Digital Oil Field
This paper explores how artificial intelligence (AI), cognitive models, and integrated digital tools can transform readiness from periodic drills into a continuous, measurable capability.
This paper presents a competency-centered, data-driven approach implemented to strengthen control-room emergency-response capability through a cloud-hosted, scenario-based virtual plant simulator.
This paper presents an autonomous, data-driven solution designed specifically for intermittent well optimization.
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This paper presents the completion strategy implemented in an intelligent well completed in Malaysian deepwater Block K. -
This paper presents the design and development of a prototype intelligent water-injection and smart allocation tool aimed at achieving autonomous waterflood operations.
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This paper addresses the challenges of integrating huge amounts of data and developing model frameworks and systematic workflows to identify opportunities for production enhancement by choosing the best candidate wells.
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This paper described the use of digital twin technology to identify design modifications required at an onshore site and visualize proposed offshore assets for a Trinidad and Tobago development.
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From the first supercomputer to generative AI, JPT has followed the advancement of digital technology in the petroleum industry. As the steady march of innovation continues, four experts give their views on the state and future of data science in the industry.
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The authors integrated azimuths and intensities recorded by fiber optics and compared them with post-flowback production-allocation and interference testing to identify areas of conductive fractures and offset-well communication.
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This paper addresses the challenges related to well control and the successful implementation of deep-transient-test operations in an offshore well in Southeast Asia carried out with the help of a dynamic well-control-simulation platform.
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The digital twin aims to allow Petrobras to optimize system settings to maximize production, increase recovery, and reduce risk.
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For today’s oil and gas companies, digital twins offer untapped potential to decarbonize the leading source of their emissions—field production.
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This paper presents the concept of a supervisory and advisory system dedicated to support the detection of abnormal events and to provide guidelines for fluid treatment.
