bluuebunny/crossref_metadata_2025_split huggingface dataset:
Utilizing Electronic Data Captured, at the Bit, in Combination with Automated Bit Dull Grading, to Improve Bit Design Features, Dull Condition, and Ultimately, Drilling Performance
Authors: Galarraga Carlos , Gusey Gabe , Wade Derek , Allen Andrew 
Published: March 2023

Abstract
Historically, downhole vibrations at the drill bit have been difficult to determine and measure. In addition, oilfield personnel has dull graded bits through visual inspection, which introduces subjectivity into the assessment of the dull condition. Tools to measure dysfunctions at the bit to help understand the root cause of bit failure, and a digital bit imaging system for reliable dull grading, have been a gap in understanding drill bit performance. This paper presents a field study where downhole measurements and automated dull grading were utilized in tandem to improve performance.
In the Permian Basin, one of the most challenging applications is the production Vertical+Curve+Lateral section, due to interbedded transitions while drilling, the inability to track tangents, and building curves. The type of vibrations at the bit and their sources were unknown, and determining bit wear location and the type of cutter damage was also a challenge in this case.
A sensor at bit to measure downhole dysfunctions, in combination with a digital imaging system that calculates the bit damage, was used to carry out a comprehensive engineering analysis to determine the bit design changes needed for enhanced drilling efficiency.
The high-frequency data recorded at the bit showed lateral events of high magnitude that indicated formation-related issues. The automated dull grading system showed catastrophic damage in the cone, along with breakage and delamination of the cutters in the lower shoulder and gauge areas, due to cutter overloading during the lateral vibration events while drilling through hard stringers. The vibrations at the bit were studied to understand how they were generated and how we can mitigate them. The recorded electronic bit data and the outputs of the digital bit dull grading system were analyzed together to determine drill bit features that need to be improved.
Based on the bit data recorded and digital dull bit analyses, an advanced bit profile and cutting structure layout with a more impactful placement of depth-of-cut (DOC) control elements were used to develop a fit-for-purpose drill bit design combined with a new generation of PDC cutters. As a result, a complete drill bit design solution was developed to drill longer runs with better dull condition and very consistent performance across the basin.
This paper describes the nature of downhole vibrations at the bit and their consequences of damaging the bit through poor drilling performance. A new digital, automated dull grading system accurately determined the detailed location, on the bit, and type of wear produced by the vibrations, and it offered practical recommendations for improving performance. Detailed field data from different runs, showing where bit design changes reduced the failures and resulted in longer intervals drilled, will be presented.
Improve Well Integrity Using an Annular Barrier AI tool
Authors: Time Eirik , Berg Eirik , Mishra Siddharth 
Published: March 2023

Abstract
The Assisted Cement Log Machine Learning (ML) tool – or Annular barrier AI tool - developed by Equinor - is being used to interpret cement logs by predicting a predefined set of annular condition codes used in the cement log interpretation process. (Reference to SPE paper: Assisted Cement Interpretation project).
Annular conditions are usually separated into High, Medium and Low probability for hydraulic isolation. The internally developed annular condition code descriptions at Equinor are separated into 30 specific classes, which supports more nuanced and objective expert interpretations. The paper will discuss how this framework has positively impacted the performance of the trained ML model.
In addition, we report how this tool is being used to speed up and increase consistency in the log interpretation process, and how it can be used to efficiently share expert knowledge when training new professionals into Equinor's Cased Hole Logging Group. Furthermore, the paper will discuss ongoing research to improve the capabilities of this tool, like supporting the use of cement logs from additional service vendors, and how it could be potentially expanded to extract relevant information from historical reports to improve formation bond predictions.
The ML model is trained using selected and calculated features from cement logs, and the tool predicts an annular condition code according to the cement classification system for each depth segment in the log. Training and prediction are done in the cloud and accessible through an Application Programmable Interface (API) which makes it convenient to integrate the tool with any cement log interpretation software. Through the API, the interpretation software uploads a cement log and swiftly receives predictions for the complete log, including hydraulic isolation probabilities and confidence curves, which are used as decision support for the final expert interpretation. The ML model is regularly retrained with an ever-growing data set from real operations performed by Equinor. The uploaded data undergoes an automatic quality assurance before it is used as training data, and the model's performance is evaluated at each retraining.
To improve the cement log interpretation consistency in the industry and to ensure that our work can benefit the industry as widely as possible, the results will be made available as open source. This paper will discuss the challenges making such an ML tool open source, and the how the idea of Federated Learning could be used to share this solution in the industry.
Record-Breaking Reservoir Drilling and Openhole Gravel Packing With Cesium Formate Fluids in a High-Pressure, Marginal Mud Window Environment at Martin Linge
Authors: Nilsen Simen Jøsang , Obrestad Hanne Undheim , Kaarigstad Håvard , Mansurova Nadia , Solvoll Tom Are , Løchen Johan , Howard Siv , Abrahams Ben , Busengdal Christian 
Published: March 2023

