bluuebunny/crossref_metadata_2025_split huggingface dataset:
Code Generation of Automatic Drilling Control System Functions with Embedded Verification and Validation Functionalities
Authors: Cayeux E. , Mihai R. , Herikstad R. V. , Olsen K. K. , Antosz K. , Pham M. 
Published: February 2025

Abstract
Over the past decade, the adoption of drilling process automation solutions has significantly enhanced drilling operation efficiency. This improvement has been achieved because Drilling Control System (DCS) providers have enabled external service companies to offer dynamic advice that can be used to parameterize Automatic Drilling Control System (ADCS) functions. However, developing externally managed ADCS functions poses challenges, particularly given the risk of potential failures due to spurious parameters. Therefore, it is essential to find a method to ensure that an ADCS function remains safe, regardless of the external inputs and measurements on which it depends. Typically, there are four types of ADCS functions: Fault Detection, Isolation, and Recovery (FDIR); Safe Operating Envelope (SOE); controllers; and automated procedures. The Drilling and Wells Interoperability Standards (D-WIS) sub-committee of the Drilling Systems Automation Technical Section (DSATS) has defined a general declarative data model that enables the description of ADCS function behavior. This data model allows external advisors to discover ADCS capabilities. Moreover, the same declarative description can be used to automatically generate code for ADCS functions, similar to how high-level programming languages are compiled into low-level microprocessor instructions. To support this, a low-level interface to the DCS has been defined. This interface is built to be resilient to unexpected communication failures, as it incorporates embedded Safe Mode Management (SMM), which transitions control from automated to manual mode in such situations. The interface is designed to handle potentially unacceptable values for each variable in its functions. Once the low-level interface to the DCS and the automatic code generator are certified, the only potential source of error lies within the logic of the ADCS function description itself. Given that this description is computer-interpretable, it is possible to execute automated test suites to verify the integrity of the ADCS function description. Additionally, it is feasible to mathematically verify certain properties of the ADCS function, such as whether it avoids infinite loops and reliably reaches an end state. Statistical information about path coverage in the finite state automaton graph underlying the data model can also be extracted. By using the ADCS declarative description as the sole information source for generating ADCS functions, the descriptions remain synchronized with their implementations. The industry-led initiative to enable interoperability between drilling computer systems at rig sites has a transformative impact, unlocking new possibilities such as the automatic generation of ADCS functions—capabilities that would be inconceivable without a comprehensive framework like the one established by D-WIS.
Impacts On Tare Quality and Best Practices from Fleet-Wide Breakover Detection Algorithm
Authors: Groh A. , Kaya M. E. , Dunbar D. 
Published: February 2025

Abstract
Previous work from this contractor highlighted development of a system to detect drillstring breakover through application of Hidden Markov Models to real-time data. The system offered to improve weight-on-bit (WOB) and differential pressure (DP) measurements through more accurate taring, as well as general torque and drag (T&D) monitoring and connection optimization. Fleet-wide deployment of this system has offered several routes for optimization and key learnings that have improved taring quality and general understanding of drillstring behaviors. This work will highlight some of these findings and provide recommendations for when and how to tare in the weight-to-slips portion of a drilling connection.
This contractor first developed the system in late 2022 and has since deployed it to all onshore drilling rigs in its fleet, with controls-level integration on several rigs in late 2023. These deployments were performed by utilizing on-location compute to detect and measure breakover events for every motion performed. Throughout deployment several cases were studied in detail that offered significant learning and improvements on best practices. Additionally, a fleet-wide analysis of over 70,000 drilling connections was performed to understand large scale behavior of the generated tare references and the behavior of drag.
While taring, the system was critical for ensuring accuracy. Traditional tares performed while tagging bottom in lateral sections, and even some deep intermediate sections, were found to be inadequate and generated significant error due to high drag or delays in pump pressure stabilization. Throughout these processes several interesting phenomena have been observed, including sudden, large changes in static hook load between stands, as well as speed-dependent drag that must be considered for accurate tares. The system also generates measurements of physical properties of the system, like drillstring axial stiffness. These estimates were found to align nicely to their theoretical values in many instances, validating the approach and measurement scheme. The above has culminated in this contractor's data-driven recommendations for taring prior to drilling connections and is of interest to members of the drilling community for protecting downhole tools and optimizing drilling performance.
Drill Pipe Damage Tracking and Analysis System to Reduce Drillstring Failure
Authors: Zhang Yifan , Cao Dingzhou , Moos Sheldon , Vora Kumar , Ashok Pradeepkumar , Chen Dongmei , van Oort Eric 
Published: February 2025

