Rudy Lai

AI @ ConocoPhillips

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

Summary

  • ConocoPhillips has steadily increased AI adoption from 2021 through early 2026, integrating machine learning and advanced analytics widely across exploration, drilling optimization, reservoir management, and operational decision-making.
  • Key initiatives include enterprise-wide deployment of the Schlumberger DELFI cognitive E&P platform (2022), global roll-out of digital twin technology for operational simulations (2023-2024), and the use of AI-driven workflows in Permian Basin assets to improve decision speed and reduce operational costs (2024-2025).
  • By 2025, AI investment underpins significant workforce reductions (~3,200 layoffs, around 25% of employees) aimed at boosting efficiency and cost savings; leadership emphasizes AI's role in operational efficiency, data quality improvements for systems like SAP S/4HANA, and positioning the company amid evolving AI-driven energy demand cycles.

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5 AI Use Cases at ConocoPhillips

Workforce Efficiency
2025
Traditional
Generative
Agentic
Outcome
Costs
AI technologies automate administrative and operational tasks resulting in significant workforce reductions and enhanced operational efficiency, highlighting transformation in staffing models and cost structures. [1]
Operational Decision
2024
Traditional
Generative
Agentic
Outcome
Costs
AI and machine learning workflows integrate multivariate data sets (geological, completion, development) to accelerate decision-making processes in asset development, notably within the Permian Basin operations. [1][2]
Reservoir Management
2024
Traditional
Generative
Agentic
Outcome
Revenue
Utilizing AI for predictive modeling and real-time analysis of reservoir data, including shut-in pressures, to improve resource development decisions and optimize production outcomes. [1][2]
Digital Twins
2023
Traditional
Generative
Agentic
Outcome
Costs
ConocoPhillips deploys portfolio-wide digital twin technology to simulate major operations such as artificial lift and well interventions, allowing data-driven optimizations and strategic decisions across mature fields. [1][2]
Drilling Optimization
2023
Traditional
Generative
Agentic
Outcome
Costs
ConocoPhillips applies machine learning models to analyze geological and drilling data to unlock optimal operational parameters, enabling drilling crews to increase advance rates and reduce supply costs. [1]

Timeline

2026 Q1

2 updates

ConocoPhillips continues to realize tangible benefits from AI investments enhancing operational safety and decision-making, with industry commentary noting generally slow ROI across oil and gas but highlighting ConocoPhillips' successes.

2025 Q4

4 updates

Continued progressive integration of advanced AI and machine learning in exploration, drilling, and operational optimization; highlighted in industry reports and stock analysis, with CEO Ryan Lance active in equity markets amid this technological transformation.

2025 Q3

4 updates

AI-powered transformation accelerated with large language models automating vital data extraction; leadership Pragati Mathur emphasized moving from AI potential to performance; company underwent major layoffs (~25%) leveraging AI for operational cost savings and efficiency gains.

2025 Q2: no updates

2025 Q1

6 updates

ConocoPhillips reported mixed outlook on AI-driven natural gas demand with focus on LNG strategy; workforce reductions of up to 3,200 jobs (~25%), with leadership highlighting AI investments as key for cost savings, operational efficiency, and future competitiveness.

2024 Q4

2 updates

ConocoPhillips recognized as one of the AI growth stocks by UBS investors; digital transformation initiatives included SAP S/4HANA clean core foundation to enhance quality data for AI and machine learning applications.

2024 Q3

3 updates

Launched AI-powered workflows integrating geological, completion, and performance data for Permian Basin assets, enabling faster, more economical decision-making; partnered with Raptor Data for plug and abandonment solutions leveraging AI.

2024 Q2

2 updates

ConocoPhillips secured additional AI-related patents related to resource development systems and methods; the company publicly addressed AI and electrification as key trends in its 2024 stockholder meeting.

2024 Q1

3 updates

ConocoPhillips presented advancements in predictive modeling and real-time reservoir data analysis, applied for AI patents including methods using shut-in pressures in reservoir management, highlighting continued innovation in AI research.

2023 Q4

2 updates

Successful pilots led ConocoPhillips to adopt portfolio-wide digital twin technology covering artificial lift, well intervention, and oilfield chemistry using AI, machine learning, and data mining to enhance mature fields and production.

2023 Q3

2 updates

ConocoPhillips signed agreements with Wyld Networks to enhance AI networking capabilities and utilized machine learning models to optimize Lower 48 drilling operations, resulting in efficiency gains including drilling crews advancing over 60 feet more per day.

2023 Q2: no updates

2023 Q1: no updates

2022 Q4: no updates

2022 Q3: no updates

2022 Q2: no updates

2022 Q1

1 updates

Enterprise-wide deployment of Schlumberger's cloud-based DELFI cognitive exploration and production environment at ConocoPhillips enabled advanced digital transformation and cognitive E&P capabilities.

2021 Q4: no updates

2021 Q3: no updates

2021 Q2: no updates

2021 Q1

1 updates

ConocoPhillips launched a comprehensive seismic processing and machine learning platform leveraging Apache Spark to handle data and interprocess communications for seismic HPC workloads.