bluuebunny/crossref_metadata_2025 huggingface dataset:
Novel Applications of Pozzolans to Treat Wellbore prior to Cement, Casing and While Drilling to Prevent Overburden Stress Fractures
Authors: Barry James Aloysius , Esatyana Erica , El Sayed Karim Loutfy , El-Husseiny Mahmoud Ahmed
Published: March 2022

This study is focused on the application of novel pozzolans (superplasticizers) ahead of cement, prior to casing and while drilling to treat and prevent wellbore fracture due to overburden stresses. This study is a combination of quantitative and qualitative analysis based on laboratory and field applications of pozzolanic materials in the construction of wells.

Pozzolans have long been applied to construction materials in order to improve lifespan and compressive strength. The application of pozzolanic materials goes back over 2000 years to the construction of Roman Aqueducts, buildings and roads known for their longevity and ability to resist corrosion and stress. These materials cover a broad range of naturally occurring and man-made materials. The most common pozzolanic materials used in drilling today include Bentonite, Kaolin, and Fly Ash. Pozzolans when combined with Portland Cement have been shown to increase the compressive strength and durability dramatically. Pozzolans are currently applied globally in cementing applications for HTHP, high loss zones and more.

This paper will examine the application in the drilling phase as an applied treatment during drilling for the reinforcement of the wellbore as well as to treat induced losses. The study will review cases for use of Novel Pozzolans for drilling, pre-cement, casing and for production zones the application of Novel acid soluble pozzolans for similar purposes. These applications validate the application of these materials beyond cementing into the drilling phase and wellbore construction for reducing backside pressure, reducing days on losses, reducing sidetrack, increasing operational ECD while drilling and cementing and achieving top of cement without inducing losses due to overburden in tight ECD window environments.

Deepwater environments provide a unique environment for the application of these novel materials as they offer some of the highest overburden environments with greatest operating costs and daily operating costs. Thusly this study has shown the applications have saved operators on multiple wells and over long periods many days and millions in operating costs with proven prevention of losses in field studies where wells were compared for offset value over a period of time. Multiple operators have adopted this technology as a result and there is a long track record of use while there are few papers on the subject. The purpose of this paper is to illustrate the best practices as well as new technologies and state of the art when it comes to the development of the latest in pozzolanics for these applications.
A Comparison of Automated and Advisory Generator Management Systems
Authors: Snijder van Wissenkerke Marcel , LaCroix Adam
Published: March 2022

Drilling rigs are typically powered by a set of diesel or natural gas-fueled generators which the rig personnel manually turn on or off to maintain the proper capacity to support each type of rig operations. Rig personnel have no trouble running enough generators to maintain the rig demand, but efficiently shutting down generators is an area for opportunity. Reducing the number of generators that share the overall load improves fuel efficiency and reduces emissions and maintenance costs. Rig personnel are accountable for ensuring sufficient power capacity, which often leads them to be overly cautious about shutting down generators.

Automated systems can effectively shut down generators when not needed but are challenged with bringing them back online quickly enough to avoid power limiting the rig tools. After experiencing power limitations, a driller may be inclined to turn off the automated system. The goal of this paper is to explore whether an advisory system, that provides real-time recommendations for the number of generators required to be online and on-screen breakdowns of the associated fuel and emission reductions, would promote better overall savings and a better rate of adoption than an automated system. This paper describes the results of a study comparing a fully automated generator management system with an advisory system, each of which were deployed on separate rigs. Specifically, the study compares utilization of the systems and their impact on generator run hours, power limit events, and fuel and emissions savings. Field results of both systems are compared to a model of the most optimized generator management practices to understand the full potential of the systems.
A Better Set of Eyes: Computer Vision Technology to Monitor Safety Zones and Automate Drill Pipe Tally
Authors: Watson Douglas , Morton Kenneth , Kern Sarah , Hausher Aaron
Published: March 2022

An indispensable item for every roughneck is the tally book, used to measure and count the drill pipe entering and exiting the wellbore. The current practice is for a crew member to measure the pipe with a pipe strap and enter the information, each time while tripping, into their tally book. This manual entry is prone to error, leading to potential mistakes in the calculated drilling depth and poorly sequenced lithologies, which in turn may contribute to an unsafe environment and drill bit damage due to inaccurate drillstring length. These mistakes often require an additional trip out of hole and increase the amount of nonproductive time. Computer vision technology has shown promise in other industries with its ability to automate similar recognition and counting tasks. A dual-use system has been developed where the same cameras for pipe counting can be used for red zone entry detection, holding the potential to enhance the overall safety of the drilling process.

A pilot application has been created serving dual applications: both counting and measuring the pipe entering the wellbore and detecting personnel movement in the red zone during pipe delivery operations. Each stage of the design process was intently developed, considering requirements for both functionalities of the system. Neural network detection algorithms, 3D localization, and drilling data signal processing all combined to interpret rig state and use the appropriate computer vision algorithms at the correct time. System practicalities such as camera placement, hardware and software robustness, and field-tested accuracy were considered. The system has been deployed for field testing in West Texas.

