bluuebunny/crossref_metadata_2025_split huggingface dataset:
Unique Development Plans for UAE Nationals in Dolphin Energy
Authors: Al Maainah Meera Ahmed 
Published: October 2022

Abstract

People Development
Breakthrough Strategies for Staff Development

Objectives/Scope: Please list the objectives and/or scope of the proposed paper. (25-75 words)
The purpose of this paper is to highlight Dolphin Energy's workforce development programs. Striving to develop and support employees is one of the company's top priorities. Hence, multiple strategies have been developed and put in place to focus on employees’ development to meet the company's growth requirements and achieve long-term success.

Methods, Procedures, Process: Briefly explain your overall approach, including your methods, procedures, and process. (75 -100 words)
Dolphin Energy's Talent Acquisition and Learning Department has designed and customized comprehensive development plans to ensure employees have the necessary competencies to perform their work safely, efficiently, and effectively.
The process begins with a thorough analysis of the employee's performance, experience, and education background, in addition to their roles and responsibilities. Following this analysis, a customized career development plan is created to ensure the competency of the employee within their respective role.
The company's current development plans are: Individual Development Plans (IDPs)Career Enhancement Plans (CEPs)Open Development Plans (ODPs)Performance Improvement Plans (PIPs)

Results, Observations, Conclusions: Please describe the results, observations, and conclusions of the proposed paper (100-200 words)
Development plans are tools to develop and prepare employees to excel in their career and hold higher positions in the future. With this in mind, the company is proud that its executive and senior level employees have completed customized development plans, which proved to be successful tools in their career progression.
The company implements high standard development plans to support its employees’ development and growth. These plans also help develop fresh graduate associates and prepare them to be fully qualified job holders by providing them with knowledge, experience and required competencies within a two year time-frame.
Dolphin Energy has succeeded in promoting UAE nationals to senior level positions through multiple career development programs, where currently the majority of UAE nationals hold senior level positions within the organization.

Novel/Additive Information: Please explain how this paper will present novel (new) or additive information to the existing body of literature that can be of benefit t and/or add to the state of knowledge in the petroleum industry. (25-75 words)
As the Oil and Gas industry is always evolving, it's important to maximize employees’ knowledge and development within their respective fields.
This paper will present details and highlight benefits of our development plans, supported with statistics on how successful they are. In addition, this paper will shed light on major milestones and advantages of our career development programs, as well as best practices which may be of interest to other business partners.
Facility Energy Strategy Development and Process Optimization: A Case Study from Saudi Aramco Khurais Facility
Authors: Bajuaifer Hatem A. , Khan Ashiff , Al Zahrani Abdullah A. 
Published: October 2022

Abstract
This paper covers an energy optimization study conducted by Saudi Aramco to maximize energy efficiency and minimize GHG emissions via onion peeling method to analyze the system from outside to inside by segregating the system to three essential layers in Khurais hydrocarbon facility to achieve operational efficiency and environmental sustainability.
This paper is intended to:
Share the optimization strategy and how it can be replicated. Presents the results of this optimization study along with operating modes energy and emissions data and graphical representations. Highlights how this approach enhanced the overall facility operating efficiency.
The onion peeling approach allows to achieve maximum efficiency by conducting sensitivity analysis on each layer's parameters to achieve the optimum operating mode for minimizing power bill (i.e., maximizing power generation), minimizing scope 1 and 2 emissions, minimizing sales gas consumptions.
The aforementioned approach was done based on the following strategies:
Maximize power generation in facility whenever reaching the threshold that makes power generation better than importing from grids in term of GHG emissions and EI. Maximize waste heat recovery for power and steam generations. Minimize recycling in major energy consuming equipment in the facility. Maximize major energy consuming equipment efficiencies through load management optimizations. Follow operating levels concept rather than optimum mode concept by ranking all possible modes in hierarchy and challenge the system to achieve better operating level (i.e., lower level number)
Figure 1 Shows the model's layer and summary
Post-Implementation of the defined strategies and following operating level concept, several initiatives introduced to achieve lower operating levels with energy savings and GHG (scope 1 and 2) reductions realized.
Finally, this study concluded that to achieve better operational mode environmentally and economically, it is recommended to analyze the overall system from outside to inside as multiple layers, to capture opportunities in the system. Such an approach shall be followed after defining the needed strategies, depending on the facility's design, demand and operating conditions.
Multiscale Oil and Gas Methane Emissions Data: From Measurements to Mitigation
Authors: Zavala-Araiza Daniel , Schwietzke Stefan , Hamburg Steven 
Published: October 2022

