Closed-Loop Digital Workflow to Drive Drilling Performance

Drilling operations in the US Permian Basin shale play with a new 4-¾" Rotary-Steerable Drilling System (RSS) revealed that with high Rates Of Penetration (ROP), high Weight On Bit (WOB) (and other drilling parameters) encountering stringers or interbedded formations can lead to unwanted effects. The Bottom Hole Assembly (BHA) can be deflected before the steering unit with its steering pads can counteract the deflection. This can lead to deviations from the directional plan and High Local Doglegs (HLD) when drilling in the horizontal/lateral section, which can have a negative impact on the electronics within the steering unit. As a countermeasure, a combination of a pin-down connection steering unit with a short box-up connection drill bit, or Integrated Bit (IB), was developed. This combination allows a much shorter bit to steering pad distance. Due to the shorter bit-to-pad-distance an improved steering response is expected resulting in fewer high local dogleg occurrences. The integrated box-up bit basically moves the drive-shaft pin-down connection into the drill bit. The remaining bit shank is very short requiring modifications to the make-up and break-out procedure. Results from the data acquired in the Permian Basin shale play yielded promising results in terms of steering accuracy. When comparing bending cycle load vs. local Dogleg Severity (DLS), local DLS are typically lower and have less bending cycles drilling through these critical local DLS when IB were deployed. The overall average ROP of runs with IB is higher than the overall average ROP of runs with standard bits. The amount of data collected for this study allows a good statistical approach for comparison of the performance of a standard drilling BHA and bit versus a BHA featuring an IB. It proves that by further reducing the distance between the first formation contact point at the drill bit to the second contact point at the steering unit there is an overall improvement in performance and wellbore placement. This provides opportunities for incremental future optimization of the drill bit and BHA system.

Summary Positive displacement motor (PDM) bottomhole assemblies (BHAs) are widely used in horizontal drilling due to their low cost and high rate of penetration (ROP) under rotary conditions. However, their limited-trajectory control ability often requires switching to sliding drilling for sharp corrections, which significantly reduces efficiency. Moreover, the quantitative relationship between build up rate (BUR) and controllable parameters such as revolutions per minute (RPM) and mud flow rate (MFR) remains unclear under rotary conditions. To address these issues, we propose a machine learning (ML)–based model predictive control (MPC) framework that regulates trajectory solely through real-time optimization of drilling parameters. A hybrid prediction model, integrating mechanical principles and ML, is developed to map weight on bit (WOB), RPM, and MFR to BUR, with a Lipschitz continuity constraint enhancing stability and robustness. The MPC objective function is improved by incorporating adaptive weighting, which accelerates convergence, reduces overshoot, and improves control consistency. The proposed method is evaluated across five simulation scenarios, which are analysis of control behavior, objective function enhancement, piecewise setpoint tracking, comparison with classical controllers, and robustness testing. The approach is validated using field data from a horizontal well in the Junggar Basin, northwest China. The results show that the ML-MPC strategy achieves accurate setpoint tracking under various conditions, maintains strong robustness to input noise, initialization variations, and measurement disturbances (with steady-state error < 0.2°/30 m), and meets real-time computation requirements (<20 seconds per control step). Analysis of the optimized control parameters provides data-driven insights into how WOB, RPM, and MFR influence BUR. Notably, a control inertia effect is observed: When the control objective aligns with the existing trend of variation, the system responds more efficiently; when it opposes the trend, the response becomes slower and more prone to overshoot. Overall, this work presents a practical framework for real-time trajectory control and contributes to the automation and intelligent drilling technologies in the oil and gas industry.