Abstract
This paper describes how high-density cesium/potassium (Cs/K) formate fluids were successfully utilised from reservoir drilling to upper completion installation in five productive Martin Linge high-rate gas wells. Four wells were completed with openhole gravel pack and one with standalone sand screens.
The gravel packing operation marks what is considered to be the highest density carrier fluid openhole gravel pack successfully completed worldwide, with SG 2.06. A complex operation under near-high-pressure/high-temperature (HP/HT) conditions, including managed pressure drilling (MPD), overbalanced screen running and openhole gravel packing, was simplified by utilising the same fluid throughout the operation.
Cs/K formate reservoir drilling fluid and screen-running fluid were designed with biopolymeric additives and minimal calcium carbonate bridging particles. Clear Cs/K formate brine (i.e., without biopolymeric additives and particles) was chosen as gravel pack carrier fluid. The use of Cs/K formate fluids for all stages of the operation reduced the complexity of transitioning between the operational stages. In addition, the reservoir was only exposed to one filtrate without application of damaging weighting solids.
The drilling fluid contributed to successful MPD and delivered wells with very good hole quality in the reservoir, which consisted of interbedded sandstone, coal stringers and shale. The shale stabilising properties of concentrated formate brine–based fluids provided acceptable conditions for extended openhole time and allowed additional logging runs, including pore pressure measurements, under near-HP/HT conditions before running the screens. One bottom-up cleanout was conducted before the screen-running fluid was circulated in and the screens installed. The spurt and seepage losses were low throughout the drilling and screen running phases. No breaker treatment was required in any of the wells. All wells have proven to have good initial productivity and high well productive efficiency as expected.
The record-breaking openhole gravel pack operations performed with the high fluid densities required in Equinor's Martin Linge field have set a new standard for completing in challenging high-pressure environments.
Damping Identification from Subsea Logger Axial Riser Response Data
Authors: Lim HyeongUk "Harry" , McNeill Scot , Kluk Daniel , Stahl Matthew , Puskarskij Konstantin , Hansen Kristian 
Published: March 2023

Abstract
For decades, it has been known that, as drilling riser deployment depths increase, the potential for excessive hook load response will also increase. Using data collected from a drilling riser deployed to a record-setting water depth, nearly 12,000 ft, this paper provides insight that significantly reduces uncertainty about the severity of this resonant response.
The typical drilling riser and blow-out preventer (BOP) stack, disconnected from the well head, has its first axial resonant period at approximately one second for each 2000 feet of deployed length, thus five seconds for 10,000 feet, six seconds for 12,000 feet, etc. Therefore, vessel heave response can incite a significant, adverse axial resonant condition in very deep water. Damping reduces resonant response. Historically, the true amount of damping has been uncertain and therefore conservatively assumed to be less than 1% of critical. The resulting uncertainty in dynamic hook load response can produce significant restrictions on riser configuration (running weight) and sea state for BOP stack deployment as well as storm hang-off of the riser and LMRP.
A recent drilling riser deployment to the record-setting water depth of 11,903 ft produced a unique opportunity to collect high-quality data that reduces the damping uncertainty. This paper describes damping ratio and natural frequency identification for the first few axial riser modes for this deployment. The data was collected during deployment and retrieval using Subsea Vibration Data Loggers (SVDLs) installed on the BOP stack, drillship, and riser.
Mud Motor Digital Maintenance with an Industry-Unique PHM Solution
Authors: Belov Dmitry , Rocchio Sergio , Zhang Zhengxin , Chen Wei , Ba Samba , Liland Eimund , Kolyshkin Anton , Shen Yuelin , Scribbins Josh , Massie Henry , Phillips Kent 
Published: March 2023

