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Real-Time Prediction of Mud Motor Failure Using Surface Sensor Data Features and Trends
Abstract
Mud motor failure is a significant contributor to non-productive time in lower-cost land drilling operations, e.g. in North America. Typically, motor failure prevention methodologies range from re-designing or performing sophisticated analytical modeling of the motor power section, to modeling motor performance using high-frequency downhole measurements. In this paper, we present data analytics methods to detect and predict motor failures ahead of time using primarily surface drilling measurements.
We studied critical drilling and non-drilling events as applicable to motor failure. The impacts of mud motor stalls and drill-off times were investigated during on-bottom drilling. For the off-bottom analysis, the impact of variations in connection practices (pick up practices, time spent backreaming, and time spent exposing the tools to damaging vibrations) was investigated. The relative importance of the various features found to be relevant was calculated and incorporated into a real-time mud motor damage index.
A historical drilling dataset, consisting of surface data collected from 45 motor runs in lateral hole sections of unconventional shale wells drilled in early to mid-2019, was used in this study. These motor runs contained a mix of failure and non-failure cases. The model was found to accurately predict motor failure due to motor wear and tear. Generally, the higher the magnitude of the impact stalls experienced by the mud motor, the greater the probability of eventual failure. Variations in connection practices were found not to be a major wear-and-tear factor. However, it was found that connection practices varied significantly and were often driller-dependent.
The overall result shows that simple surface drilling parameters can be used to predict mud motor failure. Hence, the value derived from surface sensor information for mud motor management can be maximized without the need to run more costly downhole sensors. In addition to this cost optimization, drillers can now monitor motor degradation in real-time using the new mud motor index described here.
... The primary cause of elastomer damage is motor stalling; detecting those events provides information regarding the operating parameters and the corresponding motor response. Data-driven methods and machinelearning algorithms classify the failure modes and mitigate the risks [21,22]. ...
Positive displacement motors (PDM) are utilized to drill deviated and horizontal sections and are a key technology for deep oil/gas and geothermal wells. The energy transferred at the drill bit is delivered from the drillstring and bottom hole assembly (BHA) components. Energy loss due to friction, wellbore problems (tight spots, poor hole cleaning, etc.), and damage to the drillstring reduce the energy delivered to the drill bit. As a result, there is a reduction in drilling efficiency and an increase in nonproductive time. Mud motor fatigue due to cycling loading significantly influences wellbore quality and drilling performance. This chapter aims to develop a framework using surface and downhole data to predict the condition and performance of mud motors. A systematic and automated approach to access data quality and operations recognition is a fundamental element in the study. The borehole trajectory is reconstructed by implementing the survey data with the corresponding generated forces acting on the drillstring. Mud motor operating efficiency is monitored by continuously evaluating the produced differential pressure, power efficiency, and modeled incremental torque produced from each drillstring element. The theoretical and actual torque produced from the motor and the drillstring is compared to establish a correlation with the measured sensor data.
Developing artificial intelligence (AI)-based drilling advisory software is generally straightforward when good quality labeled data are available. However, deploying such systems in the field for use by a rig crew requires careful planning and execution and often fails to provide the value proposed. It is statistically estimated that most AI projects fail, and that most companies that trial AI solutions report minimal to no impact from AI. This paper details the successful deployment and ongoing success of an AI-based drilling advisory system on rigs across an Operator's fleet, as well as deployment decisions that helped make it a high-value, sustainable, and successful program.
The Operator developing and deploying the AI system focused on five main aspects to anchor this project: setting a realistic long-term vision for automation, choosing the right tools and techniques, implementing a targeted change management plan, careful selection of team members, and planning for sustained management support. For the longer-term automation vision, decisions on where to deploy the AI models - at the rig or managed from the central office, what parts of the solution to develop in-house or out-source to achieve cost objectives, and how soon to scale AI to all rigs in the fleet were key. Finally, a thoughtful change management plan was implemented taking into consideration the company culture and industry best practices.