The drilling process in a 12.25-in. directional section with motor bottomhole assembly (BHA) in one North Kuwait field was impacted by elevated levels of vibrations, which limited weight transfer to the bit and rate of penetration (ROP), thereby affecting overall drilling efficiency. This paper analyzes the effect of introducing an axially operating friction reduction system (FRS) in the BHA while maintaining the dynamic drilling metrics, and the resulting efficiency. The approach comprises quantitative comparison of average ROP required to drill the 12.25-in. section, between well (A) with an FRS in the drillstring and those offset wells (B and C) without the FRS. The wells selected for comparison had identical well trajectory, BHA, and drilling metrics. The FRS consists of two major components – One that generates pressure pulses, and the other that converts these pressure pulses into axial excitations. The excitation keeps the drillstring in a state of constant axial oscillation, which reduces the static friction from interaction with the wellbore, especially in the directional section. Placement analysis to determine the position of the FRS in the drillstring for optimal friction reduction was executed, taking into account the well trajectory, outer diameter (OD) and inner diameter (ID) of BHA components, torque and drag (T&D), weight on bit (WOB), flow rate, and mud weight (MW). The result of the data analysis indicated that, for the same drilling metrics, the addition of an FRS in the drillstring of well A had enhanced the drilling efficiency compared to the offset wells B and C. This was evidenced by the increase in the sliding ROP by 56%, rotating ROP by 38%, overall section ROP by 34%, and reduction in on-bottom drilling hours by 35%. No interference of frequency with the measurement-while-drilling (MWD) tool was observed, and logging-while-drilling (LWD) real-time data was successfully decoded throughout the run. The FRS did not show any compatibility issues with the remainder of the BHA components. The consistent oscillatory excitation of the FRS notably reduced static and dynamic friction. As a result, it successfully assisted in mitigating vibrations and stick-slip (SS), enabling efficient transfer of WOB in the directional section that resulted in performance improvements. The overall study shows that the first FRS run on this field was significant in reducing friction and its resulting vibration in the directional section, the benefits of which include enhanced drilling performance, lower mechanical specific energy (MSE), reduced nonproductive time (NPT) and better tool reliability and maintenance. The result of this initial run has become a benchmark to expand the utilization of the FRS more widely in this field.

During the drilling operations, optimizing the rate of penetration (ROP) is very crucial, because it can significantly reduce the overall cost of the drilling process. ROP is defined as the speed at which the drill bit breaks the rock to deepen the hole, and it is measured in units of feet per hour or meters per hour. ROP prediction is very challenging before drilling, because it depends on many parameters that should be optimized. Several models have been developed in the literature to predict ROP. Most of the developed models used drilling parameters such as weight on bit (WOB), pumping rate (Q), and string revolutions per minute (RPM). Few researchers considered the effect of mud properties on ROP by including a small number of actual field measurements. This paper introduces a new robust model to predict the ROP using both drilling parameters (WOB, Q, ROP, torque (T), standpipe pressure (SPP), uniaxial compressive strength (UCS), and mud properties (density and viscosity) using 7000 real-time data measurements. In addition, the relative importance of drilling fluid properties, rock strength, and drilling parameters to ROP is determined. The obtained results showed that the ROP is highly affected by WOB, RPM, T, and horsepower (HP), where the coefficient of determination (T2) was 0.71, 0.87, 0.70, and 0.92 for WOB, RPM, T, and HP, respectively. ROP also showed a strong function of mud fluid properties, where R2 was 0.70 and 0.70 for plastic viscosity (PV) and mud density, respectively. No clear relationship was observed between ROP and yield point (YP) for more than 500 field data points. The new model predicts the ROP with average absolute percentage error (AAPE) of 5% and correlation coefficient (R) of 0.93. In addition, the new model outperformed three existing ROP models. The novelty in this paper is the application of the clustering technique in which the formations are clustered based on their compressive strength range to predict the ROP. Clustering yielded accurate ROP prediction compared to the field ROP.