AbstractMethane (CH4) is a potent greenhouse gas, responsible for at least a quarter of Today's global warming. Thus, reducing CH4 emissions from global oil and gas infrastructure represents a key opportunity to significantly slow the rate of climate change—with several recent studies highlighting that readily available and cost-effective technologies can reduce a large fraction of current emissions from this industry. Operators have announced ambitious pledges to reduce CH4 emissions from the oil and gas supply chain. For these targets to be effective, it is critical to improve the understanding in terms of how much methane emitted, identify where it is being emitted, and to empirically track progress as mitigation strategies are implemented. Here, we have synthesized results from recent multi-scale scientific studies across geographies (i.e., North America, Europe, Australia), highlighting the role of empirical data in improving emission reporting, and guiding mitigation action. We illustrate how emissions data collected at different spatial and temporal scales can be integrated to provide a clear characterization across the different segments of the oil and gas supply chain. Measurement-based approaches are now being successfully implemented, and the integration and reconciliation of data at different scales can provide useful information to reduce the uncertainty in terms of magnitude and location of emissions. As more operators incorporate these approaches and compile improved emissions data, it will be plausible to improve equipment and system design, perform root cause analysis and reduce the frequency of large emission events. Measurement-based CH4 emissions data is essential to an efficient and effective implementation of CH4 mitigation strategies. This paper highlights how a diversity of robust measurement approaches can be deployed in concert—further identifying mitigation opportunities and tracking changes in emissions over time.
Could Petroleum Sludge be Used to Produce Biomethane as a Renewable Energy Source?
Authors: El Achkar Jean H. , Husain Abrar Ben , Alotaibi Nadeen , Alhaddad Noor , Alamgir Taiyeba , Alshamali Husain , Alshammari Yousef , Almuhanna Mohammad , Albekheet Abdullah , Alenezi Khaled , Alsaba Mortadha T. 
Published: October 2022

AbstractDuring the exploration, production, and refining of crude oil, as well as the effluent treatment facilities of refineries, the petroleum sector produces a substantial quantity of sludge. This review offers in-depth insights into the methods used to treat and dispose of petroleum sludge today. It also explores the possibility of valorizing such waste while converting it to a sustainable energy source using anaerobic digestion technology.Aside from health concerns, the random disposal of untreated petroleum sludge causes land pollution, water pollution, and ecosystem devastation. Consequently, the adequate treatment and disposal of this sludge provide a substantial challenge to the oil and gas sector, which has become a worldwide concern. Various methods used, such as incineration, oxidation, ultrasounds, stabilization, and landfarming will be presented. On another note, this review imparts a new insight into the possibility of generating biomethane from petroleum sludge. It also investigates its anaerobic co-digestion with food waste and other byproducts, promoting the transition toward a circular bioeconomy.Most conventional sludge treatment methods are unstainable and insufficient to deal with a large amount of generated sludge. Ultrasonic treatment, solvent extraction, and incineration are all expensive processes. Moreover, incineration contributes to air pollution, whereas landfarming and degradation are inefficient and contribute to heavy metals leaching. Considering those disadvantages, creating a greener and more cost-effective approach to securely disposing of these hazardous materials is vital. The bacterial degradation of any substrate without oxygen is known as anaerobic digestion (AD). It is one of the highly efficient systems for recovering bioenergy from small to large sizes. Sludge treatment in anaerobic digesters yields biomethane, a substitute for natural gas, recovered while microorganisms reduce the organic matter in the sludges. However, the sludges have poor anaerobic degradability, and the presence of heavy metals might interfere with anaerobic microorganisms' ability to function. Suitable pretreatment of sludge and its co-digestion with organic wastes such as food waste can be an option to solve the above problems, tackling at the same time the food waste management issues alongside petroleum sludge management.
DMXTM Demonstrator for CO2 Capture: First Results of Experimental Campaign
Authors: Salais Clément , Streicher Christian , Albarracin-Zaidiza David , Carlier Vincent , Bachaud Pierre , Petetin Bernard , Lacroix Maxime , Santos-Moreau Vania 
Published: October 2022

Abstract
3D Project, standing for DMX™ Demonstration Dunkirk, is a European funded project to demonstrate an innovative CO2 capture process at semi-industrial scale: DMX™. The 11 partners of this project gathered their forces to demonstrate the capture process and to study the CCS chain (capture, transport and Storage) allowing to decrease the CO2 emissions from industries (steel mills, refineries, waste-to-energy plants etc).

