Contents

Cover

Title page

Copyright page

Preface

Acknowledgements

Chapter 1: Stories from the Field, Fundamental Questions and Solutions

1.1 Mysteries, Clues and Possibilities.
1.2 Paper No. AADE-11-NTCE-74 – “High-Data-Rate MWD System for Very Deep Wells.” Significantly expanded with additional photographs and detailed annotations.
1.3 References.

Chapter 2: Harmonic Analysis: Six-Segment Downhole Acoustic Waveguide

2.1 MWD Fundamentals.
2.2 MWD Telemetry Concepts Re-examined.
2.3 Downhole Wave Propagation Subtleties.
2.4 Six-Segment Downhole Waveguide Model.
2.5 An Example: Optimizing Pulser Signal Strength.
2.6 Additional Engineering Conclusions.
2.7 References.

Chapter 3: Harmonic Analysis: Elementary Pipe and Collar Models

3.1 Constant area drillpipe wave models.
3.2 Variable area collar-pipe wave models.
3.3 References.

Chapter 4: Transient Constant Area Surface and Downhole Wave Models

4.1 Method 4-1. Upgoing wave reflection at solid boundary, single transducer deconvolution using delay equation, no mud pump noise (Software reference, XDUCER*.FOR).
4.2 Method 4-2. Upgoing wave reflection at solid boundary, single transducer deconvolution using delay equation, with mud pump noise (Software reference, HYBRID*.FOR).
4.3 Method 4-3. Directional filtering – difference equation method requiring two transducers (Software reference, 2XDCR*.FOR).
4.4 Method 4-4. Directional filtering – differential equation method requiring two transducers (Software reference, SAS14D*.FOR, Option 3 only).
4.5 Method 4-5. Downhole reflection and deconvolution at the bit, waves created by MWD dipole source, bit assumed as perfect solid reflector (Software reference, DELTAP*.FOR).
4.6 Method 4-6. Downhole reflection and deconvolution at the bit, waves created by MWD dipole source, bit assumed as perfect open end or zero acoustic pressure reflector (Software reference, DPOPEN*.FOR).
4.7 References.

Chapter 5: Transient Variable Area Downhole Inverse Models

5.1 Method 5-1. Problems with acoustic impedance mismatch due to collar-drillpipe area discontinuity, with drillbit assumed as open-end reflector (Software reference, collar-pipe-open-16.for).
5.2 Method 5-2. Problems with collar-drillpipe area discontinuity, with drillbit assumed as closed end, solid drillbit reflector (Software reference, collar-pipe-closed-*.for).
5.3 References.

Chapter 6: Signal Processor Design and Additional Noise Models

6.1 Desurger Distortion
6.2 Downhole Drilling Noise.
6.3 Attenuation Mechanisms (Software reference, Alpha2, Alpha3, MWDFreq, datarate).
6.4 Drillpipe Attenuation and Mudpump Reflection (Software reference, PSURF-1.FOR).
6.5 Applications to Negative Pulser Design in Fluid Flows and to Elastic Wave Telemetry Analysis in Drillpipe Systems.
6.6 LMS Adaptive and Savitzky-Golay Smoothing Filters (Software reference, all of the filters in Sections 6 and 7 are found in C:\MWD-06).
6.7 Low Pass Butterworth, Low Pass FFT and Notch Filters.
6.8 Typical Frequency Spectra and MWD Signal Strength Properties.
6.9 References.

Chapter 7: Mud Siren Torque and Erosion Analysis

7.1 The Physical Problem.
7.2 Mathematical Approach.
7.3 Mud Siren Formulation.
7.4 Typical Computed Results and Practical Applications.
7.5 Conclusions.
7.6 References.

Chapter 8: Downhole Turbine Design and Short Wind Tunnel Testing

8.1 Turbine Design Issues.
8.2 Why Wind Tunnels Work.
8.3 Turbine Model Development.
8.4 Software Reference.
8.5 Erosion and Power Evaluation.
8.6 Simplified Testing.
8.7 References.

Chapter 9: Siren Design and Evaluation in Mud Flow Loops and Wind Tunnels

9.1 Early Wind Tunnel and Modern Test Facilities.
9.2 Short Wind Tunnel Design.
9.3 Intermediate Wind Tunnel for Signal Strength Measurement.
9.4 Long Wind Tunnel for Telemetry Modeling.
9.5 Water and Mud Flow Loop Testing.
9.6 References.

Chapter 10: Advanced System Summary and Modern MWD Developments

10.1 Overall Telemetry Summary.
10.2 Sirens, Turbines and Batteries.
10.3 References.

Chapter 11: MWD Signal Processing in China

Chapter 12: Sensor Developments in China

12.1 DRGDS Near-bit Geosteering Drilling System.
12.2 DRGRT Natural Azi-Gamma Ray Measurement.
12.3 DRNBLog Geological Log.
12.4 DRMPR Electromagnetic Wave Resistivity.
12.5 DRNP Neutron Porosity.
12.6 DRMWD Positive Mud Pulser.
12.7 DREMWD Electromagnetic MWD.
12.8 DRPWD Pressure While Drilling.
12.9 Automatic Vertical Drilling System – DRVDS-1.
12.10 Automatic Vertical Drilling System – DRVDS-2.

Chapter 13: Sinopec MWD Research

13.1 Engineering and Design Highlights.
13.2 Credits.

Chapter 14: Gyrodata MWD Research

14.1 Short and Long Wind Tunnel Facilities.
14.2 Credits.

Chapter 15: GE Oil & Gas MWD Developments (BakerHughes, a GE Company)

15.1 Recent Patent Publications.
15.2 Credits.
15.3 References.

Chapter 16: MWD Turbosiren – Principles, Design and Development

16.1 Background and Motivation.
16.2 Prototype Turbosirens and Experimental Notes
16.3 Pressure Measurement – Subtleties and Ideas.
16.4 Credits.
16.5 References.

