bluuebunny/crossref_metadata_2025_split huggingface dataset:
Subsea Multiphase Flow Meter Measurement Performance Assurance with an Applied Data Validation and Reconciliation Surveillance Methodology
Authors: Graham Emmelyn , Castillo Libsen , Yi John , Mooney Tom , Jadot Timothy , Amin Amin 
Published: April 2022

Abstract
Measurement performance assurance for subsea multiphase flow meters (MPFM) can derive motivation from several sources of technical and/or business need, ranging from well surveillance to flow assurance monitoring, to production allocation among commingled sources of varying royalty, taxation, or ownership. Often, the more sensitive the subsea MPFM measurement is to a technical or business driver the more difficult it can be to initiate a comparison to a reference measurement or reference fluids such as topside measurement. Thus, providing assurance for subsea MPFM measurement performance requires a coordinated effort of MPFM performance surveillance – a combination of data and activities that can enable continuous indication of MPFM measurement performance, with or without periodic comparisons with reference measurements. However, utilizing MPFM performance surveillance information – which can come from a multitude of sources – can be confusing and potentially misinformative if a rigorous methodology to systematize the information isn't applied. It was in this context that a surveillance methodology using data validation and reconciliation (DVR) was chosen to leverage the disparate surveillance information available and provide quantitative measurement performance assurance results for a subsea MPFM.
DVR was applied to assess the performance of a subsea MPFM incorporated within a subsea/topside field. Multiple sources of surveillance data and information were utilized in the application including the subsea MPFM, independent water-liquid ratio measurement, pressures and temperatures throughout the network, fluid properties, inlet separator flow measurements, and well test results.
Three main objectives were established to demonstrate efficacy of the applied DVR methodology for subsea MPFM measurement performance assurance: 1) quantified DVR results for direct MPFM validation via well test; 2) continuous DVR condition-based monitoring (CBM) of the subsea MPFM within a defined subsea/topsides topology during normal operations, and 3) DVR-derived uncertainty estimates for the subsea MPFM. Several case studies using DVR surveillance are presented to address subsea measurement performance assurance through direct validation, CBM and uncertainty estimation. Each case study describes the workflow and detailed explanations for the steps taken in the DVR surveillance methodology.
Implementation challenges and lessons learned are also presented, along with a strategy for sustained subsea MPFM measurement performance assurance using a DVR-based surveillance approach.
Understanding ESP Performance Under High Viscous Applications and Emulsion Production
Authors: Pastre Luiz , Biazussi Jorge , Monte Verde William , Marins Jean , Melchuna Aline , Cowie Mark , Vergara Luis , Navarro Ivamberg , Lemos Daniel , Alfonzo Antonio , Ramos Leudy , Bannwart Antonio 
Published: April 2022

Abstract
Although being widely used as an artificial lift method for heavy oil field developments, Electrical Submersible Pump (ESP) system performance in high viscous applications is not fully understood. A miscomprehension of challenges and equipment performance in such conditions might lead to operation inefficiencies and equipment failures. This paper presents results of single-phase and multiphase tests performed by University of Campinas (UNICAMP). It also presents operation data, lessons learnt, and failure examples gathered over 10 years of ESP operation in Peregrino field which is a heavy oil, high viscous oilfield offshore Brazil operated by Equinor.
Affinity laws commonly used for ESP simulations don't hold true for high viscosity applications. Hydraulic performance of centrifugal pumps is affected by fluid parameters like viscosity and density; operation parameters such as flow rate and rotational speed; and specific stage design characteristics. To determine degradation in head and efficiency as well as power requirement increase in viscous applications, Equinor performs one-phase high viscosity flow loop test to qualify each stage type prior to deployment in Peregrino field.
For the qualification of ESPs, single phase qualification tests are performed using mineral oil with viscosities specifically chosen to cover the viscosity range of the specific field. Each stage type is qualified using a prototype with reduced number of stages due to flow loop limitations. Qualification tests for the Peregrino field confirmed that affinity laws are not accurate for high viscous applications and provided important insights regarding pump performance that are used in equipment specification and system surveillance.
The UNICAMP research team has designed and performed multiphase flow tests to evaluate emulsion formation inside centrifugal pump stages and effective viscosity behavior. Phase inversion phenomenon investigation was also included in studies. Studies performed using a prototype stage allowed visualization and evaluation of oil drops dynamics inside the impeller in different rotational speeds. Two phase flow loop tests investigated the shear forces influence in effective viscosity inside pump stages and downstream pump discharge. Phase inversion phenomenon was also a point of great interest during the studies. Data gathered during lab tests was used to evaluate accuracy of mathematical models existing in the literature when a centrifugal pump is added to the system. Hysteresis effect associated to catastrophic phase inversion (CPI) was confirmed and replicated during flow loop tests. Such behavior can be related with operation parameters instabilities and equipment failures noticed in actual application in Peregrino field which are also presented in this paper.
Transforming Asset Maintenance and Optimisation Through Autonomous Operations
Authors: Pierson Nicholas , Clarke Richard , Mikhailov Oleg 
Published: April 2022

