bluuebunny/crossref_metadata_2025_split huggingface dataset:
Casing Exit in Expandable Liner Enables Operator to Avoid Redrilling 3,000-ft Hole Sections in Gulf
Authors: Emelander Tom , Muesel Justin , Carrington Casey 
Published: March 2021

Abstract
After a 13 3/8-in. expandable liner collapsed in a Gulf of Mexico ultradeepwater well, an operator considered a whipstock sidetrack, exiting as deep as possible to finish drilling and completion operations. Exiting the 16-in. casing, industry standards would have called for redrilling and casing an entire hole section. Exiting the expandable liner was an alternative option, but would require a unique solution to operate in the larger internal diameter (ID) and maintain the existing hole size.
The service provider created a fit-for-purpose solution to install a casing window in the 13.77-in. ID expandable liner. The standard casing exit system accommodates 13 3/8-in. casing through 14-in. casing and requires minimal modifications to anchor the actual concave assembly to support a 12.25-in. pilot window. Additional mill runs would then open the 12.25-in. pilot window to a full bore 13 1/2-in. outside diameter (OD) window. Despite never having performed an installation in this size of expandable liner, the provider had a run history for exits with similar modifications and extra trips to enlarge and elongate windows. Job challenges included thin-wall, channeled cement; limited flow rates because of liner pressure limits; equipment availability; and a short lead time.
The 11 1/2-in. OD assembly was quickly modified to enable the anchor engagement in the 13.77-in. ID liner. Within days the mills were dressed to the custom ODs required to enlarge the 12.25-in. pilot window to 13.50-in. On the first run, the whipstock was hydraulically set in the liner. Kickoff was achieved at 19,609-ft to cut a 27.5-ft window and ream a 45-ft rathole in 22 hours. The second bottom hole assembly (BHA) consisted of three mills with 12 1/2-in., 12 3/4-in., and 13-in. ODs. Milling and reaming took 6 hours. The third and final BHA to open the window to a 13 1/2-in. OD consisted of a 13 1/4-in. OD mill and two full-drift mills above. Milling and reaming with this BHA took 29 hours before coming back in with a motor assembly to drill ahead. This installation is the first sidetrack conducted with a whipstock in a 13 3/8-in. expandable.
This paper will show that it is possible to safely and reliably install a casing exit system in difficult applications, such as deep expandable liners, that might previously have been considered unfeasible. This approach provides an opportunity for the industry to significantly reduce non-productive time in such scenarios.
Determining Rig State from Computer Vision Analytics
Authors: Chatar Crispin , Suresha Suhas , Shao Laetitia , Gupta Soumya , Roychoudhury Indranil 
Published: March 2021

Abstract
For years, many companies involved with drilling have searched for the ideal method to calculate the state of a drilling rig. While companies cannot agree on a standard definition of "rig state," they can agree that as we move forward in drilling optimization and with further use of remote operations and automation, that rig state calculation is mandatory in one form or the other. Internally in the service company, many methods exist for calculating rig state, but one new technology area holds promise to deliver a more efficient and cost-effective option with higher accuracy. This technology involves vision analytics. Currently, detection algorithms rely heavily on data collected by sensors installed on the rig. However, relying exclusively on sensor data is problematic because sensors are prone to failure and are expensive to maintain and install. By proposing a machine learning model that relies exclusively on videos collected on the rig floor to infer rig states, it is possible to move away from the existing methods as the industry moves to a future of high-tech rigs. Videos, in contrast to sensor data, are relatively easy to collect from small inexpensive cameras installed at strategic locations.
Consequently, this paper presents machine learning pipeline that is implemented to perform rig state determination from videos captured on the rig floor of an operating rig. The pipeline can be described in two parts. Firstly, the annotation pipeline matches each frame of the video dataset to a rig state. A convolutional neural network (CNN) is used to match the time of the video with corresponding sensor data. Secondly, additional CNNs are trained, capturing both spatial and temporal information, to extract an estimation of rig state from videos. The models are trained on a dataset of 3 million frames on a cloud platform using graphics processing units (GPU). Some of the models used include a pretrained visual geometry group (VGG) network, a convolutional three-dimensional (C3D) model that used three-dimensional (3D) convolutions, and a two-stream model that uses optical flow to capture temporal information. The initial results demonstrate this pipeline to be effective in detecting rig states using computer vision analytics.
Constructing Deep Closed-Loop Geothermal Wells for Globally Scalable Energy Production by Leveraging Oil and Gas ERD and HPHT Well Construction Expertise
Authors: van Oort Eric , Chen Dongmei , Ashok Pradeepkumar , Fallah Amirhossein 
Published: March 2021