Chapter 17: Design of Miniature Sirens

17.1 Siren flowmeter applications.
17.2 Mini-siren prototypes.
17.3. Cardboard test prototyping.
17.4 Credits.

Chapter 18: Wave-Based Directional Filtering

18.1 Background.
18.2 Theory and Difference-Delay Equations.
18.3 Calculated Results.
18.4 Conclusions.
18.5 References.

Cumulative References

Index

About the Author

End User License Agreement

List of Illustrations

Chapter 1

Figure 1.1a. Prototype single-siren tool (assembled).
Figure 1.1b. Prototype single-siren tool (disassembled).
Figure 1.2a. Example MWD collar used for siren frequency and source placement optimization analysis.
Figure 1.2b. Drillpipe p/Δp to 12 Hz.
Figure 1.2c. Drillpipe p/Δp to 50 Hz.
Figure 1.2d. Drillpipe p/Δp to 100 Hz.
Figure 1.3a. Three step pulse recovery from noisy environment.
Figure 1.3b. Three step pulse recovery (very noisy environment).
Figure 1.4a. Early 1980s “stable closed’ siren (left) and improved 1990s “stable-opened” downstream rotor design.
Figure 1.4b. Streamline traces for erosion analysis.
Figure 1.4c. Velocities for erosion and pressure analysis.
Figure 1.5a.1. Short “hydraulic” wind tunnel, or simply “short wind tunnel.”
Figure 1.5a.2. Short wind tunnel, “bird’s eye” perspective.
Figure 1.5b.1. Very long “acoustic” wind tunnel.
Figure 1.5b.2. Multiple transducer array for surface noise removal (top, accommodating multiple frequencies; bottom, one configuration used).
Figure 1.5c. A pair of ganged or tandem mud sirens.
Figure 1.5d.1. Siren concepts tested in wind tunnel (standard size).
Figure 1.5d.2. Evaluation of hub convergence effects.
Figure 1.5e.1. Siren concepts, miniature sirens for slim tools (the United States quarter shown is similar to the one-yuan Chinese coin).
Figure 1.5e.2. Siren concepts, miniature sirens for slim tools (cont’d).
Figure 1.5f.1. Flow straighteners for upstream and downstream use.
Figure 1.5f.2. Flow straightener construction.
Figure 1.5g.1. Digital flowmeter.
Figure 1.5g.2. Safety message – note plastic tape at right.
Figure 1.5h. Siren test sections with differential transducers for signal strength measurement (not influenced by reflections and propagating noise).
Figure 1.5i. Real-time data acquisition and control system.
Figure 1.5j. Torque, position and rpm counter.
Figure 1.5k. Water-cooled air blower with separate power source.
Figure 1.5l. Test shed window overlooking long wind tunnel.
Figure 1.5m. Single piezoelectric transducer closest to siren for constructive interference and nonlinear harmonic generation study.
Figure 1.5n. Distant multiple transducer array setup.
Figure 1.5.o.1. Chinese fireworks.
Figure 1.5o.2. Artificial low frequency “mud pump” noise.
Figure 1.5p.1. Lead author tests wind effects at the outlet.
Figure 1.5p.2. Volume flow sensor at long wind tunnel outlet characterizes frequency or wavelength-dependent effects.
Figure 1.5q. Early prototype tool.
Figure 1.5r. At work in the test shed.
Figure 1.5s. Short wind tunnel, with long wind tunnel connection.
Figure 1.5t. Short wind tunnel “alone.”
Figure 1.5u. Wind tunnel design and test planning (Bian Hailong).
Figure 1.5v. Wave interference ideas explained (Wilson Chin).
Figure 1.5w. Test shed, left; local restaurant, center, where experimental results and test plans were reviewed and updated daily; our simple hotel, right, residing next to a pumping unit, in contrast to –
Figure 1.5x. CNPC Headquarters, Beijing.
Figure 1.6a.1. Simultaneous signal strength and torque measurements.
Figure 1.6a.2. Siren Δp signal strength vs ω at with flow rate fixed.
Figure 1.6a.3. Siren torque versus ω at with flow rate fixed.
Figure 1.6b. Low-frequency (10 Hz) long wind tunnel data.
Figure 1.6c. Low-frequency (10 Hz) signal recovery.
Figure 1.6d. High-frequency (45 Hz) long wind tunnel data.
Figure 1.6e. High-frequency (45 Hz) signal recovery.

Chapter 2

Figures 2.1, 2, 3. Positive, negative and siren pulsers (left to right).
Figure 2.4. Positive and mud siren pulsers in various telemetry channels.
Figure 2.5. “Unwrapped” downhole MWD waveguide structure, to be compared with illustration in Figure 2.4a.
Figure 2.6. Classical wave amplification solutions.
Figure 2.7. “Typical” bottomhole assembly with mud motor.
Figure 2.8a. Transmission efficiency p/Δp in drillpipe and annulus.
Figure 2.8b. P_drillpipe/Δp in drillpipe versus source position and frequency.
Figure 2.8c. P_annulus/Δp in annulus versus source position and frequency.
Figure 2.9a. Graphical user interface.
Figures 2.9b,c. MWD signal entering drillpipe (left) and annulus (right).
Figure 2.10a. Drillpipe p/Δp to 12 Hz.
Figure 2.10b. Drillpipe p/Δρ to 24 Hz.
Figure 2.10c. Drillpipe p/Δp to 50 Hz.
Figure 2.10d. Drillpipe p/Δp to 75 Hz.
Figure 2.10e. Drillpipe p/Δp to 100 Hz.
Figure 2.10f. Drillpipe p/Δp to 200 Hz.
Figure 2.10g. Drillpipe p/Δp to 300 Hz.
Figure 2.10h. Drillpipe p/Δρ to 1,000 Hz.

