Towards Real-Time Edge Analytics - A Survey Literature Review of Real-Time Data Acquisition Evolution in the Upstream Oil and Gas Industry

Automation and control systems are necessary throughout oil & gas industries, to production and processing plants, and distribution and retailing of petroleum products. Pipelines are the efficient mode of transportations of fuels for processing plants over long distances. At present Automation is achieved by using PLC’s that are communicated through SCADA. But it is complex and remote operation is not possible. With the introduction of IoT, the pipeline leak detection system is improved through real-time monitoring of the pipelines. Our Proposed system is designed to detect even small leakage that occurs within the pipeline. The implementation of IoT in oil and gas industries prevents accidents and to make quick decisions based on real-time data

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Operator Develops Fully Smart Onshore Field

Journal of Petroleum Technology ◽

10.2118/0521-0056-jpt ◽

2021 ◽

Vol 73 (05) ◽

pp. 56-57

Author(s):

Judy Feder

Keyword(s):

Real Time ◽

United Arab Emirates ◽

Oil And Gas ◽

Water Injection ◽

Health And Safety ◽

Oil And Gas Industry ◽

Oil Fields ◽

Abu Dhabi ◽

Time Data ◽

Gas Industry

This article, written by JPT Technology Editor Judy Feder, contains highlights of paper SPE 203461, “Digitalization in the Oil and Gas Industry—A Case Study of a Fully Smart Field in the United Arab Emirates,” by Muhammad Arif and Abdulla Mohammed Al Senani, ADNOC, prepared for the 2020 Abu Dhabi International Petroleum Exhibition and Conference, Abu Dhabi, held virtually from 9–12 November. The paper has not been peer reviewed. One of the first oil fields in the UAE to be fully operated remotely is in the southeast region, 250 km from Abu Dhabi. The complete paper discusses the development and commissioning of the field, which is the first smart field for ADNOC Onshore. The designed and applied technology facilitated unmanned operation of the field from downhole to export. Introduction Oilfield digitalization encompasses gathering real-time and non-real-time data from wells, flow lines, manifolds, stations, and water injection facilities; analysis of the data using algorithms, flowcharts, plots, and reports; and user access to this data on user-friendly screens. This allows engineers to focus on interpretation of data vs. searching, organizing, and formatting the data. In the bigger picture, the data collected will lead to conclusions and set bases for important decisions for similar projects in the future, enabling a lesson-learning approach to design new oil fields. The accumulated theoretical and practical research results of smart-field implementation require analysis and synthesis to maintain perspective of the entire project. Both were applied in the Mender field, which is the subject of the complete paper. Problem Statement The Mender parent field has been producing since 2013 with minimal digitalization for wellheads. Wells are not fit-ted with remote sensors, and operators have been visiting the wells to collect data using analog gauges. Collected data are stored in computers or as hard copies. Some critical data is lost, which affects decision-making. The new Mender field is 50 km from the parent field and is in a sensitive area close to international borders. The field area is a wildlife reserve for various endangered animals. The nature of operations is highly critical because of concentrations of hydrogen sulfide (H2S) that could jeopardize employees’ health and safety.

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Technology Focus: Digital Data Acquisition (January 2021)

Journal of Petroleum Technology ◽

10.2118/0121-0064-jpt ◽

2021 ◽

Vol 73 (01) ◽

pp. 64-64

Author(s):

Pallav Sarma

Keyword(s):

Data Acquisition ◽

Real Time ◽

Oil And Gas ◽

Oil And Gas Industry ◽

Digital Transformation ◽

Edge Computing ◽

Digital Data ◽

Time Data ◽

Data Accessibility ◽

Digital Data Acquisition

COVID-19 has significantly accelerated the adoption of digital technologies across all industries, and the oil and gas industry has been no exception. Consequently, interest in digital data acquisition, the backbone of all digital transformation work flows, also has increased significantly. This can clearly be seen in the multifold increase in the number of SPE papers on this topic since last year. This feature will continue to focus on technologies to improve data accessibility and data acquisition, as well as entirely new data sources and their applications. The papers chosen this year include real-time remote monitoring of steam traps and corrosion using wireless sensors, enabling faster and easier access to relevant subsurface information through deep learning of unstructured documents, and automation of real-time drilling work flows through digital transformation technologies. While not reflected in these papers, a related emerging technology that has the potential to transform the data acquisition paradigm and that is garnering much attention, however, is edge computing. As the saying goes, if you cannot bring the data to the model, take the model to the data. One of the main difficulties in faster adoption of digital transformation in oil and gas has been access to reliable real-time data that can be converted to real-time decisions. This is the case because of the remote and geographically distributed nature of most oil and gas assets and legacy outdated and piecemeal information-technology (IT) infrastructures, making it difficult to provide models with reliable, standardized data in a timely manner. Edge-computing frameworks eliminate scale and capacity constraints and bypass limitations of current IT infrastructures, truly enabling operationalization of models for real-time decision making. Edge computing, together with machine learning and artificial intelligence, will be the real enablers of digital transformation.

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The Importance of Implementing Cyber Physical Systems to Acquire Real-Time Data and Indicators

J ◽

10.3390/j4020012 ◽

2021 ◽

Vol 4 (2) ◽

pp. 147-153

Author(s):

Paula Morella ◽

María Pilar Lambán ◽

Jesús Antonio Royo ◽

Juan Carlos Sánchez

Keyword(s):

Decision Making ◽

Data Acquisition ◽

Real Time ◽

Failure Detection ◽

Cyber Physical Systems ◽

Future Research ◽

Time Data ◽

Physical Systems ◽

The Real ◽

Real Time Data

Among the new trends in technology that have emerged through the Industry 4.0, Cyber Physical Systems (CPS) and Internet of Things (IoT) are crucial for the real-time data acquisition. This data acquisition, together with its transformation in valuable information, are indispensable for the development of real-time indicators. Moreover, real-time indicators provide companies with a competitive advantage over the competition since they enhance the calculus and speed up the decision-making and failure detection. Our research highlights the advantages of real-time data acquisition for supply chains, developing indicators that would be impossible to achieve with traditional systems, improving the accuracy of the existing ones and enhancing the real-time decision-making. Moreover, it brings out the importance of integrating technologies 4.0 in industry, in this case, CPS and IoT, and establishes the main points for a future research agenda of this topic.

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