bluuebunny/crossref_metadata_2025_split huggingface dataset:
Successful Smart Completion Deployment of Autonomous Inflow Control Valve with 13 Open Hole Segmentation Lower Completion Using a Light Workover Rig
Authors: Alakberi R. S. , Igein O. F. , Aljasmi S. A. 
Published: May 2023

Abstract
This paper presents a case study of the successful lower completion deployment of 13 swellable packers and Autonomous Inflow Control Valves (AICVs) into a 2227 ft open hole using a light workover rig in ADNOC Onshore (AON).
The objective of the well was to reduce the well's high Gas to Oil Ratio (GOR) and increase production efficiency and profitability. The main concern as Drilling & Completion team was to recover the single oil producer completion and run it with lower completion safely to the Target Depth (TD) and meet the Asset team objective and requirements.
The workover rig of 750 HP can reach up to 12,000’ target depth and the maximum overpull is 210 klbs where the planned target depth is 12,127’ MD/ 8922’ TVD. A pilot study was done on this well since the production team observed an increase in the GOR where the maximum value reached 2800 scf/bbl from 2016 to 2022.
Despite the challenges presented by the light workover rig capacity limitations, deployment of 2227 ft lower completion with 13 swell packers in open hole with assurance of proper isolation, a dedicated engineering study, simulations and risk assessment were concluded during the planning phase focusing on these challenges and set the proper engineering solution through a Torque and Drag simulation and checking the feasibility of deploying lower completion using the 750 HP light workover rig. In addition, a proper hole cleaning was planned with the combined trip of open hole drift and scrapper. Furthermore, for wellbore segmentation isolation, two runs of mechanical caliper logs were conducted to guarantee optimal placement of swell packers and strive for proper isolation of each segment, which eventually supported the successful completion of the well as per plan. The study provides insights into the design, execution, and monitoring of maintenance work for workover wells that aim to retain their production rates.
One of the major challenges of the well was the limitations of the rig capacity which will be highlighted in the study along with the methods used to address these limitations. Also, the use of AICVs, 13 swell packer deployment, equipment selection, real-time monitoring, expertise, pre-planning, torque and drag performance, design modelling, and simulations during the planning phase are some of the steps taken to eventually execute a flawless completion. A proper well cleanout and dedicated drift run were among some of the things carried out to make the deployment of the lower completion successful. The eventual results showed that the use of these techniques not only helped reduced the well's high GOR and thereby increased production efficiency and profitability but also was the main reason we were able to successfully get the lower completion to target depth. It is significant to highlight that one of the lightest WO rigs in the AON field successfully completed the well as Workover well.
Cloud-Based Data Integration Between Geology & Drilling Software Using Python Tools
Authors: Mwansa P. , Hernandez B. C. H. R. , Grebe S. , Hassan M. A. , Torsæter A. , Jenssen F. 
Published: May 2023

Abstract
The oil and gas industry generates vast amounts of data throughout its operations, from exploration to production. Collecting, connecting, and optimally utilizing this data is key to maximizing efficiency, accuracy, and access to new disruptive technologies.
In a typical well-planning cycle, an engineer will spend significant amount of time looking for the data they require to do their jobs efficiently. The data are typically locked away in silos - trajectories in one data platform, Pore Pressure Gradient, Fracture Gradient or Targets in another, and so on.
A major Middle Eastern NOC and Two Norwegian software service companies teamed up to develop Proof of Concept (PoC) for a new workflow that integrates subsurface and drilling data between on-premises Geology E&P software and Drilling software through a proprietary Python Tool plug-in and Python library. This integration enables a streamlined connection to a cloud-based drilling and well planning software, facilitating collaboration among teams involved in well planning. The project's key challenges are the lack of a standardized communication, integration, and automation of data flows between subsurface and drilling teams, as well as the inability of engineers to access necessary data due to scattered information and access restrictions. The project utilizes a proprietary data science suite, named Cegal's Prizm, which allows easy configuration to integrate data from various applications, sources, and platforms. A proprietary Python Tool is used to merge data from various application silos and data sources, enabling enriched investigation. The process involves connecting to the Geology E&P software retrieving domain objects using the proprietary Python Tool, and converting these domain data objects into common Python data structures. The project aims to develop an innovative workflow that provides easier access to data for experts throughout the organization, leading to better decision-making during the well-planning cycle. This not only makes it easier, but it also ensures collaboration between the G&G and Drilling teams involved in new well planning
A Holistic Approach to Consider for Slot Recovery Based on a Failure Incident in North Sea Operations
Authors: Ioan T. , Bull R. L. 
Published: May 2023