The project launched in 2015, with the decision to deploy the AI models at the edge/rig site with an ability to push updates from a remote, central support group as needed. The AI model platform was outsourced; AI models were developed /validated one model at a time, and then deployed to all the rigs as soon as possible. The platform and models were modularized to enable rapid prototyping, field deployment, and iterative change. A key Program Sponsor along with other Stakeholders were identified for each rig, and carefully managed to ensure ongoing support, successful adoption, and regular feedback. Transparency on how the model performed calculations was shared readily to ensure acceptance of the results by the drilling engineers and the rig site crew. An agile development and deployment cycle was adopted to maintain rig crew interest to continuously use and improve the system. Over the past eight (8) years, more than ten (10) AI models have been added incrementally to the rig-based system, which has enabled a 10% improvement in drilling performance year over year.
This paper details the decisions and processes that resulted in the successful deployment of an AI-based drilling advisory system for rigs in North America and Europe. The learning and insights from this multi-year (8 years and ongoing) deployment should provide valuable insights to those planning to deploy AI software at scale, at the edge.
Operating under harsh conditions, mud motors frequently stall, causing the rotor to seize and a buildup of torque and standpipe pressure throughout the drill string. When not recovered from correctly, this event can cause abrupt changes in drill string torque, potentially damaging the motor and other BHA components. Current recovery methods usually rely upon field crews to detect and react correctly to this event, with results depending on varying levels of training, awareness, and other factors. This paper seeks to outline a method to automatically detect mud motor stalls in real-time using machine learning. The method itself involves unique methods of representing time series data that have yet to be applied to drilling data in the literature and provides a flexible technique for pattern recognition in general.
With the assistance of subject matter experts, 200ms time series data for 100+ stalls were acquired and labeled to indicate the exact moments of a stall condition. The data itself consisted of surface values for torque, differential pressure, and other traces over which a model was developed that could successfully flag a particular instant as being in a stall. Significant effort was put towards feature engineering, and a novel application of spline regression was used to create robust features that were passed to a gradient-boosted random forest classification model to determine the probability of a stall occurring. During initial training, the model was validated against unseen stall data and achieved high (greater than 90%) precision and recall and had a reaction time superior to human operators, implying that it was a suitable candidate for integration into the control system. The model was then deployed to all rigs of this drilling contractor’s onshore rig fleet, providing a robust method for detecting even further motor stalls for additional training. The final model held acceptable performance and will be integrated into control systems to trigger automated stall recovery routines.
Condition monitoring of bottom hole assembly (BHA) is essential during the different lifecycle stages of the drilling process, whether during the planning, implementation, or post-job failure analysis. Mud motor condition evaluation can assist in preventing mud motor damage and increasing drilling efficiency. This paper aims to develop a monitoring system that combines field data, data analytics and physics-based modelling to evaluate mud motor condition and performance.
The drilling monitoring system is a set of modelling and analysis tools that utilize actual drilling data, power section performance data and drillstring design to recreate the drilling process.
An unprocessed drilling dataset is required to assess the drilling operations (rotating or sliding mode, rotating off-bottom, backreaming, connections) and reconstruct the borehole trajectory from the measured survey and duty cycle (rotating and sliding mode). Interaction of the BHA and the borehole generate side forces and bending moments along the length of the BHA that are evaluated at each depth increment during the drilling process. Generated power and efficiency of the mud motor are calculated and incorporated into the dynamic simulation.
The case study investigates two motor runs in vertical and inclined sections. Dynamic modelling and extensive data analytics assist in visualizing and correlating the input and output variables during the drilling process. The continuous evaluation of the differential pressure on the motor is the primary parameter that is investigated. The motor condition is established with a continuous wear-off test while drilling and correlation matrices to indicate a constant motor state for 135 hours.
The system accurately monitors the motor's operating efficiency, with the additional advantage that the mud motor and drill bit performance are differentiated. Precise adjustments of the drilling parameters for the optimum depth of cut positively impact motor efficiency.
In addition, an interesting observation shows that accurate modelling of downhole and surface torque provides significant insights regarding bit state. The results demonstrate that with the current methodology decrease in drilling efficiency is detected and is associated with bit wear.
The work enables the evaluation of the mud motor condition and performance by utilizing a monitoring system and actual drilling data. The drilling monitoring system is a modelling analysis tool that can provide continuous feedback to the drilling operators about the condition of the BHA. Hence, it enables a real-time optimization process to manage mud motor condition and enhance drilling efficiency.