Abstract
Drill pipe (DP) damages, caused by excessive loads and suboptimal drilling operations, can lead to undesired drilling dysfunctions, extra non-productive time, and increasing pipe repair expenses. Identifying the root causes of DP damages and their correlation to the drilling programs can help optimize the well/drillstring design as well as the drilling operation and ultimately reduce the risk of severe drillstring failure. In this study, over 300 DP inspection reports (over 170,000 joints of 5" and 5.5" DPs) and drilling data from over 1,000 wells are investigated to summarize the average connection damage rates and DP thickness loss. Damage decomposition among thread, seal, hardband, reface, damage beyond repair (DBR), and thickness loss are concluded for different pipe sizes, formations, and contractors. Furthermore, operation envelope, mud type, vertical/lateral footage, lithology, drillstring structure, and other well designs are selected as essential features for the damage-operation correlation analysis. Cases of severely damaged strings are investigated as well. Based on the analysis results, a comprehensive understanding of DP damage rates and mechanisms has been achieved to practically optimize drilling jobs, reduce drillstring failure risks, and cut drilling expenses. A DP analysis automation pipeline is also built to make the analysis results evergreen.
From Bit-Rock Interaction to BHA Vibration: Experimental and Numerical Perspectives
Authors: Mahjoub M. , Nguyen K.-L. , Dao N.-H. , Menand S. , Endres L. , Cheng C. , Mada H. , Feng X. , Sun J. 
Published: February 2025

Abstract
Studies indicate that the interaction between the drill bit and rock formations induces vibrations along the bottom hole assembly (BHA). Parameters such as weight on bit (WOB) and rotation speed affect the engagement of the cutters in the rock, otherwise known as depth of cut (DOC). DOC is crucial for bit stability; a poor BHA design combined with a suboptimal choice of DOC can lead to axial, torsional, and lateral instabilities (bit bounce, stick-slip, and bit whirling phenomena). Optimizing the bit design to address these vibrations is vital for improved drilling performance. Both experimental studies in the lab and numerical simulations are essential tools to test and improve bit design before real-world drilling.
In this work, a transient bit-rock interaction model is implemented to study the evolution of cutting and friction forces on each individual cutter, whether it is a cylindrical or shaped cutter. Specific models are introduced based on laboratory scratch tests, where the performance of each shaped cutter type is related to its main geometrical characteristics. These elementary forces are combined to provide the overall response of the bit. It accounts for axial, torsional, and lateral motions of the bit as well as the possible transition between different rock layers that generally trigger bit instability. This model is coupled with a time-domain dynamics model of the drill string to examine the implications of the cutting process on the BHA vibration. Experimental lab data on a drill bit are used as a basis to calibrate the model. The experimental measurements are then complemented with the simulation results to have an in-depth understanding of the bit behavior.
Comparisons of lab and simulation results showed a good agreement for WOB, torque on bit (TOB), and lateral acceleration. Based on these results, the numerical simulations allowed investigation of the cutter elementary forces, ranking them in terms of work rate and durability. Moreover, the simulations showed how bit whirl can propagate upwards in the string, creating lateral vibrations in the rotating shaft. With the collected information on the bit behavior, an application is carried out on a realistic BHA and wellbore trajectory, and the vibration levels are analyzed along the whole BHA.
This scope of work has many implementations, testing different combinations of drill bits, rock formations, and drill string assemblies. It can be used either as a pre-analysis tool to optimize the bit and BHA designs, or as a post-analysis tool to understand a specific vibration event and prevent recurrence. The addition of new elementary cutting models for different shaped cutters provides other axes of bit design improvements, where the type, number, and placement of the shaped cutters can be investigated.
Corrosion Fatigue Analysis for Tubular Design in Geomechanical Energy-Storage Wells
Authors: Liu Zhengchun , Samuel Robello 
Published: February 2025