The system succeeded in both accurately maintaining a drill pipe count and detecting personnel in the red zone. The system is designed so that the neural network algorithms can be updated using newly collected data as new scenarios are encountered, such as new weather conditions, lighting environments, additional people on the rig floor, and other dynamic factors.

This computer vision technology is the first of its kind on a drilling rig. No other system has been developed that accomplishes not only one of the functions, but also two. Just as we have seen rapid improvements each year in driver assistance technology, the time has come to apply recent advancements in computer vision capabilities to increase the efficiency and overall safety of the rig.
Early Detection of Well Control Kick Events by Applying Data Analytics on Real Time Drilling Data
Authors: Yalamarty Sai Sharan , Singh Kriti , Kamyab Mohammadreza , Cheatham Curtis , Crkvenjakov Vladimir , Flurry Kelly
Published: March 2022

Kick events are some of the most life-threatening and environmentally disastrous events during drilling. Identifying potential kick events in time is valuable. Several hybrid algorithms combining physics and data analytics have been developed to help identify potential kick events from trends in real-time drilling data. These algorithms encompass all drilling operations like drilling, tripping, circulating, and making connections. The goal is to enable management by exception in real-time monitoring of wells.

Real-time drilling data acquired from the sensors on the rig and other static metadata like drill string and casing specifications are used in these hybrid algorithms. The exact data channels from the real-time data used differ based on the drilling operation the algorithm is associated with, but the most important ones are flow rate in (FLOWIN), flow out percentage (FLOWOUT), pump strokes per minute (SPM), active pit volume (PITACT), and trip tank volumes (TTKVOL). Additional data channels like lag depth and rig states are computed from these existing channels to help the algorithms. Other provisions have been made in the algorithms to automatically account for human operations like lining up with trip tanks and addition/removal of pits from active pit volume. To identify the potential kicks: data from trip tank volumes are utilized while tripping, flowback signatures calculated from PITACT are used during connections, and real-time hole displacement (HDISP) calculated from PITACT and lag depth is used while drilling. All the algorithms have been parameterized to facilitate easy tuning of thresholds. An alerting system has been implemented that triggers an alarm when the algorithms identify a potential kick event. This system can also send notifications to a real-time support team or field personnel.

Historical offset wells provided by an operator were used for testing the algorithms and fine-tuning the thresholds. We achieved a 12% false-positive rate while correctly identifying all the true well control kick events. False positives are defined as events identified by the algorithms as potential kicks but were due to some explainable operation that was accounted for in the algorithm scope. The user feedback from the alerting system was also used to improve the accuracy of the algorithms. The calculated data channels used to identify the potential kicks can also be displayed as real-time traces or in other suitable visualizations like a trip sheet or flowback fingerprints.

These algorithms were designed to be run with minimal user input. This makes them suitable for use by real-time support centers and field personnel. The ability to calculate the lag depth and incorporate that into the analysis is novel and improves the accuracy. The provisions in the algorithm to account for human operations that affect pit volumes also add to the novelty.
Implementation of MPD Systems in the Deepwater Gulf of Mexico to Drill Highly Depleted Reservoir Sections
Authors: Vaczi Kenneth , Morales Danilo , Chima Chima
Published: March 2022

Combined challenges of drilling deep water matured reservoir hole sections with high levels of depletion present a risk for major downhole fluid loss events, well control hazards, and the resulting high remedial cost. Reduced fracture gradient, due to depletion and near-wellbore thermal stress, combined with potential near-virgin sands results in narrow-drilling margins impacting the probability of success drilling to planned depth and meeting objectives of the well. In some can cases the narrow-drilling margins can even make these reservoirs un-drillable without alternative technologies.

Constant Bottom Hole Pressure (CBHP) variant of Managed Pressure Drilling (MPD) was identified as an enabling technology to help mitigate the risk of drilling the reservoir through the presence of highly pressure depleted sands and wellbore cooling risk mixed with virgin pressure stringers within the same interval. MPD systems were installed on two drill ships, and four (4) deepwater wells were successfully drilled through highly depleted reservoirs using MPD.

MPD enabled the downhole pressure to be reduced by using a mud weight that was hydrostatically underbalanced to the pore pressure and use surface back pressure (SBP) to maintain overbalanced to the virgin reservoir conditions during static conditions. The effect of the equivalent circulating density (ECD) due to the friction while circulating (dynamic conditions) was offset by reducing the surface back pressure and maintain a near constant bottom hole pressure at a selected depth. The MPD system also allowed the application of dynamic pore pressure verification, to reduce the uncertainty in the drilling window. At TD the drilling bottom hole assembly (BHA) was pulled while maintaining the MPD condition. Production liner was then run in MPD mode and cemented using Managed pressure cementing techniques.

