bluuebunny/crossref_metadata_2025_split huggingface dataset:
Deep Reinforcement Learning for Automatic Drilling Optimization Using an Integrated Reward Function
Authors: Huang Xu , Luu Trieu Phat , Furlong Ted , Bomidi John 
Published: February 2024

Abstract
Drilling optimization is a complicated multi-objective processing optimization problem. During drilling, drillers need to adjust WOB and RPM continuously in a timely manner, not only to maximize ROP, but also to prevent severe vibration and maintain downhole tool durability. In this study, a virtual drilling agent using a deep reinforcement learning (RL) model is developed and trained to automatically make drilling decisions and proven to effectively optimize drilling parameters.
A deep RL model using a deep deterministic policy gradient (DDPG) algorithm is developed to optimize drilling process. In RL model, the reward of drilling decisions at each drilling step is a function of drilling ROP, downhole vibration tendency, bit dull state, and risks of tool failure. Separate modules to evaluate the reward of each component are implemented and trained using field and laboratory data. Deep RL model is applied and tested comprehensively on different drilling environments including hard and abrasive rock, embedded rock, vibrational vs. stable drilling. The hyper-parameters of the actor-critic NN architecture in RL model are carefully selected to improve the model convergence.
Results show the deep RL model can effectively find the optimum drilling solutions in various drilling environments. In soft formation, RL model applies the upper limit of WOB and RPM throughout the drilling depth to maximum ROP and reduce drilling time. In hard and abrasive formation, RL model gradually changes RPM and WOB to prevent the pre-mature wear of PDC cutters. The change of the drilling parameters is optimized based on rock abrasivity and target drilling depth. In unstable drilling environment, while RL model limits the ratio of WOB and RPM to avoid stick-slip vibration, simultaneously, the WOB and RPM is controlled to maximum ROP to drill to TD. In embedded formation, RL model successfully found the optimum solution by adjusting WOB/RPM to avoid stick-slip and overloading of bit cutting structure. The learning process of RL model shows hyper-parameter selection plays a critical role in model convergence and accuracy. Improperly selected hyper-parameter in RL model can lead to the failure of solution searching or sub-optimum solution. Overall, the RL model is approved to effectively find optimum drilling solutions in the various drilling environments and can be applied for both pre-well drilling planning and real-time drilling optimization.
To the best of authors' knowledge, this is the first attempt to develop deep RL model for drilling optimization by implementing a combination of ROP, vibration, bit dull, and durability in the reward function. The proposed RL model can be extended to include more reward factors in the drilling optimization such as whirl and high frequency torsional oscillation (HFTO), stuck pipe, tool temperature and so on. The RL model can be applied for both pre-well drilling planning and real-time drilling optimization.
Managed Temperature Drilling: An Automated Real-Time Controller for Downhole Temperature Control in Geothermal and HPHT Wells
Authors: Luu A. , Wang N. , Gu Q. , Khaled M. , Ashok P. , Chen D. , Van Oort E. 
Published: February 2024

Abstract
Drilling geothermal and HPHT wells is complicated by exposure of downhole tools to high temperatures. Pro-active downhole temperature management is therefore very important to prevent heat-related tool failure which can result in significant non-productive time and increased costs. Temperature management that relies heavily on surface cooling is currently mostly a manual process. This paper presents a control-oriented platform to achieve automated managed temperature drilling in real-time. For the controller, an improved reduced drift-flux model that considers temperature dynamics, interface mass transfer, and a new lumped pressure dynamics model is used. By considering these factors, the model is used to digitally twin the transient thermal behavior of geothermal wells. The improved temperature model is validated using experimental results from the Utah FORGE 16A(78)-32 dataset. To demonstrate the utility of the model, it is used in conjunction with a controller to simulate maintaining a sufficiently cool bottom-hole temperature for downhole tools in various drilling scenarios. These thermal control scenarios demonstrate that the model can be used for control design, which effectively controls the downhole temperatures during the well construction process. This paper presents the first control-oriented platform that automatically manages the downhole temperature in a geothermal or HPHT well. By using a model capable of real-time simulation, automatic and predictive control algorithms can be applied to reduce negative thermal effects during drilling, thereby significantly decreasing non-productive time events and the cost of constructing a geothermal well.
Application of Advanced Buckling Model Leads to Lighter Well Architecture for Deepwater Development, Saving Cost and CO2 Emissions
Authors: Farmer S. , Aichinger F. , Patel A. 
Published: February 2024

