The field,
now agentic.
The year energy stopped buying AI and started building it — read across our three most recent issues.
The Number Behind the Number
A 12.2% uplift against what baseline? A 75% inspection saving on which share of cases? A 25x that rides on its floor. This quarter keeps asking what a headline figure rests on, from AI production claims and shale design models to an LNG plant with 1.8 days of tank room, and the answer is usually a denominator, a baseline or one binding limit rather than the model.
Agents in the Field
An exploration-scale full-waveform inversion project routinely consumes millions of core-hours, and the bill concentrates in one inner loop: solving the wave equation, forward and adjoint, over and over. This whitepaper maps the seismic HPC workload, locates the bottleneck, and lays out the four levers, surrogates, hardware fit, compute-aware orchestration, and sample efficiency, that are moving depth imaging from an overnight batch job on a CapEx cluster toward an interactive, uncertainty-aware, elastic-compute workflow.
From AI Customer to AI Builder
Operators start building what they used to buy: domain-native wellbore LLMs, basin-trained seismic foundation models, VeerNet log digitisation, agentic MLOps and drilling agents in the field, carbonate vug and fracture vision, and a first move into lignin.