the drilling optimization benefits of di

SPE/IADC-173112-MS

The Drilling Optimization Benefits of Direct Drillstring Surface Measurements−Case Studies from Field Operations Robert Wylie, SPE, Ian Soukup, SPE, Henry Mata, SPE, and Sean Cuff, SPE, National Oilwell Varco, and Anthony Ho, SPE, The University of Texas at Austin Copyright 2015, SPE/IADC Drilling Conference and Exhibition This paper was prepared for presentation at the SPE/IADC Drilling Conference and Exhibition held in London, United Kingdom, 17–19 March 2015. This paper was selected for presentation by an SPE/IADC program committee following review of information contained in an abstract submitted by the author(s). Contents of the paper have not been reviewed by the Society of Petroleum Engineers or the International Association of Drilling Contractors and are subject to correction by the author(s). The material does not necessarily reflect any position of the Society of Petroleum Engineers or the International Association of Drilling Contractors, its officers, or members. Electronic reproduction, distribution, or storage of any part of this paper without the written consent of the Society of Petroleum Engineers or the International Association of Drilling Contractors is prohibited. Permission to reproduce in print is restricted to an abstract of not more than 300 words; illustrations may not be copied. The abstract must contain conspicuous acknowledgment of SPE/IADC copyright.

Abstract

Correct information is crucial to drilling effectiveness and well construction success, with the greatest data accuracy achieved by measurement instruments applied as close as possible to the target load. Until recently, most drilling parameters were derived from load measurements taken on supporting structures or equipment related to the drillstring—but not actually a part of the string. The remote position of these classic sensors from the desired load often resulted in unacceptable error rates.

SPE/IADC 163475 proposed a direct measurement system, designed by integrating drilling instrumentation into a standard top drive internal blow out preventer (IBOP). The instrumented IBOP (IIBOP) makes direct-load measurements of drilling parameters along the drillstring—just below the main shaft of the top drive—thereby circumventing the errors of the traditional measurements. This provides the timely, directly measured data needed to characterize drillstring phenomena required for drilling and equipment optimization purposes, without the mechanical losses of the traveling system. The system’s primary purpose is to provide early warning signs of system failure or well control situations and to enable better decision making with regards to well construction.

The previous paper presented examples of the data captured during initial field trials. Since that time, the sensor system has been run on multiple wells, achieving more than a year of cumulative data collected and analyzed by drilling experts. This paper reviews the extension, uptake, and applications of the technology, and presents case studies to demonstrate the use of direct drillstring data, with emphasis on lessons learned from high-speed data analysis for drillstring dynamics.

Initial results demonstrate that the improved measurements provide more accurate values for surface mechanical specific energy (MSE), which is used to optimize applied drilling parameters such as weight on bit (WOB) and top drive rotation speed in revolutions per minute (RPM) for increased rate of penetration (ROP) and reduced risk of equipment failures. Additionally, improved measurements permit better friction factor estimations for greater knowledge of torque and drag effects on the drilling process, allowing drillers to initiate remedial actions earlier, and safely deliver longer extended-reach wells. The system’s high-speed torque data has been used to compare the makeup and breakout torque of individual drillpipe connections. It has also been used to indicate drilling dysfunctions such as stick-slip and improve the understanding of drillstring dynamics. Examples of drilling data will be presented, along with case histories illustrating how this technology improves real-time drilling operations.

2 SPE/IADC-173112-MS

Introduction Experience has demonstrated that data of higher accuracy and frequency is required to diagnose problems and optimize

drilling performance. Accurate drilling measurements are essential to understand and model the behavior of the drillstring components in drilling operations (Lesso et al. 2011). To better simulate drilling behavior, models have become more complex, which has increased the demand for more detailed information of process parameters. These needs for multiple measurements and data inputs have increased requirements for processing capacity, communication efficiency, and the quality and availability of data (Florence and Iversen 2010).

IADC/SPE 128958 reviewed the history of drilling data collection and highlighted the changing way data is used, processed, and stored. Historically, drilling operations used surface drilling data monitoring as a tool to make adjustments to improve performance and reduce risk. There is little dispute that conventional drilling measurement instrumentation operates sufficiently well when used as it has historically been for monitoring and trending of the basic drilling parameters. Today, however, drilling data must provide reliable input for calculations and model applications to interpret the state of the process. Rig equipment also uses this data to safely and securely control the processes. A drilling system designed for automation and optimization purposes is only as efficient and effective as the quality and accuracy of the data inputs supplied by its supporting instrumentation.

The question was raised as to whether drilling sensor designs and data processing methods have kept pace with the way the data is used today (Florence and Iversen 2010). Modern drilling rigs use sensors that are positioned too remotely to make surface measurements with the high degree of accuracy current drilling data requirements demand. Most drilling parameters are derived from load measurements taken on supporting structures or equipment related to the drillstring, but not actually part of the string (Wylie, et al. 2013). Findings indicate that the ineffective positioning from the target load is the primary cause of the error commonly found in these classic sensors. Reducing this error by measuring the load directly at the drillstring provides a more representative measurement suited for modern control systems.

