Mobile autonomous methane monitoring stations for emission measurement

2021 ◽  
Vol 61 (2) ◽  
pp. 425
Author(s):  
M. Mainson ◽  
C. Ong ◽  
M. Myers ◽  
A. Spiers

Natural gas has been forecast to continue grow up to 30% for the next 40 years and will remain as a key energy source. Alongside this projected growth, both the government and the industry have committed to reduce emission reductions. A critical focus is fugitive emissions, which are related to leaks or unintended losses of methane from sources such as hydrocarbon production, processing, transport, storage, transmission and distribution. The need for measuring and monitoring these emissions has been recognised in significant environmental inquiries related to the gas industry, such as the Northern Territory Fracking Inquiry (Pepper et al. 2018) and required in section D of the NT Code of Practice. This study describes an autonomous emission monitoring station developed to address the challenge of characterising temporally varying fugitive methane emissions. It has been designed specifically to tolerate the Australian outback’s extreme climateswhile providing laboratory-grade measurements in real-time at locations where there will be no access to grid power and standard telecommunications. Preliminary results demonstrating the continuous real-time measurements of methane and ethane concentrations of temporally varying phenomena will be presented. Specifically, the detection of methane and ethane concentrations and temporal changes related to bushfire progress will be shown.

2004 ◽  
pp. 51-69 ◽  
Author(s):  
E. Sharipova ◽  
I. Tcherkashin

Federal tax revenues from the main sectors of the Russian economy after the 1998 crisis are examined in the article. Authors present the structure of revenues from these sectors by main taxes for 1999-2003 and prospects for 2004. Emphasis is given to an increasing dependence of budget on revenues from oil and gas industries. The share of proceeds from these sectors has reached 1/3 of total federal revenues. To explain this fact world oil prices dynamics and changes in tax legislation in Russia are considered. Empirical results show strong dependence of budget revenues on oil prices. The analysis of changes in tax legislation in oil and gas industry shows that the government has managed to redistribute resource rent in favor of the state.


2021 ◽  
Author(s):  
He Zhang ◽  
Jianxun Zhang ◽  
Rui Wang ◽  
Yazhe Huang ◽  
Mengxiao Zhang ◽  
...  

AbstractWith the rapid development of the Internet of Things (IoT) in the 5G age, the construction of smart cities around the world consequents on the exploration of carbon reduction path based on IoT technology is an important direction for global low carbon city research. Carbon dioxide emissions in small cities are usually higher than that in large and medium cities. However, due to the huge difference in data environment between small cities and Medium-large sized cities, the weak hardware foundation of the IoT, and the high input cost, the construction of a small city smart carbon monitoring platform has not yet been carried out. This paper proposes a real-time estimate model of carbon emissions at the block and street scale and designs a smart carbon monitoring platform that combines traditional carbon control methods with IoT technology. It can exist long-term data by using real-time data acquired with the sensing device. Therefore, the dynamic monitoring and management of low-carbon development in small cities can be achieved. The contributions are summarized as follows: (1) Intelligent thermoelectric systems, industrial energy monitoring systems, and intelligent transportation systems are three core systems of the monitoring platform. Carbon emission measurement methods based on sample monitoring, long-term data, and real-time data have been established, they can solve the problem of the high cost of IoT equipment in small cities. (2) Combined with long-term data, the real-time correction technology, they can dispose of the matter of differences in carbon emission measurement under diverse scales.


2019 ◽  
Vol 13 (11) ◽  
pp. 2006-2014 ◽  
Author(s):  
Xinda Ke ◽  
Nader Samaan ◽  
Jesse Holzer ◽  
Renke Huang ◽  
Bharat Vyakaranam ◽  
...  

2021 ◽  
Vol 11 (22) ◽  
pp. 10596
Author(s):  
Chung-Hong Lee ◽  
Hsin-Chang Yang ◽  
Yenming J. Chen ◽  
Yung-Lin Chuang

Recently, an emerging application field through Twitter messages and algorithmic computation to detect real-time world events has become a new paradigm in the field of data science applications. During a high-impact event, people may want to know the latest information about the development of the event because they want to better understand the situation and possible trends of the event for making decisions. However, often in emergencies, the government or enterprises are usually unable to notify people in time for early warning and avoiding risks. A sensible solution is to integrate real-time event monitoring and intelligence gathering functions into their decision support system. Such a system can provide real-time event summaries, which are updated whenever important new events are detected. Therefore, in this work, we combine a developed Twitter-based real-time event detection algorithm with pre-trained language models for summarizing emergent events. We used an online text-stream clustering algorithm and self-adaptive method developed to gather the Twitter data for detection of emerging events. Subsequently we used the Xsum data set with a pre-trained language model, namely T5 model, to train the summarization model. The Rouge metrics were used to compare the summary performance of various models. Subsequently, we started to use the trained model to summarize the incoming Twitter data set for experimentation. In particular, in this work, we provide a real-world case study, namely the COVID-19 pandemic event, to verify the applicability of the proposed method. Finally, we conducted a survey on the example resulting summaries with human judges for quality assessment of generated summaries. From the case study and experimental results, we have demonstrated that our summarization method provides users with a feasible method to quickly understand the updates in the specific event intelligence based on the real-time summary of the event story.


