Tela™ agentic-AI assistant for asset evaluation insights

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Agentic-AI solution for rapid screening and evaluation of complex subsurface asset portfolios.

Overview

Asset evaluation insights uses multi-agent reasoning to extract, classify, and analyze large volumes of structured and unstructured asset data, including technical reports, well logs, time series, and models, to support acquisition, farm-in, and licensing decisions. Built on the Lumi™ data and AI platform and delivered through Tela™ agentic-AI assistant, it creates structured knowledge repositories and enables natural-language queries that surface risks, opportunities, and ranked asset potential, significantly reducing data wrangling and decision latency.

Challenges

• Asset evaluations often involve more than 100 GB of structured and unstructured technical data.
• Critical information is distributed across reports, well logs, models, schematics, and time-series datasets.
• Experts can spend more than 60% of their time on data gathering, preparation, and interpretation.
• Manual data wrangling delays investment decisions and increases opportunity costs.
• Evaluating multiple assets consistently and at scale can be difficult and resource-intensive.

Solution

• Ingest and organize structured and unstructured asset data into analysis-ready knowledge repositories.
• Automatically classify and extract production, reservoir, and technical information from diverse data sources.
• Apply multi-agent reasoning to connect, analyze, and interpret asset data.
• Enable natural-language interaction for rapid exploration of risks, opportunities, and asset potential.
• Accelerate acquisition, farm-in, and licensing evaluations through AI-driven insights and automation.

Features

• Comprehensive Data Ingestion – Ingest a wide range of asset data sources, including technical reports, well logs, schematics, time-series data, and subsurface models.
• Multi-Agent Knowledge Intelligence – Leverage specialized AI agents to classify, extract, link, and reason across asset information, creating structured knowledge repositories and traceable insights.
• Production and Subsurface Analytics – Analyze production performance, field characteristics, reservoir information, and asset metrics through structured dashboards and analytical workflows.
• Natural-Language Asset Evaluation – Query asset data using conversational prompts and receive contextual, evidence-based insights grounded in technical and operational data.
• Secure and Governed Deployment – Support human-in-the-loop validation, auditability, and deployment across hybrid, cloud, and on-premises environments.

Benefits

• Accelerate Asset Evaluation – Convert large volumes of technical data into actionable insights in a fraction of the time required by manual workflows.
• Reduce Manual Effort – Minimize data extraction, preparation, and interpretation across all asset data types.
• Improve Decision Quality – Surface contextual, data-driven insights to support acquisition, farm-in, and licensing decisions.
• Scale Across Asset Portfolios – Evaluate multiple assets consistently across different basins, environments, and portfolio sizes.
• Focus on High-Value Opportunities – Enable experts to spend more time assessing risks and opportunities rather than managing data.