When a measurement is needed as an input to a complex algorithm or an advanced drilling model, its inherent shortcomings must be addressed either through the development of enhanced sensors or adjustments integrated into the models themselves (Florence and Iversen 2010). A team of engineers set out to address the former point—the deficiencies integral in the design of classic sensors and the development of a sensor package that would overcome the existing challenges and provide more accurate measurements directly from the drillstring. They found that measurement instruments applied as close as possible to the target load provided the most accurate data.

SPE/IADC 163475 presented the resulting system, the IIBOP, designed to provide accurate drilling parameters directly from the drillstring. By performing measurements just below the main shaft of the top drive, the IIBOP circumvents the errors present in traditional sensor measurements. The sensor package enables real-time streaming of data within milliseconds, at sample rates up to 128 Hz, providing the timely direct measurements needed to characterize drillstring phenomena required for drilling and equipment optimization purposes (Wylie, et al. 2013).

The goal of the direct measurement sensor package was two-fold: 1) to provide early warning signs of system failure and well control situations and 2) to enable better decision making with regards to drilling optimization and well construction. The IIBOP system uses data to develop a complete picture of the drilling process from downhole to surface, providing information on equipment performance and identifying potential drilling inefficiencies. Being located in the drillstring’s direct load path permits the IIBOP to measure variables without the mechanical effects experienced by traditional measurement technology. As such, sheave friction and wire wear elements do not hinder data accuracy or repeatability. SPE/IADC 163475 described predicted enhancements in measurement quality and provided limited test results from the first IIBOP prototype deployed in field testing. After about one year and eight, ~18,000-ft wells drilled in a prominent shale play, the team could further verify sensor accuracy robustness by recalibrating against National Institute of Science and Technology (NIST) traceable cells to demonstrate the system’s sustained accuracy, one focus of this paper.

Sensor Robustness

An early IIBOP was deployed on a rig in a large shale region during 2013 and 2014. With more than one year in operation and eight wells drilled, each amounting to 18,000 ft or more, the engineering team was tasked with verifying the sensor robustness regarding its sustained accuracy. Two specific calibration tests were used to validate the sensor accuracy.

The unit was first loaded into the tension load frame and 251.3 Klb of tension was applied as measured by the reference cell. The load was sustained for more than 90 min. to monitor creep in the IIBOP output and quantify the accuracy after its field service. The sensor showed accuracy within its span tolerance (Fig. 1a). The result was that sensor accuracy was measured within 350 lb of the reference cell at 251.3 Klb.

The unit was then loaded into a torque calibration machine with an NIST traceable in-line torque cell. Torque was applied to the unit and sustained for more than 30 min. at 13.7 Kft-lb. The torque stand was operated with open loop control. Both the reference and IIBOP outputs illustrate an exponential decay of torque due to changes in the performance of the hydraulic system within the torque machine over time (Fig. 1b). The important finding here is that the IIBOP torque and the reference torque are nearly identical throughout the test. The data illustrates that sensor accuracy was measured to be within 20 ft-lb of the reference cell for the entirety of the test.

SPE/IADC-173112-MS 3

Figs. 1a-1b−Tension and Torque Accuracy after 1 Year Field Use

IIBOP Design Performance

Pressure effects on the tension output is a known error source that can greatly impact the accuracy of the IIBOP-measured tension (Soukup 2013). To minimize the error, the IIBOP’s design employs a compensation technique to the tension measurement that reduces the sensitivity of the circumferential strain gauges. This eliminates changes from the radial pressure forces, while also reducing the output by the axial pressure force at the top of the drillstring. Testing has shown that the uncompensated tension output is reduced by 10 kip per 1,000 psi (Fig. 2a). After applying compensation, the tension output shows a maximum shift of less than 0.5 kip over 7,500 psi of pressure (Fig. 2b).

Figs. 2a-2b−IIBOP Pressure Compensation Performance showing <.5 kip of Tension Shift after Compensation

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IIBOP Sensor Performance One of the primary indicators of the IIBOP sensor’s true value is its impact on ROP. To date, the sensor has not been used

to make drilling decisions because of the infancy of the technology. Control loop testing, predictive algorithms, well planning scripts, and post well analysis tools are currently being developed and tested to prove the real value of the sensor. Presently, the value of the sensor will be shown in several ways:

• Correlation to downhole measurements sampled at 1-Hz in the time domain • Correlation to downhole measurements sampled at 128 Hz in the time and frequency domains • Measurement differences from surface measurements in the time domain at 1 Hz • Inferred resolution enhancement compared to other surface sensors • Correlation to downhole measurements through predictive models at 1 Hz and 128 Hz

WOB Measurements

WOB is a key drilling parameter and a primary value used to improve ROP during feedback control of automated drilling operations. Of a rig’s three main power systems (hoisting, rotating, and pumping), the ability to manage the hookload of a hoisting system−and, by extension, the WOB−is of prime importance to efficient drilling. Historically, a hydraulic load cell in the deadline anchor measured this and a weight indicator displayed it (Fig. 3).