Abstract
An oilfield service company was awarded the scope by an operator in the North Sea to recover three slots from an existing offshore platform and redrill the HPHT wells to tap into unreached reservoir resources on a gas field. This paper covers the holistic approach of analysing the slot recovery operations strategy, plug and abandon the original wellbore, and how to avoid tunnel vision in the decision-making process to achieve the goals.
Cut and pull operations have one of the highest financial impacts on slot recovery and can lead to loss of the well in unfortunate circumstances. After slot recovery operations, including the cutting and milling of the 10-3/4″ × 10″ casing, the 13-3/8″ casing failed the pressure test. The incident triggered a Cause Analysis Tree Diagram of the well conditions that led to the discovery of a hole in the 13-3/8″ casing. The investigation highlighted the tunnel vision of the decision-making process where ‘stop points’ were bypassed or not efficiently identified, contributing to operational delays and potential loss of the wellbore.
The investigation concluded that insufficient information on the well was obtained during the planning phase and the financial decision tree analysis was incorrectly defined to proceed with the preparation of the contingency plans. In this process, all existing logs were re-evaluated to identify the solids behind casing, ovality, centralization, and casing-on-casing contact points. The original plan was to cut and pull the casing and then mill ~374ft of casing, with a shallow sidetrack option as contingency. However, during the execution, due to height of the top of solids encountered behind the casing, it was required to start milling from a shallower depth, with a total of ~ 1,500 ft of casing to be milled. At this stage in the operations, a fishbone diagram should have been created to perform a detailed analysis of the technical risks and cost impacts and to decide whether to continue milling or to proceed with the contingency option to sidetrack from a shallower depth. However due to peer pressure, tunnel vision goal seeking (Gasaway, n.d.), and phycological safety the multi-factor decision ‘stop points’ were not considered leading to an expensive, lengthy, and unsuccessful operations.
This paper summarizes the decisions and ‘stop points’ in the process of slot recovery operations and highlights the potential outcomes of incorrect technical risks and cost analysis. Further reviewing the utilization of the engineering analysis, and economical aspects through preparation of a fishbone diagram to manage stakeholders’ expectation on upfront commitment to continue with challenging slot recovery operations on a major decision-making point. The example and process provided in this paper will benefit the industry by helping to recognize a ‘stop points’ in the operations, highlighting the risks of having catastrophic event.
Stuckpipe Prediction Model to Detect and Notify Rig Crew Based on Drilling Parameters and Physical Models Outputs
Authors: Malki Mohammed A. , Abughaban Mahmoud F , Guimaraes Thiago T , Alshawabkeh Albara' A 
Published: May 2023

Abstract
Effective stuckpipe prediction becomes more challenging and requires real-time advanced analysis of all available drilling data. This paper presents an innovative model to predict stuckpipe incidents. A machine-learning model based on intensive feature-engineering integrated with physical models has been developed. It automates real-time drilling data collection, analysis, and detects the patterns for the most dominating drilling parameters values to achieve the success criteria of early warning signs of stuckpipe incidents. It has been applied on two equal sets of wells either stuck or non-stuck incidents. The model triggers alarms reliably and early before the stuckpipe incidents happen and therefore corrective actions could be taken properly in advance.
A Systematic Approach to Fracture Propagation Simulation with the Integrated Natural Fracture and Geomechanical Model
Authors: Guan Xu , Zhu Deyu , Tang Qingsong , Wang Xiaojuan , Wang Haixia , Zhang Shaomin , Deng Qingyuan , Yu Peng , Yu Kai , Huang Xingning , Xu Hanbing 
Published: May 2023