Abstract
The ability to analyze drilling data to obtain continuous monitoring statistics of the drilling process and make prompt decisions are two important elements of a successful drilling operation. A mud motor is one of the important components of the downhole assembly, which enables the drill bit to penetrate the rock during drilling a well. Correctly predicting mud motor failure and the remaining useful life of the components are essential for obtaining drilling efficiency, avoiding costly operational expenses, and achieving timely maintenance. The remaining useful life indicator with low uncertainty identifies the life cycle of mud motors by preventing redundant maintenance and costly drilling operation failures.
This paper presents an industry-unique prognostics and health-management (PHM) solution for monitoring and maintaining the mud motor condition. This solution combines three algorithms, including a power section PHM algorithm, lower-end critical connections PHM algorithm, and mud motor degradation algorithm. The workflow solution allows for obtaining valuable information about the mud motor condition at the system and component levels.
The power section PHM algorithm, based on a remaining useful life prediction for the mud motor's power section, provides information about the elastomer condition inside of the stator as a percentage of the remaining life cycle. The lower-end critical connections PHM algorithm estimates the remaining useful life of the mud motor's lower-end connections. Both algorithms are component level; i. e., they help to improve managing the life cycle of the appropriate components. The mud motor degradation algorithm is a system-level algorithm. This algorithm uses drilling data to compute the severity of mud motor degradation; thus, identifying possible problems with the mud motor as a complete system.
The PHM solution helps to prevent expensive mud motor failure. Furthermore, the solution provides the opportunity to perform additional drilling runs before the motor components must be retired or removed for maintenance. The significant advantage of applying the PHM solution is it only makes use of existing drilling measurements and does not require any special downhole equipment.
The mud motor PHM solution is currently in use by one of the biggest oil & gas service company worldwide. In addition to presenting the three algorithms, this paper presents field application case studies that demonstrate the commercial value and efficiency gains achieved by their use. Significant sustainability benefits have been achieved by using the power section and mud motor degradation algorithms due to their assistance in drilling applications.
Improving Performance – Electrification of Well Control Equipment
Authors: Beim Samantha , Givens Matthew , Boulanger Bruce , Olson Matthew 
Published: March 2023

Abstract
Conventional BOP systems have used hydraulic operation for decades which limits both the performance and provides limited feedback on operational conditions. Electrically actuated BOP systems replace these complex hydraulic circuits with simplified components that improve overall system reliability. This paper will discuss the ambition to pivot from conventional hydraulic BOP systems to electrically enabled ones, with specific focus on the development of an electric bonnet for ram BOPs.
The new electric components are designed to be backwards compatible, such that major components like ram blocks and ram BOP bodies do not need to be replaced. The electric BOP system features a battery powered control skid that replaces traditional accumulators, while electrically actuated BOP components replace the conventional hydraulic versions. Verification and validation of this new technology includes shear modeling, system simulation, and laboratory testing. The equipment is designed to meet the intent and exceed the performance requirements of the latest industry and regulatory standards.
During development of the electric bonnet, the design team has shown that electric actuation of BOPs will provide equivalent shear force to existing hydraulic bonnets. The controlled actuation results in a more consistent and efficient shearing action. This improved shearing performance is achieved in the same BOP footprint as existing hydraulic BOPs. Additionally, the electric bonnet can perform as both a shear ram bonnet and a pipe ram bonnet which simplifies customer maintenance and spares stocking plans. As a result of these efforts, the electric BOP system development will provide greater operational latitude to meet a broader range of shearables, improve reliability, lower total cost of ownership, and reduce size and weight of the BOP system.
Transient Modeling of Tripping Operations Enables Closed-Loop Limit Control of Tripping Processes to Reduce ILT While Maintaining Wellbore Safety
Authors: Arevalo Pedro , Becker Gerald , May Roland , Forshaw Matthew , Grymalyuk Sergiy , Houghton Glen , Lien Morten , Hovda Sigve , Evensen Kim , Reber Randi 
Published: March 2023