This paper describes the process for the selection and implementation of MPD systems on two drill ships; it highlights the process for permitting the operations and the preparation of the rig crews to apply new developed procedures. Furthermore, the paper describes the results obtained after successfully executing the MPD drilling operations.
Successful Execution of a Dynamic Driller's Roadmap Using an Automated Formation Top Detection Algorithm
Authors: McManus Brian , Wells Tony , Willerth Marc
Published: March 2022

Efficient drilling through heterogenous geology requires careful matching of drilling parameters to the rock being drilled. Failure to do so can lead to increased bit damage or poor drilling performance. The "driller's roadmap" is a list of such parameters to be changed at various depths where formation tops are expected to be crossed. Successful execution of these roadmaps relies on having a detailed geological prognosis of where specific formations will be encountered. When drilling the first well on a pad, the precise depths of geological boundaries may be unknown preventing successful roadmap execution. By providing a feedback loop between a driller's roadmap and an automated formation top detection algorithm, it is possible to identify and proactively respond to geology even when drilling in these uncertain conditions.

A roadmap was created with target drilling parameters for each formation that would be encountered when drilling. Critical formations were identified where there was a high degree of interfacial severity, suggesting a high potential for bit damage if cutter overloading occurs. To mitigate this, a transition to controlled depth-of-cut drilling would be made prior to formation entry. Gamma markers were identified for these formations, along with predictive gamma markers shallower than the transition zones. During drilling, an automated formation top detection algorithm was run on logging-while-drilling data providing a real-time alert when the predictive markers were detected. Remaining roadmap depths were updated based on whether these markers were shallower or deeper than the roadmap expectation. Gamma logs and drilling mechanics were monitored to confirm the depth where transition zones were encountered. This was repeated across the pad to confirm process reliability.

Two formation tops were identified that were expected to come in 450 and 170 feet shallower than the transition zone where the switch to depth-of-cut drilling would occur. When drilling the first well on the pad the automated formation top detection algorithm identified these tops as arriving nearly 100 feet shallower than anticipated by the pre-drill geology program. The roadmap was updated and the switch to depth-of-cut drilling was performed 100 feet earlier than originally planned. Post-well analysis showed the transition zone came in 95 feet shallower than expected, in line with the modified driller's roadmap, suggesting the modifications avoided unnecessary bit damage. Subsequent wells on the pad showed strong repeatability in formation top arrivals, and the updated roadmap was used without major modification.

The combination of driller's roadmaps and automated formation top detection is a key step toward efficient drilling/geology integration with an eye toward optimized drilling automation. This study shows this integration can lead to positive drilling outcomes even in areas with high levels of uncertainty in the location of formation boundaries.
Autonomous Directional Drilling Using the RSS Simulator for the Drillbotics 2020-2021 Virtual Competition
Authors: Saavedra Jerez Luis , Haque Md Fazlul , Magalhaes Melissa , Chevuri Rishyank , Sui Dan , Florence Fred
Published: March 2022

The automation of directional drilling is a recent development that is expanding with both physical and virtual concepts. In the same way, SPE's Drilling Systems Automation Technical Section (DSATS) supports the creation of new automated directional drilling models and ideas with its international competition Drillbotics®. This paper describes the design, algorithms, graphical user interface (GUI), and features of the rotary steerable system (RSS) Simulator V2.4, developed by the winning team of the 2020-2021 Drillbotics Virtual Rig Competition.

The RSS Simulator, developed in Python, simulates a drilling trajectory of a directional well based on target coordinates, dogleg severity (DLS) constraints, and cubic Bezier curves. The simulator has two general modules: the RSS Model and the Trajectory Control Optimizer (TCO). The first one simulates the behavior of the bit and bottom hole assembly (BHA) tool (e.g., force on the bit, inclination, azimuth) considering the uncertainties at survey stations using the RSS Model developed by the University of Stavanger. The TCO autonomously creates the well plan, controls the bit's deviation, and corrects the trajectory when it has diverged from the planned trajectory.

The simulator can drill either 2D or 3D trajectories. In the case study, one 3D trajectory example provided by the Drillbotics committee is illustrated. The results obtained show differences among the original (given), the planned (optimal, before drilling), and the simulated (during drilling) trajectories. Moreover, the comparison between the simulation with/without the TCO module reveals the necessity and importance of autonomous and real-time trajectory control. Besides, the BHA tool activation (due to the autonomous control of the simulator) is perceived in the simulation's results, which influences the rest of the parameters like the DLS, the force acting over the bit, and the rate of penetration (ROP) in the axial axis, inclination axis, and azimuth axis calculated with the RSS Model.

The work presents a novel way to predict the bit position and control the trajectory, considering bit position uncertainties, drilling parameters uncertainties, DLS, and tortuosity calculations in an automated way. It will help users to develop further automated algorithms and mathematical models for reaching autonomous directional drilling in the future.
Casing Wear Tests for Precise Wear Factor Evaluation
Authors: Osman Omer Alnoor , Merah Necar , Samuel Robello , Alshalan Meshari , Alshaarawi Amjad
Published: March 2022

The increasing complexities of wellbore geometry imply an increasing potential of damage resulting from downhole casing wear. The present method of using old wear factors results in unreliable predictions. The main objective of the present work is to develop new casing wear factors for drillpipes and casings to improve the accuracy of wear prediction. The paper focuses on design, manufacturing, control and measurements of important parameters contributing to casing wear as well as wear volume evaluation.