Author(s):  
Н.Д. Айсунгуров ◽  
П.С. Цамаева ◽  
А.А. Эльмурзаев ◽  
С.С. Юсупов

Экономической составляющей нашей страны была и остается топливно-энергетическая промышленность, в частности нефтегазовая отрасль промышленности. Снижение объемов добычи жидких углеводородов из-за истощения огромного количества эксплуатируемых скважин заставляет искать пути решения возникающих проблем. Одним из решений такого рода проблем видится увеличение числа эксплуатации нефтегазовых скважин, которые сталкиваются с проблемами из-за высокого содержания в составе вредных компонентов, в частности сероводорода. Ведущие нефтяные компании имеют свое видение решения этих проблем. Исследования ученых в этой области предлагают свои решения подобного рода вопросов. Одним из таких предложений является разработка технологии утилизации сероводорода путем окисления газов кислородом воздуха на твердых катализаторах. В статье предлагается метод выделения серы из высококонцентрированного сероводородсодержащего газа в кипящем слое катализатора. Авторами проведены испытания предлагаемого метода на опытной установке и даны рекомендации по проведению такого рода исследований. The economic component of our country has been and remains the fuel and energy industry, in particular the oil and gas industry. The decline in liquid hydrocarbon production, due to the depletion of a huge number of exploited wells, makes us look for ways to solve the problems that arise. One of the solutions to this kind of problems seems to be an increase in the number of oil and gas wells that encounter problems due to the high content of harmful components, in particular hydrogen sulfide. Leading oil campaigns have their own vision for solving these problems. Researches of scientists in this area offer their solutions to this kind of issues. One of such proposals is the development of technology for the utilization of hydrogen sulfide by oxidizing gases with atmospheric oxygen on solid catalysts. The article proposes a method for the separation of sulfur from highly concentrated hydrogen sulfide-containing gas in a fluidized bed of catalyst. The authors tested the proposed method in a pilot plant and made recommendations for conducting this kind of research.


Gruntovedenie ◽  
2021 ◽  
Vol 1 (16) ◽  
pp. 16-52
Author(s):  
E.A. Voznesensky ◽  
◽  
A.S. Loktev ◽  
M.S. Nikitin ◽  
◽  
...  

Issues of laboratory soil studies standardization in offshore geotechnical survey are discussed in connection with the end of expertise of two new regulative documents – new edition of the Code of practice and Russian national standard developed on the basis of international ISO standard. Since these documents of different level belong also to different categories (geotechnical survey and oil and gas industry), the authors analyze their interrelation and consistency, from one hand, and the preparedness of Russian soil testing practice to implementation of the new standard which results from harmonization with international ones, from the other. Complete section of the standard draft related to soil laboratory testing is presented, preceded by commentary on some important issues regarding the implementation of its specific methodic statements. It is concluded that the new national GOST draft «Petroleum and natural gas industries. Specific requirements for offshore structures. Marine soil investigations» developed on ISO basis will be a useful document supported in general by Russian normative base but expanding a possible range of voluntary methods into well time-tested foreign approaches. This documents can be considered to be a toolkit annex to the Code of practice describing testing approaches beyond the scope of typical tasks


Author(s):  
Azhari Yahya ◽  
Nurdin MH

The oil and gas industry in Indonesia has been started since 1871 by Royal Dutch Shell. Meanwhile, the oil and gas industry in Aceh began in 1971 which was marked by the discovery of the Arun oil and gas fields. At that time, the management of oil and gas is done centrally by not involving the Government of Aceh as a regional producer. This led to armed conflict between the Government of Indonesia and the Free Aceh Movement and prolonged conflict (for 32 years) ended with the approval of the joint oil and gas management pattern found in the territory of Aceh as stipulated in the MoU Helsinki on August 15 2005, Law No. 11 of 2006 concerning the Government of Aceh and Government Regulation No. 23 of 2015 concerning Joint Management of Oil and Gas in Aceh. In order to finalize joint oil and gas management in Aceh, universities, especially the Faculty of Law, need to immediately prepare human resources who are competent in the oil and gas and energy law so that they are skilled at negotiating and drafting a Production Sharing Contracts (PSC) for oil and gas or Kontrak Bagi Hasil (KBH). For this purpose, law faculties need to immediately incorporate oil and gas and energy law courses into their curriculum.


