Using Artificial Intelligence in the Upstream Energy Market

March 30, 2022

Oil and natural gas remain two of the most valuable commodities in the energy sector. There has never been a greater emphasis on efficiency, minimizing downtime, and reducing environmental impact while meeting economic goals. From an oil well to a topside platform to a refinery, meeting objectives in terms of safety, cost, carbon, and production necessitates a well-defined strategy.

Artificial intelligence (AI) can help meet these needs and save billions of dollars in capital and operating expenditures. With the integration of a data strategy and AI solutions, oil and gas firms can get vital insights to improve their business outcomes in their upstream processes.

Examples of AI applications in the oil and gas industry include:

  • Optimizing production with computer vision to analyze seismic and subsurface data faster.
  • Minimizing downtime for predictive maintenance on equipment.
  • Analyzing reservoirs and supercharging operational decision-making.
  • Modelling to predict oil corrosion risks to reduce maintenance costs.
  • Digitizing records and automating the evaluation of acquired geological data and charts, potentially revealing concerns such as pipeline damage or increasing equipment utilization.
  • Boosting or substituting some human competencies, allowing humans to focus on more creative, value-added activities.
  • Assisting in filling the labor gap as older generations retire, increasing productivity benefits.
  • Improving the efficiency of oil and gas assets, saving hundreds of thousands of dollars on inventory and tightening supply chains.

Artificial Intelligence in Action

According to a market research report by Mordor Intelligence, global artificial intelligence in the oil and natural gas market was worth $2.03 billion in 2021, and it is predicted to grow to $3.67 billion by 2027, with a compound annual growth rate (CAGR) of 10.81% over the forecast period (2022-2027).

  • Avin International, an independent tanker operator operating in the shipment of crude oil and petroleum, is partnering with Windward, a predictive intelligence business, to use AI in global marine trade. Windward will use its AI-powered platform to improve its sanctions compliance program, inspect vessels, and evaluate marine traffic and port congestion to improve tank operations. The software examines a variety of characteristics, such as vessel behaviour, ownership structures, company risks, and other factors, and makes real-time predictions.
  • Companies such as BP and Royal Dutch Shell, which have both committed to achieving net-zero carbon emissions by 2050, are under increasing pressure to reduce their carbon footprint to comply with the Paris Agreement on climate change. Shell is using AI to perform predictive maintenance on individual pieces of equipment and entire systems to lower its carbon footprint. This enables businesses to anticipate and address potential equipment failures before they occur.
  • Baker Hughes, an energy technology company, and AIQ, an AI joint venture between the Abu Dhabi National Oil Company (ADNOC) and Group 42 (G42), announced a strategic collaboration agreement in November 2021 to develop advanced analytics solutions for the global oil and gas industry. Since drilling is a capital-intensive activity, the first phase of the project will focus on developing AI solutions, evaluating drilling data, and identifying opportunities for ADNOC to optimize drilling routes and programs using existing Baker Hughes digital products.

Tips for Successfully Adopting AI into Your Business

When evaluating the implementation of AI in your oil and natural gas business, consider the following:

  1. Recognize your company's requirements and determine how AI can help. A team of advisors can help you decide what works for your specific challenges.
  2. Identify the right executive sponsorship to infuse AI within existing business processes.
  3. Implement AI across the board, not just in one division. Work to have the right IT infrastructure needed to deploy the AI solution.
  4. Expand your digital strategy and plan to include suppliers and other third parties.
  5. Create your own path — there is no one-size-fits-all solution. Clearly define the business objectives and outcomes to be achieved using AI.
  6. Apply an appropriate mix of technical team resources, such as business analyst, engineers, software developers, and data scientists. Set the right initial expectations about the potential benefits of AI with the team.
  7. Manage market or competitive pressures to accelerate AI infusion within our organization.

Having end-to-end AI-powered business decision-making solutions can help accelerate digital transformation in the oil and gas industry. AI solutions specifically designed for the oil and gas market can help you make intelligent predictions, automate operations, and seize opportunities.

About Richard Stepler

Richard Stepler is a Partner in the Private Client Services Group and leader of the Oil and Gas Services Group.