A new casing wear testing facility is designed and built by repurposing and automating an old lathe machine. Real drillpipes with tool joints and casing sections made of different materials are used. The lathe spindle controls the mandrill rotational speed on which the DP is tightly mounted. The versatile casing section holder is fixed on a sliding system comprising a dynamometer and a step-motor with a microcontroller allowing for the control and measurement of the side loadings and lateral displacements. A slurry fluid pump system is designed to feed water-based or oil-based muds at the contact surfaces.

The as-received drillpipes and casing materials were analyzed by microscope and optical emission spectrometry (OES) to determine their microstructure and chemical composition. The hardness of both casing and DP materials was also measured. The lathe main spindle was able to provide stable rotating speeds varying from 100 to 1000 rpm. Though the irregular tool joint hard-facing surface was machined to allow for better control of the side loadings, the measured radial load shows variations of +/− 15%. The designed pumping system was able to provide a continuous stream of water-based and oil-based mud, at the contact surface, during testing. The wear depth is measured both directly using a 3D optical profilometer and indirectly by the lateral sliding displacement, thus allowing for the establishment of a calibration curve that can be used for in-situ measurement of the wear depth and wear volume evaluation. The initial set of tests has shown that the designed system is performing satisfactorily. More tests are being performed to confirm the robustness of the design.
Prediction of Stuck Pipe Incidents Using Models Powered by Deep Learning and Machine Learning
Authors: Mal Anwesha , Ødegård Sven Inge , Helgeland Stig , Zulkhifly Sinaga Samuel , Svendsen Morten
Published: March 2022

One of the most common issues faced in the Drilling industry is a Stuck Pipe situation. Stuck Pipes lead to huge losses in cost, energy and productive time. The objective of this paper is to predict stuck pipe incidents prior to their occurrence by harnessing the power of machine learning and deep learning models.

Stuck incidents are some of the most difficult and challenging situations. The proposed method uses a two-step model and available historical data from prior drilling operations to predict the occurrence of such an incident well in advance so that it can be avoided. The first step of the model performs time series predictions using a Recurrent Neural Network (RNN) with Walk Forward Validation. The second part of the model uses a Random Forest Classifier to classify the predictions from the previous step and determine if a stuck situation is likely. The classification model is pre-trained using historical drilling operational data collected from old wells. It is possible to determine how far back the model should look at the data and how far ahead it should predict. For the purpose of this paper, the model looks back 5000 timesteps and predicted 3000 timesteps ahead. One timestep is 2 seconds in this case.

This model would be able to reduce nonproductive time, and help make drilling operations cleaner, faster and greener. The biggest benefit of such a model is that it can learn on the go and would not require manual intervention. Also, the model can upgrade and modify itself to changes in the drilling operations.
Event Detection in Drilling Remarks Using Natural Language Processing
Authors: Zhang Zheng , Hou Tianjun , Kherroubi Josselin , Khvostichenko Daria
Published: March 2022

Remarks in daily drilling reports (DDR) and daily mud reports (DMR) are an invaluable source of information for the analysis of ongoing operations and planning of future wells. These remarks are entered as free text and thus represent unstructured information, which requires expert knowledge for interpretation. Here, we aim to develop a machine learning algorithm to automatically detect events of interest and convert this information into a structured format. Several unscheduled events, such as losses, influx and stuck pipe, were selected to develop a prototype of our natural language processing (NLP) approach for daily DMR remarks. Data selection, data annotation and analysis workflow, and results are discussed in the manuscript.
Reducing Human Error Through Automatic Kick Detection, Space Out and Dynamic Well Monitoring
Authors: Curina Francesco , Abdo Elia , Mustapha Hadi
Published: March 2022

Influx detection and well control are critical situations where the traditional human reaction has been the accepted standard for years. This paper discusses the results of the driller stress tests and the implementation of a system to assist the operator in kick detection, space out and preparation for well shut in. The system implements dynamic well monitoring to reduce the risk of false alarms. The objective is to prove how automation helps mitigate human factors.

A stress analysis test was conducted on a variety of experienced drillers to identify the specific operations with the highest risk factors influenced by operator stress. Once the target operations were identified, an automation algorithm was designed and tested to mitigate the human factor during these specific instances. The resulting system detects drilling kicks and automatically performs the space out operation. Dynamic trip and active tank monitoring were implemented to reduce false alarms. This provides the driller with an assistant for tripping operations. The package can be adapted to any type of rigs or blow out preventer (BOP) stacks without requiring additional hardware.