Fig. 3: Traditional Hydraulic Hookload Measurement

More recently, this measurement has moved to strain-based electronic loadcells designed for applications around the

hoisting system. While they vary in design based on load format (compression, tension, shear), they share one common characteristic−they are measured in locations prone to the system’s friction effects. Even if the instrument is accurate to 0.5% of full scale, the installation location penalizes the practical system accuracy (Fig. 4).

Fig. 4: Traditional Hookload Setup Compared to the IIBOP


Hookload measurements for WOB control require fail safe, redundant, and independent signals to verify and validate the best hookload values for WOB calculations. Currently, this is accomplished using a compression cell installed on the anchor, with three independent strain-gauge bridges feeding the autodriller. Even with this level of redundancy, the friction effects in the hoisting system play an active role in the measurement accuracy and repeatability during drilling operations, with instances of block assembly performance reduction not visible to the driller or detected by the compression cell.

Current WOB measurements derived from remotely placed sensors are subject to errors (Florence and Iversen 2010). With the IIBOP located in the drillstring, the eliminated friction effects make the sensor a prime candidate for WOB control. On a shale rig, the opportunity was provided to compare the WOB from the IIBOP to that of deadline, as well as from a downhole tool. In some cases for all three sections of the well (vertical, curve, and lateral), the IIBOP WOB demonstrated better correlation to downhole WOB.

Hoisting system nonlinearities indicate that there can be many cases in which the deadline WOB does not match the IIBOP WOB. Fig. 5’s plot taken at a 15,000-ft depth shows WOB patterns for the IIBOP (SS WOB), deadline (WOB), and the downhole tool (DH WOB) in cyan, red, and green respectively. The data displayed has been filtered to show the on-bottom values only so that the WOB trends while drilling can be inspected. The data shows the IIBOP WOB following the same trends as the downhole WOB, while the surface WOB misses some of the variation.

Fig. 5−Example 1: WOB Comparison between IIBOP (SS WOB), Deadline (WOB), and EMS (DH WOB)

Another example of the dead line WOB having less resolution than the IIBOP is illustrated in Fig. 6. Between 8:50 and

9:10, the dead line WOB in red has a different profile than the DH WOB and IIBOP WOB, meaning that the friction forces within the hoisting system are affecting the deadline measurement. Again before 9:30 until just before 9:50, the deadline shows no response to the forces being measured by both the DH WOB and the IIBOP (Fig. 6).

Fig. 6−Example 2: WOB Comparison between IIBOP (SS WOB), Deadline (WOB), and EMS (DH WOB)

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Vibration/Frequency Domain Analysis High-speed data greater than 50 Hz from the IIBOP and downhole instruments was studied using frequency domain

analysis to quantify the signal’s energy patterns distributed across frequencies. The IIBOP sensor and two downhole tools produced data streams of the highest quality results. The IIBOP sensor was positioned at the top of the drillstring and integrated into the top drive. Downhole tool 1 was positioned 30-40 ft from the bit and downhole tool 2 was positioned ~5,000 ft from the bit (Fig. 7).

Fig. 7−Basic BHA Layout during Vertical Drilling Sections and 2D Well Trajectory

The wells followed a trajectory that included a vertical section followed by a curve and then a lateral. The different

sections will be referred to throughout to demonstrate the measurement capabilities of the sensor with increasing complexity in boundary conditions as the well path moves from vertical through the curve and into the lateral section (Fig. 8).

Fig. 8−Well Identification in the Time Domain for Vertical, Curve, Lateral, and BHA Identification


The IIBOP sampled data at a 128-Hz rate, while the downhole tools captured data at 50 Hz. The IIBOP system’s data was captured and stored continuously during operation, while the data from the downhole instruments was stored and then extracted periodically when the assemblies were tripped to surface. The higher-rate measurements enabled more detailed data analysis including drillstring vibration mode identification and validation. This analysis will be presented in the frequency domain to illustrate the characteristics of the data captured by the IIBOP and the other instruments.

For the vibration analysis, drilling data was studied from 20 min. segments at six different depths over two wells. The six depths included data for both rotating and sliding from the vertical, curve, and lateral sections of the well. In the time domain, each section of data represents one entire stand of drillpipe, 90 ft, occurring under near-constant surface RPM and surface ROP. The sections were identified graphically based on key drilling parameters. Appropriate rotating sections included a linear decrease in block height and linear increase in hole depth during constant surface rotation. Appropriate sliding sections included linear decreases in both block height and in hole depth with string torque but no surface rotation (Fig. 9).

