Microsoft and SLB launch Azure reservoir-modeling workflow

Microsoft and SLB have made Agile Reservoir Modeling integrated with Azure Data Manager for Energy generally available, combining SLB software with Azure high-performance computing and scalable storage to run reservoir-model ensembles against shared, governed subsurface data.

Rather than rely on a single subsurface interpretation, Microsoft says ensemble modeling evaluates hundreds of reservoir realizations together. In the new workflow, Azure Data Manager for Energy provides the governed data foundation. Engineers use SLB’s Petrel software to define interpretations and uncertainty workflows, while Agile Reservoir Modeling generates realizations, prepares simulation cases and coordinates runs for supported SLB simulators, including Intersect and Eclipse.

Azure high-performance computing runs multiple realizations in parallel. A shared Azure Files volume holds model inputs, grids, simulation decks, temporary files and results for concurrent jobs. Microsoft says compute capacity, storage capacity, throughput and input/output operations can scale independently, but it did not provide a tested configuration, performance benchmark or cost comparison.

The data layer uses OSDU-aligned services and domain data management services for seismic, wellbore, interpretation and simulation data. Microsoft’s Reservoir DDMS documentation says the service stores reservoir models, grids, simulation inputs and simulation outputs. The service was already generally available before the integration was announced.

After simulations finish, SLB reservoir engineering services manage the ensembles. Engineers can use Azure Data Manager for Energy search to discover, filter and sort realizations and published results. They can then examine the ensembles in SLB’s reservoir engineering workspace or load them into Petrel for interpretation, history matching and further studies. Search results are filtered by the user’s permissions.

Microsoft says access is governed through Azure Data Manager for Energy entitlements integrated with Microsoft Entra ID and OSDU legal tags. The company claims that building ensembles from corporate data and publishing results for discovery and reuse can reduce data movement, remove workflow friction and improve collaboration across asset teams.

It also says teams can stress-test development concepts against calibrated ensembles and update their reservoir understanding when new wells or data arrive, allowing risk-aware decisions without a major model rebuild. The supplied sources include no independent customer deployment, adoption figures or measured outcomes for the efficiency, collaboration or decision-making claims.

Separately, SLB’s product description says Agile Reservoir Modeling generates multiple subsurface models, uses cloud high-performance computing and stores labeled data for access through an OSDU platform. Microsoft’s announcement did not specify Azure region availability, pricing, minimum deployment architecture, virtual-machine families, concurrency limits or supported simulator versions.