SummaryReamers are an integral part of deepwater Gulf of Mexico (GOM) drilling and their performance significantly impacts the economics of well construction. This paper presents a novel programmatic approach to model rate of penetration (ROP) for reamers and improve drilling efficiency. Three field implementations demonstrate value added by the reamer drilling optimization (RDO) methodology.Facilitated by user interface panels, the RDO workflow consists of surface and downhole drilling data filtering and visualization, detection of rock formation boundaries, frictional torque (FTRQ) and aggressiveness estimation, ROP modeling with analytical equations and machine learning (ML) algorithms [regression, random forests, support vector machines (SVMs), and neural networks], and optimization of drilling parameters. ROP model coefficients and bit and reamer aggressiveness are dependent on lithology and computed from offset well data. Subsequently, when planning a nearby well, bottomhole assembly (BHA) designs are evaluated on the basis of drilling performance and weight and torque distributions between cutting structures to avoid early reamer wear and dysfunctions. Geometric programming establishes optimal drilling parameter roadmaps according to operational limits, downhole tool ratings, rig equipment power constraints, and adequate hole cleaning.Separate ROP models are trained for reamer-controlled and bit-controlled ROP zones, defined by the proportion of surface weight on bit (WOB) applied at the reamer, in every rock formation. This novel concept enables ROP prediction with the appropriate model for each well segment depending on which cutting structure limits drilling speed. In the first of the three RDO applications with field data from deepwater GOM wells, optimal bit-reamer distances are determined by analyzing reamer weight load in uniform salt sections. Next, ROP modeling for the addition or removal of a reamer from the BHA is used in contrasting well designs to conceivably alleviate a USD 16 million casing inventory surplus. Finally, active optimization constraints are investigated to reveal drilling performance limiters, justifying equipment upgrades for a future deepwater GOM well.The proposed innovative workflow and methodology apply to any drilling optimization scenario. They benefit the practicing engineer interested in drilling performance optimization by providing insights on how different cutting structure sizes affect ROP behavior and ultimately aiding in the selection of appropriate bit and reamer diameters and optimal operational parameters.

When drilling wells for hydrocarbon extraction, completing a specific interval of the well in the fastest time possible is a key requirement. One of the main contributing factors for improved performance is the drill bit. It is well known in the drilling industry that the stress state of the formation around the bit and drilled well is significantly lowered once penetrated by the bit. Conventional single diameter polycrystalline diamond compact (PDC) drill bits are not capable of taking advantage of this reduced effective rock strength. Dual-diameter bits address the identified challenges through the use of elegant physical principles and offer an efficient, reliable means of drilling. The concentric, dual-diameter design lowers the effective rock strength encountered by the critical shoulder-to-gauge area of the bit's cutting structure. The smaller pilot section of the bit design drills a pilot hole, which reduces the confinement and thus strength of the rock drilled by the larger reamer section. The reamer section of the bit is able to utilize the bedded pilot bit for stabilization to offset the greater forces associated with larger diameter drilling. The offset blade configuration of the bits also offers 360-degree contact the borehole and helps deliver a gun barrel hole quality. This paper introduces the development of a unique, two-stage, dual-diameter profile, and polycrystalline diamond compact drill bit for an application in Indonesia. Typically, multiple drill bits are required to finish the section, which consists of abrasive sandstone with some layers of coal. The objective was to improve the drilling performance while also minimizing non-productive time (NPT) for a bit trip. The paper provides and in-depth evaluation of the bit performance over several field trials. The first bit was run in a motor assembly and improved 14% rate of penetration (ROP) with exceptional dull condition. The drilling parameters indicated that the bit generated higher ROP with lower weight on bit (WOB) compared to other bit types. This performance convinced the operator to run the dual-diameter PDC bit in a more challenging field where its remarkable performance achieved field records. In comparison to the closest offset well, dual-diameter drill bits replaced three-bit runs with 56% longer intervals drilled and improved overall ROP by 41%. In addition, rig time was reduced by 5.3 days. The operator was extremely pleased with the bit performance and decided to use a dual-diameter PDC bit as the primary option to drill this section in every field.