Chapter 3

Figure 3.A.1. Different propagation modes.
Figure 3.B.1. Collar-pipe acoustic two-section waveguide.
Figure 3.B.2a. MWD signal, open reflector, dynamic rotatable view.
Figure 3.B.2b. MWD signal, open reflector, dynamic rotatable view.
Figure 3.B.2c. MWD signal, open reflector, static view.
Figure 3.B.2d. MWD signal, open reflector, static view.
Figure 3.B.2e. MWD signal, solid reflector.
Figure 3.B.2f. MWD signal, solid reflector.

Chapter 4

Figure 4.1a. Wave reflection at solid reflector.
Figure 4.1b. Wide signal – low data rate.
Figure 4.1c. Wide signal – low data rate.
Figure 4.1d. Narrow pulse width – high data rate (with widened green trace).
Figure 4.1e. Narrow pulse width – high data rate.
Figure 4.1f. 12 Hz low frequency carrier wave with phase shift keying.
Figure 4.1g. 24 Hz low frequency carrier wave with phase shift keying.
Figure 4.1h. 24 Hz low frequency carrier wave with phase shift keying.
Figure 4.1i. New high data rate 48 Hz carrier with PSK.
Figure 4.1j. Very, very high 96 Hz carrier with PSK.
Figure 4.2a. Wave reflection at solid reflector, with pump noise.
Figure 4.2b. 12 Hz carrier, phase shift in presence of large pump noise.
Figure 4.2c. 24 Hz carrier, phase shift with large pump noise.
Figure 4.3a. General bi-directional waves.
Figure 4.3b. MWD signal with pump noise (S/N = 1, approximately).
Figure 4.3c. Very noise environment, S/N about 0.25.
Figure 4.3d. Very, very noisy environment.
Figure 4.3e. Very, very, very noisy environment.
Figure 4.3f. MWD pulse in non-periodic noise (desurger distortion field).
Figure 4.4a. General bi-directional waves.
Figure 4.4b. Recovery of three step pulses from noisy environment.
Figure 4.4c. Recovery of three step pulses from very noisy environment.
Figure 4.4d. Bypass loop for multiple transducer implementation.
Figure 4.5a. Solid boundary reflection, waves from dipole source.
Figure 4.5b. Long, low data rate pulse.
Figure 4.5c. Higher data rate, faster valve action.
Figure 4.5d. PSK example, 12 Hz frequency.
Figure 4.5e. 24 Hz, coarse sampling.
Figure 4.6a. Open end bottom reflection, waves from dipole source.
Figure 4.6b. Rectangular pulse run.
Figure 4.6c. Higher data rate, narrower pulse (note distorted green trace).
Figure 4.6d. Phase-shift-keying, 12 Hz carrier (blue and black are identical).
Figure 4.6e. Phase-shift-keying, 24 Hz carrier wave.
Figure 4.6f. Phase-shift-keying, 48 Hz carrier wave.

Chapter 5

Figure 5.0. MWD collar – drillpipe area mismatch.
Figure 5.1a. MWD dipole pulser in drill collar and drillpipe system, with drillbit modeled as open-end reflector.
Figure 5.1b. Phase-shift-keying, 12 Hz carrier wave.
Figure 5.1c. Phase-shift-keying, 24 Hz carrier wave.
Figure 5.1d. Phase-shift-keying, 96 Hz carrier wave.
Figure 5.1e. Short rectangular pulse with rounded edges.
Figure 5.2a. Phase-shift-keying, 12 Hz carrier wave.
Figure 5.2b. Phase-shift-keying, 24 Hz carrier wave.
Figure 5.2c. Phase-shift-keying, 96 Hz carrier wave.
Figure 5.2d. Short rectangular pulse with rounded edges.

Chapter 6

Figure 6.1a. Desurger.
Figure 6.1b. “One-hundred feet hose” analogue signal amplifier.
Figure 6.1c. MWD signal distortion for low data rate pulsers (confirmed experimentally in mud loop tests).
Figure 6.2a. Positive displacement motor (see noise spectra in Figure 6.8a).
Figure 6.2b. Turbodrill motors.
Figure 6.3a. Newtonian model input form.
Figure 6.3b. Newtonian attenuation solutions.
Figure 6.3c. Non-Newtonian flow menu.
Figure 6.3d. Example non-Newtonian attenuation results.
Figure 6.4a. Wide signal – low data rate.
Figure 6.4b. Pressure versus “t” at given “x.”
Figure 6.6a. Raw unprocessed wave signal with random noise and propagating wave.
Figure 6.6b. LMS processed signal, with random noise removed by adaptive filtering.
Figure 6.6c. Savitzky-Golay smoothing filter.
Figure 6.7a. Low-pass Butterworth filter.
Figure 6.7b. Low-pass FFT filter.
Figure 6.7c. Notch filter.
Figure 6.8a. Signal strength harmonic distribution.
Figure 6.8b. Typical frequency spectrum for 12 Hz carrier signal.

Chapter 7

Figure 7.1. Early-to-late 1980s “stable-closed” design.
Figure 7.2. New 1990s “stable-opened” improvement.
Figure 7.3. A “stable-closed” four lobe siren used in flow loop tests.
Figure 7.4. Typical inviscid lift coefficient versus inclination.
Figure 7.5. Exact model and thin airfoil theory.
Figure 7.6. Exact model and approximate thin engine nacelle theory.
Figure 7.7. Three-dimensional mean surface approach.
Figure 7.8. Basic mud siren with upstream swirl.
Figure 7.9. Three-dimensional mud siren with annular passages.
Figure 7.10.1 Annular passage flow examples (refer to the “inlet cones” tested for signal influence).
Figure 7.10.2 Example for guided flow device.
Figure 7.11. Aerodynamic cascade problem.
Figure 7.12. Periodic cascade of upstream and downstream lobes.
Figure 7.13. Periodic boundary value problem flow domain.
Figure 7.14. Streamline patterns at different degrees of closure.
Figure 7.15. Velocities for erosion prediction at different degrees of closure.
Figure 7.16. Run A siren torques.
Figure 7.17. Run B siren torques.
Figure 7.18. Run C siren torques.
Figure 7.19. Run I siren torques.
Figure 7.20. Run E siren torques.
Figure 7.21. Run F siren torques.
Figure 7.22. Run G siren torques.
Figure 7.23. Run H siren torques.
Figure 7.24. Run I siren torques.
Figure 7.25. Run F siren torques.