Testing was conducted in both simulated and real-life situations, during tripping and drilling operations. The system was able to predict tool joint positions in the well with a mean error consistently below 1%. The automation of the space out operation allowed the system to perform the operation in significantly shorter times and with higher accuracy, eliminating the risk of any tool joint being placed across BOP elements. During tripping operations, dynamic tank tracking effectively eliminated risks of kicks helping the driller keep a constant and adequate filling of the well. Finally, a comparison of the operator stress levels with and without the use of the automation package shows the positive impact such a system can have on situational awareness and concentration. The plug and play aspect of the system proved critical for easy and fast implementation, as well as ensuring a quick familiarization of the driller with the different functionalities. The tests also highlighted the importance of accurate and high-resolution sensors to ensure optimal working conditions.

Automation in the field of well control is a relatively new subject. This paper showcases the impacts this type of systems can have on operations and proposes an implementation method to profit from automation while minimizing its impact on critical operations. The field implementation showed how different sensor configurations can lead to different degrees of automation and, thus, different impacts on the operations.
Triaxial Leak Criterion for Generic Premium Connection Under Combined Tension and Pressure Loads
Authors: Goodman Malcolm A.
Published: March 2022

Recent papers introduced a triaxial leak criterion with hydrostatic dependence through the Mean Normal Stress P defined as the average of the three normal stresses. The new criterion with linear dependence on P required two leak constants. Example applications in these papers addressed American Petroleum Institute (API) connections. This paper applies the triaxial criterion to a generic premium connection and determines the leak constants from finite element analysis (FEA) for combined loads with tension.

Instead of a linear dependence on P, the FEA results for the generic premium connection correlate better with a quadratic relationship in terms of (P - σn) where σn is the Lubinski neutral stress. The quantity (P - σn) is proportional to effective stress. Quadratic dependence means that three leak constants are needed for premium connections. A plot of the leak limit curve superimposed on the pipe-body yield envelope shows load combinations where leak occurs before the pipe yields. A key conclusion is that internal leak cannot occur without tension for the loads investigated. Indeed, with sufficient tension, both internal and external leak can occur at low pressures for this modified generic premium connection. Actual premium connections should be designed so this triaxial limit curve for leak is outside (or mostly outside) the pipe-body failure envelope.
Automated Well Control Versus Traditional Well Control: A Human Error Comparison Process
Authors: Atchison Bryan Wade , Sarpangal Varun
Published: March 2022

Traditionally, well control systems have been entirely reliant on a single human reliably and accurately detecting an influx and shutting-in the well.  The human condition means the driller can be distracted, or unexpectedly influenced by extraneous factors. Over-reliance, then, on humans in well control can be dangerous, because of the inherent and constant exposure to human factors risk. An automated well control system has been designed to fully automate influx detection and shut-in sequences and reduce personnel exposure to rig-floor safety risks.

A comparative human factors study for the use of automated well control against traditional well control methods was performed. The analysis, completed by means of Human Reliability Assessment methodology, provides a qualitative and quantitative assessment of the human failure modes associated with the operation of the automated well control compared with the equivalent associated with traditional methods.

A Systematic Human Error Reduction and Prediction approach was used to provide the basis for subsequent quantitative assessments of human reliability. Once scenarios were subjected to the qualitative modelling process, the Success Likelihood Index methodology was applied to quantify the human error probabilities.  

The outcome of the comparative analysis highlights a significant reduction in the human failure risks that automated well control brings to well control.

By examining the opportunities for human error/failure to impact upon the successful identification and shut-in of an influx, the study demonstrates that automated well control could achieve 94% reduction in the probabilities of human failures for a blowout, or 96% for a large influx.

This paper will describe the automated well control technology and summarise the outcomes of the comparative analysis between automated well control and traditional well control.
IADC Dull Code Upgrade: Objectives and Organization
Authors: Pastusek Paul , Daechsel Dustin , Macmillan Robin , van Kuilenburg Robert , Propes Chris , Shackleton David , Lyles Dustin , Oberkircher Jim , Sharples Jonathan , Neil Paul , Illerhaus Roland , Roberts Tom , Watson Willie
Published: March 2022

This paper describes the progress in upgrading the IADC dull code system. The IADC code is a compact, text-based way to describe the bit condition. The current PDC code was created in 1987 (Clark et.al. 1987) and revised in 1992 (Brandon et. al. 1992) along with roller cone bits (McGehee et. al. 1992) and more recently proposed for other cutting tools (Ulvedal et. al. 2011). It has held up well, however with the introduction of automated systems, machine learning, evolving products, and requirement for more detailed analysis, there is a substantial need to improve the system.

The key objectives are to: rework the IADC dull grading system to better support continuous improvement workflow, root cause analysis, reduce the subjectivity inherent in the current system, support human and emerging automated bit dull grading systems, and create a best practice for a digital storage format including searchable metadata.

Over 160 volunteer subject matter experts have been divided into four workgroups to focus on: 1) a qualitative classification scheme for PDC cutters, drill bits, and tools, 2) BHAs, motors, RSS tools, and stabilizers, 3) case studies, and 4) data definition, storage, retrieval, and exchange.