Abstract
Autonomous Operations is about utilising the latest available fit-for-purpose technology in operations, maintenance, inspection, and asset optimisation. It involves collecting operating data such as visual, thermal, low- and high-frequency acoustic, FLIR (Forward Looking InfraRed), and gas-sensing through devices mounted on autonomous robots or drones, possibly mixed with stand-alone fixed devices.
This "mobile sensor" approach is ideal for existing infrastructure where adding enhanced sensing capabilities with an IoT solution is cost prohibitive. It is flexible: if a site is modified, the robots can be given a new route to monitor. It is also future proof as sensors can be easily upgraded as technology advances.
Autonomous robot inspection is enabled by a software platform designed for full processing "at Edge" as a typical robotics inspection generates tens of gigabytes of data per hour. Data pre-processing, construction of detailed 3D temperature, vibration amplitude and gas concentration maps, identification of anomalies, their classification by criticality and communication to operators is done by computers at the facility.
Time lapse analysis is used to process the data either in-situ, or remotely, depending on site connectivity. Reports are automatically generated indicating whether the site is functioning within normal working conditions, or an anomaly has been detected. The electronic reports contain the 3D model and are viewable on mobile devices providing the field engineer with detailed diagnostic data literally at their fingertips.
The process builds and maintains the living digital twin without having to expend engineering hours to update 3D models. This process not only removes the need for people, which reduces cost and safety risk, but also improves reliability by increasing the available data set and reducing inspection intervals. By utilising data analytics and artificial intelligence, the anomalies detected can be risk ranked, prioritised and scheduled based on a latest acceptable completion date.
This technology has been tested through a pilot program at an activated carbon plant in Wyoming during the summer of 2021. In this paper, we will present a case study of this pilot, covering installation, data acquisition and processing, as well as the key challenges and results.
Development of Tethered Flying Robots with PAUT Capabilities for C-Scan and In-Service Inspection Mini-Crawler/Uav: Marsupial Robotic Approach
Authors: Tavakoli Reza , Kamalinejad Pouya 
Published: April 2022

