Data-Driven Insights from Nigeria's Natural Gas Data Using PowerBI

2021 ◽  
Author(s):  
Adenike Adejola ◽  
Omowumi Iledare ◽  
Paraclete Nnadili
Keyword(s):  
Value Chain ◽  
Industrial Revolution ◽  
Oil And Gas ◽  
Data Driven ◽  
Business Decisions ◽  
Gas Industry ◽  
On Demand ◽  
The Future ◽  
Gas Market ◽  
Data Tables

Abstract Each year, the Nigerian gas industry churns out big data on all channels of its value chain. The data is collated, analyzed, and reported by government agencies, corporate companies, institutions, and even academia. Some of these reports are the NNPC and DPR annual oil and gas reports. The annual oil and gas reports contain data tables, charts, and data driven insights. Considering the growing uncertainty in business intelligence triggered by the COVID-19 pandemic and the fast-paced 4th industrial revolution, the future of data reporting, analyzing, and presentation is also experiencing a new normal. Oil and gas stakeholders desire quick data-driven and actionable insights to reduce business risks caused by the impacts of these key drivers. This article explores and presents the use of Power BI on Nigerian gas data from 2000 to 2018. It extracts data on demand, production, utilization, gas flare volumes, export, current infrastructure capacity, domestic gas supply, and other relevant data categories. The collated data is developed into a dataset by appending and merging tables from the different reports. This data is prepared, and model relationships are created to answers questions on demand, production, infrastructure, and sustainability of the Nigerian Gas market. Empirical results show that new insights can be obtained from the dataset using new tools and a thoughtful data design process. These insights are presented on a dashboard where key takeaways for quick business decisions and policy implementations are easily assessed. The method is proposed as the future of annual energy reporting. It is also a continuous improvement process that can be applied by all oil and gas stakeholders in their data architecture.

Accelerating Digital Transformation in E&P Business

2021 ◽  
Author(s):  
Anak Karim
Keyword(s):  
Industrial Revolution ◽  
Oil And Gas ◽  
Oil And Gas Industry ◽  
Digital Transformation ◽  
Gas Industry ◽  
New Normal ◽  
Strategic Objectives ◽  
The Future ◽  
Energy Companies

Abstract As a resourced based economy, Malaysia relies heavily on the energy oil, and gas industry - a critical sector contributing to the economic growth of the Malaysian economy; which makes up in the range of 20% - 25% of the total gross domestic product (GDP) of Malaysia as of 2017. No analysts can properly predict prices of the future, with the highs and lows of crude and natural gas and renewables as the fuel of the future and are perhaps new way of things. This "new normal" in which countries, including Malaysia, must learn to adapt in a more agile manner to the "new way of work" of increased productivity and efficiency (de Graauw, McCreery, & Murphy, 2015). In adapting to the new normal, measures of increased productivity must continue to be pushed forward and implemented. Energy companies and services provider still need to continue with exploration and development (E&P) operations and activities to meet long term strategic objectives and demands of the nation, in line with the aspirations of the national oil company, however, it needs to add more value to every dollar spent as margins have continued to shrink and reduce profit margins of energy producers. This is where Digital Transformation comes into play and the urgency for implementation has gone from novelty solutions to critical business survival. Changing industry trends such as Industrial Revolution 4.0 have made it more prevalent than ever to make better use of capital at a time when productivity is essential. At the same time, the industry needs to continue to explore and develop to meet long-term demands, which continues to grow albeit slower than before.

Artificial Intelligence and Robotics in the Oil Industry: Will it Take My Job?

2021 ◽  
Author(s):  
Armstrong Lee Agbaji
Keyword(s):  
Artificial Intelligence ◽  
Oil And Gas ◽  
New Technologies ◽  
Oil Industry ◽  
Oil And Gas Industry ◽  
Human Robot Interaction ◽  
Gas Industry ◽  
Deep Dive ◽  
The Future ◽  
And Robotics

