bluuebunny/crossref_metadata_2025_split huggingface dataset:
Dynamic Process Optimization Using a Reduced Order Modeling Framework
Authors: Guddeti Ravikishan , Sankaran Sathish 
Published: November 2020

AbstractThe role of process operations in upstream, midstream and downstream is critical to fundamental business resiliency and production optimization in a dynamic environment. State-of-the-art technologies today rely heavily on human intervention to react to environmental changes. Building reliable physics-based models that are continuously updated are often challenging. For dynamic models, there are no practical solutions available. Prior attempts using adaptive system identification methods have been made to model transient processes, whereas these methods don't scale to large number of variables without extensive human design or guarantee accurate prediction of nonlinear processes.In this work, we propose to use a fast and hybrid, self-learning dynamic process modeling method from routine plant measurements that can be used for short-term forecasts, scenario modeling, process optimization and control.A reduced order modeling (ROM) method based on input-output dynamic mode decomposition has been adapted to develop a dynamic process model based on historical data collected from plant sensors. From time series data, the ROM method computes a set of modes, each of which is associated with a fixed frequency and decay/growth rate. Hence, the ROM models are both parsimonious and meaningful. We applied the proposed approach to an upstream multi-phase separation process. The inlet streams parameters and controller setpoints are used as inputs, the effluent streams variables are used as outputs and the intermediate process variables are used as states. The trained model was used to predict unseen inputs arising from changes in well alignment and slugging. In this sense, the ROM model simplifies the physical equations to a low dimensional form. The ROM model was then used to optimize process performance to reject inlet feed disturbances by adjusting the controller setpoints to reduce process variability.ROM method was used for moving horizon estimation of states and outputs, where the models provided very good predictions without any human intervention. Unlike black-box data-driven methods, the ROM method uses an interpretable approach that can be used to explain causal relationships. The optimization using the ROM model runs several orders of magnitude faster in closed loop and open loop modes, which can be used to evaluate several alternate scenarios. Common process disturbances such as inlet feed variations, loss of partial plant capacity, process upsets, change in target product rates and inventory are handled within the optimization framework.The proposed ROM method provides a unique and sustainable way to combine latest analytical techniques and physics to develop an explainable reduced order dynamic model for the process facility that can be effectively used to assist operations in optimizing performance. The derived hybrid model lends itself naturally to fast computation, as would be required for real time optimization and supervisory control such as application on an IoT edge device.
Enhanced Flow Profile Evaluation by Combining Acoustic Noise Log and Thermal Modeling in Complex Design Wells
Authors: Khalaf Al-Enizi Nawaf , A. Mohsen Saleh Batoul , Zaid Al-Sulaili Mousa , Al-Ghanim Wafaa , Morad Raed , Dashti Qasem , A. Clark Robert , Rajabli Nuran , Ayyad Hazim , Mehraj Majid , Tahar Mosbah Mohamed , Yakupov Alfir , Rourke Marvin , Ismail Moustafa 
Published: November 2020

Abstract
The evaluation of injection efficiency is an important component of monitoring oilfield development; it is often complicated by well design, such as horizontal wells, dual or triple completions, and the use of inflow control devices (ICDs). This paper demonstrates how standard production logging (PL) measurements can be improved with the addition of a high sensitivity noise log and a quantitative temperature analysis that is sensitive to flow behind the tubing and casing.
The latest generation noise tools are highly sensitive instruments that record data during multiple short duration stations. The tools acquire noise energy across a wideband spectrum ranging from 8 to 60,000 Hz. To improve interpretation and visualization, the noise data is separated into two displays: an ultra-low frequency narrowband spectrum (8 to 4,000 Hz) and a wideband spectrum (100 to 60,000 Hz). The implementation of high-resolution temperature data with thermal modeling enables improved multiphase flow profiling using the Joule-Thomson effect and near-wellbore temperature behavior in the surrounding formations.
The integration of the noise tool and temperature modelling enables the detection of very low rate fluid flow that is not otherwise detectable with conventional production logging tools (PLT) and the quantification of multiphase flow behind the pipe in multi-barrier completions.
This paper includes three case studies that demonstrate the integration of noise spectral data, temperature modeling, and spinner data. The first case is a single-string vertical injector well with separate injection at various layers. In this case, the well completion was challenging because the upper production interval was located behind the tubing. In the second example, the injection distribution changes under different flow rate conditions. At a high injection rate, the formation fracture pressure is exceeded; at low flow, the injection is below the fracture pressure.
These results demonstrate that it is possible to qualitatively determine all injection intervals by noise logging and to quantitatively estimate the fluid distribution by thermal modeling, which was used to plan successful well workovers and restore injection. This technology identified zones that were taking injection that other conventional tools failed to identify, significantly improving the understanding of water injection conformance in the super giant Burgan field waterflood.
Screening Artificial Lift and Other Techniques for Liquid Unloading in Unconventional Gas Wells
Authors: Ejim Chidirim , Xiao Jinjiang 
Published: November 2020