Fig. 9−Data Identification for Rotating and Sliding

After the specific time periods were identified, the downhole sensors, standard surface sensors, and IIBOP data series

were synchronized. This procedure was manually accomplished by inspection (Fig. 10). Each data section was aligned by identifying the transient response at the start and the end of the drilling sections and aligning the signal characteristics from sensor to sensor to match the appropriate response. Rotational velocity provided the most definitive characteristics for time syncing the signals and was used extensively for that purpose. All time periods were converted and stored in GMT.


Fig. 10−Time Sync Identification

Vibration analysis consisted of studying the system’s frequency response for axial and torsional resonances. This was

accomplished by analyzing each data set within the frequency domain and capturing the frequencies that produced associated peaks in magnitude from the signal response. Specific data set measurements were used to differentiate between the axial resonances and the torsional resonances. IIBOP string weight and downhole WOB measurement data was used to determine the axial resonances, while the IIBOP torque and downhole torque on bit were used to determine the torsional resonances. The data was processed to minimize bias errors by discretizing the signal into smaller sections and normalizing it. Frequency domain calculations employed an averaging estimator and incorporated the Hamming window approach to accurately identify and separate the resonances from the noise spectrum.

Results showed that the torsional resonances were most easily captured because they dominated the frequency spectrum, while the axial resonances were in some cases dominated or disturbed by an excitation frequency that occurs at a frequency of one drillpipe revolution. In the worst cases, the lowest axial natural frequency had to be estimated from the higher harmonics due to disturbances from the excitation forces. The resonances extracted from the sensor frequency spectrum showed two things: 1) that the IIBOP sensor data contained similar characteristics to those of the downhole sensors and 2) that the IIBOP data identified the drillstring vibration modes in the axial and torsional degrees of freedom. The first conclusion can be seen in Fig. 11 by the overlapping of the signals with the characteristic power densities occurring at the same frequencies.

Fig. 11−Frequency Response Plots Show Close Correlation to Downhole Data and Identify Drillstring Vibration Harmonics

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To validate the signal characteristics and define their physical meanings, calculations were performed to estimate the drillstring natural frequencies under the conditions for each data section analyzed. The calculated axial natural frequencies and calculated torsional natural frequencies are shown in Table 1 for the vertical section plotted in Fig. 11. The table shows close correlation between the calculated and measured values. From the frequency domain plots, it is also evident that a 1-Hz excitation frequency exists for this section of data. Its drillstring rotational velocity is 60 RPM which confirms an excitation occurring once per revolution of the drillstring.

Also, the excitation frequency is large enough to mask the lower harmonics of the drillstring. Results from the torsional data indicate that the torsional natural frequency and the higher harmonics dominate the signal characteristics and there is not an identifiable excitation frequency (Table 1).

Table 1−Vertical Section

Data captured during the well’s lateral sections demonstrate similar results to those shown previously, except for some

signal degradation at the surface (Fig. 12). This indicates that drillstring vibrations are damped such that it becomes more difficult to differentiate them from external excitations. However, the IIBOP can still measure the excitation and frequency harmonics, but just not as clearly.

Fig. 12−Frequency Response Plots in Lateral Section Show IIBOP Correlates with Downhole Data

Again, IIBOP data analysis results show good correlation to predictive calculations of natural frequency as well as

identifying the once per revolution harmonic for this data set at 90 RPM and 1.33 Hz (Table 2). Table 2: Lateral Section

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Lastly, sliding sections were analyzed and studied. From the sliding section data, it was clear that the string was not excited enough to identify the system’s natural frequencies either at the surface or from the downhole tools. The signal characteristics do identify a few higher frequency excitations present with small magnitudes that match similar measurements from the downhole sensors (Fig. 13).

Fig. 13−Frequency Data Plots in Sliding Sections do not Identify System Resonances

It was determined that the data from the well’s vertical section exhibited the most accurate correlation to estimated natural frequencies. Frequency analyses performed on data from the sliding sections indicate that the natural modes of vibration of the drillstring did not have large enough amplitudes to measure above the extraneous excitation perturbations.

Torque Data Analyses

As with WOB control, managing the torque applied to the drillstring has also been a critical concern for drilling applications. Casing crews regularly provide torque-turn graphs to show that each joint of casing has been properly engaged and made up to recommended torque values. These peak make-up values are held at a set point for a specified time, allowing the use of slower measurement systems to capture the peak accurately.

Similarly, it is important that drillstring connections are torqued to the correct value before running in hole. Also, standard measurement system speeds must be adequate to report the peak torque value. In drilling operations, these drillstring connections can be subjected to significant torque events, in both the make-up (typically right-hand or forward) and break-out (left-hand or reverse) directions. Applying localized high-torque levels in the reverse direction can lead to the connection backing off downhole and resulting in fishing operations−or worse. Exceeding specified operational torque values can result in drillstring damage and downhole twist offs (pipe breakage), leading similarly to fishing operations or unwanted sidetracks. Therefore, knowledge and control of connection and break-out torque at each pipe joint is critical in preventing drillstring component losses from twist offs or connection breaks.