Abstract
Deep closed-loop geothermal systems (DCLGS) are introduced as an alternative to traditional enhanced geothermal systems (EGS) for green energy production that is globally scalable and dispatchable. Recent modeling work shows that DCLGS can generate an amount of power that is similar to that of EGS, while overcoming many of the downsides of EGS (such as induced seismicity, emissions to air, mineral scaling etc.). DCLGS wells can be constructed by leveraging oil and gas extended reach drilling (ERD) and high-pressure high-temperature (HPHT) drilling expertise in particular.
The objectives of this paper are two-fold. First, we demonstrate that DCLGS wells can generate significant geothermal power, i.e. on the order of 25-30 MWt per borehole initially. To this extent, we have developed a coupled hydraulic-thermal model, validated using oil and gas well cases, that can simulate various DCLGS well configurations. Secondly, we highlight the technology gaps and needs that still exist for economically drilling DCLGS wells, showing that it is possible to extend oil and gas technology, expertise and experience in ERD and HPHT drilling to construct complex DCLGS wells.
Our coupled hydraulic-thermal sensitivity analyses show that there are key well drilling and design parameters that will ultimately affect DCLGS operating efficiency, including strategic deployment of managed pressure drilling / operation (MPD/MPO) technology, the use of vacuum-insulated tubing (VIT), and the selection of the completion in the high-temperature rock formations. Results show that optimum design and execution can boost initial geothermal power generation to 25 MWt and beyond. In addition, historical ERD and HPHT well experience is reviewed to establish the current state-of-the-art in complex well construction and highlight what specific technology developments require attention and investment to make DCLGS a reality in the near-future (with a time horizon of ~10 years). A main conclusion is that DCLGS is a realistic and viable alternative to EGS, with effective mitigation of many of the (potentially show-stopping) downsides of EGS.
Oil and gas companies are currently highly interested in green, sustainable energy to meet their environmental goals. DCLGS well construction allows them to actively develop a sustainable energy field in which they already have extensive domain expertise. DCLGS offers oil and gas companies a new direction for profitable business development while meeting environmental goals, and at the same time enables workforce retention, retraining and re-deployment using the highly transferable skills of oil and gas workers.
Risk-Controlled Wellbore Stability Criterion Based on Machine Learning Assisted Finite Element Model
Authors: AlBahrani Hussain , Morita Nobuo 
Published: March 2021