Abstract
Unconventional gas reservoirs are characterized by steep declines in reservoir pressure as production progresses. This results in frequent liquid loading problems, thereby reducing gas production to zero. To resume production, a means of unloading the liquid is required. This paper presents a review of artificial lift methods and other techniques that can be employed to unload liquids from these wells. A ranking is also presented to highlight the most preferred system for a target well.
A detailed review of liquid loading was performed for an unconventional gas well with 5.5-inch casing size. A total of 19 artificial lift methods and other techniques capable of unloading liquids in high gas content flows were investigated. These included gas lift (continuous, plunger-assisted, gas-assisted, etc.), positive displacement pumps (progressing cavity, sucker rod pump, etc.), electric submersible pumps (ESPs), jet pump, and other techniques such as supersonic nozzles, wellbore heating and downhole wet gas compression. Subsequently, a ranking of the different methods was performed. The ranking constraints included setting depth, operating temperature, production rate, gas handling limitation, and economics.
The results indicate that the gas lift related artificial lift methods (continuous, plunger-assisted, gas-assisted), plunger/dual stage plunger lift systems, ranked highest as a suitable means to unload liquids in unconventional gas wells. This highest ranked group was followed closely by the positive displacement artificial lift methods, such as sucker rod pumps and long-stroke rod pump methods. The method with the lowest ranking was the linear ESP. The other techniques with mid-ranking showed promising applicability, which may likely become viable in the future. For methods within the highest ranked bracket, the specific method finally selected by the application engineer will depend on existing infrastructure and the economics of adding existing equipment to implement the system.
This study highlights the results from screening artificial lift methods and other techniques for use in unloading liquids from an unconventional gas well. It brings together these different unloading methods in one paper and serves as a guide for field engineers to assess operational suitability for their unconventional gas wells. Such knowledge serves as a worthwhile first step toward planning and implementation of a means to unload liquids in a target unconventional gas well.
Physics Guided Machine Learning Significantly Improves Outcomes for Data-Based Production Optimization
Authors: Staff Gunnar , Zarruk Gustavo , Hatleskog Johan , Stavland Simon , McNulty Henry , Ibarra Roberto , Calen Nicholas , Hagemann Ola , Lawrence Chris , Selanger Torbjørn , Ayati Anis , Renstrøm Therese 
Published: November 2020

Abstract
Hydrocarbon production systems generate huge datasets, often with time series going back many years. However, much of the data may be obsolete due to changing reservoir conditions and modification of the asset, and there may be scant data close to optimal operating conditions due to the inadequacy of existing optimization tools. It is widely recognized that data science, artificial intelligence (AI) and machine learning can contribute significantly to the optimization of production operations, and there is a trend towards hybrid AI, which combines data science with traditional physics-based simulators to deliver added value. In our work we show how to make use of physical principles in feature engineering to improve machine learning outcomes. This squeezes additional value from a pure data-based approach while avoiding expensive, time-consuming and often inaccurate simulations. Our toolbox includes energy, mass and force balances; PVT data for production fluids; order-of-magnitude analysis; and dimensional analysis.
We illustrate the value of physics guided machine learning with three examples from production optimisation: First example shows a significant improvement in separator operation to achieve environmental limits for safe disposal of produced water using a root-cause analysis to identify bad actors in the production system and recommending operator actions to mitigate oil-in water issues. By physics modeling of key physical processes, such as choke-dispersion and separator efficiency, the predictions were greatly improved. Second example is a data-based VFM using physics-based feature engineering, outperforming a VFM based purely on measured data. Last use-case is a dynamic maximum separator flow capacity calculation that safely allows flow rates above static design limits.
We conclude that physics-guided machine learning can add tremendous value to digitalisation rollout across a wide range of production optimisation use cases, and speed up the decision process toward mitigation of production losses in complex industrial phenomena.
Combination of Radial Drilling Technology with Acid Jetting: New Approach in Carbonate Reservoir Stimulation
Authors: Bashirov Ayrat , Lyagov Ilya , Galas Ilya 
Published: November 2020