Rig automation is becoming common practice, due to increased instrumentation on the drill-floor and the possibility to communicate and control the drilling machines via an Automated Drilling Control System. Active control of the drilling process itself (i.e. hole creation) is an active field of innovation, with several solutions being currently developed. We consider here the testing and validation of such a drilling optimization system. This system continuously computes set-points for the three main rig machines (hoisting, rotation, and circulation systems) so that the performances are optimized (highest Rate of Penetration (ROP) as possible) while ensuring that the process as a whole is still conducted in a safe manner. This involves limiting the possible range of setpoints to avoid cuttings transport issues, buckling or high downhole pressures. In this context, one of the key features is the ability to react quickly to changes in downhole conditions: abrupt formation changes and founder point excess are the two main scenarios that are considered. When such changes occur, it is important to react in a timely fashion to avoid unwanted situations (for example high Weight on Bit (WOB) when entering a hard formation while in ROP mode). This feature requires a continuously updated response model of the drill-bit: this relies on constant calibration of a bit-response model, that relates the surface parameters (Block velocity, top drive RPM and pump rates) to the well’s response, WOB, bit torque and estimated ROP. The system involved in this study performs this calibration using particle filter algorithms, providing constant estimates of the current formation properties and bit characteristics. The calibrated model is thereafter used to generate optimum set-points to the machines. Testing such a system can be challenging because of the inter-dependency between the bit-response calibration and the set-points computation. Offline or passive testing provides little value because the calibration relies on sufficient excitation of the system: standard drilling data sets usually use constant set-points while on-bottom, and the calibration becomes suboptimal. In turn, the set-point generation process cannot determine optimum values due to the lack of properly calibrated models. A solution is to base the testing and validation on a simulated environment. This requires a high-fidelity drilling simulator that can be integrated with the automation system. We present in this paper how such a simulator was used to test the drilling optimization system under a variety of possible scenarios, which would have been impossible in a passive mode on a drilling rig. Along with the requirements on the simulation environment, the testing methodology will be presented, together with the different metrics used to validate the system.

This paper describes a new Rotary Steerable System (RSS) and results from its field testing program. The RSS has been designed to handle the technical requirements of the most challenging wells, but also to be economical for use in low cost wells. This important feature was achieved by a unique hydraulics and electronic design and through the use of durable but low cost materials. The tool itself consists of three active and independent steering blades placed close to the bit, and a near-bit stabilizer which acts as a fulcrum. The steering blades apply a constant force to the formation. The displacement of the blades is measured to offset the Bottom Hole Assembly (BHA) in the desired direction. The clamping force of the tool in the hole acts to stabilize the lower part of the BHA and remove unwanted vibration and instability from the drill bit. This significantly improves BHA response, borehole quality, ROP and bit life. Since the RSS has a full 3D capability, it can drill constant curvature boreholes in any direction. The tool has been tested in wells in Texas, Louisiana, Oklahoma and the Gulf of Mexico. The results of these tests will be presented in detail. It is shown that BHA optimization can make a significant difference to the quality of directional holes drilled with a RSS. The data obtained during testing have, in fact, lead to an optimized BHA configuration which is unique compared with any other existing RSS. This optimized BHA configuration was determined from test runs in both point-the-bit and push-the-bit modes. Through the course of this exercise, it was shown that point-the-bit technology can provide superior borehole quality, improved Rate Of Penetration (ROP) and consistent Dog Leg Severity (DLS). Finally, the improved performance and time saving obtained with this new RSS will be compared with offset data from directional wells that were drilled with conventional steerable motor assemblies.

This paper outlines the development of a gas field in a mature carbonate reservoir via an onshore Extended Reach Drilling (ERD) well in Abu Dhabi, featuring a 24,000-foot lateral section. The operator aimed to achieve a drilling rate of 1 mile per day. However, both the landing and lateral sections presented significant drilling and geological challenges, including subsurface uncertainty, rig limitations, high downhole temperatures, and Effective Circulating Density (ECD) management. In addition, maintaining 100% reservoir contact required frequent well path adjustments via manual geosteering, introducing performance variability and human error. These challenges constrained the rate of penetration (ROP) and increased overall well costs. This paper presents a customized drilling and subsurface solution combined with a downhole drilling automation system that enabled 100% reservoir contact and saved 4.6 drilling days. A new Intelligent Rotary Steerable System (RSS) was deployed in combination with an Ultra High Torque Motor to maintain consistent weight on bit (WOB) and differential pressure (>500 PSI while drilling) along with compatible bit to achieve target ROP. Deep Reservoir Mapping tools were critical in navigating the thin carbonate reservoir, enabling real-time identification of formation dip changes and reservoir boundaries above and below the wellbore, contributing to higher ROP. Autonomous downhole directional drilling tools allowed continuous well-path adjustments, enhancing placement precision within the reservoir. Integration with automated geosteering software reduced decision-making cycle time from ∼15 minutes to <5 minutes. The closed-loop automation also minimized RSS setting changes, promoting smoother wellbores and facilitating efficient deployment of the production Bottom Hole Assembly (BHA), while reducing invisible lost time. Vibration mitigation was achieved through the combined use of Motorized RSS and Anti-Stick Slip tools. The well reached total depth (TD) at 34,127 feet Measured Depth (MD) successfully with 23,095 feet of 8½" lateral section drilled, and 100% reservoir contact achieved. A record onshore daily footage of 4,076 feet was attained in the UAE. This marked the global debut of the new 6¾" Motorized RSS. Integration of the autonomous downhole directional drilling system with the Motorized RSS and Deep Reservoir Mapping enabled precise control throughout the lateral section. The solution reduced RSS control interventions, improved ROP by 47%, and significantly enhanced the speed and accuracy of geosteering versus offset wells. The successful integration of automated and customized drilling technologies represents a transformative step in ERD well execution, significantly reducing well time and increasing drilling efficiency. The scalable and repeatable nature of this autonomous downhole drilling solution offers a robust framework for future field development in similarly complex environments.