Chapter 8

Figures 8.1 and 8.2. Single-stage MWD turbine versus multistage jet engine.
Figure 8.3. Spanwise pressure loading as function of rotor tip clearance (rotor tips do not support transverse pressure loadings).
Figure 8.4. Qualitative comparison, aircraft versus MWD turbines.
Figure 8.5. Kinematic viscosity versus temperature for various fluids.
Figure 8.6. Torque and power versus ω. Also, ω_NL versus axial speed U.
Figure 8-7. Wind vs mud performance utility.
Figure 8-8a. Wind tunnel torque (foot-1bf)
Figure 8-8b. Wind tunnel power (note units).
Figure 8.8c. Torque in mud test.
Figure 8.8d. Power in mud test.
Figure 8-9. Doubling volume flow rate.
Figure 8-10a. Mud torque with flow rate doubled.
Figure 8-10b. Mud power with flow rate doubled.
Figure 8.11. Stall torque versus flowrate.
Figure 8.12. No-load rpm versus speed.
Figure 8.13. Power versus rpm (experimental data indicated).
Figure 8.14. Torque results.
Figure 8.15. Rotor tip erosion (left), stator trailing edge erosion (right).
Figure 8.16. Tip vortex flows, high lift aircraft (left), computer simulation (middle), and flow visualization (right).
Figure 8.17a. Aerospace blade rows with shrouds.
Figure 8.17b. Turbine prototypes with and without shroud.
Figure 8.17c. Blade twist, aerospace designs (pressure variations in spanwise direction clearly evident).
Figure 8.17d. Blade twist, downhole turbine concept.
Figure 8.18. Turbine test setup (top, conceptual; bottom, implementation – also shown, reflective tape attached to black “torque wheel”).
Figure 8.19. Flexible rubber airfoil with copper skeleton.
Figure 8.20. Wind tunnel concepts for preliminary evaluation.

Chapter 9

Figure 9.1. Very early (historical) short wind tunnel.
Figure 9.2a. Short wind tunnel test system.
Figure 9.2b. Long wind tunnel system with pressure transducers (see Figure 1.5b.1 for additional photos).
Figure 9.3. Short wind tunnel in horizontal table-top position.
Figure 9.4a. Simple stable-closed siren.
Figure 9.4b. Conceptual measurement of restoring torque.
Figure 9.4c,d. Self-spinning “turbosiren” designed in wind tunnel and validated in mud flow loop (U.S. Patent 5,831,177).
Figure 9.5. Siren torque from numerous mud tests fit to single straight line (results applicable to a research design never used commercially).
Figure 9.6. Eroded turbine rotor tips and siren lobes, both from vortex damage.
Figure 9.7a. Stationery “ball in cage” in straight flow.
Figure 9.7b. Rotating “ball in cage” in recirculating vortex flow.
Figure 9.8. Different propagation modes (identical to Figure 3-A-1).
Figure 9.9a. Single transducer speaker test set-up.
Figure 9.9b. Siren signal test set-up explained in detail.
Figure 9.10a. Signal strength amplitude spectrum measured in wind tunnel.
Figure 9.10b. Time (left) and frequency domain (right) displays.
Figure 9.10c. Experimental CNPC results, Δp versus frequency.
Figure 9.11. Three pressure disturbance modes.
Figure 9.12a. Early long wind tunnel wound on small diameter reels.
Figure 9.12b. Mechanical siren layout, hydraulic and control system, electrohydraulic and angular velocity control servomechanisms from Gardner (2002).
Figure 9.13. Siren control and signal processing station.
Figure 9.14. Siren test concepts, test section for both air and mud.
Figure 9.15. Measured frequency-shift-keying and periodic signals (not quite the perfect sinusoids shown in common illustrations!).
Figure 9.16a. Wood prototypes used for torque and erosion testing.
Figure 9.16b. Wind tunnel forerunner to turbosiren (U.S. Patent 5,831,177).
Figure 9.16c. Sirens in series (left) and “swept” rotors (right, middle).
Figure 9.17. Wind test fixture used in mud and field tests (Gardner, 2002).
Figure 9.18. Lousiana State University 9,460 feet flow loop.
Figure 9.19. Halliburton 11,000 feet flow loop.
Figure 9.20. Simple “one hundred feet hose” analogue signal amplifier.
Figure 9.21. Drillbits with different nozzle sizes.
Figure 9.22. Multiple mud sirens in series (U.S. Patent No. 5,583,827).
Figure 9.23. Turbosirens in series (U.S. Patent 5,831,177).
Figure 9.24. Erosion flow loop.
Figure 9.25. Conceptual attenuation test fixture.

Chapter 10

Figure 10.1. A typical resistivity-at-bit (or, “RAB”) tool.
Figure 10.2a,b,c. Six-segment acoustic waveguide results.
Figure 10.3. Six-segment acoustic waveguide assumptions.
Figure 10.4. Section view, a pair of ganged or tandem mud sirens (e.g., see U.S. Patent No. 5,583,827 for details).
Figure 10.5. From Presco Inc. website, on siren pulsers (http://www.prescoinc.com/science/drilling.htm in April 2011 – – this page is no longer available).
Figure 10.5. From Presco Inc. website, on siren pulsers, continued (http://www.prescoinc.com/science/drilling.htm in April 2011 – – this page is no longer available).
Figure 10.6a. Recovery of three step pulses from noisy environment.
Figure 10.6b. Recovery of three step pulses from very noisy environment.
Figure 10.7. Critical frequency calculation.
Figure 10.8. Cumulative results, critical carrier frequencies.
Figure 10.9. Critical frequencies, hypothetical MWD tools.