Abstract
In recent years, tight sandstone gas as one of the important types of unconventional resources, has been rapid explored and developed. There are large-scale tight sandstone gas production in Sichuan Basin, Ordos Basin, Bohai Bay Basin, Songliao Basin and other basins, and it has become a key part in the area of increasing gas reserves and production in China. Due to the influence of the reservoir characteristics, tight gas reservoirs have low porosity and permeability, and the tight gas can only be effectively developed by improving the conductivity around the wellbore. Therefore, it is required to perform hydraulic fracturing after the completion of horizontal well drilling to improve the permeability of reservoir. It can be seen that hydraulic fracturing is the core technology for efficient development of tight gas resources. The implementation of hydraulic fracturing scheme directly determines the horizontal well production and EUR. This paper describes the workflow of 3D geomechanical modeling, technical application for Well YQ 3-3-H4 reservoir stimulation treatment, and carries out hydraulic fracture propagation simulation research based on 3D geomechanical model. This paper also compares the micro-seismic data with the simulation results, and the comparison results show that the propagation model is consistent with the micro-seismic monitoring data, which verifies the accuracy of the model. This paper clarifies the distribution law of hydraulic fractures in the three-dimensional space of horizontal wells in YQ 3 block, and the research results can be used to provide guidance and suggestions for the optimization of fracturing design of horizontal wells in tight gas of Sichuan Basin.
Well Simulator Technology Overview and Results for Onshore, Offshore and Subsea Drilling Operations
Authors: Santoro D. , Forno L. Dal , Ferrara P. , Bianchini L. P. , Bartucci G. , Bianchi L. , Lahou K. , Nabavi J. , Huseynov P. , Gocmen E. B. , Lye J. , Loh J. 
Published: May 2023

Abstract
Well simulator technologies have become an ever more important part of Well Construction design and Drilling Operations follow-up worldwide. Adopted initially by Company to support personnel training through virtual environment applications, they were then used for planning, real time support and post job analysis for drilling operations, being integrated in all engineering processes. This paper presents an overview of its current use and procedures, highlights current and potential benefits and suggestions for future developments.
Selected wells are configured inside the well simulator which is then latched to mud log data streams. Dynamic models calibration is performed by adjusting dedicated coefficients to reach an overlap between simulated and measured drilling parameters. The degree of drift between curves allows to identify well operations-related issues. Outputs are mostly time-based, in mud log and driller-cabin-like layouts fashion. Depth-based plots, such as roadmaps for axial and torsional friction factors are also available and can be used as input for advanced analyses for both planning and post job phases.
Systematic application of the well simulator was started early 2021 with real time monitoring for North Sea and Africa offshore/subsea operations. Deployment along 2022 spread out across several other business units in various operated countries, for onshore, offshore and subsea drilling operations. Experience gained in a number of relevant case histories, dedicated to both real time support and what-if post-analyses, allowed to provide earlier feedbacks on drilling operations good practice but also to predict, avoid and mitigate consequences of wellbore problems and equipment malfunctions, boosting interest for further developments. Nowadays, well simulator technologies constitute a fundamental step towards drilling automation, since their dynamic modelling approach allows the definition of drilling parameter envelopes inside which robotic tools can operate and generate alerts if envelopes are overridden. Anomalous behavior of the drilling parameters can be recognized and governed. Automatic configuration and calibration of real time driven models are key enablers of real time optimization of operational drilling parameters and contactless operations, reducing back-office support to minimum.
Well simulator solutions that have been tested and deployed in our operations allow adaptability to a variety of existing platforms from both the operators and service companies side. The new upgrades, for data input and results visualization, are prone for user-friendly application, reducing the amount of training required for operative personnel to familiarize themselves with the tool and apply it during drilling operations.
A Hybrid Physical and Machine Learning Model to Diagnose Failures in Electrical Submersible Pumps
Authors: Al-Ballam S. , Karami H. , Devegowda D. 
Published: May 2023