Establishment of data-driven multi-objective model to optimize drilling performance

The oil and gas industry is constantly motivated to implement strategies focusing on cost management and operational optimization to maximize productivity. Rate of Penetration (ROP) serves as a key performance metric, reflecting the speed at which a drilling bit penetrates subsurface formations. Increasing ROP can minimize costs by reducing drilling time. ROP prediction models aid drilling optimization plans since accurate models are required to find ideal controllable parameters to increase ROP using optimization algorithms. Drilling characteristics that significantly influence ROP include bit type, formation properties, and operation parameters, such as Weight on Bit (WOB) and Rotations per Minute (RPM). The number of significant parameters makes it difficult to develop analytical expressions for predicting ROP. The present work investigates the applicability of Artificial Neural Networks (ANN) for ROP prediction using public data from three wells extracted from the Volve oil field in the North Sea. The adopted strategy is to learn from offset wells, which means using data from two wells to predict the ROP for the third. This approach helps to address a practical scenario where historical data are used to make predictions for a new well in a close region. This study uses MLP (Multilayer Perceptron) networks with WOB, RPM, Torque, Fluid Flow rate, and Delta-T Compressional as features, and the training process is conducted using the GridSearchCV method for hyperparameter tuning, comparing different model architectures to improve results. To assess the final performance of the model, metrics such as Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) are applied to the tested well. The results show that the developed model can capture ROP patterns without requiring any data stratification of the two wells regarding lithology information.

Motion states of bottom hole assembly (BHA) have a great effect on the trajectory control and drilling efficiency while rotary drilling. In order to study the motion states of BHA in horizontal wells, a BHA dynamic model with the finite element method was established. Meanwhile, an indoor experimental setup based on similarity criterion was designed and built to verify the numerical simulation results. Finally, the effects of measuring positions, rotate speeds, weight on bit (WOB), and friction coefficients on the motion states were analyzed in numerical simulation and experiment. The results show that the experimental results can match well with the numerical simulation results. The motion states of BHA in horizontal wells can be divided into three kinds, including circular arc swing, "8" shape swing, and dot-like circular motion. The circular arc swing mainly appears at middle section of BHA and occurs through the collective result of gravity and tangential friction. The dot-like circular motion mainly appears at near-bit or near-stabilizer area because drill bit and stabilizer can steady the BHA at the center part of the wellbore. The "8" shape swing mainly appears at the crossed area and occurs through collective disturbance of the other two motions. Moreover, rotate speed and friction coefficient have promotions on the lateral vibration while WOB have a much smaller effect. Through analyses, related suggestions are given for the drilling engineering. The related conclusions and suggestions in this paper can help to further understand the lateral dynamic characteristics of BHA in horizontal wells and select suitable parameters for drilling engineering.