Chapter 11

Figure 11.1. High temperature environmental effects.
Figure 11.2. Signal processing, PSK methods (CNPC).
Figure 11.3. Downlink strategies for rotary steerable systems.
Figure 11.4. Signal processing (CNPC).
Figure 11.5. Delay line methods for pump noise removal (CNPC).
Figure 11.6. Wind tunnel simulation for signal processing (CNPC).
Figure 11.7. Neural network approaches (CNPC).
Figure 11.8. Wind tunnel simulation methods for signal processing.
Figure 11.9. Wind tunnel analysis.
Figure 11.10. Nonlinear signal processing approach (CNPC).
Figure 11.11. Signal processing.
Figure 11.12. Signal processing, adaptive filtering methods (CNPC).
Figure 11.13. Downhole turbine design (CNPC).
Figure 11.14. Theoretical considerations (CNPC).
Figure 11.15. Signal processing, modern “compressive sensing.”
Figure 11.16. Computational siren torque analysis (CNPC).
Figure 11.17. Signal processing (CNPC).
Figure 11.18. Signal processing.
Figure 11.19. Downlink design.
Figure 11.20. Magnetic dipole analysis.
Figure 11.21. Signal transmission.
Figure 11.22. Inertial sensing.
Figure 11.23. PDM borehole technology.
Figure 11.24. Horizontal wells.
Figure 11.25. MWD analysis.
Figure 11.26. Mud pulse signal processing.
Figure 11.27. Drillstring vibrations.
Figure 11.28. Signal processing.
Figure 11.29. Siren design.
Figure 11.30. Signal detection.
Figure 11.31. Electromagnetic design.
Figure 11.32. Electromagnetic design.
Figure 11.33. Electromagnetic design.
Figure 11.34. Electromagnetic design.

Chapter 12

Figure 12.1-1. DRGDS tool architecture.
Figure 12.1-2. CAIMS tool architecture and hardware.
Figure 12.1-3. WLRS tool architecture.
Figure 12.1-4. DRMWD tool architecture.
Figure 12.1-5. Near-bit resistivity measurement.
Figure 12.1-6. Near-bit measurement sub configuration.
Figure 12.1-7. Near-bit measurement sub.
Figure 12.1-8. Downhole information wireless electromagnetic short transmission overview.
Figure 12.1-9. Near-bit parameter measurement.
Figure 12.1-10. Near-bit information wireless short transmission.
Figure 12.1-11. Downhole information transmission to surface.
Figure 12.1-12. Adjusting tool face and bent angle of bent housing assembly.
Figure 12.1-13. Resistivity measurement depth of investigation and transmitter position.
Figure 12.1-14a. Mr. Ning Sun, President, CNPC Drilling Engineering Technology Research Institute, addressing conference attendees.
Figure 12.1-14b. CNPC DRGDS geosteering system.
Figure 12.1-14c. Dr. Yinao Su, co-author, introducing CNPC’s DRGDS geosteering and EILog surface systems.
Figure 12.1-14d. EILog surface system and sample CFDE screen.
Figure 12.1-15a. Conventional geosteering.
Figure 12.1-15b. Near-bit geosteering.
Figure 12.1-16a. Field test activities.
Figure 12.1-16b. Field test activities.
Figure 12.2-1a. DRGRT configuration (English).
Figure 12.2-1b. DRGRT configuration (Chinese).
Figure 12.2-2a. Geological parameter measurement sub (English).
Figure 12.2-2b. Geological parameter measurement sub (Chinese).
Figure 12.2-3a. Data measurement overview (English).
Figure 12.2-3b. Data measurement overview (Chinese).
Figure 12.2-4. Field test and tool preparation for downhole operation.
Figure 12.2-5a. DRNBLog tool configuration (English).
Figure 12.2-5b. DRNBLog tool configuration (Chinese).
Figure 12.4-1. Resistivity tool (note antenna slots).
Figure 12.5-1. Well calibration.
Figure 12.5-2. Well calibration -Indoor adjustments and tank test.
Figure 12.5-3. Neutron generator performance test.
Figure 12.5-4. First, second and third tests, top to bottom.
Figure 12.5-5. Data read-out.
Figure 12.6-1. High pressure test facility and test, top; full-scale MWD system simulation facility and test site, center and bottom.
Figure 12.7-1. DREMWD system transmission path.
Figure 12.7-2. Drill collar and surface electric field.
Figure 12.7-3a. Hardware display.
Figure 12.7-3b. Hardware display.
Figure 12.7-3c. Hardware display.
Figure 12.8-1a. DRPWD system configuration (English).
Figure 12.8-1b. DRPWD system configuration (Chinese).
Figure 12.8-2. Downhole equipment assembly.
Figure 12.8-3. 6.75 in (left) and 4.75 in (right) downhole annular pressure measurement sub.
Figure 12.8-4. Product announcement.
Figure 12.9-1. DRVDS-1 tool architecture and hardware.
Figure 12.9-2. DRVDS-1 tool architecture and hardware.
Figure 12.9-3a. Test fixtures.
Figure 12.9-3b. Test fixtures.
Figure 12.9-3c. Test fixtures.
Figure 12.9-4. Field testing.
Figure 12.10-1. DRVDS-2 tool architecture and hardware.