Abstract
In many drilling scenarios that include deep wells and highly stressed environments, the mud weight required to completely prevent wellbore instability can be impractically high. In such cases, what is known as risk-controlled wellbore stability criterion is introduced. This criterion allows for a certain level of wellbore instability to take place. This means that the mud weight calculated using this criterion will only constrain wellbore instability to a certain manageable level, hence the name risk-controlled. Conventionally, the allowable level of wellbore instability in this type of models has always been based on the magnitude of the breakout angle. However, wellbore enlargements, as seen in calipers and image logs, can be highly irregular in terms of its distribution around the wellbore. This irregularity means that risk-controlling the wellbore instability through the breakout angle might not be always sufficient. Instead, the total volume of cavings is introduced as the risk control parameter for wellbore instability. Unlike the breakout angle, the total volume of cavings can be coupled with a suitable hydraulics model to determine the threshold of manageable instability.
The expected total volume of cavings is determined using a machine learning (ML) assisted 3D elasto-plastic finite element model (FEM). The FEM works to model the interval of interest, which eventually provides a description of the stress distribution around the wellbore. The ML algorithm works to learn the patterns and limits of rock failure in a supervised training manner based on the wellbore enlargement seen in calipers and image logs from nearby offset wells. Combing the FEM output with the ML algorithm leads to an accurate prediction of shear failure zones. The model is able to predict both the radial and circumferential distribution of enlargements at any mud weight and stress regime, which leads to a determination of the expected total volume of cavings.
The model implementation is first validated through experimental data. The experimental data is based on true-triaxial tests of bored core samples. Next, a full dataset from offset wells is used to populate and train the model. The trained model is then used to produce estimations of risk-controlled stability mud weights for different drilling scenarios. The model results are compared against those produced by conventional methods. Finally, both the FEM-ML model and the conventional methods results are compared against the drilling experience of the offset wells.
This methodology provides a more comprehensive and new solution to risk controlling wellbore instability. It relies on a novel process which learns rock failure from calipers and image logs.
Innovative Drilling Fluid Technology Conquered Tough Geomechanics Offshore Mexico
Authors: Reyna Ricardo , Parra Viridiana , Volbre Daniel , Ballinas Raul , Maldonado Reinaldo , Rockwood Jene 
Published: March 2021

Abstract
The reservoir field highlighted in this paper is located Offshore Mexico in the southeast part of Campeche Bay and hidden below a troublesome, unstable formation that must be transacted before reaching the new production zone. During the exploration phase, this section experienced severe lost circulation and unstable conditions before reaching the final depth. Based on lessons learned, the team worked to develop a best- practices approach using geomechanics analysis and a novel fluid technology which enabled the operator to safely drill through this problematic intermediate section under high-pressure, high-temperature (HPHT) conditions.
The methodology started with identifying the geomechanics challenges, implementing operational best practices, and finally, use of an innovative, low-invasion fluid technology, which creates a thin and impermeable shield at the wellbore wall, effectively sealing the fractures and preventing fracture propagation in the highly unstable formation of interspersed carbonates, shales, and sandstones. The strong mechanical properties of the thin, but firm, barrier created at the wellbore wall minimized the destabilizing effect of fluid invasion. Synergy from the geomechanical team, best practices for the operation, and innovative drilling fluid technology solved the wellbore instability drilling challenge encountered in the exploration well.
In offset wells, losses of more than 2,200 m3 of drilling fluid, stuck pipe, and major NPT were observed. By incorporating the shielding technology, wellbore instability was improved in the intermediate section. In addition, the fluid technology was easily pumped through the bottomhole assembly (BHA) to seal formation fractures between 2,000 and 3,000 μm in size. This well, utilizing the barrier technology to mitigate the wellbore instability and drill within a narrow fracture gradient operating window, was the first in the area to have zero loss of drilling fluid as compared to the typical 5 to 10-m3/hr circulation losses experienced during exploration drilling in the intermediate section characterized by interbedded layers of carbonates, shales, and sandstone under high-pressure, high-temperature (HPHT) conditions. The coordination between the teams using best practices was critical to meeting the challenge of the intermediate geomechanically weak formation.
This case history in offshore Mexico will demonstrate both the importance of teamwork and the utilization of a proven technology that improves wellbore instability, minimizes NPT, mitigates pipe tripping issues and avoids huge volumes of drilling fluid lost into the geomechanically weak formation. This barrier technology can be applied globally to troublesome formations - such as interbedded carbonates, shales, and sandstones - to improve operations and provide cost savings for the operator.
Setting a New Standard: PDC Bits Equipped with Compact Vibration Recorders Monitor Entire Run and Reveal Stick-Slip Mitigation System Dysfunction and Downhole Motor Under Performance
Authors: Pelfrene Gilles , Cuilier Bruno , Ezzeddine Dhaker , Dourfaye Alfazazi , Dimov Dimo , Gallego Gilles , Roccas Christopher , Mangeny Aurélien , Reboul Sébastien 
Published: March 2021