Abstract
The use of basic torque and drag modeling as well as the application of industry-standard buckling formulae can limit the options for well design. Advanced buckling modeling, and a fundamental understanding of the effects of buckling, can be used to generate lighter well architectures, resulting in significant savings in cost and CO2e emissions, without compromising well integrity and zonal isolation.
The fundamental load regime, and associated assumptions, were analyzed to define the worst-case axial load that could be applied to the surface casing of the proposed lighter well architecture. Two different configurations of the surface casing string were modeled in engineering software using a stiff-string model with unique post-buckling capabilities. The identified load cases were simulated, and different sensitivities were performed, to refine the configuration of the surface casing. The detailed results (including von Mises stress, casing deformation, and axial displacement) were interpreted and combined with operational constraints to produce a final surface casing configuration that met all requirements.
The final configuration of the surface casing for the lighter well architecture was estimated to save the operator 5.1 days of operational time per well, generating savings in the region of $4M USD and 1367klbm of CO2e per well. The operator decided to deploy the new architecture on six wells of their ongoing drilling campaign, two of which have already been successfully realized. With this success, the operator is looking to optimize the architecture further by refining some of the conservative load inputs, with measured data, to justify a reduction in the maximum expected load. The advanced buckling model revealed that the distance between centralizers and the radial clearance (created by the geometry of the centralizers) influences the bending stresses in the casing in a nonlinear way and that there is a sweet spot to be found, depending on the axial load. This discovery would have otherwise been missed if industry standard buckling equations were used. Understanding this allowed an informed decision to be made regarding the final configuration of the surface casing.
Understanding the limitations of industry-standard buckling formulae and their use with basic torque and drag modeling will make the practicing engineer aware of other methodologies and processes that can be applied to reimagine their well design.
Avoiding High Local Doglegs by Integrating the Drill Bit into the Rotary Steerable System
Authors: Hahn M. , Heinisch D. , Small C. G. , Cuadros I. , Duerholt R. , Bilen M. 
Published: February 2024

Abstract
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.
Advancement in Autonomous Directional Drilling for Curve and Tangent
Authors: Ba Samba , Roh Si Jine , Riyami Aktham Ali Al , Akkaoui Ziad , Galindo Diana 
Published: February 2024

Abstract
Being able to automate the Directional Drilling (DD) process has significant sustainability effects on the well construction through remote operations and also increased efficiency on the usage of drilling rigs.
In this paper, we will present our advancement on autonomous directional drilling highlighting recent achievements in delivering autonomous sections in numerous fields around the world.
Achieving this fully autonomous mode with rotary steerable system (RSS) applications is not a small feat. It requires state estimation algorithms that can fuse all available downhole measurements to precisely predict the location of the bit at all times. These outputs can further estimate the steering capacity while the bottomhole assembly (BHA) navigates through different formation layers to include a surface deviation controller, which will actively monitor any unexpected deviations and will take the appropriate course of actions to rectify the situation. The state estimation is then fed into a surface automation algorithm that will automatically perform the necessary downlinks and engage suitable downhole control modes inside the RSS tool.
Our autonomous directional drilling system is being utilized and field tested across numerous locations. The system derives the steering recommendations and automatically sends downlinks via the on-target well delivery solution system. This system provides the flexibility for our customers to better design their wellsite footprint accommodating traditional crew models or the ability to operate completely remote. It has been deployed in many countries and with different complexity of directional drilling BHAs. For RSS applications, the solution utilizes both surface and downhole technologies, that creates a symbiosis between the downhole close-loop control and the surface close-loop control for directional drilling.
A novel autonomous directional drilling solution is described here. This intelligent system can automatically derive and execute directional drilling decisions while augmenting the technical personnel’s insights into the drilling process whether they are still on the wellsite or in a remote operation center.
Drill String Failures: Inevitable or Not?
Authors: Plessis G. , Morgan D. , Meinders D. , Wade C. 
Published: February 2024

