Drilling Analysis Using Big Data has been Misused and Abused

Maidla, E.E.; Maidla, William Rochel; Rigg, J. C.; Crumrine, M.J.; Wolf-Zoellner, Philipp

doi:10.2118/189583-ms

Cited by 14 publications

(6 citation statements)

References 3 publications

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“…Besides, early detection of anomalies affects penetration and ensures avoidance of undesired events such as kicks, blowouts, etc. The quality of generated data is also necessary to evaluate to prevent the misuse of the drilling data and avoid future calamities resulting from wrong decision-making [83]. Through optimization, drilling operations can unite the logging [34].…”

Section: ) Drilling and Completionmentioning

confidence: 99%

A Comprehensive Review on Big Data for Industries: Challenges and Opportunities

et al. 2023

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Technological advancements in large industries like power, minerals, and manufacturing are generating massive data every second. Big data techniques have opened up numerous opportunities to utilize massive datasets in several effective ways to improve the efficacy of related industries. This paper presents a review of big data technologies used in the power, mineral, and manufacturing industries for various purposes. We analyze the meta-data of the collected papers before reviewing and selecting papers by applying selection criteria and paper quality assessment strategy. Then we propose a taxonomy of big data application areas in the power, mineral, and manufacturing industries. We have studied current big data architectures and techniques implemented in industry sectors and have uncovered the big data research gaps in industry sectors. To address the gaps, we point out some relevant research questions and, to answer the questions, we make some future research recommendations that might explore interesting research ideas for building a big data-driven industry. As the careful use of big data benefits every other industry sector; hence, supportive big data frameworks need to be developed to speed up the big data analysis process. Proper multi-dimensional big data assessment is also needed to take into account for serving effective data analysis tasks.INDEX TERMS Big data for industry, smart grid, power system, oil and gas industry, minerals, big data technology, manufacturing industry, big-data-driven industry.

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Section: ) Drilling and Completionmentioning

confidence: 99%

A Comprehensive Review on Big Data for Industries: Challenges and Opportunities

et al. 2023

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“…The demand for intelligent fields, smart wells, and real-time analysis has increased the utilization of I4.0 technology in the O&G industry. For example, BD was used to smarten the drilling platforms and pipeline infrastructure in [165], to evaluate drilling rig efficiency and performance [166], [167], as well as to reduce the risk of drilling operations [168]. Johnston et al [168] applied big DA in the attempt to minimize the operational risks in drilling and wells domains.…”

Section: ) Risk Analysismentioning

confidence: 99%

A Survey on Industry 4.0 for the Oil and Gas Industry: Upstream Sector

et al. 2021

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The market volatility in the oil and gas (O&G) sector, the dwindling demand for oil due to the impact of COVID-19, and the push for alternative greener energy are driving the need for innovation and digitization in the O&G industry. This has attracted research interest from academia and the industry in the application of industry 4.0 (I4.0) technologies in the O&G sector. The application of some of these I4.0 technologies has been presented in the literature, but the domain still lacks a comprehensive survey of the application of I4.0 in the O&G upstream sector. This paper investigates the state-of-the-art efforts directed toward I4.0 technologies in the O&G upstream sector. To achieve this, first, an overview of the I4.0 is discussed followed by a systematic literature review from an integrative perspective for publications between 2012-2021 with 223 analyzed documents. The benefits and challenges of the adoption of I4.0 have been identified. Moreover, the paper adds value by proposing a framework for the implementation of I4.0 in the O&G upstream sector. Finally, future directions and research opportunities such as framework, edge computing, quantum computing, communication technologies, standardization, and innovative areas related to the implementation of I4.0 in the upstream sector are presented. The findings from this review show that I4.0 technologies are currently being explored and deployed for various aspects of the upstream sector. However, some of the I4.0 technologies like additive manufacturing and virtual reality are least explored.INDEX TERMS Artificial intelligence (AI), cyber-physical systems, digital-twin, framework, oil and gas (O&G), industry revolution 4.0 (IR 4.0), industry 4.0 (I4.0), internet of things (IoT), simulation, upstream sector

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“…The invention, improvements and application of new data recording tools (e.g., seismic acquisitions devices, channel counting, fluid front monitoring geophones, carbon capture and sequestration sites, logging while drilling), measurement and data formats have made it even more applicable to employ big data analytic tools in drilling operations [100]. In this area, big data analytics can be deployed to improve the drilling performance [105], find invisible non-production time [106], and reduce the risks associated with drilling operations, the risks of drilling failures, and can also lower drilling development costs [107], [108]. A report done by B. Marr, [109] noted that Shell uses big data analytics in near realtime to detect failures.…”

Section: Decision Support Through Big Data Analyticsmentioning

confidence: 99%

Human Centric Digital Transformation and Operator 4.0 for the Oil and Gas Industry

et al. 2021

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Working at an oil and gas facility, such as a drilling rig, production facility, processing facility, or storage facility, involves various challenges, including health and safety risks. It is possible to leverage emerging digital technologies such as smart sensors, wearable or mobile devices, big data analytics, cloud computing, extended reality technologies, robotic systems, and drones to mitigate the challenges faced by oil and gas workers. While these technologies are not new to the oil and gas industry, most of its existing digital transformation initiatives follow business or process-centric approaches, in which the critical driver of the technology adoption is the enhancement of production, efficiency, and revenue. As a result, they may not address the challenges faced by the workers. As oil and gas workers are among the essential assets in the oil and gas industry, it is vital to address the challenges faced by these workers. This paper proposes a human-centric digital transformational framework for the oil and gas industry to deploy existing digital technologies to enhance their workers' health, safety, and working conditions. The paper outlines the critical challenges faced by oilfield workers, introduces a system architecture to implements a human-centric digital transformation, discusses the opportunities of the proposed framework, and summarizes the key impediment for the proposed framework.

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Drilling Analysis Using Big Data has been Misused and Abused

Cited by 14 publications

References 3 publications

A Comprehensive Review on Big Data for Industries: Challenges and Opportunities

A Comprehensive Review on Big Data for Industries: Challenges and Opportunities

A Survey on Industry 4.0 for the Oil and Gas Industry: Upstream Sector

Human Centric Digital Transformation and Operator 4.0 for the Oil and Gas Industry

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