Chapter 13

Figure 13.1. Sinopec headquarters, Houston and Beijing.
Figure 13.2. Author providing Sinopec MWD seminar in Dongying City.
Figure 13.3. Prototype turbine and “turbosiren” in discussion.
Figure 13.4. Reviewing flow loop test facilities.
Figure 13.5a. Sinopec MWD wind tunnel.
Figure 13.5b. Sinopec MWD wind tunnel.
Figure 13.5c. Sinopec MWD wind tunnel.
Figure 13.5d. Sinopec MWD wind tunnel.
Figure 13.5e. Sinopec MWD wind tunnel.
Figure 13.6. Sample rotor and stator prototype test pairs (two, three and four lobe designs shown).
Figure 13.7. Disassembled turbosiren prototype (rotor reflective tape for optical tachometer measurememts).
Figure 13.8. Turbosiren in motion (right).
Figure 13.9. Dongying, Shandong MWD technical staff.
Figure 13.10. Sinopec management, Houston headquarters, with author.

Chapter 14

Figure 14.1. Gyrodata headquarters in Houston.
Figure 14.2. Short wind tunnel for torque, erosion and signal testing.
Figure 14.3. Long wind tunnel for telemetry testing and signal processing.
Figure 14.4a. Plastic test prototype.
Figure 14.4b. Plastic test prototype.
Figure 14.4c. Plastic test prototype.
Figure 14.5a. Wind tunnel test section.
Figure 14.5b. Wind tunnel test section with test prototype.
Figure 14.5c. Illumination for (helium soap bubble) flow visualization.
Figure 14.6. Upstream flow straighteners create uniform conditions.
Figure 14.7. Neutrally buoyant helium-filled soap bubbles flow past tool prototype to visualize erosion-causing fluid paths – inexpensive modeling clay modifications are rapidly re-tested, useful fixes are identified, and refined hardware is shipped for more comprehensive field evaluation.
Figure 14.8. Neutrally buoyant helium soap bubble generator shown with high speed camera to record flowlines and streaklines.
Figure 14.9. Computerized flow loop control (top), real-time remote monitoring and sharing (middle), automatic movie creation (bottom).
Figure 14.10. Streamline enhancement by digitally “stacking” multiple stored video frames to enhance physical understanding.
Figure 14.11. Computational fluid dynamics (CFD) capabilities used to simulate observed phenomena – here, calculated vortex bubble correlates with location of empirically observed erosion – rapid experiments were enabled using modeling clay changes to wind tunnel prototypes.
Figure 14.12. Summary screen events recorded to movie.
Figure 14.13. Desirable features found experimentally are automatically captured in CAD update files.
Figure 14.14. Computational fluid dynamics (CFD) results checked for physical consistency against wind tunnel observations.

Chapter 15

Figure 15.1. Oil and Gas Technology Center (Oklahoma City).
Figure 15.2a. MWD “sandwich” siren patent application.
Figure 15.2b. MWD “sandwich” siren patent application.
Figure 15.2c. MWD “sandwich” siren patent application.
Figure 15.2d. MWD “sandwich” siren patent application.
Figure 15.2e. MWD “sandwich” siren patent application.
Figure 15.2f. MWD “sandwich” siren patent application.
Figure 15.3. Generic (non-GE) mud siren with rotor and stator plates.
Figure 15.4. A pair of ganged or tandem mud sirens.
Figure 15.5a. Advanced MWD signal processing patent award.
Figure 15.5b. Advanced MWD signal processing patent award.
Figure 15.5c. Advanced MWD signal processing patent award.
Figure 15.5d. Advanced MWD signal processing patent award.
Figure 15.5e. Advanced MWD signal processing patent award.
Figure 15.5f. Advanced MWD signal processing patent award.
Figure 15.5g. Advanced MWD signal processing patent award.
Figure 15.5h. Advanced MWD signal processing patent award.

Chapter 16

Figure 16.1. Mud siren schematic, three-lobe design in sketch.
Figure 16.2. Generic mud siren, six-lobe design shown.
Figure 16.3. Card-board siren with “stable closed” characteristics.
Figure 16.4a. “Rotor downstream, stable open” mud siren.
Figure 16.4b. “Rotor downstream, stable open” mud siren.
Figure 16.5a. MWD “turbosiren” pulser.
Figure 16.5b. MWD “turbosiren” pulser.
Figure 16.5c. MWD “turbosiren,” “sirens in series” very high signal strength pulser.
Figure 16.5d. MWD “turbosiren” pulser.
Figure 16.6. Turbosiren hardware and wind tunnel prototype.
Figure 16.7. “Single turbosiren” – rotor moves with shaft supported on bearings installed in left stator and right turbine (top); test section without flow straighteners (middle); and test section with flow straighteners (bottom).
Figure 16.8. Wheel for stall torque measurement (tangent linear force times radius gives torque at any prescribed volume flow rate).
Figure 16.9. Linear force gauges for torque measurement (several used to cover wide range of force magnitudes).
Figure 16.10. Differential pressure signal measurement.
Figure 16.11. Alternative flow straightener designs.
Figure 16.12. Two-stage turbosiren with flow straighteners and torque wheel.
Figure 16.13. Three-stage turbosiren (pressure ports for Δρ measurement circled at left and right).
Figure 16.14. Reference power turbine.
Figure 16.15. Turbine assemblies with pressure compensation module.
Figure 16.15. Two-stage turbosiren with pressure compensation module.
Figure 16.16. CAD rotation animations for design validation.
Figure 16.17. 3D printing setup for turbosiren components.
Figure 16.18. Rotors and stators with different lobe numbers and tapers (a Chinese yuan and a United States quarter, top).
Figure 16.20. Single, dual and triple turbosiren test models – straight, zero taper rotors and stators used for all tabulated data – triple turbosiren RPM and torque data unavailable since shafts of joined units are not connected.
Figure 16.21. Signal strength, frequency and torque versus volume flow rate and siren number.
Figure 16.22. Signal strength, Δp frequency spectrum and harmonics (wide “spikes” or lines due to test assembly vibration and blower noise).
Figure 16.23. Baseline zero-taper rotor configuration.
Figure 16.24. Signal strength and frequency versus GPM.
Figure 16.25. Signal strength and frequency versus GPM.
Figure 16.26. Signal strength and frequency versus GPM.
Figure 16.27. Signal strength and frequency versus GPM.
Figure 16.28a. Flow straightener, wind anemometer and force gauge.
Figure 16.28b. Axial turbine with rotating reflector disk for optical tachometer RPM measurement.
Figure 16.29. Pin-wheel toy, conventional turbine and turbosiren.
Figure 16.30. Wind tunnel axial turbine data.
Figure 16.31. Turbine design software.
Figure 16.32. Performance characteristics in air.
Figure 16.33. Extrapolated performance in water at 400 GPM (producing about 3,000 watts peak power).
Figure 16.34. Extrapolated performance in water at 150 GPM (producing about 150-160 watts peak power)
Figure 16.35. Combined signal data from Test Series A and B.
Figure 16.36. Dongying, Shandong MWD technical staff.