Mud motors are widely used in directional drilling and their failure during operation leads to costly non-productive time. There is currently no existing literature investigating the correlation between stalls detected using downhole sensors and concurrent signals produced in surface sensor data. Current motor stall detection algorithms using surface sensors are still rudimentary and error-prone. The objective of this study was to develop a robust stall detection algorithm using insights gained from correlating downhole and surface data.
Previous studies have indicated that stalls are a major contributing factor to elastomer damage in a mud motor. Using downhole sensor datasets from multiple operators, we first identified all instances of motor stalls. These events are typically characterized by a sudden reduction in downhole vibration and rotation at the bit, accompanied by a sudden increase in torque. We then proceeded to map these stall events to time-synchronized surface data to identify the associated behavior of surface parameters during a stall, noting the differences in behavior during rotary and slide drilling periods.
We analyzed 268 distinct stall events in the downhole data as well as several clusters of micro-stalls (characterized by a momentary spike in downhole torque coupled with a downward spike in downhole RPM that last less than one second, typically lasting for a few milliseconds at most). Mapping these events to the surface data helped identify a set of primary signals produced at the surface during every motor stall, and secondary signals that are produced in a majority of motor stalls. The primary surface signals we observed during a stall included a sharp spike in differential pressure and a sharp decline in weight on bit (WOB), typically within a 10-second window. Secondary surface signal observed in over 70% of motor stalls include decrease in rate of penetration (ROP). Statistical analysis of the downhole and surface signals demonstrated a strong correlation (p < 0.05) between the length of a motor stall and the magnitude of the differential pressure increase produced at the surface. Our analysis of stalls in downhole datasets demonstrated that the vast majority of surface-detectable stalls occurred during slide drilling, while rotary drilling contained significant clusters of micro-stall events that were too short to produce identifiable signals at the surface.
This study builds upon existing literature and understanding of mud motor failure by correlating time-synchronized events in downhole and surface data. We have compiled our observations to create a comprehensive framework for detecting motor stalls at the surface using a set of surface signals. Our findings establish a robust way to detect motor stalls from surface data, which should be of significant value to lower-cost well construction operations and real-time monitoring of drilling operations.
It is useful during drilling operations to know when bit failure has occurred because this knowledge can be used to improve drilling performance and provides guidance on when to pull out of hole. This paper presents a simple polycrystalline diamond compact (PDC) bit wear indicator and an associated methodology to help quantify wear and failure using real-time surface sensor data and PDC dull images.
The wear indicator is used to identify the point of failure, after which corresponding surface data and dull images can be used to infer the cause of failure. It links rotary speed (RPM) with rate of penetration (ROP) and weight-on-bit (WOB). The term incorporating RPM and ROP represents a "sliding distance", i.e. the number of revolutions required to drill a unit distance of formation, while the WOB represents the formation hardness or contact pressure applied by the formation.
This PDC bit wear metric was applied and validated on a data set comprised of 51 lateral production hole bit runs on 9 wells. Surface electric drilling recorder (EDR) data alongside bit dull photos were used to interpret the relationship between the wear metric and observed PDC wear. All runs were in the same extremely hard (estimated 35 – 50 kpsi unconfined compressive strength) and abrasive shale formation. Sliding drilling time and off-bottom time were filtered from the data, and the median wear metric value for each stand was calculated versus measured hole depth while in rotary mode.
The initial point in time when the bit fails was found to be most often a singular event, after which ROP never recovered. Once damaged, subsequent catastrophic bit failure generally occurred within drilling 1-2 stands. The rapid bit failure observed was attributed to the increased thermal loads seen at the wear flat of the PDC cutter, which accelerate diamond degradation. The wear metric more accurately identifies the point in time (stand being drilled) of failure than the ROP value by itself.
Review of post-run PDC photos show that the final recorded wear metric value can be related to the observed severity of the PDC damage. This information was used to determine a pull criterion to reduce pulling bits that are damaged beyond repair (DBR) and reduce time spent beyond the effective end of life. Pulling bits before DBR status is reached and replacing them increases overall drilling performance.
