, so time-saving is also a benefit. The bulk storage tank system occupies less space than the cuttings skips and is beneficial for limited rig space. A challenge with the system is that the cuttings blower can be a bottleneck for cuttings transportation, limiting the rate of penetration (ROP) during drilling [31].
A lot of information can be extracted from looking at the shale shakers. Circulation before pulling out of hole is measured in how many times the full volume of the well is circu- lated from the bottom and up. The desire is to circulate all the cuttings out of the well to avoid packing off the BHA when pulling out of hole and to optimize hole conditions before running casing. Generally, there will always be a return of cuttings from the well when circulating, and the end point of circulation must be determined by when the amount of cuttings in the return line is sufficiently low [28].
When circulating after drilling to TD, the size of the cuttings often decreases after circu- lating approximately one and a half times bottoms up. Experiments have shown that larger cuttings arrive at surface before the smaller ones, because the larger cuttings are easier to remove. As drilling with a high ROP leads to larger cuttings, the amount of cuttings over the shakers can also vary with ROP. Variation in cuttings concentration over the shakers in inclined wells can be due to the position of the drillstring in a build-up section during rotation. Rotating while drilling or running in hole will push the drillstring to the low side of the well stirring up the cuttings that have accumulated there. Rotating while pulling out of hole will drag the drillstring along the high side of the well and there is no stirring up of the cuttings [28].
Fig. 5.2– Overview of the cuttings transfer system using cuttings blowers [31].
Studying the solids that are separated from the flow at the shakers can give important infor- mation, such as the origin of the solids. Rounded, smaller solids are often cuttings, created by the bit during drilling. Edged and elongated solids can often be cavings, which is a result of wellbore instability. However, due to long transport distances, the solids are often eroded to small, rounded pieces, making it different to interpret the origin. When large amounts of cavings are seen at the shale shakers, drilling parameters should be adjusted to manage the borehole instability [30].
Chapter 6
Soft Sensing
Chapter 6 is taken directly from the TPG4560 project report by Steinsheim [1]. This chapter is included to provide an important foundation for the extended literature study conducted in Part I and for the flow loop project in Part II.
Soft sensing is the method of using measurable variables to estimate non-measurable vari- ables. When considering using soft sensing many elements needs to be investigated, such as what techniques are available, what non-measurable quantity is wanted, and which measurable variables are needed to compute it. Choosing the soft sensing approach can be justified if it is believed to be better and cheaper than existing methods of determining the non-measurable quantity. Soft sensing requires suitable models to describe the rela- tionship between the measured and the estimated variables. There are several different models that can be used, and they can be separated into two main groups. One group is based on theories of probability and the other is based on numerical optimization. The Kalman filter is a tool for estimating the statistically optimal state for linear systems. The numerical optimization approach is the preferable method when handling non-linearities and constraints. Computational time-consume is usually a disadvantage of the tool [32].
Soft sensing has been investigated as a method to optimize real-time downhole monitoring of flow. This can be measured directly, but existing meters are either costly, not able to obtain accurate measurements or not working optimally due to the harsh downhole condi- tions. The real-time downhole monitoring is a part of the smart wells movement with the incorporation of digital and automated processes in well operations. The goal is to opti- mize reservoir management for instance by using the information obtained from real-time monitoring to control inflow valves to the well. In multilateral wells, this can be used to close only the branch where water or gas breakthrough has occurred, instead of closing down the whole well. In single wells, it can be used to close in only one section of the well. The advantage of using downhole monitoring instead of surface monitoring to con- trol inflow valves is the short response time. Inflow changes are detected at an earlier stage
and can be dealt with faster, minimizing the consequences. Sand production is highly de- pendent on flow rate and eliminating it early can prohibit damage to both the connectivity and stability of the formation, as well as damage to equipment in the well and at surface [33].
De Kruif et al. [33] ran a series of simulations to investigate the use of soft sensing in moni- toring flow rates for two and three-phase flow in both unilateral and multilateral wells. The simulations were performed to test if downhole pressure and temperature readings were enough to estimate flow, together with dynamic multiphase flow models. Wellhead mea- surements were added if downhole measurements proved to be insufficient. The extended Kalman filter for non-linear systems was used to estimate the flow rates. It employs re- cursion, so the estimate is updated every time new information is available. For highly non-linear systems the extended Kalman filter will be inaccurate due to the applied lin- earization. A model of the downhole set-up for a unilateral well is seen inFig. 6.1.
Fig. 6.1– Model of the downhole set-up for a unilateral well [33].
For two-phase flow in a unilateral well, it was found that downhole measurements were enough to estimate the flow of liquid and gas. For three-phase flow in a unilateral well, the surface measurements are needed in addition, to be able to separate oil flow and water flow.
For two-phase flow in multilateral wells, the flow rates were estimated correctly since it is only based on downhole measurements in the different branches. The problem occurred when trying to estimate three-phase flow rates in a multilateral well. In the unilateral well, the surface measurements had to be added in order to estimate flow rates. The flow from the different branches in the multilateral well flow together in the riser up to the wellhead.
The surface measurements performed on the combined flow at surface were not able to correct the estimates of the different fluid flows in the branches downhole. The similar densities of water and oil led to inaccurate estimates of flow. This was adjusted by making the difference between the densities artificially large [33].