Chapter 17

Figure 17.1. Simple desk-top test fixture.
Figure 17.2. Miniature prototypes, plastic model and machined.
Figure 17.3. Mini-siren, about one inch across, with low friction bearings (the quarter is about the size of a Chinese yuan).
Figure 17.4. Downstream rotor with parallel tapers.
Figure 17.5. Four different mini-sirens.
Figure 17.6. Close-up of straight rotor mini-siren.
Figure 17.7. Close-up of notched mini-siren design.
Figure 17.8. Close-up of tapered rotor.
Figure 17.9. Hair dryer test of mini-siren, high speed rotation at bottom (sound video available on request).
Figure 17.10. Modeling drillbit reflections and siren position in collar – “MWD drill collar assembly” installed in long instrumented PVC tubing.
Figure 17.11. Low torque, non-jamming, reversible bi-directional flow – note water vapor on plastic tubing as author breathes in and out.
Figure 17.12. Cardboard siren with paper clip shaft.
Figure 17.13. Siren installed in open plastic bottle, with hair dryer used to identify “stable closed” properties.
Figure 17.14. Very early (historical) short wind tunnel.

Chapter 18

Figure 18.1a - Method 4-3, A-002 (8 feet).
Figure 18.1b - Method 4-3, A-003 (12 feet).
Figure 18.1c - Method 4-3, A-004 (16 feet).
Figure 18.1d - Method 4-3, A-005 (20 feet).
Figure 18.1e - Method 4-3, B-002 (8 feet).
Figure 18.1f - Method 4-3, B-004 (16 feet).
Figure 18.1g - Method 4-3, A-002 (8 feet).
Figure 18.1h - Method 4-3, A-003 (12 feet).
Figure 18.1i - Method 4-3, A-004 (16 feet).
Figure 18.1j - Method 4-3, A-005 (20 feet).
Figure 18.1k - Method 4-3, B-003 (12 feet).
Figure 18.1l - Method 4-3, B-006 (24 feet).
Figure 18.1m - Method 4-3, A-002 (8 feet).
Figure 18.1n - Method 4-3, A-004 (16 feet).
Figure 18.1o - Method 4-3, A-006 (24 feet).
Figure 18.1p - Method 4-3, B-006 (24 feet).
Figure 18.1q - Method 4-3, B-008 (32 feet).
Figure 18.2a - Method 4-4, Run C-1.
Figure 18.2b - Method 4-4, Run C-2.
Figure 18.2c - Method 4-4, Run C-3.
Figure 18.2d - Method 4-4, Run C-4.
Figure 18.2e - Method 4-4, Run C-5.

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Library of Congress Cataloging-in-Publication Data
ISBN 978-1-119-47915-4

Preface

The physical theories behind Measurement-While-Drilling design should be rich in scientific challenges, engineering principles and mathematical elegance. To develop the next generation of high-data-rate tools, these must be understood and applied unfailingly without compromise. But one does not simply peruse the latest petroleum books, state-of-the-art reviews, or the most recent patents to understand their teachings. Most descriptions are just wrong. The science itself does not exist. All simply rehash hearsay and misconceptions that have proliferated for more than three decades – recycled street narratives and folklore about sirens, positive and negative pulsers, and yes, mud attenuation; over-simplified product brochures from oil service companies that monopolize the industry; and, unfortunately, all preach the same complaints about low data rates and industry’s failure to address modern logging needs.

The truth is, there have been no substantive developments in MWD telemetry and design over the years. Not one paper has appeared that deals with telemetry in a manner worthy of scientific publication. New tools, more like muscle-machines than intelligent instruments, are designed without regard for acoustic concepts, while signal optimization and surface processing, more often than not based on “hand-waving” arguments, proceed without guidance from wave equation models. True, tools are better engineered; mechanical parts erode less, pulser modulation is controlled more reliably, high-powered microprocessors have replaced simple circuit boards, electronic components survive higher temperatures and pressures, and overall reliability is impressive, all of which enables the logging industry to reach deeper targets. However, these are incremental improvements unlikely to change the big picture. And the big picture is bleak: unless conceptual breakthroughs are made, the present low datarate environment is likely to persist.

Through this rapid progress, several disturbing problems are apparent. The author, having consulted for established as well as start-up companies over the past twenty years, is aware of no comprehensive theory addressing MWD acoustics. There are no university courses developed to educate the next generation of telemetry designers. The one-dimensional wave propagation models that are available are no more sophisticated that organ acoustics formulas from Physics 101. And tight-lipped service companies have been reluctant to publicize their failings, for obvious reasons, a business decision that has stymied progress in an important commercial endeavor. But unless companies are willing to share ideas and experiences, no one will benefit.