Abstract
Recently, geomechanical pumped storage (GPS) emerged as a new approach for storing electric energy from solar or wind power. To charge, water is pumped down the well into high-pressure reservoir. To discharge, high-pressure water flows up to drive a turbine. The cyclic operations in a GPS well cause changes in temperature and pressure of the wellbore, which may lead to fatigue failure. This paper presents an integrated solution of fatigue analysis for GPS well integrity. The varying casing temperatures and temperature-dependent casing loads were obtained through numerical simulations of cyclic operations such as water injection, shut-in, and water production. All these simulations were accomplished using commercial software, including a thermal flow simulator and stress analyzer. The previously simulated casing loads were then used to calculate localized stress amplitude, strain amplitude, and mean stress. Finally, the localized strain and stress values were used as input parameters of a corrosion fatigue model to estimate the lifetime (cycles) of each tubing or casing section. The corrosion fatigue model was implemented in a computer program and integrated with the thermal flow and stress analysis commercial software. A field case of a GPS well was studied with the integrated thermal fatigue simulation. The tubing/casing failure locations were analyzed and explained in terms of environmental conditions and cyclic stress/strain conditions. The field case study indicates that the traditional stress or strain-based fatigue analysis might not be adequate to assure wellbore tubular integrity. In the aqueous environment, corrosion fatigue is necessary for certain carbon steels and alloy steels. When integrated with numerical thermal flow simulation and multi-string stress analysis, the corrosion fatigue model provides a more accurate fatigue life estimation of casing and tubing in GPS wells. Corrosion fatigue model was coupled with wellbore thermal flow analysis, helping to proactively prevent tubing/casing fatigue failure during the cyclic operations in GPS wells and other similar scenarios. It provides an important design rationale for total well integrity.
Rethinking CO2 Injection Wells for Next-Generation Offshore Carbon Storage
Authors: Hassan A. , Jaculli M. A. , Schei H. , Stanko M. , Sangesland S. 
Published: February 2025

Abstract
Carbon Capture and Storage (CCS) is critical for meeting global climate goals, yet its large-scale deployment faces significant economic and operational challenges. This study introduces lean CO2 injection well designs to address scalability issues, emphasizing cost efficiency and well integrity. By leveraging design innovations such as mechanical Downhole Safety Valves (DHSVs) and simplified casing configurations, the proposed concepts achieve up to 25% cost savings compared to traditional designs. These improvements are tailored to meet regulatory requirements while enabling large-scale implementation.
The research evaluates three novel well concepts, analyzing material and operational cost reductions alongside well integrity consid- erations. The study highlights the limitations of conventional two-barrier philosophies for CCS and presents strategies to align innovative designs with existing frameworks. By integrating cost-effective and scalable solutions, this work provides a pathway for advancing CCS technologies and achieving storage targets of 1 Gt annually by 2030.
Well Repurpose Potential for Geothermal Heat: Comprehensive Assessment Tool Integrating Economic and Environmental Aspects to Facilitate Educated Investment Decisions
Authors: Mozas J. M. , Zikovic V. , Reinicke A. 
Published: February 2025

