Rudy Lai
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AI @ ConocoPhillips

Focus on upstream oil & gas
Industry
Last updated
July 3, 2025 at 10:44 AM

Summary

  • ConocoPhillips has progressively integrated advanced AI and machine learning technologies from 2021 through 2025, focusing on seismic data processing, reservoir management, and operational optimizations, including portfolio-wide digital twin implementations and AI-driven workflows for decision-making.
  • The company has developed proprietary AI patents and formed strategic partnerships to leverage AI for improving drilling efficiency, plug and abandonment activities, and real-time anomaly detections, thereby optimizing resource development and reducing operational costs.
  • Key figures include CIO Pragati Mathur leading digital transformation efforts, CEO Ryan Lance highlighting AI's role in business strategy, and multiple AI-related patents granted in late 2023 and early 2024, positioning ConocoPhillips as a recognized AI-driven leader in the oil & gas sector by 2025.

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7 AI Use Cases at ConocoPhillips

Information Extraction
2025
Traditional
Generative
Agentic
Outcome
Costs
Large language models autonomously extract and synthesize vital information from vast datasets to inform field development decisions, thereby enabling faster and better-informed strategic planning. [1]
Market Forecasting
2025
Traditional
Generative
Agentic
Outcome
Revenue
Using AI to analyze energy market trends and AI-driven demand forecasts helps ConocoPhillips optimize its LNG and gas strategies amid volatile markets and emerging technologies. [1][2]
Anomaly Detection
2025
Traditional
Generative
Agentic
Outcome
Risk
AI models monitor equipment such as plunger lifts by analyzing vibration and motor current patterns to detect anomalies early, preventing downtime and reducing maintenance costs. [1]
Operational Decision-Making
2024
Traditional
Generative
Agentic
Outcome
Costs
Machine learning workflows ingest geological, completion, development, and performance data to accelerate complex decision-making processes on assets like the Permian Basin, improving operational efficiency and cost-effectiveness. [1][2]
Reservoir Optimization
2024
Traditional
Generative
Agentic
Outcome
Revenue
AI-driven predictive modeling and real-time data analytics are applied to transform reservoir management challenges into operational opportunities, increasing recovery rates and operational efficiency. [1][2]
Digital Twins
2023
Traditional
Generative
Agentic
Outcome
Risk
Deployment of digital twin technology across the asset portfolio allows ConocoPhillips to simulate operational scenarios, optimize production, and preemptively manage interventions such as artificial lift and well maintenance. [1][2]
Seismic Analysis
2021
Traditional
Generative
Agentic
Outcome
Costs
ConocoPhillips utilizes AI to process and analyze vast seismic datasets rapidly and accurately, enhancing exploration efficiency and identifying optimal drilling locations. [1]

Timeline

2025 Q3

3 updates

Implementation of purpose-built AI models including large language models autonomously extracting critical information to drive efficient field development decisions; CIO Pragati Mathur leads AI transformation.

2025 Q2: no updates

2025 Q1

5 updates

Focus on optimizing plunger lift systems and artificial lift operations with AI models detecting anomalies; detailed market analyses reflect AI-driven energy demand forecasting amid volatile markets.

2024 Q4

2 updates

ConocoPhillips recognized among top AI growth stocks by UBS and monitored for AI-driven market and inflation response, highlighting investor confidence in AI contributions to future growth.

2024 Q3

3 updates

Development and deployment of AI- and ML-driven workflows accelerate decision-making for Permian Basin assets, improving efficiency in geological analysis, completion, and development processes; also involvement with Raptor Data for plug & abandonment optimization.

2024 Q2

2 updates

Continuation of AI patent development with three patents in Q1 2024 focused on resource development systems; management discusses AI's role alongside electrification in achieving sustainability goals.

2024 Q1

3 updates

ConocoPhillips continues innovation with five AI patents related to pressure management and resource development, and emphasizes AI-driven predictive modeling and real-time data analysis for reservoir challenges.

2023 Q4

2 updates

After successful pilots, ConocoPhillips expands digital twins technology globally across its portfolio, including artificial lift, well intervention, and mature fields for operational analytics.

2023 Q3

2 updates

ConocoPhillips partners with Wyld Networks and applies machine learning models to optimize Lower 48 operations, achieving significant drilling efficiency and cost reductions.

2023 Q2: no updates

2023 Q1: no updates

2022 Q4: no updates

2022 Q3: no updates

2022 Q2: no updates

2022 Q1

1 updates

Deployment of Schlumberger’s DELFI cognitive E&P cloud platform across ConocoPhillips, enabling enterprise-wide integration of AI-driven exploration and production workflows.

2021 Q4: no updates

2021 Q3: no updates

2021 Q2: no updates

2021 Q1

1 updates

ConocoPhillips launches a comprehensive seismic processing platform using Spark technology to enhance data analytics and machine learning capabilities in seismic high-performance computing (HPC) and cloud environments.