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You’ve heard of generative artificial intelligence, and odds are you’ve used it. But do you know how it works?
Each year during its Annual Technical Conference and Exhibition (ATCE), SPE honors members whose outstanding contributions to SPE and the petroleum industry merit special distinction. Recipients will be recognized at the Annual Awards Banquet on Tuesday, 24 September.
Since the late 1930s, the offshore industry has advanced from the first platform in 14 ft of water to the ultradeepwater 20K era. Driven by seismic, drilling, and development breakthroughs, the industry has pushed into deeper waters, high-pressure reservoirs, and new frontiers like Guyana, continually expanding the limits of offshore exploration.
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In this inaugural episode of his vodcast and column, 2025 SPE President Olivier Houzé shares his insights on the challenges facing our Society and its members, as well as his vision for his presidency. -
Surveillance technologies have undergone a revolution, reshaping how facilities, wells, and reservoirs are monitored. These advancements not only have increased the scale at which these technologies are deployed but also have led to an unprecedented influx of data. The sheer volume of data, however, poses a significant challenge to traditional analytical methods.
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Collaboration agreement lays foundation for advancing tech and know-how for harsh environment operations.
The firm’s latest report, Leading a Data-Driven Transition, presents the results of its annual survey of nearly 1,300 senior professionals and divides the respondents into two groups, which it calls “digital leaders” and “digital laggards.”
The support vessel operator has invested in project-management software and in making connections using Starlink satellites.
European oil and gas company Aker BP has agreed to a software-as-a-service collaboration with software firm Aize.
The Norwegian data company has launched a 3D seismic survey in the Equatorial Margin area.
The company has agreed using its innovations in automation in an effort to derisk ultradeep offshore drilling for the Brazilian national oil company.
The company says the field has achieved a 25% production capacity increase through the user of advanced digital technology.
Implemented for the first time offshore, the technology uses artificial intelligence to operate wells autonomously.
The planned long-term partnership aims to digitally transform Aker BP’s subsurface workflows in an effort to lower costs, shorten planning cycles, and increase production.
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This paper presents a novel modeling framework for predicting residual oil saturation in carbonate rocks. The proposed framework uses supervised machine learning models trained on data generated by pore-scale simulations and aims to supplement conventional coreflooding tests or serve as a tool for rapid residual oil saturation evaluation of a reservoir. -
This paper describes a new integrated workflow for automated well monitoring using pressure and rate measurements obtained with permanent gauges and flowmeters. -
This paper proposes a method to radically revise the well-path-generation process to reach the vision of planning a well in one day with high quality, relying on the collection of experienced-based constraints from each discipline to generate possible alternatives. -
The goal of the project described in this paper was to test the added value of shear-wave velocity interpreted from underwater multichannel analysis surface waves, particularly as a propagation tool of geotechnical information.
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This paper describes the development of a comprehensive digital solution for well surveillance and field-production optimization for an offshore field consisting of four stacked reservoirs, each containing near-critical fluids. -
This paper describes a workflow that has been established to calculate the value of reservoir surveillance in producing gas fields based on established value-of-information methods. -
This paper describes an approach that combines rock typing and machine-learning neural-network techniques to predict the permeability of heterogeneous carbonate formations accurately. -
This study describes the performance of machine-learning models generated by the self-organizing-map technique to predict electrical rock properties in the Saman field in northern Colombia.
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This paper presents an automated underwater robot and a nondestructive testing eddy-current probe for alternating-current field measurement analysis of jacket main welds.
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This study compares seven imputation techniques for predicting missing core-measured horizontal and vertical permeability and porosity data in two wells drilled in the North Rumaila oil field in southern Iraq.
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It’s hard to create corporate or master data strategies when every user group you talk to has a different idea of what “good” should look like from their perspective.