Torque data has traditionally been derived from a measurement of electrical power draw combined the motor power curves used in each top drive, rather than by a calibrated strain measurement. Further, the motor output suffers from similar frictional losses as the hoisting measurements, overcoming both static friction and running friction. Hence, the measured top drive torque does not accurately reflect the torque applied to the drillstring. Also, peak values can be missed due to slower top drive signal measurement systems.

High-speed IIBOP torque measurements have shown value by improving measurement accuracy, evaluating drillstring connection performance, providing torque data while the top drive is being driven by torsional oscillators, and providing data while drilling with downhole motors (Wylie, et al. 2013).

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Figs. 14a and 14b show the IIBOP’s ability to measure the torsional response of the top drive while making connections, whereas the top drive cannot measure the resulting torsional drive shaft oscillations. This is not just a result of the higher frequency sampling, because the torsional oscillations last for several seconds before damping returns them to steady state. The top drive is unable to measure this response because it does not directly measure the main shaft response as does the IIBOP; these oscillations can lead to potential consequences for top drive maintenance.

Fig. 14c demonstrates the use of the IIBOP for high-speed, direct-string measurements to evaluate drillstring connection performance (ST). It can be seen that after pipe rotation stops and the pipe is set in the slips, reverse torque has been applied to break out the connection. When the connection breaks, the applied torque immediately falls back, and unscrewing rotation begins. The break-out torque is the peak of that applied torque, and can only be measured for a fraction of a second. When the connection is subsequently made up, the applied torque is held for a period of seconds, and can be measured by standard means. The torque delta during the longer make up (Fig. 14 b) is 1.97 Klb-ft, while the deltas of quicker breakout in Figs. 14a and 14c are 2.28 Klb-ft and 4.76 Klb-ft, respectively, with the top drive torque measuring less. From observation, the larger deltas during the breakout show that the peaks are being missed by the lower speed sampling of the top drive torque sensor measurement (TDT).

Figs. 14a-c−IIBOP Data shows Higher Resolution using its Torsional Vibration Measurements (14a-14b (top));

IIBOP Higher-Speed Data Provides more Accurate Magnitudes for Short Duration Events compared to Top Drive Torque (14c (bottom))

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A rig test demonstrated the friction factors and inertial contributors to top drive torque. Stepping the top drive rotational velocity from 0 to 160 RPM indicated that the stiction on this rig accounted for 600 ft-lb and inertial losses of 2800 ft-lb (Fig. 15). The data indicates that there is a viscous damping loss that is proportional to speed and contributes a loss of 450 ft-lb at 100 RPM. Fig. 15 shows that the IIBOP torque is not subjected to these factors and measures zero torque during this test. This may contribute to the MSE differences discussed later in this paper.

Fig. 15−Top Drive Torque Characterization from Stiction and Running Friction In an example of consistent connections, most connections are made at 33 Klb-ft and break out smoothly at about 30

Klb-ft (Fig. 16a). The top drive torque during breakout is missing the peaks as its value drops from 29.5 to 24.5 to 23.5 Klb-ft over three successive breakouts while the IIBOP string torque maintains -29 Klb-ft for each breakout (see data tags). Fig. 16a also shows a separate makeup and breakout tool is used just after 50 min., which allows the IIBOP (ST) to record torque data whereas the top drive (TDT) is unable to make the measurement while not engaged.

Figs. 16a-b−Consistent Connection Example (16a); Excessive Downhole Torque Example (16b)

Fig. 16b shows an example in which excessive torque downhole has caused problems with some of the connections. The connection at 10 min. has required a force of about 40 Klb-ft to break out; the connection at 180 min., when carefully analyzed, has required several attempts by the driller to break out, with reverse torque of more than 45 Klb-ft applied. At 55 min., the top drive torque appears to closely capture the breakout magnitude, as its measured value is close to the IIBOP (23.5 Klb-ft vs. 26.5 Klb-ft). However at 180 min., the top drive torque is almost 10 Klb-ft less than the IIBOP’s measured value (35.8 Klb-ft vs. 45 Klb-ft). IIBOP high-speed direct drillstring measurements can be used to help identify potential damage to the drillstring connection and assist in decision making of whether to lay down a drillpipe joint for inspection, rather than risking lost time events due to subsequent drillstring failure.

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Surface drillstring torque while drilling with downhole motors is often not measured because the top drive is inactive with the rotary brake engaged. The IIBOP is able to measure the reactive torque through the drillstring while downhole motors are used (Fig. 17). The string torque (ST) of the IIBOP during slide drilling along with the torque measured by two downhole tools is shown in Fig. 17. In this example at 8,000-ft−10,000-ft depths, the IIBOP torque shows good correlation to these tools. Using IIBOP to display the string torque provides a continuous stream of accurate data during these events.