The presented wear metric is simple and cost-effective to implement, which is important to lower-cost land wells, and requires only real-time surface sensor data. It enables a targeted approach to analyzing PDC bit wear, optimizing drilling performance and establishing effective bit pull criteria.
The power section of a positive displacement drill motor (PDM) consists of a steel rotor and a tribe with a molded elastomeric lining (stator). Power section failures are typically due to the failure of the stator elastomer. Stator life depends on many factors such as design, materials of construction, and downhole operating conditions. This paper focuses on the stator failure mechanisms and factors affecting stator life. An analytical method for predicting the effect of various design and operating parameters on the strain slate and heat build-ill, within elastomers is discussed. The effect of parameters such as rotor/stator design, downhole temperature, drilling fluid, stator elastomer properties, motor speed, and motor differential pressure on the stator life is discussed. Nonlinear finite clement analysis is used to perform thermal and structural analysis on the stator elastomer. Data from laboratory accelerated life tests on power section stators is presented to demonstrate the effect of operating conditions on stator life.
Variable and feature selection have become the focus of much research in areas of application for which datasets with tells or hundreds of thousands of variables are available. These areas include text processing of internet documents, gene expression array analysis, and combinatorial chemistry. The objective of variable selection is three-fold: improving the prediction performance of the predictors, providing faster and more cost-effective predictors, and providing a better understanding of the underlying process that generated the data. The contributions of this special issue cover a wide range of aspects of such problems: providing a better definition of the objective function, feature construction, feature ranking, multivariate feature selection, efficient search methods, and feature validity assessment methods.
The continued growth in unconventional drilling has resulted in downhole motors being pushed to drill more complex geometries faster, often higher downhole temperatures. This has resulted in increased rates of failure for downhole motors. The most common method to postpone motor failure has been to select a larger motor. This option ignores the root causes of motor failure and is shown to actually not improve failure rates. Impetus for this work centered on an operator who was experiencing high rates of motor failure, however in the process of investigating the failures, important findings were made that apply to any BHA with a motor.
Damage occurs in all motors in the data set, regardless of whether or not they are considered "failed." This points to a potential, unrecognized industry-wide issue wherein motor performance may be degrading over a run and is not recognized by operations teams. The result is a version of "hidden NPT" which is limiting drilling performance in wells drilled with downhole motors. Calculating the RPM factors on the operator's wells using actual motor speeds measured by downhole sensors show that motor degradation is a significant problem, resulting in a reduction of up to 40% in bit RPM.
In order to measure performance, motor properties are used to convert the traditional surface MSE measurement into a more representative downhole MSE. Further refinement of this metric was tested as downhole MSE is calculated using a simple factor and a more exact but complicated multi-dimensional correlation. Drilling data is used to show that the simplicity of the simple factor more than offsets minor loses in MSE accuracy. As noted, the real time RPM factors are also computed using downhole data showing the stark differences between the actual factors and the originally reported factors. The difference is used to determine the degree of motor damage while drilling.
A suite of downhole sensors was placed above and below the motor to monitor the rate of motor damage. Differential pressure was also analyzed in the frequency domain spectrum to demonstrate the damaging effect of bottom hole assembly (BHA) whirl during rotating.
The use of depth of cut control (DOCC) is analyzed as a method to improve motor efficiency and decrease damage. Two identical wells and BHA's are compared, one with and one without DOCC. The uses of the first derivative of differential pressure is suggested as a method to better quantify and visualize the effects of DOCC. Ultimately, the research presented provides quantitative insights into the operation of a motor, and shows that motor performance is not as expected based specification sheet values.
The challenging environment in the Kvitebjørn field offshore Norway comprises high-temperature wells, long drilling hours, low rate of penetration (ROP), managed pressure drilling (MPD), and mud additive requirements, all of which are very detrimental for operations and reliability of the positive displacement motor (PDM) power section. In fact, until now, no one has successfully drilled the 5 ¾-in. section in a single run due primarily to motor failures such as elastomer chunking and debonding.