Abstract
Electrical submersible pumps (ESPs) are among the most common artificial lift techniques in highly productive oil wells. The ESP failures are extremely costly to the producers and must be minimized. This study proposes a hybrid approach utilizing multi-class classification machine learning (ML) models to identify various specific failure modes (SFMs) of an ESP. A comprehensive dataset and various ML algorithms are utilized, considering the physics of fluid flow through the ESP.
The ML models are based on field data gathered from the surface and downhole ESP monitoring equipment over five years of production of 10 wells. The dataset includes the failure cause, duration of downtime, the corresponding high-frequency (per minute) pump data, and well-production data. The prediction periods of 3 hours to 7 days before the failure are evaluated to minimize false alarms and predict the true events. Four modeling designs are used to handle the data and predict ESP failure. These designs differ in the input parameters used for the model and signify the effect of including the physical parameters in failure prediction. Several ML models are tested and evaluated using precision, recall, and F1-score performance measures. The K-Nearest Neighbor (KNN) model outperforms the other algorithms in forecasting ESP failures. Some other tested models are Random Forest (RF), Decision Tree (DT), Multilayer Perceptron (MLP) Neural Network, etc.
According to the data, most ESP operational failures are characterized as electrical failures. The ML models show similarly good performances with high true prediction rates in predicting ESP failures for all the tested designs. The design that integrates the effects of gas presence and pump efficiency while minimizing the number of input variables is suggested for general use. Increasing the prediction period up to 3 days results in a negligible drop in the model’s performance, showing that the model can predict ESP failures accurately three days before their occurrences. However, the forecasts show increases in missed failures and false alarms for prediction periods of more than three days, making three days the selected prediction period. These ML models will aid operators in avoiding undesirable events, reducing downtime, and extending the lifespan of ESPs.
ESP failures are unanticipated but common occurrences in oil and gas wells. It is necessary to detect the onset of failures early and prevent excessive downtime. This study’s model allows engineers to detect failures early, diagnose potential causes, and propose preventive actions. It is crucial in transitioning from a reactive event-based to proactive and predictive maintenance of artificial lift operations.
Cost-Effective Development Mode for Marginal Oil fields – Best Practice of CNPC
Authors: Wu Bohong , Nie Zhen , Li Yong , Deng Xili , Ma Ruicheng , Xu Jiacheng 
Published: May 2023

Abstract
Marginal reserves are an important play in future energy development. Based on the statistics of China National Petroleum Corporation (CNPC), the low permeability and unconventional reservoirs occupied 92% of newly found proven reserves in China. To overcome challenges such as poor reservoir conditions, weak natural energy, low displacement efficiency, and insufficient single well production, CNPC has conducted years of research and operation to cost-effectively develop China's marginal reserves.
To develop the marginal fields economically, it is required to maximize single well production, recovery and reservoir sweep with minimum CAPEX and OPEX reasonably. The production enhancement is realized by 3 key technologies, namely, sweet spot identification, multi-layered 3D short spacing horizontal well pattern, and volumetric fracturing techniques. The cost reduction is achieved by the full life cycle practice of utilizing "large cluster, factory" well design and field operation, drilling prognosis optimization, integrated intelligent surface system, and unmanned operation.
CNPC cost-effective development mode is practical and successful, marginal fields characterized with heterogeneous, multi-layered oil-bearing intervals with poor continuity are being economically developed in China. By comprehensive geological study, fit-for-purpose technologies application, and geoscience-to-engineering integration, the fracture control degree of horizontal wells increased from 60% to more than 90% based on micro-seismic events, stimulated reservoir volume (SRV) increased by 46.8%, average cumulative oil production per well is more than 100 times than original production in the field. Fast and early cash flow is realized by minimum production facilities. The average drilling cycle is shortened by 61%, the surface facility construction time is reduced by 65%, and the average single well investment is reduced by 42%.
Sour Rated 10,000-psi System High Temperature Gas Development Wells: A Journey of Optimization in North Malays Basin While Sustaining the Nation Gas Demand
Authors: Jong Siaw Chuan , Aziz Khairil Faiz Abdul , Goo Jia Jun , Hiew Ronnie , Strickland Kenny , Hussin Arief , Yusof Khazimad , Macleod Andy , Yusoff Syukur , Chung Chay Yoeng , Liew Alex 
Published: May 2023