Fig. 17−Torque Measured by IIBOP and Downhole Tool while Sliding

MWD Pressure Pulses Plots

IIBOP pressure data has shown its ability to pick up MWD pulses with much clarity. MWD pulses are typically measured on a standpipe pressure transducer, which is physically separated from the drillstring by the top drive and flexible hose between the top drive and derrick. This remote measurement can reduce the clarity of these pulses from damping within the flexible mud line and introduce extraneous impulses from the top drive and/or mud pumps (which are closer within the flow path to the standpipe). Fig. 18 demonstrates IIBOP-measured pulses vs. time and their density within a specific time span, illustrating a pattern of pulses being transmitted to the surface for decoding.

Fig. 18−IIBOP-Measured MWD Pulses vs. Time [Source: Austefjord, A. and Kyllingstad, A.]


Torque and Drag Model Further advancements using the IIBOP for data collection is evident through specific analysis tools such as predictive

modeling and post-well calculations. The first example demonstrates the use of IIBOP data in a torque and drag model. Two different surface torque measurements were taken on two example wells to compare their accuracy when input into a torque and drag model that uses surface torque to estimate downhole torque. To provide an objective measurement with which the surface torque measurements and their subsequent downhole torque estimations can be compared, downhole torque measurements were also obtained using a downhole tool.

Surface torque measurements from both the top drive and the IIBOP were input into the model and their downhole estimates calculated. The results were then plotted and compared with actual downhole tool measurements. The objective was to identify the surface measurement that produced the downhole estimate that most closely matched the downhole measurement. The surface measurement identified as such would, at least in some sense, be considered the “more accurate measurement.”

Tables 3 and 4 illustrate that, in general, both the top drive and IIBOP measurements produce similar downhole estimations. However, there are differences in these estimations. To gain more precise insight into the accuracy of the different estimations, each well was divided into sections. The first well was divided into four sections—surface, intermediate, curve, and lateral. These sections are color-coded in Fig. 19.

Fig. 19−Various Torque Measurements vs. Depth for Well 1

An analysis of each section is provided in Table 3. In the table, the absolute difference of a section is the average difference between the downhole measurement and the downhole estimate. The relative difference of a section is average of the difference between the downhole measurement and downhole estimate and divided by the downhole measurement. The data in Table 3 shows that the IIBOP measurements provide significantly better downhole estimates than the top drive measurements in the surface and curve sections. Also, both measurements provide decent estimations for the lateral section, but neither one provides a good estimate for the intermediate section.


Table 3−Well 1

A similar analysis was conducted on the second well, but due to a lapse in downhole data collection during the drilling of

the intermediate section, five sections were analyzed rather than four. Therefore, dividing the intermediate section into two and omitting one section from the analysis would increase its accuracy. These five sections are shown color-coded in Fig. 20.

Fig. 20−Various Torque Measurements vs. Depth for Well 2


Table 4 provides a summary of the analysis. From the table, the IIBOP measurements are more accurate in the surface casing. And discounting the first intermediate section, the IIBOP measurements provided significantly better downhole torque estimations throughout the entire drilling process—the second intermediate section, the curve, and the lateral section.

Table 4−Well 2

The authors recognize the discrepancy between using model predictions as a means of evaluating the accuracy of the surface measurements and evaluating the measurements themselves. However, integral to assessing the quality of surface measurements is to evaluate their application in drilling models, which is what this field example demonstrates. There appears to be a significant improvement in the IIBOP vs. top drive torque measurements when used as model inputs to estimate downhole torque measurements, substantiated in the comparisons with actual downhole tool measurements.

This example also illustrates that when a model is used to predict the more challenging scenarios that introduce additional uncertainty, as was the case in the lateral sections, even the best data cannot overcome the challenges model predictions encounter in such circumstances. MSE Data Analysis

The second example demonstrates IIBOP data usage in post-well mechanical specific energy (MSE) calculations. The use of MSE calculations can take place while drilling in real time or during post-well analysis for the planning of future wells in the same area. The IIBOP was installed to capture drilling data immediately below the top drive and its data was compared to that of a conventional surface data system (EDR). This EDR provided data only at 10 sec. intervals, and some of the required inputs for the MSE calculations were not available directly. Therefore, additional calculations were performed on this drilling data to determine all MSE inputs, namely WOB, differential pressure, torque, and bit RPM while sliding (Dupriest and Koederitz 2005).

Tour sheets and 24 daily drilling reports were used to determine rig activity and operations whenever this was not clear from the EDR data. Surface data was used to back-calculate MSE using both sets of data and comparisons made to identify both the differences and the value added by IIBOP calculated MSE values. The analysis was performed in the vertical and curve section as well as in the lateral.


Fig. 21 shows the MSE values from below the surface casing shoe to final TD. Other than the expected differences in both sets of data, careful analysis determined that two intervals demonstrated certain types of abnormal MSE trends, indicating potential downhole dysfunctions. As such, these two intervals were analyzed in closer detail using MSE calculations from both EDR and IIBOP data.

