An Empirical Analysis of Artificial Intelligence, Big Data and Analytics Applications in Exploration and Production Operations

2021 ◽  
Author(s):  
Armstrong Lee Agbaji
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Empirical Analysis ◽  
Oil And Gas ◽  
Oil Industry ◽  
Digital Transformation ◽  
Deep Dive ◽  
Exploration And Production ◽  
Oil And Gas Operations

Abstract Oil and Gas operations are now being "datafied." Datafication in the oil industry refers to systematically extracting data from the various oilfield activities that are naturally occurring. Successful digital transformation hinges critically on an organization's ability to extract value from data. Extracting and analyzing data is getting harder as the volume, variety, and velocity of data continues to increase. Analytics can help us make better decisions, only if we can trust the integrity of the data going into the system. As digital technology continues to play a pivotal role in the oil industry, the role of reliable data and analytics has never been more consequential. This paper is an empirical analysis of how Artificial Intelligence (AI), big data and analytics has redefined oil and gas operations. It takes a deep dive into various AI and analytics technologies reshaping the industry, specifically as it relates to exploration and production operations, as well as other sectors of the industry. Several illustrative examples of transformative technologies reshaping the oil and gas value chain along with their innovative applications in real-time decision making are highlighted. It also describes the significant challenges that AI presents in the oil industry including algorithmic bias, cybersecurity, and trust. With digital transformation poised to re-invent the oil & gas industry, the paper also discusses energy transition, and makes some bold predictions about the oil industry of the future and the role of AI in that future. Big data lays the foundation for the broad adoption and application of artificial intelligence. Analytics and AI are going to be very powerful tools for making predictions with a precision that was previously impossible. Analysis of some of the AI and analytics tools studied shows that there is a huge gap between the people who use the data and the metadata. AI is as good as the ecosystem that supports it. Trusting AI and feeling confident with its decisions starts with trustworthy data. The data needs to be clean, accurate, devoid of bias, and protected. As the relationship between man and machine continues to evolve, and organizations continue to rely on data analytics to provide decision support services, it is imperative that we safeguard against making important technical and management decisions based on invalid or biased data and algorithm. The variegated outcomes observed from some of the AI and analytics tools studied in this research shows that, when it comes to adopting AI and analytics, the worm remains buried in the apple.

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?

scholarly journals Significance of Technology and Digital Transformation in Shaping the Future of Oil and Gas Industry

2021 ◽  
Vol 12 (3) ◽  
pp. 3345-3352
Author(s):  
Shubham Parsoya Et.al
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Internet Of Things ◽  
Data Analytics ◽  
Oil And Gas ◽  
Big Data Analytics ◽  
Oil And Gas Industry ◽  
Digital Transformation ◽  
Gas Industry ◽  
The Future

Digital transformation in the field of oil and Gas industry is already a significant impact creator. It is actually act like catalyst through which the overall functionality of the oil and gas industry get enhanced and the overall output with the help of technologically-advanced mechanism, increased up to manifold. In the present scenario, the over-all quest is not just about the volume of the oil and petroleum, but it is also regarding the overall value generated throughout the process. And such enhanced level of value generation is taking place with great pace with the help of enhanced level of implementations of different types of technologies in different type of activities related to the oil and gas industry. In the present scenario, oil and gas industry’s business model is no longer depending upon just the inflated and narrow based value-chain mechanism. It is actually depending upon the almost all modernized and futuristic technologies. The modern technologies include big data analytics, 3D printing technology, cyber security, digital marketing, Artificial Intelligence, Internet of Things, drone technologies, database management system, etc. all these technologies are not only supports in handling the overall business capability of the oil and Gas Industries, but also eliminate the overall negative impact generating elements. With the help of technologies and digital transformation, the overall profitability of the oil and gas industry enhanced. Digital transformation is a prominent and significant impact creator which is not limited to the oil and gas industry, but also reaching up to the all-global level Businesses. It is transforming the overall business operations by enhancing the speed of innovation and making the use of practical knowledge base which ultimately enhance the overall power of operations and increase efficiencies. With the emergence of digital transformation technologies especially with the emergence of big data analytics, the Internet of Things and Artificial Intelligence have supports several types of innovative and new ways of developing and transforming the overall market as well as the customer satisfaction in significant manner. All such innovative technologies and digital transformations are contributing significantly in shaping the future of oil and gas industry

Drilling and Service Contracts in Offshore Oil and Gas Operations

1973 ◽  
Vol 11 (3) ◽  
pp. 480
Author(s):  
J. M. Killey
Keyword(s):  
Oil And Gas ◽  
Oil Industry ◽  
Offshore Drilling ◽  
Oil Companies ◽  
Drilling Rig ◽  
Service Contracts ◽  
Oil And Gas Operations ◽  
Offshore Oil And Gas ◽  
Offshore Oil ◽  
Offshore Operations