Abstract
In the Netherlands and across Europe, many oil and gas wells are scheduled for plugging and abandonment due to uneconomical conditions. The potential for repurposing these wells for geothermal heat production or energy storage is often overlooked due to conversion costs, liability transfers, marginal economics, and well integrity challenges. However, well repurposing is increasingly recognized as a strategic research priority in Europe, supported by several past and ongoing projects. To address the lack of publicly available methodologies, we propose a structured approach for screening wells and guiding users in the selection process. This methodology is based on reservoir, well, and surface requirements, with future integration of heat networks to complete the ranking options. The workflows help identify promising candidates and their specific repurposing potential. Once options are identified, an economic assessment, including a life-cycle analysis, is performed to determine the net present value (NPV), levelized cost of heat (LCoH), and specific CO2 footprint of each repurposing option. A comparison with the costs and energy output of constructing a new well is then conducted to identify the most advantageous solution. This paper presents a standardized workflow to assess the repurposing potential of wells, both in generic terms and as applied to Dutch wells using publicly available data.
Effect of Modularity on the Thermal Management of Optimized Printed Circuit Boards for Geothermal Drilling Tools
Authors: Plata G. , Singh S. , Clegg J. 
Published: February 2025

Abstract
This paper investigates a novel approach to thermal management in high-temperature Measurement While Drilling (MWD) tools, addressing critical challenges in geothermal drilling where conventional systems fail to operate efficiently above 175-185 °C. The proposed design integrates modular mechanical housing and advanced thermal management systems optimized for circular, axially stacked Printed Circuit Boards (PCBs).
Using Aluminum Nitride (AlN) ceramic PCBs for their superior thermal conductivity, the design enables radial heat dissipation, reducing thermal resistance and maintaining operational stability under extreme conditions.
Results indicate that the modular design ensures effective heat evacuation through metal-to-metal contacts and optimized chassis geometry. At a nominal chip power of 0.5 W, the maximum temperature increase remained below 3.5 °C for four PCB stacks and 210 °C mud temperature, highlighting the system's reliability. The findings underscore the importance of modularity for simplifying assembly and improving thermal management in harsh environments.
Predicting Drill Bit Remaining Useful Life and Identifying Drilling Disfunctions by Physics-Based Inversion and Data-Driven Model - Case Study of Utah Geothermal Wells
Authors: Lee H. , Mitkus A. , Ziehm T. , Gee T. , Reynerson P. , MCcarthy K. , Gupta P. , Agarwal N. , Willerth M. , Pare A. 
Published: February 2025

Abstract
Drilling through hot rocks in geothermal wells often leads to multiple unplanned trips due to issues such as drilling dysfunctions, thermal degradation of cutters, inadequate hole cleaning, tool failure, and lost circulation. Accurately predicting bit conditions in real-time can help avoid poor decisions, such as continuing to drill with a damaged bit or pulling the bit out too early. This paper focuses on developing a hybrid model that combines physics-based inversion with data-driven techniques to accurately estimate the remaining useful life (RUL) of drill bits and detect drilling dysfunctions in geothermal wells in Utah.
This approach combines inversion models for depth relaxation with machine learning algorithms to predict the drilling performance of each bit run in geothermal drilling operations. Data on drilling dynamics, total flow area (TFA), and bit dull grade were collected from 63 PDC bit runs in the lateral sections of 15 geothermal wells with an 8.75-inch hole size. The collected data was used in physics-based inversion to calculate relaxation depth, while the machine learning model identified patterns related to bit wear, drilling anomalies, and dysfunctions. Historical data and real-time drilling parameters were utilized to train and validate the model.
The hybrid model showed substantial improvements in predicting the RUL of drill bits and detecting drilling anomalies and dysfunctions. Specifically, it was observed that short run depths could result from fast relaxation depth, which is linked to inefficient drilling, anomalies, or dysfunctions. Additionally, the study found that increasing TFA could mitigate the thermal degradation of bit cutters. These factors—relaxation depth, run depth, and TFA—were used as inputs for a machine learning model to predict RUL and bit dull grades for each bit run. Furthermore, the physics-informed machine learning model can guide the selection of drilling set points when anomalies or dysfunctions occur, enabling timely resolution. The integration of physics-based and machine learning approaches yielded high prediction accuracy, reducing non-productive time and optimizing drilling performance. This method has the potential to be applied across various geothermal fields, providing a valuable tool for enhancing drilling efficiency and lowering operational costs.
This research presents a novel integration of physics-based and data-driven models for predicting drill bit RUL and identifying drilling dysfunctions. A key aspect is the exploration of the previously unexamined relationship between run depth and relaxation depth in the inverted domain. This analysis aims to enhance predictive accuracy and operational efficiency in geothermal drilling. The innovative approach marks a significant contribution to the advancement of drilling optimization techniques.
Slot Recovery Based on the 3D Dubins Curve Method
Authors: Liu Haoge , Aadnøy Bernt Sigve , Gjersvik Tor Berge , Kaarstad Eirik , Krossnes Bjørn Schmidt 
Published: February 2025