Abstract
Avestec has successfully developed proprietary contact-based flying robots (SKYRON™) for ultrasonic (UT) A scan measurement of metallic surfaces. The technology has been successfully validated with many asset owners in onshore and offshore industrial campaigns.
Although the flying contact-based robot can easily access most asset surfaces to perform inspections, it has some limitations when it comes to challenging and dense spaces. Such shortcoming is exasperated specially for pipe inspection in offshore environments. Pipes are usually located in the vicinity of one another or in close proximity to walls or other structures, which makes it practically impossible for an unmanned aerial vehicle (UAV) to reach to every side of the pipe and carry out circumferential (3/6/9/12) measurement as needed.
In order to enhance the advantages of contact-based aerial robots and overcome the aforementioned limitations, a marsupial robotic methodology has been followed by means of combining the proprietary contact-based UAV and a custom omni-directional mini crawler in a collaborative robotics fashion. An advanced marsupial connection between the two robots both in terms of mechanical (e.g., carrier/passenger roles) and control mechanism (e.g. master/slave roles) and versatility of the task deliveries can potentially introduce a lot of advantages over a single flying robot for asset inspection.
In addition, Phased Array Ultrasonic (PAUT) sensory package has been integrated into the marsupial robot to expand NDT capabilities for inspection including thickness measurements, corrosion mapping, defect detection (e.g. such as cracks, voids, and pits caused by corrosion), weld inspection and many more.
Correlation Pattern Exploration of Wave Energy Density Hotspot Distribution and Hurricane-Induced Wave in Gulf of Mexico
Authors: Gu Chengcheng , Li Hua 
Published: April 2022

Abstract
The activities in the Gulf of Mexico are thriving with a considerable number of oil and gas platforms operating in this area. Wave power can provide a substantial portion of clean power to substitute for the inefficient gas turbines used on the platforms. Wave power density (wave energy flux) is one of the ways for directly assessing the potential and available wave power. The task of a wave energy capture device is to effectively capture the wave energy flux. The average wave power density is generally between 20 kW/m and 65 kW/m in the Gulf of Mexico. During tropical storms or hurricanes, the theoretical wave power density could reach 1,600 kW/m. However, higher wave height and period could damage the energy capture devices. This project explores the correlation pattern between available wave power density hotspots and hurricane-induced wave distribution within 10 years (2010-2019) using a deep convolutional neural network.
The correlation pattern was explored and validated by applying meteorological data in the Gulf of Mexico area from the NOAA WAVEWATCH III system. A wave power hotspot was defined as an event when wave power density over a certain threshold during a period of time in a predefined location. The distribution of wave power hotspots has the segmentation threshold on wave power depending on the wave energy converter, location, wave height and wave period. The meteorological data from WAVEWATCH III was visualized as images of wave power density in 3-hour time steps, which were used for wave power density hotspot identification, classification and localization through a deep convolutional neural network.
With the distribution of wave power density hotspots along with the coordinates attached through matching the local wave and hurricane-induced wave conditions and the GIS mapping support, the project was able to reveal the impacts of hurricanes based on pattern recognition between the wave power hotspots distribution and hurricane-induced wave track distribution. Meanwhile, the comparison of the wave power density hotspot distribution with extreme weather conditions and under the regular circumstances was analyzed. The results could also provide feedback to and support wave energy harvesting or hurricane forecasting and harvesting.
Improving Erosion Wear Life of Completion Equipment in High Flow Rate Conditions by Numerical Design Optimization for Influx Equalization
Authors: Chochua Gocha G , Kumar Amrendra , Gurses Sule F. , Rudic Aleksandar , Dikshit Ashutosh , Sinha Nityanand 
Published: April 2022

Abstract
The durability of sand screen completions is essential to longer well life, especially for high rate wells with sand screen erosion concerns. An excessive fluid flow enters the conventional screens near the heel or high permeability/fracture zones, causing premature sand control loss. The high rate screens with a simulation-driven approach address this concern by achieving the annulus-to-tubing flow equalization and reducing the influx spike near the heel or high permeability/fracture zone.
The study presents a comprehensive modeling approach including a single-well model workflow for initial production screening along the wellbore with different reservoir conditions, which provides input to the novel multiscale 3D-2D-3D computational fluid dynamics (CFD) modeling technique to design or validate high-rate completions for the specific operating conditions. The principle of operation is based on equalizing the production influx along the screen by achieving the distributed inflow control devices (ICD) effect on the basepipe. The modeling approach was used to compute maximum local velocities in the vicinity of the screen near the heel under 39,000 RB/D of ultra-light oil production in one case and 200 MMscf/D of gas production in another.
The design methodology is validated through erosion and sand retention tests performed to verify the screens’ correct slot/gauge size. The high-rate completion case history consists of seven deepwater wells with chemical tracers. The novel design and the modeling methodology are validated by physical erosion tests and verified through field installations.
Getting Serious with Net-Zero: Implementing Large-Scale Carbon Capture and Storage Projects in ASEAN
Authors: Lau Hon Chung , Zhang Kai , Bokka Harsha Kumar , Ramakrishna Seeram 
Published: April 2022