As onshore oil and gas deposits are becoming more difficult to locate, and as the world demands for energy continue to increase at an alarming rate, oil companies are channeling much of their exploration activities towards offshore operations, and in particular, towards operations centered off Canada's coast lines. Because of the environment, offshore drilling presents problems which are novel to the onshore-geared oil industry. J. M. Killey discusses in detail many of the considerations involved in drafting the offshore drilling contract, concentrating on problems such as the liability of the various parties; costs; scheduling; pollution; conflict of laws; etc. Similarly, he discusses service contracts (such as supply boat charters; towing services; helicopter services; etc.^ which are necessity to the operation of an offshore drilling rig. To complement his paper, the author has included number of appendices which list the various considerations lawyer must keep in mind when drafting contracts for offshore operations.

scholarly journals Out of the loop? On the radical and the routine in urban big data

Urban Studies ◽  
2021 ◽  
pp. 004209802110140
Author(s):  
Sarah Barns
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Computational Models ◽  
Data Driven ◽  
Urban Systems ◽  
Out Of The Loop ◽  
Urban Futures ◽  
Urban Behaviour ◽  
The City

This commentary interrogates what it means for routine urban behaviours to now be replicating themselves computationally. The emergence of autonomous or artificial intelligence points to the powerful role of big data in the city, as increasingly powerful computational models are now capable of replicating and reproducing existing spatial patterns and activities. I discuss these emergent urban systems of learned or trained intelligence as being at once radical and routine. Just as the material and behavioural conditions that give rise to urban big data demand attention, so do the generative design principles of data-driven models of urban behaviour, as they are increasingly put to use in the production of replicable, autonomous urban futures.

scholarly journals The Role of Artificial Intelligence in Fighting the COVID-19 Pandemic

2021 ◽  
Author(s):  
Francesco Piccialli ◽  
Vincenzo Schiano di Cola ◽  
Fabio Giampaolo ◽  
Salvatore Cuomo
Keyword(s):  
Artificial Intelligence ◽  
Clinical Trials ◽  
Digital Transformation ◽  
Daily Activities ◽  
Commercial Vehicles ◽  
Human Skills ◽  
To Come ◽  
Complex Scenario ◽  
The Impact

AbstractThe first few months of 2020 have profoundly changed the way we live our lives and carry out our daily activities. Although the widespread use of futuristic robotaxis and self-driving commercial vehicles has not yet become a reality, the COVID-19 pandemic has dramatically accelerated the adoption of Artificial Intelligence (AI) in different fields. We have witnessed the equivalent of two years of digital transformation compressed into just a few months. Whether it is in tracing epidemiological peaks or in transacting contactless payments, the impact of these developments has been almost immediate, and a window has opened up on what is to come. Here we analyze and discuss how AI can support us in facing the ongoing pandemic. Despite the numerous and undeniable contributions of AI, clinical trials and human skills are still required. Even if different strategies have been developed in different states worldwide, the fight against the pandemic seems to have found everywhere a valuable ally in AI, a global and open-source tool capable of providing assistance in this health emergency. A careful AI application would enable us to operate within this complex scenario involving healthcare, society and research.

Accelerating oil and gas investment and reserves by design

2018 ◽  
Vol 58 (2) ◽  
pp. 557
Author(s):  
Barry A. Goldstein
Keyword(s):  
Natural Gas ◽  
Fossil Fuels ◽  
Oil And Gas ◽  
South Australia ◽  
Land Access ◽  
Oil And Gas Exploration ◽  
Oil And Gas Producers ◽  
Crude Oil Prices ◽  
Exploration And Production ◽  
Oil And Gas Operations

Facts are stubborn things; and whatever may be our wishes, our inclinations, or the dictates of our passion, they cannot alter the state of facts and evidence (Adams 1770). Some people unfamiliar with upstream petroleum operations, some enterprises keen to sustain uncontested land use, and some people against the use of fossil fuels have and will voice opposition to land access for oil and gas exploration and production. Social and economic concerns have also arisen with Australian domestic gas prices tending towards parity with netbacks from liquefied natural gas (LNG) exports. No doubt, natural gas, LNG and crude-oil prices will vary with local-to-international supply-side and demand-side competition. Hence, well run Australian oil and gas producers deploy stress-tested exploration, delineation and development budgets. With these challenges in mind, successive governments in South Australia have implemented leading-practice legislation, regulation, policies and programs to simultaneously gain and sustain trust with the public and investors with regard to land access for trustworthy oil and gas operations. South Australia’s most recent initiatives to foster reserve growth through welcomed investment in responsible oil and gas operations include the following: a Roundtable for Oil and Gas; evergreen answers to frequently asked questions, grouped retention licences that accelerate investment in the best of play trends; the Plan for ACcelerating Exploration (PACE) Gas Program; and the Oil and Gas Royalty Return Program. Intended and actual outcomes from these initiatives are addressed in this extended abstract.

