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SLB Releases Agile Reservoir Modeling (ARM) on Azure for Subsurface Uncertainty Analysis
Key points
- SLB's Agile Reservoir Modeling (ARM) is now generally available.
- ARM integrates with Azure Data Manager for Energy (ADME).
- The solution supports ensemble modeling for subsurface uncertainty.
- It uses Azure HPC and scalable storage for large-scale simulations.
New Solution for Reservoir Modeling
SLB has announced the general availability of its Agile Reservoir Modeling (ARM) solution. This offering is integrated with Azure Data Manager for Energy (ADME) and is designed to address challenges in subsurface uncertainty analysis for the energy industry.
Addressing Industry Challenges
Drilling campaigns are costly and complex, requiring precise subsurface understanding. Existing modeling infrastructures often struggle with the increasing scale and complexity of subsurface data. The ARM and ADME integration aims to provide a faster, more connected way to convert subsurface uncertainty into actionable decisions.
Ensemble Modeling Capabilities
ARM on Azure supports ensemble modeling, which evaluates hundreds of model realizations to provide a broader view of potential outcomes and better understand uncertainty and risk. This approach helps asset teams make more informed decisions by moving beyond single-model interpretations.
Historically, the adoption of ensemble modeling has been limited by infrastructure not designed for large-scale, parallel studies. ARM addresses this by distributing realization generation and simulation across elastic Azure high-performance computing (HPC) and utilizing scalable storage for capacity and parallel access.
Integrated Data Foundation
The solution connects reservoir modeling workflows to a governed data foundation. This integration helps manage various data sources, including seismic, wellbore, interpretation, and simulation data, along with the applications and compute resources that process them. This aims to prevent data fragmentation and facilitate large-scale simulations.
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Reporting from
SLB has made its Agile Reservoir Modeling (ARM) solution generally available, integrated with Azure Data Manager for Energy (ADME). This co-engineered cloud-scale solution aims to improve reservoir uncertainty analysis for drilling campaigns by connecting ensemble-centric reservoir modeling with Azure's high-performance computing and scalable storage.