Drilling rate of penetration (ROP) is one of the most important factors that have their significant effect on the drilling operation economically and efficiently. Motorized bottom hole assembly (BHA) has different applications that are not limited to achieve the required directional work but also it could be used for drilling optimization to enhance the ROP and mitigate the downhole vibration. Previous work has been done to predict ROP for rotary BHA and for rotary steerable system BHA; however, limited studies considered to predict the ROP for motorized BHA. In the present study, two artificial intelligence techniques were applied including artificial neural network and adaptive neurofuzzy inference system for ROP prediction for motorized assembly in the rotary mode based on surface drilling parameters, motor downhole output parameters besides mud parameters. This new robust model was trained and tested to accurately predict the ROP with more than 5800 data set with a 70/30 data ratio for training and testing respectively. The accuracy of developed models was evaluated in terms of average absolute percentage error, root mean square error, and correlation coefficient (R). The obtained results confirmed that both models were capable of predicting the motorized BHA ROP on Real-time. Based on the proposed model, the drilling parameters could be optimized to achieve maximum motorized BHA ROP. Achieving maximum ROP will help to reduce the overall drilling cost and as well minimize the open hole exposure time. The proposed model could be considered as a robust tool for evaluating the motorized BHA performance against the different BHA driving mechanisms which have their well-established models.

Several directional wells have been drilled in Majnoon oilfield at wide variation in drilling time due to different drilling parameters applied for each well. This technical paper shows the importance of proper selection of the bit, Mud type, applied weight on Bit (WOB), Revolution per minute (RPM), and flow rate based on the previous wells drilled. Utilizing the data during drilling each section for directional wells that's significantly could improve drilling efficiency presented at a high rate of penetration (ROP). Based on the extensive study of three directional wells of 35 degree inclination (MJ-51, MJ-52, and MJ-54) found that the applied drilling parameters for MJ-54 and the bit type within associated drilling parameters to drill 36", 24", 16" and 12 1/4" hole sections is the best, although the drilling parameters in 8 1/2" hole section for MJ-51 and selected bit type are the best for future wells.

The demands of the oil and gas industry are placing an increased importance on drilling harder, faster, and longer, giving rise to the challenge of premature bit failure due to drilling through transitions of varying rock strength. To address this, new strategies have become more prevalent, such as using automatic drillers operating with a constant rate of penetration (ROP). In this study, a method was developed to analyze the effects of drilling through transitions on bit cutting structures and construct an ideal drilling strategy to mitigate the forces overloading cutters using a detailed drilling model. A digital environment was created to model transitional drilling with the capability to predict downhole conditions when provided with various complex inputs. A polycrystalline diamond compact (PDC) bit design, including cutting structure and other features was first loaded into the model. The desired drilling parameters were provided, and the lithologies of the rock transitions throughout the interval were set. Drilling was then simulated within this digital environment, producing the bit performance data. The data included several high-level performance indicators, such as weight on bit (WOB), ROP, and torque, as well as detailed transient information on individual cutter loading and stress levels. Additionally, the simulation can be viewed as an animation to allow intuitive visualization of the effects of varying transitions on bit performance. By analyzing the outputs from the simulated transitional drilling, conclusions were drawn relating certain drilling parameters and rock strengths to areas of cutting structure damage. When drilling with a constant WOB, it was observed that transitioning from soft to hard formations causes a large increase in instantaneous forces on the cutters in the nose of the bit. In contrast, when transitioning from hard to soft formations, the forces are increased on the cutters in the cone and shoulder. These observations correlate with drilling data and field dull observations. It was found that when drilling with a constant downhole ROP, the cutting structure does not experience transient spikes in cutter loads. The loads approach a new steady state distribution based on the compressive strength of the newly entered formation with little to no overshoot. However, when drillstring compliance was accounted for it was found that drilling at a constant surface ROP can still lead to transient spikes in cutter loads, especially when transitioning from hard to soft formations. Transient load overshoot can be minimized through the use of depth of cut (DOC) limiting features when drilling from hard to soft formations. Based on these observations, the ideal strategy for drilling interbedded transitions is to use a customized cutting structure including DOC features and drill at constant, controlled ROP. These findings, along with the virtual environment and digital simulation capabilities, have the potential to save operators time and resources, and decrease the overall environmental impact of future oil and gas exploration.