Abstract
Downhole vibration measurements are used real-time and post-run to monitor drilling dynamics. Real-time monitoring tools are applied to facilitate immediate corrective actions but their deployment adds operational constraints and costs. This paper describes a new high-capability vibration recorder embedded in the drill bit as a standard component. The analysis of two case studies in the Middle East shows how memory devices available at a reduced cost and on every run are a valuable option for many appraisal or development wells.
Developing a fleet of reliable downhole recording tools typically takes years and involves teams of experts in various fields. The paper describes the strategy followed by a drill bit manufacturer to develop and deploy a compact, high capability and cost-effective vibration recorder to provide continuous readings of accelerations, rotation speed (RPM) and temperature at 100Hz and over 250 hours. Sensors and batteries have been packaged to fit into the drill bit shank or elsewhere in the bottom hole assembly (BHA). The recording starts automatically and thus removes the need for onsite personnel. The paper also presents proprietary data analytics software used to retrieve, process and synchronize the recorded data with other available data (mud logs, Measurement/Logging While Drilling logs) and to present critical drilling events.
In the first application, the 8 ½-in. bit drilled a 20,000 ft horizontal drain. More than 250 hr of data were recorded showing intense levels of stick-slip. During the entire run, the drilling team deployed several strategies to mitigate stick-slip, including the use of two surface-based stick-slip mitigation systems. The analysis shows that these systems are sometimes unsuccessful in mitigating stick-slip and are difficult to calibrate. It is demonstrated how the vibration recorder may contribute to fine tuning these mitigation efforts through optimization of their settings. In the second application, the vibration recorder was mounted on a 12 1/4-in. bit used to drill 5,000 ft through cement and formation. The analysis shows the motor was subjected to erratic RPM cycles, leading to frequent stalls and acceleration peaks during the run. It is shown how motor performance then decreased consistently during the last hundreds of feet of the section and how this affected rate of penetration (ROP).
Deployment of a vibration recorder over the entire drill bit manufacturer's fleet allows continuous monitoring of critical drilling issues and malfunctions related to a variety of drilling equipment that enables the operator to improve drilling performance. The bit-sensor package makes high frequency data systematically available at a reduced cost for every drilling application.
Use of Fiber Optic Information to Detect and Investigate the Gas-in-Riser Phenomenon
Authors: Santos Otto L. , Williams Wesley C. , Sharma Jyotsna , Almeida Mauricio A. , Kunju Mahendra K. , Taylor Charles E. 
Published: March 2021

Abstract
Potential applications of optical fiber technologies in the well control area are to detect the presence of gas and to unfold the gas dynamics inside marine risers (gas-in-riser). These issues became even more relevant now when considering the application of managed pressure drilling (MPD) operations in deep and ultradeep waters that may allow for a controlled amount of gas inside the riser.
The application of these fiber optic technologies in the well control domain is currently being evaluated at Louisiana State University (LSU) as a part of a gas-in-riser research project granted by the Gulf Research Program (GRP). To accomplish that, an actual well was recompleted and instrumented with fiber optic sensors to continuously collect data along the wellbore and with four pressure and temperature downhole gauges to record those parameters at four discrete depths. A 2-7/8 in. tubing string with its lower end at a depth of 5026 ft and a chemical line to inject nitrogen at the bottom of the hole were also installed in the well.
This paper discusses the results of four out seven experimental runs that were performed in this full-scale apparatus using fresh water and nitrogen in order to calibrate the installed pieces of equipment, to train the crew of researchers to run the tests, to check experiments repeatability and to obtain experimental results under very controlled conditions since water and nitrogen have well defined and constant properties.
The paper also presents a mathematical model based on the unsteady-state flow of a two-phase mixture that was developed to help design the experimental runs. The results obtained in the seven runs were used to calibrate the model that was additionally modified to read the experimental parameters. The simulated results produced a remarkable agreement with the fiber optic and pressure and temperature sensors gathered data.
Finally, the paper shows and analyzes simulation results of gas-in-riser operations on an actual drilling floater unit after the mathematical model has been adapted to predict pressures and output flow rates during gas circulations out of the riser. The effects of circulation flow rate, backpressure applied at surface and amount of gas inside the riser on pressures and flow rates are displayed and analyzed.
Improve Installations of Liners and Lower Completions with Real-Time Downhole Data
Authors: Mathisen Kim , Sorheim Tore , Keerthivasan Vijay Kumar , Pink Stephen , Young Dustin 
Published: March 2021