Abstract
High temperature, high carbon dioxide coupled with hydrogen sulfide contents, and rapid PPFG pressure ramp increase gas development well tends to cause high well capex for Operator. This well type typically needs high CRA material with at least a 10,000-psi rated system to complete. Offshore peninsular Malaysia’s North Malay Basin (NMB)’s deep reservoirs also fall into the described category.
This paper aims to share the optimization journey, applications, and learnings of the company’s H.T. sour-rated 10Ksi gas development wells through several phases, besides fulfilling the gas delivery need for the country. In addition, engineering and operational optimizations are identified to reduce the well’s time and cost without sacrificing the crew’s safety as the team focus.
The company wells engineering team applied Lean approaches encompassing the complete Plan-Do-Check-Adjust cycle to achieve the optimization. Well data usage, lessons learned, collaboration, continuity, and striving for continuous improvements are the key factors to ensure good optimization results. Fit-for-purpose drilling and completions equipment design and application, rig offline capabilities planning, wellhead dummy hanger plug design for offline cementing, intervention-less production packer setting device, offline annulus nitrogen cushion fluids displacement and other applications will be explained in the paper.
The paper explained the operational challenges, how and what optimizations applied to achieve excellent well performance compared to targets and previous campaigns. The wells team optimizations spread out from engineering to execution stages, including rolling out in-house talent of digitization and digitalization of well performance surveillance, in line with the industry's way forward. The recent campaign post optimization concluded with no safety incidents, below budgeted time and cost, low overall NPTs, and achieved first gas to meet the country's power generation demand. Open, collaborative, and proactive cross departments communications are the catalysts that contributed to the positive optimization journey's results.
An Incidence of Superior Mesenteric Venous Thrombosis in Mild COVID-19
Authors: Batra Sakshi , Nair Asha G , Syal Kirtimaan 
Published: May 2023

Abstract
SARS-CoV-2, an etiological agent of COVID-19, has been reported to inflict remarkably diverse manifestations in different subjects across the globe. Though patients with COVID-19 predominantly have fever, respiratory and constitutional symptoms, atypical presentations are becoming increasingly evident. COVID-19 may predispose to both venous and arterial thromboembolism due to excessive inflammation, hypoxia, immobilization, and diffuse intravascular coagulation in moderate to severe symptomatic cases. In this case report, we are reporting thromboembolic complications of COVID-19 in a mild symptomatic subject incidentally diagnosed with mesenteric venous occlusion with no abdominal symptoms. Early recognition of the abdominal symptoms, diagnosis, initiation of anticoagulants, and timely surgical intervention may improvise the outcome in a patient with COVID-19 Infection-induced mesenteric thrombosis. Superior mesenteric artery and venous thrombosis may lead to subsequent ischemia necessitating emergency laparotomy. Thus, the usage of low-dose anticoagulants in all the patients of COVID-19 irrespective of the categorization into mild, moderate, and severe COVID-19 disease should be considered.