Lee and Zahrani [34] describe the development and implementation of soft sensors at the Abqaiq Plant in Saudi Arabia. It is the largest plant in the world for crude oil stabiliza-
tion. The soft sensors were used to monitor the amount of H2S in the oil, together with true vapor pressure (TVP) and Reid vapor pressure (RVP). To estimate these quantities pressure, temperature and flow rates were measured at several different segments of the process. The urge to develop soft sensors for estimating H2S, TVP, and RVP was due to the excessive work and cost required to maintain the existing analyzers. The estimates were based on recursion and a steady-state model together with dynamic synchronization.
The model was calibrated with 2 years of historical data from the plant, as well as data from a 20 days-long step test. The goal of the implementation was to achieve process control in an efficient and economical way.
H2S is a toxic gas and poses a threat to personnel and environment. It will also increase corrosion when a sufficient amount is present in crude oil. Controlling the amount of H2S is important for maximizing revenue. TVP is the equilibrium partial pressure employed by the crude oil at a specific temperature. It is important to monitor in order to avoid cavitation in pumps and vapor locks. TVP computations are often not accurate. RVP is easier to get accurate and can be used as an approximation of the TVP [34]). RVP is the absolute pressure needed to get a vapor/liquid ratio of 4 at 37.8 degrees Celsius [35].
Chapter 7
Real-time Downhole Data
7.1 Measurements While Drilling and Logging While Drilling
During the drilling process measurements while drilling (MWD) are performed for col- lection of data, process control, and optimization. Examples of parameters that can be measured are annular pressure, temperature, shock and vibrations, intensity of natural gamma-rays, revolutions per minute (RPM), and steering “tool face”. In more compli- cated formations it is also normal to perform logging while drilling (LWD). Examples of measurements are density, porosity, resistivity, seismic, sonic, caliper, and formation pres- sure. In addition, it is possible to take samples of the formation fluid that can be brought to surface and perform measurements that can “look” into the formation around the borehole and in front of the bit [36]. The MWD and LWD tools are usually located in the BHA, and an example of an advanced BHA is shown inFig. 7.1. The data can be transmit- ted to surface by several different telemetry technologies. The available bandwidth of the telemetry system is shared between the different MWD/LWD services.Fig. 7.2shows the distribution of a case investigated by Klotz et al. [37].
Fig. 7.1– Example of an advanced BHA [38].
Normally the power to run the MWD and LWD tools comes from downhole lithium batter- ies or turbines. With turbines, the hydraulic energy of the drilling mud is transformed into
Fig. 7.2– Bandwidth distribution of a case investigated by [37].
electrical energy used to power the downhole tools in the BHA. The method is effective, but the system has a high risk of wear and failure, as there are many moving parts and large amounts of fluids running through. The use of battery also has several challenges, including limitations for temperature and battery lifetime, required personnel to handle the batteries at rig site, and requirements for environmentally proper disposal with the asso- ciated costs. The complexity, cost, and length of the BHA are increased by the addition of downhole batteries and turbines. Adding to the length of the BHA means that some important MWD and LWD tools are pushed further up the string, which can lead to de- creased quality of the measurements and difficulties when it comes to directional drilling and steering of the BHA [36].
High data rates for telemetry are important during drilling to be able to utilize data from MWD and LWD tools, and thereby optimize drilling parameters, wellbore conditions, and drilling navigation. Increasing the amount of data that can be transmitted by telemetry will allow for more real-time data, for instance by higher log data density. More information available can help make well-educated decisions that can improve the drilling process, increase reservoir coverage, minimize drilling costs, and lead to a safer operation. Getting critical downhole information transmitted quickly to surface is also a safety measure, as dangerous situations can be detected rapidly [37]. The reduction in drilling cost can for example be accomplished by the improved data rates enabling an increase in ROP [38].
Steerable Bottom Hole Assemblies
To perform directional drilling a steerable BHA is utilized. The conventional approach was using a mud motor, together with a bent sub. The drillstring slides in the well while the mud motor rotates the drill bit. Building inclination or azimuth is accomplished by the angle in the bent sub. The method has issues with accuracy, restricted drilling distances, and irregular well trajectories. An alternative method, rotary steerable systems (RSS), was developed in the late 1980s and early 1990s. When drilling with RSS the entire drillstring is rotated by the top drive. Inclination and azimuth are controlled by rotating mechanisms
within the RSS tool. Downlinking is used to change the settings of the RSS tool during drilling. Steering commands are transmitted by series of mud pulses propagating down in the drillstring. The mud pulses are created by adjusting the flow rate at the mud pumps.
The RSS tool processes and decodes the pressure signal and adjusts the current settings accordingly, before sending a confirming signal back to surface using MWD technology.
Data is also stored within the memory of the RSS tool and can be accessed after the run is completed and the tool is retrieved at surface. To allow for the RSS tool settings to change the bit can be pulled off bottom, but downlinking can also be performed while drilling ahead, if the ROP is sufficiently low.Fig. 7.3shows examples of common RSS downlink sequence scenarios. Analyzing the RSS downlinking data can be used in evaluation of key performance indicators of the drilling process. Operational and economical aspects are considered when choosing between the two steerable BHA methods. The day rate of the RSS assemblies are usually higher than the day rate of the conventional assemblies. Which method is operationally favorable depends on the conditions of each specific scenario [39].
Fig. 7.3– Common RSS downlink sequence scenarios [39].
An example of how implementation of downhole tools led to process optimization is the improved directional drilling. Before the introduction of MWD technology, directional drilling was a very time-consuming process. To perform a survey, drilling had to be stopped and the string pulled off bottom and set in slips. The survey was then conducted by running a survey tool on slickline in the well, dropping a survey tool into the drillstring, or if the well was deviated, a survey tool had to be pumped down the string. The survey tools