Abstract
A new solution to stimulate carbonate formations with bedding water or a gas cap was proposed. It is a combination of acid jetting and Perfobur radial drilling technology. Perfobur is a technology of a mechanical radial drilling with using of slim mud motor. The main advantages of the technology are controlled trajectory and the possibility of re-entry into the channels. After channel drilling, a jetting gun with four nozzles is run into the drilled channel. Acid is injected through these nozzles at a flow rate of 100 m/s (328 ft/s). In addition to the effect of dissolving the formation, the additional caverns, which in theory are up to one meter long, are washed out.
This technology was applied on the carbonate reservoir of Bashkirian stage, which is characterized by high heterogeneity and close location of the underlying water. Two adjacent well candidates with identical reservoir properties were selected. Acid fracturing was performed on well-A. Two channels 46 feet long each were drilled on well-B using the Perfobur technology. Then acid was injected through the jetting gun. In each channel, acid was injected at two points. In total, 48 m3 of acid were injected. The productivity index of well-A was 0.4 m3/day/atm and on well-B - 1.07 m3/day/atm. Watercut on well №1 was 28%, and on well №2 - 10%.The experience of combination Perfobur technology and acid jetting showed a number of advantages. Firstly, it is an increased acid penetration length. Secondly, controlled acid injection minimizes the risk of breakthrough into the water. Thirdly, it is high productivity of wells after the workover.
The novelty of this technology is in ability to deploy acids far out in the rock away from wellbore through the mechanically drilled holes with known depths and azimuths. Precise locations of drilled channels allow to stay away from contacting the water or gas zones. The different chemicals can be deployed through the channels to treat the wells with various challenges, for example the heave oils and others.
Resolution of Step Change in Vibration Levels of a Steam Turbine
Authors: Mr. Mohammed Ashour , Mr. Sherif Mekawey 
Published: November 2020

Abstract
This is a Steam turbine unit of three casings (HP/IP, LP1 and LP2) connected to a Generator through a rigid coupling. The rated power of the Generator is 660 MW. The unit was commissioned in 2014 and undergone a major outage in February 2018. During the outage, the generator stator windings were replaced and coupling bolts between all rotors were modified and replaced with new design (hydraulically fitted coupling bolts) to ensure smooth assembly/ disassembly procedure. After the maintenance, the unit was started up in March 2018 and it was running at baseload with normal vibration levels below alarm set points. It was reported that sudden increase of vibration at LP2 turbine was noticed on 16th July 2018 followed by another step change on 26th July 2018. Maximum recorded vibration levels reached 130 μm PP (Alarm 120 μm PP) at LP2 BRG (towards LP1 side)). While the machine was still under service and during the period of January to April 2019, several vibration step-changes events occurred with the highest vibration levels at LP2 Bearings (both ends). All these events were recorded only on DCS trends whereas there was no online diagnostics system to capture the dynamic behavior of the machine.
A check list of maintenance activities was carried out by the customer during the planned outage to ensure the machine integrity and rule out some suspects (coupling and hold down bolts tightening, alignment check between LP2 & Generator, bearings clearances check etc.).
A multichannel analyzer was hooked to collect the data after the outage. The machine was started up with the same vibration levels!! The review of data during the transient mode (Startup) and at steady state indicated a clear symptom of unbalance. Also, the historical review of DCS data for various step changes showed that the vibration changes were localized to LP2 turbine mainly.
This case study is focused on how the unbalance was detected using the transient as well as steady state vibration plots which was matching with the inspection findings of broken LP-2 rotor blades of last two stages.
Also, this case study is focusing on how the process data from DCS data helped in identifying the root cause for the broken LP rotor blades (abnormal extraction temperature, abnormal change of LP-2 differential expansion etc.) which helped in fixing the issue permanently.
New Approach to the Development of Gas Hydrate Accumulations Located at the Bottom of the Seas and oceans
Authors: Sabawon Aminullah , Iskender Rza-zade Samad Ali , Wazeri Samandar , Rovshan Akhundova Nargiz , Oqtay Bakshaliyeva Shirin , Muxtar Mammadov Ramil , Panakhov Rasim , Ghani Ahmad Ghani , Haleemi Salman , Khyal Muhammad Muhammad Tariq , Hamidov Elmir 
Published: November 2020