Abstract
As a region, the ten nations of ASEAN emitted 1.65 Gtpa CO2 in 2020 from the combustion of fossil fuels. Analyses reveal that ASEAN's renewable energy resources are low to moderate and unevenly distributed geographically. Furthermore, there are substantial sustainable issues related to hydropower and bioenergy. The current rate of addition of new renewable power capacity is too slow to allow ASEAN countries to achieve net-zero by the middle of the century. More tools, in addition to renewable energies, will be needed. It is found, however, that carbon capture and storage (CCS) is a key enabling technology to decarbonize ASEAN's fossil-fuel power and industrial plants and to produce blue hydrogen needed to decarbonize the industry sector. Furthermore, results of CO2 source-sink mapping exercises show that there is enough capacity in major sedimentary basins in ASEAN to permanently store two centuries of anthropogenic CO2 emission. Six first mover large-scale CCS projects in ASEAN with potential to mitigate up to 300 Mtpa CO2 from Singapore, Indonesia, Malaysia and Thailand have been identified. Furthermore, the steps needed to implement these CCS projects are also discussed.
Design of a 750 °F, 15 K packer for Enhanced Geothermal Systems, Supercritical CO2 - Sequestration and SAGD: Energy Transition Through Technology Synthesis
Authors: Roy Ting , Ben Naceur Kamel , Singh Manjinder , Markel Daniel , Harp Leonard , Ardic Hifzi , Wilkinson Christian , Roy Indranil 
Published: April 2022

Abstract
Several technology building blocks are required for the growth of geothermal energy to match what is needed to enable the energy transition. One key technology required in this field is a reliable packer that can withstand the extreme environments frequently seen in geothermal wells: elevated temperatures (750°F/400°C); high differential pressures (up to 15K psi); and extremely corrosive fluids.
The authors present a concept which is thought to offer a promising solution to this challenge. It builds upon the wealth of experience obtained by operators designing packers for the oil and gas wells and couples this with advancements in materials processing technology in elastomers, composites, and metals.
The presented concept uses the sealing advantages that elastomers are known to offer, with a compound specifically designed by a strategic partner. This elastomer is then surrounded by a layer of flexible gel-insulation of extremely low thermal conductivity to shield it from the intense heat seen in geothermal wells. It is predicted that the elastomer core will see temperatures no higher than 400°F when the surrounding environment is at 750°F. The system is then encased in a Grain Boundary Engineered (GBE) nano-metallic flexible skin material to prevent contact with corrosive fluids. Though the elements are the greatest challenge, the other components of the packer design are also specially designed with material processing techniques tailored to both enhance mechanical properties and corrosion resistance.
The technology behind the design is detailed and has been proven. The integrated concepts will be further tested at subcomponent level to show their merit, before integration into a full system for qualification to 750°F, 15K psi.
Flow Pattern, Pressure Gradient Relationship of Gas Kick Under Dynamic Conditions
Authors: Obi Chinemerem Edmond , Falola Yusuf , Manikonda Kaushik , Hasan Abu Rashid , Rahman Mohammad Azizur 
Published: April 2022