This paper presents the steps used for optimizing the selection of a PDM section to achieve a single-run drilling operation with improved ROP. The method includes understanding the drilling environment, type of wells, rig capabilities, formations, temperatures, MPD, and drilling fluid requirements. Furthermore, the usual motor and bottomhole assembly requirements must be evaluated and the mud compatibility with the elastomer must be scrutinized. All of these variables were then input into a modeling engineering workflow to simulate and analyze the power output, the elastomer fatigue life, the hysteresis heating, and the debonding stress to select the best possible PDM candidate for the drilling job.
A new long-life elastomer and the drilling parameters recommended by the mud motor modeling resulted in drilling this section in a single run for the first time in the field. Simultaneously, it was possible to drill to the deepest total depth without any need to set the section total depth shallower, as occurred in previous wells due to motor failures. The motor drilled through a very thick cemented sandstone stringer with no stall incidents. This motor set new records for drilling the 5 ¾-in. section with a total run length 60% longer than the previous longest run and a total pumping time 67% greater than the previous record.
The combined new technologies of the modeling and the new long-life elastomer were applied for the first time in the anticipated challenging drilling conditions. The successful results demonstrated that with thorough analysis and proper planning, one can achieve a step change in performance and reliability without additional costs. The scope of the operation is even broader than the mud motor application.
The deployment of a new positive displacement motor (PDM) technology as a solution to improve drilling performance in deep vertical exploration wells in northern Kuwait. The new technology of the positive displacement motor was developed within the framework of new capabilities in motor optimization modeling, a holistic approach to configuring motor components as an integrated unit, and new engineering advances in the material and design of motor components. The engineering advances and innovations can be distinctly categorized into two major components, the power section and the lower end. The power section components went under extensive empirical and experience-based failure analysis to refine the design of the subcomponents. The refined designs were then scrutinized with the industry-first motor optimization modeling that simulates both the performance and fatigue of the power section by analyzing eight influential variables of down-hole conditions, and components material and geometry. The second component, is the newly designed high torque lower end which houses an overhauled assembly of transmission and bearing sections. The new lower end was engineered to reliably handle and fully harness the full capabilities of the power section. The result, is an integrated new motor technology that is characterized by its superior resistance to stall, ability to sustain higher limits of differential pressure, and performance reliability in harsh drilling environment.
Kuwait Oil Company (KOC), with its ever-expanding exploratory drilling campaign in northern Kuwait, was looking for significant improvements in drilling performance of vertical deep-drilling exploration wells. As such, KOC agreed to test the new motor technology in an exploration field north of Kuwait. The deployment of the new technology would take place in the 16 in section of a vertical well with a starting planned depth of 10,565 ft (3,220 m) and a total depth of 14,605 ft (4,456 m). The section drills through highly-interbedded and abrasive sandstone and carbonates strata with highly-variable windows of pore pressure and rock compressive strength. Given the complex lithology and the high-pressure environment, previous drilling campaign were tainted by low penetration rates, and motors and bits failures.
In March of 2017, the new motor technology was field tested for the first time worldwide in northern Kuwait. The field test run covered an interval of 3,658 ft (1,115 m) over three runs. The new motor technology justified its higher specifications by improving the rate of penetration (ROP) by 62% compared with the fastest offset well drilled. The superior rate of penetration can be attributed to the new motor ability to deliver higher ranges of differential pressure, specifically 57% higher than offset wells. The deployment of the new motor technology successfully proved the capabilities of the new motor in drilling optimization and reliability, and also validated the engineering and modeling processes behind the new components.
Severe vibrations in drilling systems are one of the main limiting factors for an efficient drilling operation. An adjustment of drilling parameters is necessary to avoid the negative impact of vibrations on reliability, measurement quality, and rate of penetration. The time to drill a well is therefore directly or indirectly affected if vibrations are not properly managed; measurements must be repeated, damaged tools can lead to additional tripping time, and rate of penetration is limited by reduced power that is delivered to the bit and restrictions of operational parameters.
Complex well trajectories, a difficult drilling environment, and the extended-reach of wells are additional challenges for drilling operations. The use of a mud motor in the bottom-hole assembly (BHA) is one option to supply power directly to the bit. However, if the mud motor is not properly managed, its operation can lead to lateral vibrations. BHA design and optimization of operational parameters are options to mitigate lateral vibrations. A basic understanding of mud motor vibrations is necessary for this purpose.
