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In this podcast episode and transcript, Terry Palisch shares his thoughts about how SPE and its members fit into the energy transition and what it means for our energy future.
We must admit that the oil field is still in the early days of its digital journey. It’s time to give serious thought to the expectation/reality gap, the cultural differences between the way we’ve always done things and the way that digital is changing us, and the pain points that may trip us up unless we’re careful.
This year, 13 individuals join this elite group, bringing the total membership of A Peer Apart honorees to 211 dedicated members.
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This article explains what deep learning is and how it works and presents an example use case from the energy industry. -
In this inaugural podcast episode and transcript, Terry Palisch, who will officially begin his 2024 SPE presidency in October, discussed his views of the challenges facing our industry and SPE members, his outlook for our industry, and what his goals will be during his presidency.
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Over a 10-year period, sensors monitoring the motion and loads near subsea wellheads have been mounted on more than 300 drilling campaigns. Integrity parameters were calculated to assess whether subsea conductors provided the intended amount of support during drilling operations. In several of these campaigns, loss of conductor support due to integrity issues was obse…
The partnership plans to develop an overlying software suite, Data Mesh, to consolidate data from various sources and increase data-access efficiency.
A recently signed contract lines the company up to provide autonomous ocean robots for inspection of the oil giant’s subsea field developments in the Gulf of Mexico.
The agreement will put SLB’s Delfi software to work in Ineos’ oil and gas operations.
The 5-year contract with global ROV equipment and services provider ROVOP supports Energean’s field development within the wider Katlan area adjacent to Israel’s Karish gas field.
With a rapid transition toward renewable energy, the energy sector has an increased reliance on technology. This makes it particularly vulnerable with regard to cybersecurity.
The Angolan oil and gas producer will use the Palantir Foundry software suite across its operations.
While master data management is crucial for maintaining data integrity and supporting business processes, it often goes ignored in mid- to large-size oil and gas companies. Most think that implementing robust enterprise resource planning will solve all master data problems. They find they are sorely mistaken when, after investing millions of dollars in a new accountin…
The data center will tap into India’s wealth of geoscience data to investigate key exploration and production data while building an extensive knowledge base of India’s sedimentary basins and fields.
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The authors of this paper propose an automated approach to sand prediction and control monitoring that improved operational efficiency by reducing time spent on manual analysis and the decision-making process in a Myanmar field. -
This paper explores electrical submersible generator design considerations, theoretical underpinnings, and potential future applications. -
This paper focuses on characterization of fracture hits in the Eagle Ford, methods to predict their effects on production, and mitigation techniques. -
Machine learning has been shown to have a promising role in oil and gas explorations in recent years. Among the applications, determining a proper location for injection and production wells along with their optimal operating conditions is a complex problem.
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This paper presents an approach to optimize the location of wellhead towers using an algorithm based on multiple parameters related to well cost. -
The authors of this paper present an artificial-lift timing and selection work flow using a hybrid data-driven and physics-based approach that incorporates routinely available pressure/volume/temperature, rate, and pressure information. -
Large methane emissions occur from a wide variety of oil and gas industry sites with no discernable patterns, thus requiring methods to monitor for these releases throughout the production chain. This paper describes a continuous monitoring system based on the Internet of Things using methane concentration sensors permanently deployed at facilities and connected to a… -
This paper presents a comprehensive technical review of applications of distributed acoustic sensing.
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The authors of this paper describe a procedure that enables fast reconstruction of the entire production data set with multiple missing sections in different variables.
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This paper presents a physics-assisted deep-learning model to facilitate transfer learning in unconventional reservoirs by integrating the complementary strengths of physics-based and data-driven predictive models.
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This paper examines how connected technology can help streamline safety processes and improve worksite efficiency.