2021 ◽  
Author(s):  
Henry Ijomanta ◽  
Lukman Lawal ◽  
Onyekachi Ike ◽  
Raymond Olugbade ◽  
Fanen Gbuku ◽  
...  

Abstract This paper presents an overview of the implementation of a Digital Oilfield (DOF) system for the real-time management of the Oredo field in OML 111. The Oredo field is predominantly a retrograde condensate field with a few relatively small oil reservoirs. The field operating philosophy involves the dual objective of maximizing condensate production and meeting the daily contractual gas quantities which requires wells to be controlled and routed such that the dual objectives are met. An Integrated Asset Model (IAM) (or an Integrated Production System Model) was built with the objective of providing a mathematical basis for meeting the field's objective. The IAM, combined with a Model Management and version control tool, a workflow orchestration and automation engine, A robust data-management module, an advanced visualization and collaboration environment and an analytics library and engine created the Oredo Digital Oil Field (DOF). The Digital Oilfield is a real-time digital representation of a field on a computer which replicates the behavior of the field. This virtual field gives the engineer all the information required to make quick, sound and rational field management decisions with models, workflows, and intelligently filtered data within a multi-disciplinary organization of diverse capabilities and engineering skill sets. The creation of the DOF involved 4 major steps; DATA GATHERING considered as the most critical in such engineering projects as it helps to set the limits of what the model can achieve and cut expectations. ENGINEERING MODEL REVIEW, UPDATE AND BENCHMARKING; Majorly involved engineering models review and update, real-time data historian deployment etc. SYSTEM PRECONFIGURATION AND DEPLOYMENT; Developed the DOF system architecture and the engineering workflow setup. POST DEPLOYMENT REVIEW AND UPDATE; Currently ongoing till date, this involves after action reviews, updates and resolution of challenges of the DOF, capability development by the operator and optimizing the system for improved performance. The DOF system in the Oredo field has made it possible to integrate, automate and streamline the execution of field management tasks and has significantly reduced the decision-making turnaround time. Operational and field management decisions can now be made within minutes rather than weeks or months. The gains and benefits cuts across the entire production value chain from improved operational safety to operational efficiency and cost savings, real-time production surveillance, optimized production, early problem detection, improved Safety, Organizational/Cross-discipline collaboration, data Centralization and Efficiency. The DOF system did not come without its peculiar challenges observed both at the planning, execution and post evaluation stages which includes selection of an appropriate Data Gathering & acquisition system, Parts interchangeability and device integration with existing field devices, high data latency due to bandwidth, signal strength etc., damage of sensors and transmitters on wellheads during operations such as slickline & WHM activities, short battery life, maintenance, and replacement frequency etc. The challenges impacted on the project schedule and cost but created great lessons learnt and improved the DOF learning curve for the company. The Oredo Digital Oil Field represents a future of the oil and gas industry in tandem with the industry 4.0 attributes of using digital technology to drive efficiency, reduce operating expenses and apply surveillance best practices which is required for the survival of the Oil and Gas industry. The advent of the 5G technology with its attendant influence on data transmission, latency and bandwidth has the potential to drive down the cost of automated data transmission and improve the performance of data gathering further increasing the efficiency of the DOF system. Improvements in digital integration technologies, computing power, cloud computing and sensing technologies will further strengthen the future of the DOF. There is need for synergy between the engineering team, IT, and instrumentation engineers to fully manage the system to avoid failures that may arise from interface management issues. Battery life status should always be monitored to ensure continuous streaming of real field data. New set of competencies which revolves around a marriage of traditional Petro-technical skills with data analytic skills is required to further maximize benefit from the DOF system. NPDC needs to groom and encourage staff to venture into these data analytic skill pools to develop knowledge-intelligence required to maximize benefit for the Oredo Digital Oil Field and transfer this knowledge to other NPDC Asset.


Author(s):  
Muhammad Mazhar Ullah Rathore ◽  
Awais Ahmad ◽  
Anand Paul

Geosocial network data provides the full information on current trends in human, their behaviors, their living style, the incidents and events, the disasters, current medical infection, and much more with respect to locations. Hence, the current geosocial media can work as a data asset for facilitating the national and the government itself by analyzing the geosocial data at real-time. However, there are millions of geosocial network users, who generates terabytes of heterogeneous data with a variety of information every day with high-speed, termed as Big Data. Analyzing such big amount of data and making real-time decisions is an inspiring task. Therefore, this book chapter discusses the exploration of geosocial networks. A system architecture is discussed and implemented in a real-time environment in order to process the abundant amount of various social network data to monitor the earth events, incidents, medical diseases, user trends and thoughts to make future real-time decisions as well as future planning.


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