The bit and BHA sub groups are defining a standard set of examples and descriptions for each damage classification. They are gathering and labeling a set of photo examples for human training and machine learning. Once complete, the proposed codes will be sent out for an end user trial of the new system. Updated codes and best practices instructions will be created based on this feedback and submitted to the IADC for publication.

The Case Study group is collecting and documenting case studies for continuous improvement and forensics analysis to provide examples for the industry based on the input of a large group of industry and academic experts. Much of this work is presented in a companion paper. (Watson et. al. 2022)

Last, the required metadata needed to support this effort has been documented and examples of best practice storage methods for image and metadata are offered to the industry for voluntary adoption. This is the scope of workgroup 4.

This is the first major revision of the IADC dull code system in 35 years. It is taking into account changes in the data needed and available for continuous improvement, with a plan for future developments in photometrics, AI classification, and storage technologies. It is also the first joint industry attempt to document case studies and forensics workflow best practices.
Engineering and Data-Led Sustainability for Real-Time Monitoring
Authors: Samuel Robello , Adari Rishi , Srinivasan Nagaraj
Published: March 2022

The environmental impact of oil and gas wells from exploration to abandonment is a primary focus during well planning and drilling. However, there is no industry standard to quantify the impact of complex indicators and associated variables, particularly when the well is drilled in real time. Thus, a quantification method using the associated variables used for real-time well monitoring as the well is drilled and produced can be useful. A new model for the sustainability index for well design and engineering during drilling is presented and validated. This proposed method avoids some of the vagueness of well sustainability and can be used and applied in a practical manner. It is based on various metrics and weightage assigned when a well is drilled and compared to the planned metrics. Evaluating the index for well engineering is based on elements of environmental impact, well design and engineering, the impact of functionality and optimization, well and maintenance costs, health and safety, and societal impact. Each element contains subelements. This process involves individual indexing through backpropagation of neural networks combined with the bat algorithm to obtain the echo location to identify the overall index.

The proposed method uses a well-engineering-based approach that defines boundaries and thresholds as the well is drilled. The Powell Method, designed for nonconstraint optimization, is also used for fast convergence for this derivative-free problem. The algorithm is fast and provides results based on an iteration method. Because engineering during the well lifecycle involves several nonlinear system and asymmetric inputs, it has been observed that identifying the effects of input uncertainties and other related calculation uncertainties (i.e., variation and errors in log data, survey data, etc.) create an effect. It was also observed that uncertainty analysis provided an optimized index without assigning preferential weightage to some of the components. The method does not reduce uncertainty, but can be used to estimate the influence of various parameters on the sustainability index. To achieve runaway uncertainty, a mutation strategy is introduced to maintain the population diversity of the indices within the defined limits.
Annular Temperature Variation and its Impact on Fracture Gradient in a Deepwater Environment
Authors: Rizvi Aijaz , Hashemian Yahya , Yao Ziheng , Nelson Mark , Yuan Zhaoguang
Published: March 2022

Fracture gradient prediction is a crucial step in wellbore planning, casing setting depths, and fluid design. Knowing the exact fracture gradient during the drilling phase of well construction is also essential to avoid lost circulation and other hole-related problems. Most commonly, fracture gradient modeling uses a previously known formation pressure integrity test, i.e., leak-off test and rock properties but fails to consider various effects that can reduce fracture gradient. Annular drilling fluid temperature is one of the most important. This paper aims to investigate annular temperature variation and develop a practical method to avoid wellbore problems in deepwater wells.
Relationship Between the Tat Protein Transport System and Virulence of Enterotoxigenic Escherichia Coli
Authors: gong zhaolong , Wang Liyuan , Cheng Jiali , Zhuo Qin
Published: March 2022

Background We aimed to investigate the effect of Tat deletion on the pathogenicity of enterotoxigenic Escherichia coli (ETEC). Changes in bacterial dynamics and virulence after deletion were examined using mobility and animal toxicity tests for ETEC. Further, differential expression of proteins between the gene-deletion and wild-type strains was analyzed using two-dimensional gel electrophoresis and matrix-assisted laser desorption/ionization time-of-flight mass spectrometry to explore the possible mechanisms underlying the effects of this gene on bacterial virulence. Results After Tat knockout, the virulence of ETEC10407 was strongly attenuated, and its invasion in rabbit intestinal mucosa was significantly reduced. Mass spectrometry revealed that 17 differentially expressed proteins involved in physiological functions of bacteria, such as virulence and substance or energy metabolism might affect bacterial pathogenicity. Conclusions The Tat protein transport system of ETEC is closely related to its virulence.
Prognostic Nomograms Based on Microvascular Invasion Grade for Early-stage Hepatocellular Carcinoma Patients After Curative Hepatectomy
Authors: Ke Jingpeng , Ye Honghao , Lin Fangzhou , Shi Yingjun , Zhong Aoxue , Yang Huang , Chen Hengkai
Published: March 2022

