data science

This paper introduces an agentic artificial-intelligence framework designed for offshore production surveillance and intervention.

The objective of this study is to field test a non-nuclear multiphase flowmeter and assess its performance under challenging operating conditions.

Reaching further than dashboards and data lakes, the agentic oil field envisions artificial intelligence systems that reason, act, and optimize.

This paper describes the implementation of a one-way wave equation in slowness domain outputting gathers up to Nyquist frequency, which can be used to generate high-resolution seismic sections and amplitude-vs.-offset studies.

This paper presents a self-supervised approach for training a seismic foundation model and demonstrates scenarios in which it is used for seismic data conditioning, interpretation, and inversion through six real-use cases.

This paper provides an overview of an operator’s application of 4D time-lapse seismic technology over approximately a decade and includes future perspectives.

Sustainability in reservoir management emerges not from standalone initiatives but from integrated, data-driven workflows, where shared models, closed-loop processes, and AI-enabled insights reduce fragmentation and make sustainable performance a natural outcome.

This paper describes a decision-support system that integrates field data, system specifications, and simulation tools to quantify system performance, forecast operational challenges, and evaluate the effect of system modifications in water management.

GeoMap Europe is the latest in a series of interactive global geothermal maps that combine large subsurface and surface data sets to highlight where geothermal resources and development opportunities are strongest for power, heat, cooling, and storage.

This research aims to develop a fluid-advisory system that provides recommendations for optimal amounts of chemical additives needed to maintain desired fluid properties in various drilling-fluid systems.