AIQ to integrate Rock Flow Dynamics’ tNavigator into Genesis AI-native energy operating system

AIQ to integrate Rock Flow Dynamics’ tNavigator into Genesis AI-native energy operating system

ABU DHABI, 5th November, 2026 (WAM) -- AIQ, the Abu Dhabi-based industrial AI company developing innovative solutions for the energy sector and beyond, announced the accessibility of Rock Flow Dynamics’ (RFD) tNavigator all-in-one subsurface platform, spanning seismic interpretation to surface network optimisation, on Genesis, AIQ’s AI-native energy operating system.

Announced at ADIPEC 2026, where AIQ is the AI Co-Host, this cooperation represents a milestone in connecting advanced engineering intelligence with enterprise-wide workflows and execution across the energy value chain.

tNavigator integrates every stage of subsurface work, from seismic interpretation to surface network optimisation, in one sophisticated package. It is an established integrated geoscience, modeling and simulation platform, supporting geoscientists and engineers in making complex technical decisions.

With tNavigator’s integration into Genesis, AIQ is advancing a new paradigm: moving from engineering intelligence in individual applications to intelligence connected across workflows, disciplines, and enterprise decisions.

Saravan Penubarthi, Chief Technology Officer of AIQ, said, “Traditionally, reservoir engineering workflows involve multiple applications, engineering specialists, datasets and decision-making processes. While each system delivers significant technical capabilities, connecting their outputs to broader operational and business workflows can require substantial manual coordination. Genesis is designed to address this challenge, and the integration of tNavigator extends this vision into reservoir engineering and simulation.”

Kirill Bogachev, Chief Technology Officer of RFD, stated, “Openness and extensibility are a core part of our roadmap, and tNavigator’s physics-based foundation is built to open a dialogue with AI technologies. This collaboration with AIQ is a genuine articulation of that strategy on the ground, bringing our reservoir modelling and geoscience analysis together with AIQ’s AI-native operating environment and making it all meaningfully accessible to our customers.”

Amin Harby, Vice-President Middle East at RFD, said, “This move puts tNavigator’s closed-loop modelling, high-speed calculations and solid physics at the heart of AI-enabled workflows for geoscientists and engineers. For operators in the Middle East and worldwide, it means trusted AI across seismic, geology, and field development planning. With AIQ’s expertise and RFD’s global reach, we will help customers unlock a new horizon of agile decision-making.”

Through this collaboration, subsurface workflows can become part of broader AI-enabled processes, connecting geoscience and reservoir analysis with multidisciplinary engineering, field development planning, and operational decision-making.

Potential applications include AI-assisted subsurface workflows: Supporting geoscientists and engineers in navigating static and dynamic modelling workflows, retrieving relevant subsurface information and interpreting results; and AI-enabled seismic interpretation: Applying machine learning to seismic data, from facies and horizon clustering to inversion that predicts petrophysical properties between wells, and connecting the results to modelling and decision workflows.

It also includes connected modelling and simulation workflows: Linking geological modelling, reservoir simulation and surface network activities with broader field development and planning processes; Multidisciplinary collaboration: Enabling subsurface insights to inform decisions across geoscience, reservoir, production, facilities and other engineering disciplines; Dynamic intelligence workflows: Connecting geoscience and engineering tasks, specialised tools, AI capabilities and human expertise through adaptive workflows; and Faster decision cycles: Reducing manual handoffs between technical analysis, scenario evaluation and downstream decision-making.