Background: Hepatocellular carcinoma (HCC) is among the most frequent causes of cancer-related deaths worldwide. Although predictive models for postoperative early recurrence in patients with HCC have been established, this is the first study to develop and evaluate a predictive model based on the microvascular invasion classification for early recurrence and survival after curative hepatectomy in patients with early-stage HCC.Methods: The database of patients with early-stage HCC who underwent curative hepatectomy in the First Affiliated Hospital of Fujian Medical University and the First Affiliated Hospital of Xiamen University was retrospectively reviewed. Kaplan-Meier curves and Cox proportional hazards regression models were used to analyse disease-free survival (DFS) and overall survival (OS). Nomogram models were constructed on the datasets from the First Affiliated Hospital of Fujian Medical University, which were validated using bootstrap resampling with 30% samples as internal validation. Data of patients from the First Affiliated Hospital of Xiamen University were used for external validation.Results: A total of 703 patients with early-stage HCC were included in our study. An eight-factor nomogram for predicting recurrence or metastasis and a six-factor nomogram for predicting survival were created. The concordance indexes were 0.775 (95% confidence interval [CI], 0.720-0.830) for the DFS nomogram and 0.812 for the OS nomogram (95% CI, 0.732-0.892) in the training cohort; 0.865 (95% CI, 0.806-0.924) and 0.839 (95% CI, 0.675-1.00), respectively, in the internal validation cohort; and 0.857 (95% CI, 0.763-0.951) and 0.842 (95% CI, 0.708-0.970), respectively, in the external validation cohort. The calibration curves showed optimal agreement between the predicted and observed DFS and OS rates. The predictive accuracy was significantly better than that of the classic HCC staging systems.Conclusions: This study developed and validated nomograms for predicting recurrence, especially early recurrence, and overall survival in patients with early-stage HCC after curative resection with high predictive accuracy.
Quality of Life and Symptom Distress After Cytoreductive Surgery and Hyperthermic Intraperitoneal Chemotherapy: A Prospective Study
Authors: Wang Ya-Fen , Wang Ting-Yao , Liao Tzu-Ting , Lin Meng-Hung , Huang Tzu-Hao , Hsieh Meng-Chiao , Chen Vincent Chin-Hung , Lee Li-Wen , Huang Wen-Shih , Chen Chao-Yu
Published: March 2022

Purpose
Cytoreductive surgery and hyperthermic intraperitoneal chemotherapy (CRS/HIPEC) for peritoneal surface malignancy can effectively control the disease, however it is also associated with adverse effects which may affect quality of life (QoL). This study aimed to investigate early perioperative QoL after CRS/HIPEC, which has rarely been discussed in the literature.
Methods
This single institution, prospective cohort study enrolled patients who received CRS/HIPEC. We assessed QoL using the Taiwanese version of the MD Anderson Symptom Inventory (MDASI-T) and European Organization Research and Treatment of Cancer Core Quality of Life Questionnaire (EORTC QLQ-C30). Participants completed the questionnaires before CRS/HIPEC (S1), at the first outpatient follow-up (S2), and 3 months after CRS/HIPEC (S3).
Results
Fifty-eight patients were analyzed. There was no significant perioperative difference in global health status. Significant changes in physical and role functioning scores decreased at S2, and fatigue and pain scores increased at S2 but returned to baseline at S3. Multiple regression analysis showed that age and performance status were significantly correlated with QoL. In the MDASI-T questionnaire, distress/feeling upset and lack of appetite had the highest scores at S1, compared to fatigue and distress/feeling upset at S2, and fatigue and lack of appetite at S3. The leading interference items were working at S1 and S2 and activity at S3. MDASI-T scores were significantly negatively correlated with the EORTC QLQ-C30 results.
Conclusion
QoL and symptom severity improved or returned to baseline in most categories within 3 months after CRS/HIPEC. Our findings can help with preoperative consultation and perioperative care.
Non-cruelty eradication of European wild rabbit Oryctolagus cuniculus from a small Mediterranean island (Isola delle Femmine, Italy)
Authors: Valvo Mario Lo , Lillo Francesco , Dio Vincenzo Di
Published: March 2022

European wild rabbit is, among mammals, one of the most widespread species almost worldwide, introduced on over 800 islands. In microinsular habitats, the introduction of alien species represents a major threat for the biodiversity, and the wild rabbit is included in the IUCN published list of the 100 worst invasive species. In 2008, an eradication plan was launched on “Isola delle Femmine”, a small and uninhabited island of about 14,5 hectares, located in the Mediterranean basin and established as nature reserve in 1997 to protect its flora and vegetation. The plan was realised without the use of poison and avoiding the killing of rabbits, which were live-trapped and moved out for successive conservation projects in Sicily. The Wild Rabbit eradication plan began in December 2007 and ended in 2016, with the complete eradication of the species achieved in 2012. During the 5 years in which trapping took place on the island, a total of 799 rabbits were trapped and translocated. A significant positive correlation (r = 0.986; p = 0.014) was observed between the number of catches made during the year and the estimated rabbit density in July (considered the highest of the year). The method used showed considerable efficacy for the management of rabbit populations in microinsular environments, highlighting the possibility of intervention with these methods when control by the use of poison or direct culling is impractical or inadvisable.
Antiviral Therapy Use and Related Outcomes in Patients with Cancer and Viral Infections: Results from SWOG S1204
Authors: Hwang Jessica P. , Arnold Kathryn B. , Unger Joseph M. , Chugh Rashmi , Tincopa Monica A. , Loomba Rohit , Hershman Dawn , Ramsey Scott D.
Published: March 2022