Abstract
Nowadays fundamental scientific researches and practical works are carried out worldwide to identify and use alternative sources and resources of energy carriers in place of oil and gas. In the world practice, to date, there is no technology for the development of gas hydrate accumulations and gas hydrate deposits located at the bottom of the seas and oceans. In this article, some methods of possible drilling of conditional wells are being discussed, that is, the creation of gas-hydrodynamic channels for lifting gas through the water column and decomposition of gas hydrates inside gas-hydrate clusters-strata. The possibility of creating double-barrel horizontal wells for supplying the heat carrier and inhibitor to the bottom hole zone for fracturing the gas hydrate and producing gas by a single well is considered.
Operation Room: A Key Component for Upscaling Robotic Solutions on Site
Authors: Munoz Jean-Michel , Bartoli Eric , Macrez Serge 
Published: November 2020

Abstract
Many oil & gas operators are now seeing unmanned facilities as the next frontier for safer operations and further cost reductions. However, these benefits only appear once the time between site visits is extended as much as possible. In its Next-Generation Facilities concept, Total is pushing the limits by targeting planned interventions only once a year.
Tremendous challenges must be tackled to make this concept a reality, from initial lean and robust facility design to management of operations. Subsea installations remain a source of inspiration on many levels, particularly for the handling of inaccessible installations using Remote Operated Vehicles.
As a result, Total has been very active in the field of autonomous ground robotics for many years with its ARGOS project. Many other oil & gas operators or robot manufacturers are also following similar paths. Consequently, more and more videos showing a robot on site, tele-operated or not, in the direct sight of a technician in charge of its control have been published. Improving robot capabilities, testing and learning how to handle these new tools is important and a very encouraging signal for the industry, but the integration and cost scaling effect are still to be demonstrated.
A step change in the experimentation has to materialize, since one robot alone on a site will not be able to achieve much. Moreover, the reproduction of the scheme ‘one robot/one technician’ is not optimal when numerous robots are involved.
Therefore, the addition of a new component in the field architecture in charge of bridging robot site activities and the off-site Control Room is seen as essential to rise to the next level and meet the requirement of the new operating philosophy: continuous operations with multiple robots working simultaneously on an unattended site. Total calls this new function the "Operation Room". In Total's concept, the Operation Room is located next to the existing Control Room which would also become remote. From the Operation Room, robot panel operators, very much like air traffic controllers, will remotely supervise and coordinate the robots that will autonomously perform the very activities that the field operators once used to do on conventional facilities, from routine operation and maintenance tasks to emergency response.
This article will give an overview and some examples of how Total has matured the design of its Operation Room concept, including a description of the key elements that have to be addressed to manage a fleet of autonomous robots in an efficient and safe manner from a remote location.
Safety Competence Assessment SCA
Authors: Bosco Massimo , Selvaroli Giampaolo , Gallo Gabriele , Gioia Giuseppa 
Published: November 2020

Abstract
The analysis done on actual and direct experience on the majority of past events occurred within the Company, in particular fatalities or serious injuries, showed that among the main contributing factors, the two most recurrent are inadequate supervision and incorrect perception of actual exposure to operational risks.
Supervision shall be ensured by all functions in charge of supervising and coordinating the individual activities as well as a broad supervision of the whole operative site.
The incorrect perception of risks is usually caused by a lack of training and lack of knowledge of minimum basic principles on how to execute an activity.
If supervisors are lacking in these aspects, their leadership and the transfer of knowledge to front-liners is ineffective.
Therefore, Eni Upstream developed a simple tool with the aim to determine the level of safety knowledge and competencies of all supervisory personnel, thus identifying all safety areas that might need a specific, customized, and effective training approach that could fill competencies gaps and strengthening safety supervision at work site. Increased competence would, in turn, improve the perception of risk.
The "Safety Competence Assessment - SCA" is a web-based, two-phase tool that allows users (supervisors involved in the program) to assess their knowledge and competencies in a number of safety aspects ranging from safety leadership to basic content of safety procedures, HSE Integrated Management System (HSE IMS) principles, SIMOPS and emergency response.
During the first stage, the selected employees (or candidates hereafter) are confronted with open and closed questions that allow for the customization of the answers based on the working environment they are assigned to at the time of the assessment.
The second stage requires the involvement of HSE Managers and HR representatives to review all answers during a face-to-face discussion with the workers. This stage is aimed at the final consolidation of the user's assessment results (with possible amendments and incorporations by the Managers) and the identification of customized training paths that are facilitated by the HSE function.
Through the SCA tool, all Managers have access to valuable statistical information that could effectively help in determining areas of strengths and areas of improvements of single individuals as well as homogeneous groups or specific sites, further enhancing the effectiveness of the training that will be provided to the workforce and ultimately supervisory competence and knowledge.