Abstract
The past few years have seen many experienced drilling operations personnel retire. Coincidently, the industry saw an increase in the number of drillstring failures, some of which could have potentially been avoided. These failures can result in non-productive time (NPT) like fishing trips, side tracking, or exorbitant repair bills, all of which can be costly. The consequence of these failures can be steep, and the objective of this paper is to assist with recognition and prevention of these failures. The number and type of field failures allow us to identify areas of neglect in which shared best practices may have been forgotten or not passed on. A renewed advocation of these essential drillstring running practices will help to mitigate issues before they cause operation disruption and budget overage.
In identifying issues, our intent is to recognize observed variances in running and handling practices that have potential to add complications to well construction, exacerbate budgets, and/or possibly create unsafe working environments. The solutions presented are based on actual field cases and have proven effective. More than ever, variances in best operational practices when running the string have immediate or long-term consequences. Whether the task is slips setting, connection makeup or breakout, elevator positioning, thread compound application, etc., all operations can be poorly executed when adequate information/education is not shared/passed on. As a result, over-torquing (uncontrolled down hole make-up) or, on the flipside, loosening of connections (reactive torque) is far too common and is intensified by the increase of laterals lengths.
One cannot ignore our industry's extreme drive on operation efficiency and cost reduction. Unfortunately, ignoring best practices or minimizing proven steps can be counterproductive, especially in today's more complex wellbore trajectories and demanding drilling programs. The expected outcome of this paper is to identify poor procedural conduct, explain consequences of the same, and inform drilling operations personnel with operational alternatives that will yield results. Explaining the importance and value of these best practices can renew an industry culture driven by safety and performance. Knowing and, more importantly, understanding why procedures require improvement will promote a virtuous behavior. This includes understanding the touch points and critical interfaces that the string has with the rig surface pipe handling equipment, in particular the iron roughneck and the top drive.
Enhancing Operational Efficiency in Directional Drilling Through Precise Hole Bottom Orientation
Authors: Sahli Hussein , Ba Samba , Omr Medhat , Olanubi Olakunle , Galindo Diana 
Published: February 2024

Abstract
This study presents a groundbreaking methodology aimed at achieving optimal precision in estimating the orientation of hole bottoms—a critical factor for the success of Directional Drilling (DD) operations. This process plays a pivotal role in enhancing operational efficiency and reducing costs by integrating measurements from the Measurement While Drilling (MWD) and Rotary Steerable System (RSS). By combining these multiple data sources, a comprehensive perspective of drill bit orientation is obtained, effectively addressing the inherent limitations of individual measurement methods.
The process involves assessing the current bit orientation in relation to the initial plan through RSS measurements and merging it with continuous MWD measurements, tendency estimation, and automated steering mode detection. By integrating these different elements, the process overcomes occasional low azimuth measurement precision associated with RSS due to magnetic interference.
The application of this methodology has yielded substantial improvements in accurately determining hole bottom orientation, achieving an impressive 80% reduction in RMSE compared to conventional measurements. These results establish the methodology as a robust tool in the field of DD. Its successful implementation in drilling operations across diverse geographical locations, including North and South America, the Middle East, East Asia, and Europe, serves as a testament to its potential for widespread adoption. Notably, this methodology has been deployed in 13 different countries.
From a business standpoint, this breakthrough carries significant implications, as it serves as a pivotal digital enabler for reducing personnel requirements in directional drilling and enabling fully remote operations. Consequently, it has the potential to revolutionize the sector.
Beyond enhancing drilling efficiency and reducing operational costs, the solution offered in this study contributes substantially to sustainable well construction. This is accomplished by minimizing resource utilization and energy consumption through precise hole bottom orientation, reducing carbon emissions through remote operations, and extending well lifespans through increased drilling accuracy. The anticipated integration of real-time gyro measurements holds promise for further enhancing operational precision, thereby minimizing waste, and reducing environmental impact.
In conclusion, this transformative approach to hole bottom orientation in drilling operations holds tremendous promise for the future of Autonomous Directional Drilling, with the potential to redefine operational efficiency, cost-effectiveness, and sustainability within the sector.
Drilling Advisory Automation with Digital Twin and AI Technologies
Authors: Cao Jie , Nabavi Josef , Oedegaard Sven Inge 
Published: February 2024