Purpose
Information is limited about adherence to practice guidelines in patients with hepatitis B virus (HBV), hepatitis C virus (HCV), or HIV infection receiving anticancer treatment.
Methods
Newly diagnosed adult cancer patients were enrolled in a multicenter, prospective cohort study (SWOG S1204) from 2013-2017 to evaluate the prevalence of HBV, HCV, or HIV in patients initiating anticancer treatment. At 6 months, records of virus-positive patients were reviewed for antiviral therapy use; anticancer treatment dose reduction; and HBV reactivation (elevated viral load). Categorical variables were compared using chi-square or Fisher’s exact test.
Results
Of 3055 enrolled patients with viral testing, 230 had chronic or past HBV, HCV, or HIV with 6-month follow-up data (chronic HBV, 15 patients; past HBV, 158; HCV, 49; HIV, 30). Twenty percent (3/15) of chronic HBV and 11% (17/158) of past HBV patients were co-infected with HCV and/or HIV. Rates of antiviral therapy use by 6 months were as follows: chronic HBV, 85% (11/13); past HBV receiving anti-B cell therapy, 60% (3/5); past HBV receiving systemic anticancer therapy without anti-B cell therapy, 8% (8/105); HCV, 6% (2/35); and HIV, 90% (19/21). Among patients with available data, anticancer treatment dose was reduced in 1 of 145 patients with past HBV and 1 of 42 with HCV. HBV reactivation occurred in 1 of 15 patients with chronic HBV; this patient was not receiving antiviral therapy.
Conclusion
In many patients with cancer and viral infections, antiviral treatment does not match guidelines. Further education is needed to improve adherence to guidelines.
Differential Regulation of Intramuscular Fat and Abdominal Fat Deposition in Chickens
Authors: Luo Na , Shu Jingting , Yuan Xiaoya , Jin Yuxi , Cui Huanxian , Zhao Guiping , Wen Jie
Published: March 2022

Background: Chicken intramuscular fat (IMF) content is closely related to meat quality and performance such as tenderness and flavor. Abdominal fat (AF) in chickens is one of the main waste products at slaughter. Excessive AF reduces feed efficiency and carcass quality.Results: To analyze the differential deposition of IMF and AF in chickens, gene expression profiles in the breast muscle (BM) and AF tissues of 18 animals were analyzed by differential expression analysis and weighted co-expression network analysis. The results showed that IMF deposition in BM was associated with pyruvate and citric acid metabolism through GAPDH, LDHA, GPX1, GBE1, and other genes, whereas AF deposition was related to acetyl CoA and glycerol metabolism through FABP1, ELOVL6, SCD, ADIPOQ, and other genes. Carbohydrate metabolism plays an important role in IMF deposition, and fatty acid and glycerol metabolism regulate AF deposition.Conclusion: In conclusion, this study elucidated the molecular mechanism governing IMF and AF deposition through key genes and signaling pathways and provided a theoretical basis for producing high-quality broilers.
Fall Predictors in Hospitalized Patients Living with Cancer: A Case-Control Study
Authors: Zeneli Anita , Montalti Sandra , Masciangelo Itria , Manieri Gloria , Golinucci Monica , Nanni Oriana , Montella Maria Teresa , Martinelli Giovanni , Petracci Elisabetta
Published: March 2022

Purpose
to identify fall predictors and develop an assessment tool to be used for screening hospitalized cancer patients at risk for fall.
Methods
a retrospective case-control study was conducted in 2018 at a cancer center in Northern Italy. The study participants were 448 adult cancer patients admitted to the oncology ward from 2009 to 2013. The cases group consisted of 112 patients presenting at least one fall, while controls were randomly chosen by matching each case for age, sex and admission period with three patients who did not fall. Data for the fall predictors were extracted from the electronic medical records. Conditional logistic regression was used to evaluate the association between patient’s characteristics and fall risk.
Results
the overall prevalence of patients having at least one candidate fall predictor was high (98%). Seven of the studied variables showed an independent association with fall risk at multivariate analysis. These were tumor site, the presence of neurologic diseases, gait imbalance disorders, fatigue and the assumption of certain medications such as diuretics, hypnotics and opioids (odds ratios and 95% confidence intervals in brackets were 3.78 (1.78-8.13), 2.26 (1.08-4.77), 4.22 (1.87-9.52), 2.76 (1.45-5.26), 2.66 (1.52-4.66), 2.41 (1.20-4.85), and 3.03 (1.68-5.45), respectively).
Conclusions
results of our study highlight the need for developing risk assessment tools based on the characteristics of cancer centres. The validation with a prospective independent cohort is necessary before implementing our screening tool in clinical practice.