AbstractThe warning signs of possible kick during drilling operation can either be primary (flow rate increase and pit gain) or secondary (drilling break, pump pressure decrease, and stroke increase). Likewise, the drillers rely on the pressure readings at the surface to have an insight into in-situ downhole conditions while drilling. The surface pressure reading is always available and accessible. However, understanding or interpretation of this data is often ambiguous. This study analyses significant kick symptoms in the wellbore annulus while drilling/circulating.We have tied several observed annular flow patterns to the measured pressure, and flow data from the surface during water-air, and water-carbon dioxide complex flow. This is based on experiments using a 140 ft high tower lab, with a hydraulic diameter of about 3 in. The experiments have been carried out under dynamic conditions to simulate circulating drilling mud from the wellbore. We used both supervised and unsupervised learning techniques for flow regime identification and kick prognosis. These include an Artificial Neural Network (ANN), Support Vector Machine (SVM), K-Nearest Neighbor (KNN), Decision Trees, K-Means and Agglomerative Clustering. All the machine learning techniques used in this work made excellent predictions with accuracy greater than or equal to 90%. For the supervised learning, the decision tree gave the overall best results with an accuracy of 96% for air-influx cases and 98% for carbon dioxide influx cases. For the unsupervised learning, K-Means clustering was the best, with Silhouette scores ranging from about 0.7 to 0.8 for the rate data clusters, and 0.4 to 0.5 for pressure data clusters. The mass rate per hydraulic diameter and the mixture viscosity also resulted in the best type of clusters. This is because this approach accounts for the fluid properties, flow rate, and flow geometry.The estimation of the influx size and type is highly dependent on the duration of kick and the overbalance kick influx pressure. The quantity of the mass influx significantly controls the flow pattern, pressure losses, and pressure gradient as the kick migrates to the surface. The resulting turbulent flow after the initial kick (After Taylor bubble flow) varied with duration of kick, average liquid flow rate, influx type, and drilling scenario. Surface pressure readings can be tied to flow regime to better visualize well control approach while drilling.This works provides an alternative and easily accessible primary kick detection tool for drillers based on measured pressure responses at the surface. It also relates this pressure data to certain annular flow regime patterns to better tell the downhole story while drilling.
Completing the Production Logging Puzzle Through Data-Driven Integrative Analysis
Authors: Bari Abdul , Khan Mohammad Rasheed , Zubair Talha , Atiq Mustafa , Shahid Muhammad Hasan , Awase Azar , Tanveer Muhammad Sohaib , Sarili Mahmut , Panhwar Aadil , Ahmed Qazi Ismail , Arsalan Ullah Hafiz Muhammad 
Published: April 2022

Abstract
In response to the highly volatile industry situation post-Covid19, E&P companies are abandoning or delaying exploration projects. It is anticipated that to meet growing energy demand in the future, it would require robust reservoir surveillance to improve individual well productivity. Production logging plays a key role in developing reservoir flow characterization and its integration with multiple data sources can allow for a holistic well dynamic description, leading to production enhancement on a well-by-well basis. Multiple case studies are presented in this work that propose a data-driven, integrated workflow which combines production logging data with plethora of under-utilized data sources to constitute an investigative analysis to solve water production conundrum.
The workflow developed as part of this work incorporates three distinct stages. Firstly, an in-depth data analysis is conducted utilizing all historical production data/trends and well events to link it with water production as each will have its distinct impact on the type of production logging tools/techniques that would be deployed on the subject well to achieve job objectives. Secondly, real-time production logging is conducted to ensure job objectives as defined in stage one is being met which is crucial to the resultant wellbore zonal profiling. Finally, once the production log visual representation is created, various other open-hole petrophysical and cased-hole well integrity logs are analyzed to make sense of the derived results and suggest reasoning to the state of the reservoir production pertaining to producing water. The case studies discussed in this paper include the use of petrophysical logs, MDT formation testing data, ultrasonic cement evaluation logs, and production log time-lapse analysis.
Integrating various data sources with production log analysis allowed for establishment of water production sources in the various case studies discussed. In one case, production related ambiguity was resolved by integrating formation testing and production logging data together. Another analysis revealed channeling behind the casing through a micro-channel in the cement which caused water to encroach shallow perforations. This highlighted the importance of azimuthal cement logging to detect small channels even when omni-directional sonic measurements are depicting good cement placement. Finally, through integrated time-lapse production log analysis, it was discovered how wellbore dynamics were changing chronologically.