Abstract
This paper introduces the application of the 3D Dubins curve method for sidetrack trajectory design in slot recovery. With the constraints and the objective given, the method can quickly determine the optimal sidetrack kickoff point (KOP) location and generate the optimal sidetrack trajectory in just seconds. Robustness and efficiency of the method are demonstrated in the case studies with both synthetic data and real field data with various constraints such as location limits, angle limits and anticollision. The case studies also demonstrate how different constraints or objectives affect optimal sidetrack trajectory. Compared to the conventional sidetrack design process when complex constraints are involved, our method can be a game changer as it only cost seconds to investigate the objective subjected to the target and various constraints information.
Automated Correction of Drillstring Data for Improved Reliability and Trust in Use of Physics-Based Models in Drilling Advisory Systems
Authors: Yoon D. , Yi M. , Cortez J. , Behounek M. , Ashok P. 
Published: February 2025

Abstract
A major challenge in utilizing physics-based models such as torque and drag (T&D), hydraulics, cutting transport, drillstring dynamics, etc., in real-time, and with high reliability and confidence has been the lack of accuracy in drillstring data available as input to these models. This paper describes a methodology to automatically cleanse drillstring data, ensuring that the model outputs are accurate and trustworthy.
The data cleansing process involves comparing measured data with model predictions and iteratively resolving the anomalies. First, the unit weights and lengths of the bottom hole assembly (BHA) components are adjusted by minimizing a specially defined loss between the measured and predicted hook load from a T&D model. Subsequently, the outer diameter (OD) and inner diameter (ID) of the components are corrected by minimizing the discrepancy between the observed standpipe pressure and the modeled pump pressure using a hydraulics model. In addition, the method leverages a comprehensive database of manufacturer drillstring specifications to ensure that the corrected values are realistic.
The proposed approach was rigorously validated using field data, demonstrating its effectiveness across various BHA combinations and wellbore conditions. Additionally, by using a comprehensive drillstring specifications database, the process achieved greater robustness, particularly improving corrections in scenarios where field data was limited. After data cleansing, both the T&D and hydraulics models showed significant improvements in accuracy. The T&D model aligned more closely with field data, resulting in more accurate friction factor and downhole weight on bit (WOB) estimations. Furthermore, the hydraulics model provided better pressure estimates along the drill string, enhancing the safety of well construction. Other models, such as hole cleaning and drillstring dynamics, also stand to benefit significantly, leading to better downhole situational awareness and more reliable drilling operations.
This paper is the first to describe an automated drillstring data cleansing method that enhances the quality of critical input parameters for various drilling-related models. The proposed approach seamlessly integrates information from multiple models, real-time data, and a comprehensive database to ensure precise and consistent correction of drillstring specifications. This approach promises to significantly increase the use of physics-based models in real-time advisory and automation systems.