To characterize mud motor-induced vibrations, a statistical evaluation of averaged vibration measurement data from several runs is conducted. Distributions of the vibrational amplitudes are analyzed, in reference to different designs of the mud motor power section. Analysis continues by reviewing a large quantity of time-based acceleration data with a sampling frequency of 1000 Hz. Special downhole tests are conducted that cover the entire range of operational parameters of the mud motor. High-frequency vibration data with distributed sensors are collected for different motor types and stabilizer configurations.
The outcome of the analysis is used to determine the ideal mud motor for a given application. Existing models for drillstring dynamics simulation are fine-tuned. Based on the models, sweet spots for operational parameters that avoid severe vibrations are derived and displayed in an innovative way.
The extensive analysis of high-frequency vibration data enables a reliable determination of operational parameters for mud motor applications that correspond to low levels of lateral vibrations. The approach enables efficient drilling with a high rate of penetration and results in increased downhole tool reliability. This ultimately leads to an optimized service delivery for drilling operations.
One of the most challenging aspects of using positive displacement motors (PDMs) is understanding the influence of each variable on the motor functioning and failure modes. Rotor-stator fit is the most critical factor in achieving maximum service life and performance. The objective of this paper is to present a new method to predict the rotor-stator fit that accounts for all main downhole variables.
This new methodology will enable the selection of a rotor-stator combination that delivers a balance between performance, efficiency, and service life. Fit selection is complex and should be made based on physics models, testing data, field data, and experience. However, downhole temperature is commonly the only variable used to calculate thermal expansion of the elastomer and the resulting rotor-stator fit. Effects of environmental conditions and operating parameters are normally neglected. This paper presents a calculation method for predicting rotor-stator fit in PDMs that includes environmental conditions and operating parameters.
A mathematical model is proposed to account for additional expansion caused by internal heat buildup (hysteresis). Additionally, a time-sensitive equation is used to estimate elastomer volume changes resulting from the interaction between the fluid and the elastomer. In conjunction with the equations developed, collected rotor and stator wear data captures the effect of rotor coatings, drilling fluid, solids content, and elastomer mechanical properties. An additional equation is also utilized to estimate the change of elastomer volume caused by the system hydraulics (downhole pressure and flow rate). Final fit prediction is obtained by combining all these effects. Normalized fit ranges can then be correlated with expected performance and risk of failure. After testing and validation, results from the new method have proven to be accurate in applications with both low and high downhole circulating temperatures and for different elastomer types, drilling fluids, and varying operational conditions. A real case is presented.
Unlike any current temperature-based prediction method, this new model integrates the effects of the most important downhole variables to accurately predict the rotor-stator fit. As a result, uncertainty in operations decrease; risk of failure is drastically reduced; and the reliability, performance, and service life of positive displacement motors are improved.
We present in this paper a comprehensive and universal tool/model for the mud motor power section. The model includes performance, fatigue, and hysteresis heating simulation capability. It can be used for improved and optimized power section design, motor selection prior to jobs, drilling parameters optimization, failures analysis, and training. Model predictions are compared with real field cases with good accuracy.
There are many challenges to build a proper model of the power section: a geometry that involves complex kinematics with progressive cavities moving in a spiral motion, unusual contact mechanism with high deformation from the elastomer, the elastomer itself being a highly nonlinear material that experiences hysteresis heating, the fluid aspect with complex 3D path, the interaction between the fluid and the elastomer, the sliding and rotating operating modes, and the load fluctuation in typical downhole instable conditions. To build an adequate model we have developed a set of modules with a unique apparatus helping to make cross-interacting links between them.
The present simulation capability allows us to predict the performance and the fatigue life of the power sections with good precision. We have already run many different power section simulations under different conditions showing good correlation with field data. We provide here direct field operation applications with comparative results between some field failures and model predictions. In addition, we expose how combining accurate profile measurements of the rotor and the stator with the modeling capability can prevent failures due to wrong interference fit or incompatibility between rotors and stators. Besides that, a comparative study with different elastomers in the same power section is also considered. We show also how we can use the model for well planning by selecting the right motor for the right application. Moreover, during the well execution, by combining its prediction and the monitoring system to derive optimized drilling parameters for performance and reliability, one can achieve higher shoe-to- shoe rate of penetration (ROP).