Abstract
This paper presents an autonomous drilling advisory system powered by digital twins and AI solutions. Such an advisory system aims to automate real-time monitoring and parameter optimization, reduce subject-matter experts, and meet the demands for safer and more efficient drilling toward autonomous operation.
The methodology proposed in this research involves the creation of a comprehensive Digital Twin model that accurately replicates the drilling process by integrating hydraulic, thermal dynamic, and mechanical models. To ensure high model accuracy, an auto-calibration approach is developed, driven by real-time data, to fine-tune the Digital Twin models. Additionally, AI-based model reasoning techniques are employed to detect potential hazards and risks ahead of the bit proactively. This is achieved by comparing the ideal behavior of the digital twin replica with the actual behavior observed from downhole and the rig. As a result, real-time diagnostics are generated to supervise ongoing operations, accompanied by suggestions to mitigate identified risks. Furthermore, the system leverages the capabilities of the Digital Twin and optimization methods to create multiple combinations of operational parameters. These parameters are optimized by ranking the predicted performance derived from the Digital Twin. The optimized operational parameters are automatically generated as forward advice to drillers, enabling them to make informed decisions and enhance drilling performance.
Testing results on multiple wells from different operators are presented, showcasing the system's capabilities in real-time monitoring and drilling parameter optimization. The system demonstrates its effectiveness in providing diagnostic messages with early anomaly detection during drilling and casing running. These diagnostic warnings include losses, leakage, poor hole cleaning, and stuck pipe, enabling proactive intervention to mitigate risks. Furthermore, the system optimizes operational parameters during drilling and tripping in real-time without requiring human intervention. This optimization covers parameters such as flow rate, rotary speed (RPM), and rate of penetration (ROP) during drilling, and tripping speed during tripping in and pulling out of the hole. The time savings achieved through the use of optimized parameters are quantified for both cases, demonstrating a substantial improvement in operational efficiency while maintaining safety margins. The scalability and adaptability of the system are also highlighted, emphasizing its ability to accommodate diverse drilling scenarios and integrate with existing solutions in various deployment conditions.
The proposed methodology demonstrates the development of a robust and efficient system that enhances decision-making and improves drilling performance. In addition, the results highlight the potential benefits of combining AI and Digital Twin technologies in the drilling industry, paving the way for future innovations and advancements in the field.
Identifying Cumulative TVD Error in Horizontal Wells Drilled with Rotary Steerable Systems
Authors: Dunn Joel 
Published: February 2024

Abstract
It is known that the Stockhausen Effect, characterized as the accumulation of TVD error in directional wellbores resulting from the slide/rotate process employed with bent-housing mud motors, can have a significant impact on wellbore placement in the TVD plane. While much research has been conducted, and commercial solutions have been deployed to account for and correct these errors, all are focused on mud motor slide/rotate drilling. As contemporary drilling programs move to ever-increasing lateral lengths, utilization of Rotary Steerable Systems (RSS) is also trending upward. While potential advantages may exist in favor of RSS, like the elimination of slide drilling, it is important to consider that not all undesirable phenomena associated with slide drilling (well placement error, tortuosity, rugosity, high localized DLS, etc.) vanish from the wellbore. These characteristics are still present in the RSS wellbore and should be analyzed and quantified to ensure that wellbore quality metrics are consistent for all drilling methods.
To investigate cumulative TVD error in RSS wells, we developed a system to utilize the real time downhole steering data from RSS to populate a steering sheet that can be processed through an algorithm designed to account for TVD errors resulting from the Stockhausen effect. By capturing the RSS toolface and steering proportion in real time, we can determine at what intervals the RSS is actively steering and during what intervals it is drilling in a neutral, non-biasing mode. The result of cycling between steering and non-steering cycles creates a pattern similar to a slide/rotate sequence experienced when using steerable mud motors. This information allows us to construct a more accurate representation of the true trajectory of the wellbore than is provided by minimum curvature between the standard 95’ survey course lengths. In addition to uncovering TVD error this method also provides a higher resolution picture of various tortuosity metrics like borehole curvature and torsion.
We examined data from numerous wells across several basins to observe the TVD error generated by RSS steering mechanisms. It was concluded that these TVD errors should be considered for accurate wellbore positioning, and in addition revealed potential to enhance trajectory optimization capabilities of some Rotary Steerable Systems. In addition to uncovering TVD error, the high-resolution trajectory allows for a thorough examination of wellbore tortuosity, including localized DLS, and wellbore curvature and torsion to aid in identifying potential trouble zones in the lateral.