Fig. 21−Calculated MSE vs. Depth

Interval 1

For Interval 1, the BHA used included a steerable motor, MWD tools, and a PDC bit. It was a vertical section with a hole inclination of less than 1°. At 2,538 ft−2,540 ft, the drilling mode changes from sliding to rotating (Fig. 22). The MSE from both IIBOP and EDR are practically the same while sliding since torque and bit RPM are calculated from the mud motor output and flow rate (GPMs). At around 2,540 ft, when rotation begins, the IIBOP MSE shows higher amplitude cyclic fluctuations than does the EDR MSE (Fig. 22). At the start of rotation, the EDR MSE shows an exaggerated MSE spike not observed in the IIBOP’s. This is associated with the stiction of the top drive, or sharp spikes in torque. Fig. 22 shows that the average IIBOP MSE while rotating is almost 2,300 psi, about 30% less than the EDR. This can also be explained by the fact that IIBOP does not produce such exaggerated torque values as rotating starts, but does capture more fluctuations in both drillstring torque and string RPMs.

Fig. 22−Interval 1: Calculated MSE vs. Depth

KOP @ 5980’ 7” shoe @ 7128’


The two graphs in Fig. 23 show the fluctuations in string torque and RPM measured by the IIBOP and to a lesser extent by the EDR.

Fig. 23−Interval 1: String Torque Measurements

After this transition subsides and rotation stabilizes, both MSE trends are similar, but the IIBOP MSE is lower than the EDR MSE by 1,300 psi (~26%), as shown in Fig. 24. This suggests that torsional and lateral vibrations may go undetected as rotating starts after a slide drilling period, if relying on the EDR measurements alone, and the fluctuations detected by the IIBOP sensors in torque and MSE are not considered. The IIBOP measurements are more accurate, and hence, provide better MSE calculations for drilling performance analysis.

Fig. 24−Interval 1: Calculated MSE vs. Depth


Interval 2 For Interval 2, the BHA also used a steerable motor, MWD tools, and PDC bit. It was also a vertical section with a hole

inclination of less than 1°. At about 3,150 ft, the bit is picked up off bottom. Drilling resumes with lower WOB and torque. RPM becomes erratic (higher fluctuations) and ROP drops. Fig. 25 shows two plots, with the top graph showing EDR data and the bottom graph displaying IIBOP data from the same interval.

Fig. 25−Interval 2: EDR (top) and IIBOP (bottom) Parameters vs. Depth

The trend lines for calculated MSE values along with the average ROPs for the EDR and the IIBOP are shown in Fig. 26.

Fig. 26−Interval 2: EDR- and IIBOP-Calculated MSE Values and Average ROPs vs. Depth

Upon analysis of the plots of the EDR values as well as the IIBOP-calculated MSEs, the previously mentioned drilling dysfunction becomes clearly evident, but is less obvious with the MSE calculations using the EDR values.

WOB is decreased

RPM trend changes.

Higher TQ fluctuations

WOB is increased


The cyclic behavior of the IIBOP string torque, string velocity (RPM), and corresponding MSE supports the fact that there was a vibration event, most probably lateral vibrations which were mitigated with a WOB increase at about 3,175 ft MD. From there on, the trends in MSE and other drilling parameters become normal, with ROP again increasing. Without the IIBOP values and its MSE calculations, this dynamic event may have been overlooked. A more detailed graphical representation of the dysfunction before, during, and after is shown in Fig. 27.

Fig. 27−Interval 2: Cyclic Parameter Behavior Demonstrated Other observations are that the MSE calculated from IIBOP data is on average about 30% less than that from the EDR.

However, during the vibration event, the IIBOP MSE varies by as much as 4,500 psi while that from EDR varies by only 2,900 psi. Before and after the dysfunction, the difference between both calculated MSE values is about 23%. Lateral Sections

In addition to the study in the two vertical sections, two additional intervals from the lateral were analyzed and compared. In the first lateral, the average MSE from the EDR is 2.6 times greater (35 Kpsi higher) than that from the IIBOP (Fig. 28).

Fig. 28−Lateral Section 1: Average EDR-Calculated MSE is 2.6 times more than IIBOP’s


In the second lateral, the average EDR MSE is 2.5 times greater (34 Kpsi higher) than that from the IIBOP (Fig. 29).

Fig. 29−Lateral Section 2: Average EDR-Calculated MSE is 2.5 times more than IIBOP’s

Another Example Well To illustrate the impact of the IIBOP measurement on MSE and correlate it to ROP, data from a second entire well was

filtered and MSE calculations were made with data from both the IIBOP and traditional EDR surface sensors. First, the data shows that the IIBOP MSE is substantially lower than the EDR MSE throughout the well and illustrates the inverse relationship to ROP as expected. Next, the average MSE from the IIBOP and that from the EDR is used for the entire well to back calculate the ROP. The actual ROP is then graphed along with the calculated ROP to show the IIBOP predictions more closely match the well’s true ROP (Fig. 30). This is an important result showing that for well planning and post-well analysis tools IIBOP data will provide a more accurate evaluation and planning tool which can lead to increased ROP.