Achieving balance between performance and longevity of drilling motors is a constant struggle. Operating above recommended parameters delivers higher Rates of Penetration (ROP) but can be too aggressive, causing accelerated component wear and potentially, premature failure. Conservative operation decreases the component wear but can be detrimental to drilling performance. A novel approach to controlling motor performance allows operators to operate at specified limits while preventing load spikes that damage motors.
Stalling is a problem that affects bearing loading, occasionally leading to driveshaft torsional failure, but more commonly causing power section damage in the stator, reported as chunking. Chunking occurs when the elastomer in the stator has reached the fatigue limit and small pieces break free of the profile. The output performance of the power section decreases as the effective area of power section is reduced and it becomes less efficient. Reduction in output performance decreases ROP and operators will typically push motors harder to maintain ROP, further accelerating the time to failure.
An innovative internal device prevents premature failure by limiting the amount of differential pressure applied across the motor. Excess pressure is relieved by porting fluid through the center of the rotor, bypassing the power section inlet. Rotational speed decreases as flow into the power section is decreased. The pre-determined relief point is adjustable to optimize motor performance for specific applications. Preventing motor damage delivers longer drilling hours with reduced unplanned trips.
Field testing of the device has resulted in a significant reduction in motor component damage. ROP improved and was consistent through the drilling program with the controlled and steady operation of the device. Cost per foot decreased as longer intervals were drilled per motor. This device gives operators a new tool to optimize motor performance.
The use of downhole mud motors to improve drilling performance in vertical wells is becoming more common throughout the oil and gas industry. The additional torque provided by a downhole mud motor allows for a more aggressive drill bit design to be selected, and achieve a greater ROP. This paper will present a series of case studies where a near bit dynamics recorder has been used to determine the dynamic conditions below a motor. In several cases a dynamics recorder was also located above the motor, providing two discrete points of measurement.
In the first case, near bit dynamic measurements allowed for BHA stick-slip to be identified as the cause for severe bit damage rather than difficult formation as was suspected. In the second case study, a near bit recorder coupled with a recorder above the mud motor identified that a significant level of vibration was generated by the motor. A different motor design was used on the following well and a reduction in vibration severity allowed for the section to be drilled in a shorter time. In the third case study, frequency analysis of near bit dynamic data conclusively identified backwards bit whirl as the cause for severe bit damage.
In conclusion, the use of a near bit dynamics recorder has allowed for a greater understanding of the dynamics involved in performance motor assemblies. The application of this knowledge has helped to address the root cause of previously misunderstood vibration problems and improve drilling performance.
Achieving balance between performance and longevity of drilling motors is a constant struggle. Operating above recommended parameters delivers higher Rates of Penetration (ROP) but can be too aggressive, causing accelerated component wear and potentially, premature failure. Conservative operation decreases the component wear but can be detrimental to drilling performance. A novel approach to controlling motor performance allows operators to operate at specified limits while preventing load spikes that damage motors.
Stalling is a problem that affects bearing loading, occasionally leading to driveshaft torsional failure, but more commonly causing power section damage in the stator, reported as chunking. Chunking occurs when the elastomer in the stator has reached the fatigue limit and small pieces break free of the profile. The output performance of the power section decreases as the effective area of power section is reduced and it becomes less efficient. Reduction in output performance decreases ROP and operators will typically push motors harder to maintain ROP, further accelerating the time to failure.
An innovative internal device prevents premature failure by limiting the amount of differential pressure applied across the motor. Excess pressure is relieved by porting fluid through the center of the rotor, bypassing the power section inlet. Rotational speed decreases as flow into the power section is decreased. The pre-determined relief point is adjustable to optimize motor performance for specific applications. Preventing motor damage delivers longer drilling hours with reduced unplanned trips.