Abstract
Well construction activities including liners and lower completions deployment have historically realized downtime and unforeseen challenges. Surface data, torque and drag simulations, and previous experience are all sources of data commonly used to plan and facilitate these installations. Field development campaigns often include longer laterals, frequent three-dimensional bends, varying pressure profiles, and other challenges that cannot be sufficiently planned for by using surface data, torque and drag simulations, and experience alone. The industry requires a better quality set of data, and quicker access to this data, to more successfully and efficiently complete wells.
Wired drill pipe is a real-time data acquisition platform that has been used on more than 146 wells, 65 of those offshore wells, since 2015. While improved drilling operations have been the primary use of the wired drill pipe platform, operators have since challenged providers to increase the scope of real-time data acquisition capabilities using the wired drill pipe platform.
In order to address the challenges of understanding downhole dynamics during liner deployment and completion operations, a dynamic logging tool with real-time data transfer capability and restriction-less internal bore was developed.
The dynamic logging tool couples the data acquisition capabilities of the memory-based dynamic logging tool with the wired drill pipe platform to provide operators with real-time access to axial loads, torque, temperature, pressures, vibrations, and RPM during the lower completion and liner deployment operations. The data provided by the inclusion of this tool can be used to facilitate the optimization and continuous improvement of liner deployment operations. This in turn allows operators to minimize non-productive time (NPT) and overcome a steep learning curve for challenging field development campaigns.
This paper discusses the real-time logging tool technology implementation and its role in development campaigns. Examples of lower completion applications and data gathering techniques are presented, along with examples of how the data can be used to improve understanding of downhole dynamics, facilitate continuous operational improvements, and ultimately achieve a robust field development strategy.
Socio-demographic correlates of public stigma about mental illness: a population study on Hong Kong’s Chinese population
Authors: Lo Lincoln Lik Hang , Suen Yi Nam , Chan Sherry Kit Wa , Sum Min Yi , Charlton Cheung , Hui Christy Lai Ming , Lee Edwin Ho Ming , Chang Wing Chung , Chen Yu Hai Eric 
Published: March 2021

Abstract
Background Individuals with psychiatric disorders are often unwilling to seek help or often follow treatment regimens, fearing public stigma. This study identified the sociodemographic correlates of public stigma while accounting for mental health literacy and life satisfaction. Methods This study analysed data for 1,514 individuals who participated in a population-based random telephone survey conducted in 2018. Sociodemographic characteristics included gender, age, education level, and occupation. Data on public stigma, mental health literacy and life satisfaction were also collected. A multiple linear regression was conducted to examine the effects of sociodemographic characteristics on public stigma. A moderation analysis was performed to investigate the role of age and education in the relationship between mental health literacy and public stigma. Results Sociodemographic characteristics, such as female gender, older age groups, lower education, and occupation (particularly retired and homemakers), were associated with a higher public stigma. The association between public stigma and mental health literacy was the most significant among individuals aged 50 years and above and with lower education levels. Conclusions This study showed that certain population subgroups, based on their sociodemographic profile, have higher stigma about mental illnesses. Understanding the differential effects of sociodemographic factors on public stigma is imperative to developing effective anti-stigma campaigns. Keywords public stigma, mental health literacy, sociodemographic correlates, anti-stigma campaigns