Objectives/Scope
Carbon capture is due to play a fundamental rote in achieving Net Zero Emissions scenario in 2050. Amine scrubbing is considered nowadays a suitable technology for the sectors with large-fixed CO2 emissions due to its robustness, adaptability, and capability of producing a highly concentrated CO2 stream, suitable to be transported. Four main challenges need to be addressed for the industrial deployment of this technology: process footprint reduction, process energy penalty reduction, solvent and VOC emission limitation and long-term process stability. Some challenges can be addressed through solvent formulation and process configuration. IFPEN has developed a novel solvent and process configuration, the DMX™ process, showing promising results in terms of energy consumption and process stability. This work aims at the demonstration of the DMX™ process by means of a set of experimental campaigns with a demonstration plant treating real gases in the frame of H2020 funded project called 3D (grant agreement n° 838031).
The demonstration plant is installed in the Steel Mill of ArcelorMittal Dunkirk and will absorb CO2 present in the blast furnaces gases. The design and construction of the unit is realized under the supervision of Axens. The demonstration plant is operated by a mixed team from IFPEN and TotalEnergies.

Methods, Procedures, Process
The DMXTM technology is a CO2 chemical absorption process involving a demixing solvent. This process consists in the continuous operation of two sections: 1) the absorption section, in which the CO2 is captured by the lean solvent, and 2) the regeneration section, in which the rich solvent is thermally stripped from the CO2 and recirculated to the absorption section. The particularity of this process is the solvent demixing in the regeneration section. Only the CO2 rich aqueous stream is thermally stripped. In addition, since the regeneration of the solvent can be performed at a relative high temperature (150-160 °C), the DMX process produces a relatively high-pressure CO2 effluent (5-6 bara). Hence, energy and investment cost savings are expected to be obtained.
Comprehensive Design and Diagnostic Approach for Horizontal Completions in Carbonate Environment
Authors: Alobaid Hashem , Khan Abdul Muqtadir , Almulhim Abdulrahman , Hansen Jon , Kabannik Artem 
Published: October 2022

Abstract
The development of tight carbonate reservoirs is moving towards drilling and completing wells with longer laterals. This leads to challenges of longer completion time, high number of fracturing stages, longer interventions, and eventually higher costs. Design cycle implementation is required to devise an engineered strategy to mitigate these challenges.
Lateral landing was conducted based on the cross-section grid consisting of two offset horizontal wells completed with up to 13 fracturing stages. A longer lateral greater than 6,000 ft was drilled compared to 4,000 ft in offset wells to get the production potential. With a strategic design involving engineered chemistry and numerical simulation models, a cluster design was devised to reduce to stages. A mathematical algorithm employing tube wave velocity calculations was used as a diagnostic to ensure diversion success after each stage.
The horizontal lateral was landed traversing the prolific layer. Stage reduction sensitivity simulations were conducted using multiphysics numerical models and novel beta factor workflows to evaluate the extent of stage reduction. The design was extended to plan for five stages only, with increased number of perforation clusters per stage. The reliable diversion chemistry utilized was accompanied by a revised perforation length as dictated by the beta factor workflow. A total of 39 clusters, 2-ft each, were distributed across 6,000 ft with four mechanical isolation plugs. A novel nonintrusive diagnostic model built on mathematical fundamentals of wave travel time was used with a Bayesian statistical approach after each diversion pill placement to ensure fracture fluid entry points and enough coverage in each stage. The high fluid viscosity and operating pumps during the water hammer events resulted in low signal-to-noise ratio in the input data. To overcome these limitations, the water hammer events were processed with a combination of two newly developed algorithms: predictive deconvolution and comb filter, which produced more robust results than the traditional approach. Consequently, the well production was analyzed to show equivalent or higher productivity index compared to the offset laterals with up to two times higher stage count.
The paper presents a unique example in which an experiment was fully engineered from design to evaluation and monitored with reliable diagnostics. This example gives a blueprint for future completion designs.
Digitalization Deployed – Enabling Sustainable Operations with Autonomous Well Control
Authors: Schnabl Helmut , Wimmer Helmut 
Published: October 2022