Field testing of the device has resulted in a significant reduction in motor component damage. ROP improved and was consistent through the drilling program with the controlled and steady operation of the device. Cost per foot decreased as longer intervals were drilled per motor. This device gives operators a new tool to optimize motor performance.
An in-depth study of surface torque and its effect on drillstring and bit movement has led to the development of automated technology for optimizing directional drilling with a downhole motor/measurement while drilling (MWD) system. By assimilating surface torque with downhole bit and drillpipe behavior, the technology allows drillers to maximize drilling efficiency and improve wellbore quality (due to less trajectory tortuosity) during the sliding part of the drilling process. This paper describes this proprietary1,2,3 surface system and how developers used torque control to optimize slide drilling without introducing new equipment downhole.
The new technology integrates surface and MWD data to provide the following benefits in the sliding mode:
Improved ROP and horizontal reach capability Improved tool-face correction while drilling Improved well trajectory Improved motor life (less stalling) Quick and accurate tool-face orientation No lost-in-hole exposure Time savings from switching from rotating to sliding without coming off bottom; faster tool-face orientation; overall performance optimization (as listed above)
The elastomer and its bonding system has always been the one of the most critical areas in downhole motor design. The elastomer's physical properties change due to temperature or from reactions with certain chemicals commonly used in drilling applications. This limits both the motor's operational temperature range and the chemicals that can be used in the mud system. While drilling with a conventional motor, heat is concentrated in a regular elastomer power section's lobes forming hot spots which contribute to a premature heat aging of the elastomer. Today, however, a new manufacturing process for stator tubes permits the forging of a pre-contoured lobe configuration - significantly reducing the elastomer content in the power section. This new design broadens motor capabilities by allowing heat to radiate faster from the thin elastomer and significantly improving the motor's mechanical and volumetric efficiency.
The power output of all sizes of positive displacement downhole motors has more than tripled during the past fifteen years. For example, today's 4–3/4" motors are significantly stronger than the 9–1/2" motors built in the 1980's. The latest step change in motor power was achieved in the manufacturing processes that eliminated 60%–80% of the elastomer used in the power section's stator.
These latest generation downhole motors are used as performance motors - delivering over 50% more power output compared to the previous generation motors of the same length and diameter and permitting the operator to select more aggressive bit designs. As a result, operators have experienced Rates of Penetration (ROP) improvements of 100%–300%. In addition, high speed configurations with bit speeds up to 1200 RPM are used in hard and abrasive formations with temperatures up to 160°C (320°F). These configurations outperform previously used turbines where the motors have greater torque capabilities while maintaining full steerability throughout the entire run. Typical performance drilling applications cover re-entry, deepwater and extended reach wells in all parts of the world.
This paper describes the technical features of the latest generation downhole motors in detail and documents their capabilities with case histories from various worldwide applications.
Introduction
Since the commercial introduction of hydrostatic downhole motors to the oil and gas industry in the 1970's, development engineers have worked on the increase of reliability and power output of these systems. Today downhole motors are among the most reliable components in the BHA - providing rotary power to the bit and keeping the well on the desired wellpath. Due to the development of improved manufacturing processes, better materials, and the application of latest design and simulation software, the power output of these downhole motors has increased steadily. Figure 1 shows the development in power output for three typical tool sizes during the past 20 years. Power sections are available asHigh-speed power sections for applications with impregnated bits,High-torque power sections for PDC bit applicationsLow-speed power sections for roller cone bit applications
The latest generation of high-performance motors delivers up to twice the power of previous generation motors and was developed specifically for challenging performance drilling applications. The rugged design reduces the number of thread connections and includes strengthened thread connections to prevent tool failures, high load axial and radial bearings for the use of greater weight-on-bit and faster penetration rates and an improved steering head for more precise directional control.
Setting Free the Bear: The Challenges and Lessons of the Ursa A-10 Deepwater Extended-Reach Well
- Gradishar
Drilling Demanding 16" Hole Section in Deep Gas Fields, Saudi Arabia: Challenges and Advances. Paper presented at the SPE/IADC Middle East Drilling Technology Conference and Exhibition
- S Alkhamees
- Z Klink
- M Isbell
Slide Drilling-Farther and Faster
- Duplantis