Who’s making the decisions? How managers can harness artificial intelligence and remain in charge

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Pooya Tabesh
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Decision Making ◽  
Big Data ◽  
Digital Transformation ◽  
Decision Processes ◽  
Decision Makers ◽  
Content Type ◽  
Human Decision ◽  
Practical Implications

Purpose While it is evident that the introduction of machine learning and the availability of big data have revolutionized various organizational operations and processes, existing academic and practitioner research within decision process literature has mostly ignored the nuances of these influences on human decision-making. Building on existing research in this area, this paper aims to define these concepts from a decision-making perspective and elaborates on the influences of these emerging technologies on human analytical and intuitive decision-making processes. Design/methodology/approach The authors first provide a holistic understanding of important drivers of digital transformation. The authors then conceptualize the impact that analytics tools built on artificial intelligence (AI) and big data have on intuitive and analytical human decision processes in organizations. Findings The authors discuss similarities and differences between machine learning and two human decision processes, namely, analysis and intuition. While it is difficult to jump to any conclusions about the future of machine learning, human decision-makers seem to continue to monopolize the majority of intuitive decision tasks, which will help them keep the upper hand (vis-à-vis machines), at least in the near future. Research limitations/implications The work contributes to research on rational (analytical) and intuitive processes of decision-making at the individual, group and organization levels by theorizing about the way these processes are influenced by advanced AI algorithms such as machine learning. Practical implications Decisions are building blocks of organizational success. Therefore, a better understanding of the way human decision processes can be impacted by advanced technologies will prepare managers to better use these technologies and make better decisions. By clarifying the boundaries/overlaps among concepts such as AI, machine learning and big data, the authors contribute to their successful adoption by business practitioners. Social implications The work suggests that human decision-makers will not be replaced by machines if they continue to invest in what they do best: critical thinking, intuitive analysis and creative problem-solving. Originality/value The work elaborates on important drivers of digital transformation from a decision-making perspective and discusses their practical implications for managers.

Big data analytics capabilities and organizational performance: the mediating effect of dual innovations

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Xiaofeng Su ◽  
Weipeng Zeng ◽  
Manhua Zheng ◽  
Xiaoli Jiang ◽  
Wenhe Lin ◽  
...  
Keyword(s):  
Big Data ◽  
Organizational Performance ◽  
Empirical Analysis ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Mediating Effect ◽  
Content Type ◽  
Mediating Role ◽  
The Relationship

PurposeFollowing the rapid expansion of data volume, velocity and variety, techniques and technologies, big data analytics have achieved substantial development and a surge of companies make investments in big data. Academics and practitioners have been considering the mechanism through which big data analytics capabilities can transform into their improved organizational performance. This paper aims to examine how big data analytics capabilities influence organizational performance through the mediating role of dual innovations.Design/methodology/approachDrawing on the resource-based view and recent literature on big data analytics, this paper aims to examine the direct effects of big data analytics capabilities (BDAC) on organizational performance, as well as the mediating role of dual innovations on the relationship between (BDAC) and organizational performance. The study extends existing research by making a distinction of BDACs' effect on their outcomes and proposing that BDACs help organizations to generate insights that can help strengthen their dual innovations, which in turn have a positive impact on organizational performance. To test our proposed research model, this study conducts empirical analysis based on questionnaire-base survey data collected from 309 respondents working in Chinese manufacturing firms.FindingsThe results support the proposed hypotheses regarding the direct and indirect effect that BDACs have on organizational performance. Specifically, this paper finds that dual innovations positively mediate BDACs' effect on organizational performance.Originality/valueThe conclusions on the relationship between big data analytics capabilities and organizational performance in previous research are controversial due to lack of theoretical foundation and empirical testing. This study resolves the issue by provides empirical analysis, which makes the research conclusions more scientific and credible. In addition, previous literature mainly focused on BDACs' direct impact on organizational performance without making a distinction of BDAC's three dimensions. This study contributes to the literature by thoroughly introducing the notions of BDAC's three core constituents and fully analyzing their relationships with organizational performance. What's more, empirical research on the mechanism of big data analytics' influence on organizational performance is still at a rudimentary stage. The authors address this critical gap by exploring the mediation of dual innovations in the relationship through survey-based research. The research conclusions of this paper provide new perspective for understanding the impact of big data analytics capabilities on organizational performance, and enrich the theoretical research connotation of big data analysis capabilities and dual innovation behavior.

Big Data, Artificial Intelligence, and the Internet of Things in Cross-Border E-Commerce

2021 ◽  
pp. 257-272
Author(s):  
Aboobucker Ilmudeen
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Internet Of Things ◽  
Economic Globalization ◽  
The Internet ◽  
Technological Revolution ◽  
Cross Border ◽  
Wide Range ◽  
The Internet Of Things

Today, the terms big data, artificial intelligence, and internet of things (IoT) are many-fold as these are linked with various applications, technologies, eco-systems, and services in the business domain. The recent industrial and technological revolution have become popular ever before, and the cross-border e-commerce activities are emerging very rapidly. As a result, it supports to the growth of economic globalization that has strategic importance for the advancement of e-commerce activities across the globe. In the business industry, the wide range applications of technologies like big data, artificial intelligence, and internet of things in cross-border e-commerce have grown exponential. This chapter systematically reviews the role of big data, artificial intelligence, and IoT in cross-border e-commerce and proposes a conceptually-designed smart-integrated cross-border e-commerce platform.

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