Abstract
Tripping operations can take up a significant portion of well construction time and the associated cost. In the last decade, there has been extensive development and deployment of real-time tripping applications to optimize tripping parameters while maintaining formation integrity. This paper presents a system that utilizes transient modeling of tripping behavior to determine the optimum parameters that safeguard the integrity of the formation and the mechanical equipment at the rig site. The system delivers tripping boundaries to automated drilling control systems (ADCS) for every stand.
A digital twin of the wellbore, equipped with physics-based transient models, estimates the permissible axial velocities and accelerations developed when running drillstring in and out the wellbore. These motions develop pressure waves which travel along the wellbore and which can compromise formation integrity. The digital twin, prepared in the planning phase and deployed in the real-time drilling environment, uses smart triggering algorithms to automatically update the models and refine simulation results. Automation systems consume the predicted limits via an aggregation layer to refine fit-for-purpose tripping applications. The automation system finds optimum proposals of tripping limits and updates them directly in the rig control system in real-time.
The trip monitoring system automatically and continuously publishes optimum velocity and acceleration tripping limits per stand and transmits them as set points to the ADCS to define a safe operating envelope (SOE). This approach can greatly reduce the overall tripping time in comparison to non-automated deployments. Furthermore, the reduction of invisible lost time (ILT) takes place while maintaining the integrity of the formation, and the integrity of the surface equipment. Finally, reduction of the energy required to perform the tripping process consequently decreases the amount of carbon emissions involved in the process.
A set of case studies confirm the effectiveness of the approach and illustrate its benefits. A case study addresses the topic of adoption of drilling automation applications such as the tripping advisor. Another case presents the concept of interoperability using as example a deployment on a rig simulator setup in Europe to perform closed-loop control using the tripping application to write velocity and acceleration limits continuously to the ADCS.
Deployment of a Hybrid Machine Learning and Physics Based Drilling Advisory System at the Rig Site for ROP Optimization
Authors: Behounek Michael , McKenna Kirt , Thetford Taylor , Peroyea Trey , Roberts Michael , Pearce Julie , Hickin Gary , Ashok Pradeepkumar , Yi Michael , Ramos Dawson 
Published: March 2023

Abstract
During well construction, automatic monitoring of the sensor signals for drilling dysfunction detection through pattern recognition algorithms is key to improving rate of penetration (ROP) and preventing tool failure. The addition of physics-based models can enable further improvement, but often one is limited by the contextual data needed by these models, as well as the computational power available at the edge. This paper details the successful field deployment of a system that address these challenges.
The dysfunction tracking algorithms used were built using Bayesian networks as base models and validated using downhole data. Physics based models in the advisory system are used to compute the first five modes of natural frequencies for axial, torsional and lateral vibration. The contextual data required for the calculations consists of the bottom hole assembly (BHA) and survey data. Scripts were deployed to transfer this data directly from the operator's database to rig site.
This system has been deployed on rigs in the US for over 4 years now, and the fact that they are being actively used to this day is a testament to its success. A key enabler here is the automatic transfer of contextual data from the office database to the rig site. The contextual data used in the model is something the crew have to input into the office database outside the needs of the advisory system. So, a process was already in place to properly record this information, and that worked to the advantage of the system. Eliminating the need to re-enter this data at the rig site was key to the success of this advisory system. Using the physics-based model, critical RPM bands are plotted on the drilling advisory screen to alert the driller whenever they are near an RPM that needs to be avoided. Visual indicators on a weight on bit (WOB)-RPM grid provide guidance to the driller on which direction to move the parameters to avoid dysfunctions and optimize drilling.
Physics based models nicely complement data-based ML models in an advisory system, but real-world application of such combined systems are limited due to reasons such as timely availability of contextual data at the rig-site, or the need for contextual data that is not readily measured. In this paper, we demonstrate how the problem can be solved, and provide guidance for larger adoption of the process followed by team.
Downhole Trajectory Automation of RSS Tools: Autonomous Drilling Becomes Reality
Authors: Ignova Maja , Mantle Katharine , Brovko Katerina , Abe Vincent , Gorodnov Andrey , Li Ling 
Published: March 2023

Abstract
The ultimate goal of automated drilling is to be able to drill a well with any trajectory autonomously, and any human involvement being purely supervisory.
This goal is evolutionary and began 20 years ago with the introduction of hold-vertical and inclination-hold modes. Since then, hold the inclination and azimuth mode for both push-the-bit and point-the-bit rotary steerable system (RSS) tools was developed and is widely used. More recently, downhole hold-the-curve mode has been introduced for push-the-bit RSS tools. The next in the line for automation is hold-the-curve mode for the point-the-bit RSS tools. This mode is currently in field testing phase with very successful results so far.
This paper presents the path hold-the-curve technology transfer and firmware implementation has taken from one RSS system to another, from concept study to introduction to the field. The automation technology transfer is not a straightforward task because the two RSS systems are different in steering mechanism, the type and noise level of the sensors, the positions of the direction and inclination sensors, their filtering characteristics, and the current downhole control system implementation for both.
The technology transfer and firmware implementation process was accelerated compared with the previous introduction to the field of the downhole automation module because the field has already drilled wells with this type of automation module albeit on a different RSS system. It was easy to transfer the knowledge of how the automated system works and the field personnel learned about the technology on the job, understood it well, and adopted it quickly. The field personnel were confident in using the automated system independently on the first field test and continued to drill the entire section to total depth in this mode.