Fig. 30—Actual and Calculated ROP Comparisons


The authors have made the following IIBOP-calculated MSE observations: • MSE values calculated from IIBOP data are consistently lower than those from traditional EDR sensor data. • The MSE difference discussion between EDR (traditional rig sensors) and IIBOP is more of a dialog of the error and

inaccuracies from the conventional rig sensors when a good EDR system is employed. From the preliminary analysis of drilling parameters and MSE, the trend supports that an MSE calculated using IIBOP data will be not only more accurate, but also more consistent across wells and correlate more closely with rock strength (CCS). This will be especially true with torque values, because by experience, torque measurements on the rig are often the most inaccurate, erratic, and least consistent measurements.

• For the same rock strength, the drilling efficiency (CCS/MSE) calculated with IIBOP data is actually higher because the MSE is lower. This should hold true in any section of a well (straight, curve or lateral). However, the major difference seems to be in the lateral where the MSE from EDR is 2.5- 2.6 that of the IIBOP.

• Based on the previous observation, the use of 0.35 as the standard Em factor in the MSE formula may need to be reconsidered when applying it to the more accurate IIBOP data. Instead, about 0.26 may be more appropriate.

• Using IIBOP torque data and calculated MSE to adjust WOB and/or RPM in real time, allows the driller to be more aggressive and run higher parameters because the EDR’s WOB and torque values are exaggerated, and hence, the EDR MSE is too high.

• Using EDR WOB instead of IIBOP increases the chances to induce lateral vibrations (which are the worst and more difficult to identify and mitigate) because of drilling with less WOB than required for control. Also, the MSE, torque, and RPM behaviors do not show enough variance or cyclic fluctuations like the data from IIBOP.

• IIBOP data and calculated MSE seem to pick up more drilling dysfunctions and events than the EDR data, especially during slide drilling and/or when changing from sliding to rotating or just as rotating starts. This could be important to avoid bit damage and downhole tool failures not identified with EDR data only.

Conclusions

The authors have drawn several conclusions to date following their research, field trials, and data analysis of the IIBOP: • The IIBOP measurements proved accurate and stable over an extended period of use. • The more accurate IIBOP measurements provide benefits in applications such as autodriller controls, torque and

drag measurements, and MSE calculations, leading to improved knowledge of drilling efficiencies and subsequent improvements in real-time drilling operations.

• The IIBOP provides specific benefits for autodrilling as illustrated with WOB analysis in which it was shown that the IIBOP WOB tracked downhole WOB more precisely than deadline WOB.

• Since IIBOP measurements avoid the friction losses inherent in traditional hookload and torque measurements, a lower value of Em should be considered when calculating MSE using this data.

• IIBOP measurement usage for drilling efficiency calculations should allow the driller to use a wider range of WOB and RPM values, resulting in potential ROP improvements and reduction in drilling dysfunctions.

• Direct drillstring measurements of string tension and torque can have higher resolution than traditional measurements, and are able to identify transients undetected by traditional methods, as identified in the torque and WOB analyses.

• High-frequency data indicates that the IIBOP accurately measures the vibrational modes of the drillstring and suggests that it can be used to predict downhole drillstring dynamics.

Acknowledgments

The authors would like to thank National Oilwell Varco’s Christian Gomez Suasnavas for his detailed analysis of the surface data, both EDR and IIBOP, and original MSE calculations; Arne Austefjord and Åge Kyllingstad for their detailed analysis and correlation of high-frequency data; Bill Koederitz for his drilling technical expertise; Jason Anderson and Jim Standefer for their in-depth sensor knowledge; and Sheila McLean Popov for her editorial support. Additionally, the authors thank National Oilwell Varco for permission to publish this paper.

References Dupriest, F.E. and Koederitz, W.L. 2005. Maximizing Drill Rates with Real-Time Surveillance of Mechanical Specific Energy. SPE/IADC

92194 presented at the SPE/IADC Drilling Conference held in Amsterdam, The Netherlands, 23–25 February. Florence, F. and Iversen, F. 2010. Real-Time Models for Drilling Process Automation: Equations and Applications. SPE/ IADC 128958

presented at the SPE/ IADC Drilling Conference, 2-4 February, New Orleans, LA. Lesso, B., Ignova, M., Zeineddine, F., Burks, J., Welch, B. 2011. Testing the Combination of High Frequency Surface and Downhole

Drilling Mechanics and Dynamics Data under a Variety of Drilling Conditions. SPE/IADC 140347 presented at the SPE/ IADC Drilling Conference and Exhibition, 1-3 March, Amsterdam, The Netherlands.

Soukup, I. 2013. Pressure Sensor Compensation Validation Theory. Internal NOV paper; pending publication. Wylie, R., Standefer, J., Anderson, J., Soukup, I. 2013. Instrumented Internal Blowout Preventer Improves Measurements for Drilling and

Equipment Optimization. SPE/IADC 163475 presented at the SPE/IADC Drilling Conference and Exhibition held in Amsterdam, The Netherlands, 5–7 March.

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