Abstract Historically, the oil and gas industry has been slow and extremely cautious to adopt emerging technologies. But in the Age of Artificial Intelligence (AI), the industry has broken from tradition. It has not only embraced AI; it is leading the pack. AI has not only changed what it now means to work in the oil industry, it has changed how companies create, capture, and deliver value. Thanks, or no thanks to automation, traditional oil industry skills and talents are now being threatened, and in most cases, rendered obsolete. Oil and gas industry day-to-day work is progressively gravitating towards software and algorithms, and today’s workers are resigning themselves to the fact that computers and robots will one day "take over" and do much of their work. The adoption of AI and how it might affect career prospects is currently causing a lot of anxiety among industry professionals. This paper details how artificial intelligence, automation, and robotics has redefined what it now means to work in the oil industry, as well as the new challenges and responsibilities that the AI revolution presents. It takes a deep-dive into human-robot interaction, and underscores what AI can, and cannot do. It also identifies several traditional oilfield positions that have become endangered by automation, addresses the premonitions of professionals in these endangered roles, and lays out a roadmap on how to survive and thrive in a digitally transformed world. The future of work is evolving, and new technologies are changing how talent is acquired, developed, and retained. That robots will someday "take our jobs" is not an impossible possibility. It is more of a reality than an exaggeration. Automation in the oil industry has achieved outcomes that go beyond human capabilities. In fact, the odds are overwhelming that AI that functions at a comparable level to humans will soon become ubiquitous in the industry. The big question is: How long will it take? The oil industry of the future will not need large office complexes or a large workforce. Most of the work will be automated. Drilling rigs, production platforms, refineries, and petrochemical plants will not go away, but how work is done at these locations will be totally different. While the industry will never entirely lose its human touch, AI will be the foundation of the workforce of the future. How we react to the AI revolution today will shape the industry for generations to come. What should we do when AI changes our job functions and workforce? Should we be training AI, or should we be training humans?

Asset of the Future - Comprehensive Business Transformation Program

2021 ◽  
Author(s):  
Alexander Sitnikov ◽  
Sergei Doktor ◽  
Andrei Margarit
Keyword(s):  
Oil And Gas ◽  
Energy Transition ◽  
Oil And Gas Industry ◽  
Gas Industry ◽  
Average Return ◽  
Debt Capital ◽  
Timely Response ◽  
The Future ◽  
Return On Capital ◽  
Traditional Approaches

Abstract In the recent years the oil and gas industry has started facing an unprecedented number of challenges. The average return on capital in the industry has deteriorated which results in investor mistrust and costs being higher than ever. Debt capital became two times costlier than for alterative types of energy. More conventional oilfields become depleted and new reserves are usually quite complex to develop. These and other challenges such as intense competition between oil and gas companies, the energy transition agenda as well as the volatility of oil prices in the aftermath of the pandemic are pushing the O&G companies to transform themselves. Gazprom Neft introduced the "Asset of the Future" program in late 2018 as a timely response which was aimed at completely transforming the Upstream business model. The main issue with the transformation was the scale of it, which included 10 subsidiaries (or subs) and more than 200 different processes. In this case traditional approaches such as improving each operation one by one would not suffice as the company sought a rapid and highly efficient implementation of changes. As such the program had to develop a new approach that focused on the integration of all business parts and continuous improvement. Integration of people, technology and processes will lead to better collaboration and as a result - to smarter decisions and better execution.

A Comprehensive Review of the Fourth Industrial Revolution IR 4.0 in Oil and Gas Industry

2021 ◽  
Author(s):  
Cenk Temizel ◽  
Celal Hakan Canbaz ◽  
Hakki Aydin ◽  
Bahar F. Hosgor ◽  
Deniz Yagmur Kayhan ◽  
...  
Keyword(s):  
Industry 4.0 ◽  
Industrial Revolution ◽  
Oil And Gas ◽  
Petroleum Industry ◽  
Oil And Gas Industry ◽  
Learning Technologies ◽  
Real Field ◽  
Gas Industry ◽  
History Of ◽  
History Of Use

Abstract Digital transformation is one of the most discussed themes across the globe. The disruptive potential arising from the joint deployment of IoT, robotics, AI and other advanced technologies is projected to be over $300 trillion over the next decade. With the advances and implementation of these technologies, they have become more widely-used in all aspects of oil and gas industry in several processes. Yet, as it is a relatively new area in petroleum industry with promising features, the industry overall is still trying to adapt to IR 4.0. This paper examines the value that Industry 4.0 brings to the oil and gas upstream industry. It delineates key Industry 4.0 solutions and analyzes their impact within this segment. A comprehensive literature review has been carried out to investigate the IR 4.0 concept's development from the beginning, the technologies it utilizes, types of technologies transferred from other industries with a longer history of use, robustness and applicability of these methods in oil and gas industry under current conditions and the incremental benefits they provide depending on the type of the field are addressed. Real field applications are illustrated with applications indifferent parts of the world with challenges, advantages and drawbacks discussed and summarized that lead to conclusions on the criteria of application of machine learning technologies.

Status of Data-Driven Methods and their Applications in Oil and Gas Industry

2018 ◽  
Author(s):  
Karthik Balaji ◽  
Minou Rabiei ◽  
Vural Suicmez ◽  
Celal Hakan Canbaz ◽  
Zinyat Agharzeyva ◽  
...  
Keyword(s):  
Oil And Gas ◽  
Oil And Gas Industry ◽  
Data Driven ◽  
Gas Industry
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