All of this is not new to science and certainly not unique to the commercialization of new products. The aerospace industry, decades ago just as subdued and secretive, suffered from similar failings. In that era though, just as the author completed his Ph.D. from the Massachusetts Institute of Technology in aerospace engineering, companies like Boeing, Lockheed and McDonnell-Douglas, for instance, finally recognized that the best way forward was free dissemination of scientific methods and ideas. Engineers openly carried their Fortran decks from one company to the next, published their findings in open journals and debated their ideas with new-found colleagues near and far. Increased employment mobility only increased idea dissemination more rapidly. The rest is history: the Space Shuttle, the Space Station, the 767, 777 and 787. It is in this spirit that the present book is written: intellectual curiosity and honesty and a genuine interest to see MWD data rates improve.

The author, no new-comer to MWD, earned his stripes at Schlumberger and Halliburton, managing MWD telemetry efforts that developed and refined new hardware concepts and signal processing techniques. However, research funding was fragmented and scientific objectives were unclear. Knowing the right questions, it is understood, solves half the problem. But it was not until the new millenium that progress in the formulation and solution of rigorous wave equation models took hold. Numerical models, notorious for artificial dissipation and dispersion, that is, phase error, were abandoned in favor of more challenging exact analytical solutions. Physical principles could, for once, be clearly understood. New methods to model acoustic sources were developed and special studies were initiated to define broad classes of noise together with the requirements for their elimination. New experimental procedures based on acoustics models were designed, as were special “short” and “long wind tunnels” that accommodated subtle physical mechanisms newly identified.

Theories and models, even the most credible, can be incorrect. In the final analysis, well designed experiments are needed to validate or disprove new ideas. In this regard, China National Petroleum Corporation (CNPC) offered to build laboratory facilities, test siren designs, educate staff and evaluate new telemetry methods, and importantly, to share its results and technology openly with the petroleum industry.

A comprehensive project overview was first presented by CNPC authors in “High-Data-Rate Measurement-While-Drilling System for Very Deep Wells,” Paper No. AADE-11-NTCE-74, at the American Association of Drilling Engineers’ 2011 AADE National Technical Conference and Exhibition, Houston, Texas, April 12-14, 2011. The paper summarized key ideas and results, but given page limits, could not provide details. All theoretical and experimental methods are now explained and summarized in this book, with numerous examples, providing useful tools to students and designers alike – our signal processing methods, dealing with signal reflection, distortion and optimization, are formulated, solved, validated and described for the first time.

In addition, we offer a new prototype roadmap for high-data-rate MWD that has found strong support from knowledgeable industry professionals. Since publication of the above paper, numerous commercial drivers have made high data-rate telemetry needs increasingly urgent. In the “old days,” conventional well logging data, e.g., resistivity, sonic or positioning, was simply transmitted to the surface for monitoring and evaluation. However, recent trends call for near-bit geosteering and rotary-steerable capabilities, in support of real-time economic and pore and annular pressure measurements. Despite their importance, few industry publications or websites provide “behind the scenes” descriptions of tool and software development processes, offering little to newer engineers eager to understand the technology – an unfortunate circumstance occurring even as the industry’s “great crew change” takes place.

To fill this need, China National Petroleum Corporation (CNPC) had encouraged us to document in detail its engineering processes, new tools and well logging sensors, in a comprehensive collection of laboratory and field photographs. Much of this work parallels ongoing developments in the West and sheds considerable insight into the country’s efforts to embrace high technology, e.g., stealth fighters, moon missions, fast computers and deep-sea submersibles, and its new-found open-ness in sharing its intellectual property. This book captures the spirit of MWD engineering in China – we also provide recent paper abstracts and describe advanced sensor development activities.

Importantly, since the appearance of first edition of this book, other organizations have adopted our ideas and methods, among them Gyrodata, GE Oil & Gas, Sinopec and others. It is the author’s hope that the newer insights offered in the following chapters will contribute to the industry’s expertise in developing more sophisticated and reliable telemetry devices. We have developed an exciting technology and are confident that the best is yet to come.

Wilson C. Chin, Ph.D., M.I.T.
Houston, Texas
Email: wilsonchin@aol.com
Phone: (832) 483-6899

Acknowledgements

The author gratefully acknowledges the insights, experiences and friendships he has acquired during his numerous MWD activities over the years with Schlumberger, Halliburton, GE Oil & Gas, China National Petroleum Corporation, Sinopec and others – pleasant memories that much more than compensate for the frustrations and sleepless nights brought upon by the challenges of high data rate telemetry.

What started as a simple wind tunnel long ago, constructed from plastic tubing, a squirrel cage blower and several balsa wood models, has evolved into a useful technology with a life of its own – one that will no doubt benefit the petroleum industry for years to come. The work reported here would not have been possible without the dedication and contributions of many talented people, among them,

Professor Yinao Su, Academician, Chinese Academy of Engineering, and his able colleagues Limin Sheng, Lin Li, Hailong Bian and Rong Shi with Drilling Engineering at the China National Petroleum Corporation (CNPC) in Beijing,
Shan Li, Hai Ma and Jin Zhou Yang, with MWD Research at Sinopec Shengli Oilfield in Dongying,
Professor Wenxiao Qiao, with the Chinese University of Petroleum, in Dongying and Beijing,
Stephen Bonner, Marcus Cantu, Robert Jan, Onyemelem Jegbefume, Rob Kirby, Adrian Ledroz, Eugene Linyaev, James Riley, John Rogers, Siddharth Shah, Rob Shoup and Gary Uttecht with Gyrodata in Houston,
Stewart Brazil, Kamil Iftikhar, Jihan Jiang, Paul Reeves and Shadi Saleh with GE Oil & Gas in Houston, and last but not least,
Jose Trevino and Larry Leising, previously with Schlumberger, who introduced this author to MWD technology and importantly guided his initial work more than two decades ago.