Abstract
Hydrocarbons have powered economic growth for 150 years, but their emissions are destabilizing the earth's climate. Now that the atmospheric impact of fossil fuels is widely recognized, the sector is under increasing pressure. Policy makers, investors, and society are pressing for change, threatening operators’ license to operate.
Operators have responded with strategic convening and conspicuous investments in innovation and diversification. Yet they have barely begun to address the 4.1 GtCO2e of emissions—almost 10 percent of all anthropogenic greenhouse gas—created every year by their own operations, two-thirds of it from upstream activities.
Technologies to optimize and decarbonize the extraction and production of hydrocarbons already exist and many are economically viable, yet the sector's atmospheric emissions continue to rise.
This paper describes a comprehensive field operating concept that leverages latest technologies — edge computing, data analytics, artificial intelligence (AI) to optimize wells using artificial lifts. Our research and pilot onshore deployments have focused initially on sucker rod pumping (SRP) models because they are a predominant solution for maintaining the productivity of mature, low-pressure wells. We are confident our concept can be applied also to other artificial lift technologies like electric submersible pumps (ESPs) or progressing cavity pumps (PCPs), whether onshore or offshore.
The solution is based on an open and scalable software stack that is capable of performing advanced analytics and softsensing to calculate pump conditions, trigger alerts, and optimize production from wells using artificial lift technology. What's more, with the addition of secure connectivity capabilities, E&P operators of multiple wells, even thousands of them, can gain remote fleet management and enterprise-wide visibility of their artificial lift operations.
Advances in data analytics and sensor technology have opened the door for industrial asset management and optimization across all vertical markets, including oil and gas. Edge computing, data analytics, artificial intelligence (AI), and Internet of Things (IoT) connectivity make it possible to scale up and optimize whole fleets of equipment. The machine learning aspects covered in the pilot implementation made the effective motoring of sucker rods feasible.
Sea Water Injection Department's Unmanned Operation
Authors: AlRammah Ahmed Mustafa , AlFuwaires Saleh Saad , Ghuwainem Fadhel 
Published: October 2022

Abstract
By exploiting forth industrial revolution technologies such as advanced facility data analytics, robotics for inspection, and highspeed network connectivity through fiber optics and industrial wi-fi Saudi Aramco's Sea Water Injection Department was able to disturb conventional operation and transition its UWIP1 to a smartly operated plant. UWIP1 has been transferred from manned operation into unmanned operation.
Aramco's Sea Water Injection Department (SWID) is pioneering industry-leading Digital Transformation (DT) initiatives in advanced facility data analytics, robotics for inspection, and industrial Wi-Fi through an evolving "Integrated Intelligent Operation for Seawater Treatment".
Reservoirs distant from the Gulf used to require significant quantities of saline, non-potable groundwater for injection. To replace most withdrawals from this source, Aramco built in 1979 the Qurayyah Seawater Treatment Plant (QSWP), the world's largest for reservoir pressure maintenance. SWID operates QSWP together with a vast associated pipeline network over a large geographic area covering Ghawar, one of the largest conventional oil fields in the world, as well as Khurais, development of which was the largest crude oil expansion program in oil industry history. Seawater is conveyed to hundreds of injection wells. Operating this system is challenging, with the compound effects of massive throughput, complex network, ageing equipment, corrosive seawater, and the "Great Crew Shift" onboarding young talent in place of experienced ones. To resolve these challenges, SWID tapped into the transformational power of DT technologies across the end-to-end water injection value chain to yield benefits in productivity, sustainability and workforce engagement.
Intelligent Production Optimization Decisions: Prioritizing Production Optimization Through Machine Learning Aided Uplift Quantification
Authors: Sharma Akriti , Chonghyun Ahn Alex , Park Jihoon , Singh Vikash , Rodriguez-Buno Mariana , El-Bakry Amr , Kwong John , Garrison Brett , Gelowitz Tyler 
Published: October 2022

AbstractDue to complexity and scale, managing and engineering a modern hydrocarbon asset is extremely challenging. The problem becomes more difficult if an asset has thousands of wells to manage because, most of the time, operation resource is limited (either manpower or tool) to achieve production optimization and the amount of information to process during decision making is enormous. Bringing necessary data from multiple different sources and analyzing it in a relatively short period of time to provide actionable/reliable insight to field operators’ and engineers’ is the key to enhance and optimize production performance.The production optimization best practice is shared amongst field operators and engineers given the geology, reservoir character, and operation strategy which include artificial lift, stimulation, and other workover. This approach has been applied and proven successful mostly in low well count assets by identifying opportunity and providing robust qualitative guidance towards optimum production condition. However, in high well count assets such as unconventional, it is impossible to execute traditional manual approach and it is essential to develop an integrated, flexible, and automated workflow that enhances the efficiency and effectiveness of production operation and achieve "operate-by-priority".Thus, to have efficient and optimized management of hydrocarbon production from individual well of a high well count asset requires prior, more certain and almost real time knowledge of production rates from the currently or upcoming production wells. Production data, thus, from individual well is very important. Well tests are carried out to obtain production rates and then utilize these rates to provide optimized production decisions and actions. In a well test, a test separator splits the production stream into oil, gas, and water using gravity and support in the management of hydrocarbon production. However, well test are infrequent and doesn't fit the purpose alone with such low frequency for real time surveillance and decision support. Also, well tests are expensive and, hence, it is also not economically viable to do more frequent well tests.