Tuesday, December 17, 2024

The Role of Artificial Intelligence in Energy Exploration in 2025

Artificial intelligence (AI) seems to be permeating everything we do, from the innocuous to the incomprehensibly complex. It’s hard to find an industry that hasn’t identified, and started implementing ways, to supercharge operations and strategy using AI.

In the energy industry, AI is beginning to revolutionize software, hardware, and system integration encompassing downstream, midstream, upstream oil and gas among other sectors.

The explosive growth is driven by the increasing adoption of AI technologies for optimizing operations, improving safety, and adding a measurable degree of certainty in decision-making.

North America

North America is a leader in the adoption of AI in the energy industry. The region accounts for slightly over 38% of the global AI energy market. Why?

Major energy companies and tech giants are developing AI solutions – primarily in Canada and the United States. Unconventional methods of oil and gas production have also driven the adoption of AI technologies to optimize performance.

In 2023, the oil and gas market in North America was valued at approximately $2.8 billion. It is projected to rise to $5.96 billion by 2028, at a compound annual growth rate of 13.3% from 2023 to 2028.

Key Applications and Technologies

1.    Enhanced Oil Recovery

Enhanced Oil Recovery (EOR) refers to a class of techniques used to increase the amount of crude oil that can be extracted from an oil field. Typically, after traditional methods, EOR helps extract a significant amount of oil trapped in a reservoir that can’t be recovered.

AI can often help with:

  • Reservoir characterization to get accurate characterization, including porosity, geological features, permeability, and fluid properties, to calculate the precise reservoir simulation and performance prediction
  • Intelligent reservoir monitoring and management for optimized production.
  • Selecting the most suitable EOR techniques based on reservoir conditions improves recovery rates.
  • Optimizing EOR operations to maximize oil recovery while minimizing operational costs.

The benefits don’t end there; however, with machine learning and deep learning, genetic algorithms, digital twins, AI and IoT integration, companies can fine-tune the extraction process to a high degree.

2.    Predictive Maintenance

Unexpected maintenance issues are a common occurrence due, in part, to the complexity and scale of oil and gas production in North America. Machine learning algorithms are now being deployed to analyze data from sensors and sift through historical records.

AI brings insights that help predict equipment failures before they happen. This technology can be applied in the field as well to monitor equipment performance and detect issues early. This helps reduce downtime and maintenance costs.

3.    Drilling Optimization

AI can be leveraged to provide real-time data analysis and precise drill-bit steering, reducing non-productive time, improving safety, and enhancing drilling efficiency. These systems can be trained to detect anomalies and abnormal conditions and take immediate action to correct errors.

Additionally, the algorithms can analyze historical data to create decision-making systems, such as drill bit selection and techniques.

4.    ESG (Environmental, Social and Governance) Goals

The Internet of Things (IoT) promises to be a game changer for companies looking to meet their ESG requirements. Machine learning algorithms can process data from a wide variety of sources, such as geological surveys and sensors, to monitor and detect things such as leaks and emissions.

Most people feel that we are still behind on this issue and the new technologies are part of vindicating that sentiment. This leap forward should be viewed as an opportunity for oil and gas companies to coordinate timely interventions and adhere to environmental regulations.

These companies hope to optimize energy usage in oil and gas operations to reduce their carbon footprint significantly. AI can also help predict energy demand and help identify opportunities for integrating renewable energy sources into the process.

5.    Digital Twins

A digital twin is a virtual replica of a physical asset, system, or process, and oil and gas companies are using them in conjunction with real-time data gathering and simulations to mirror the performance, condition, and behavior of its real-world counterpart.

Digital twins are often designed for real-time monitoring and diagnostics, predictive maintenance, operations optimization, asset lifecycle management, and remote monitoring and control.

For example, BP has implemented digital twins for its offshore platforms, Chevron uses them to optimize the performance of its refineries, and Shell has deployed digital twins for its deepwater operations in the Gulf of Mexico.

6.    Logistics

AI is being extensively applied to logistics in several ways, with interesting results:

  • AI provides insights into demand forecasting, inventory management, and logistics planning. Predictive analytics can anticipate demand fluctuations, allowing companies to adjust their operations accordingly.
  • Analysis of real-time data from sensors and historical data is leveraged both off- and on-shore to maintain optimal inventory levels and reduce risks of overstocking or understocking.
  • AI-driven demand planning and forecasting tools analyze market trends, external factors, and data to predict future demand and plan procurement and logistics accurately.
  • AI can automate procurement processes by analyzing supplier performance, market conditions, and historical data.

Almost every aspect of logistics, from monitoring to route optimization, can benefit from powerful AI solutions.

Future Prospects

According to an extensive report by Research and Markets, the integration of AI in the oil and gas industry is expected to continue growing, with a focus on:

  • Sustainability – AI is expected to play a crucial role in reducing the environmental footprint of oil and gas operations by optimizing resource use and minimizing waste.
  • Safety – AI can enhance safety by providing real-time monitoring and identifying potential hazards.
  • Operational efficiency – AI is already streamlining logistics and refining decision-making for smoother operations.
  • Greater automation – Companies will increasingly automate as many processes as they can for efficiency gains.
  • Enhanced predictive analytics – To anticipate needs and meet them accurately will help with demand forecasting and inventory management.
  • Carbon Capture and Storage – What was once a hypothetical technology is now seeing increased investment and breakthroughs that show its true potential could be world-changing.

The full impact of artificial intelligence is still unfolding, and companies need to keep an eye on the market as AI technologies advance, to make full use of these new capabilities.

Looking for a digital engineering partner for your next project?

Vista Projects is an integrated engineering services firm able to assist with your energy project. With offices in Calgary, Alberta, Houston, Texas, and Muscat, Oman, we help clients tailor engineering phases for the unique needs of their projects. Contact us today!



source https://www.vistaprojects.com/the-role-of-artificial-intelligence-in-energy-exploration-in-2025/

source https://vistaprojects2.blogspot.com/2024/12/the-role-of-artificial-intelligence-in.html

Tuesday, December 10, 2024

Digital Twins in the Energy Industry: Transforming Operations in North America

According to a new report by GlobalData, the global digital twins market is set to hit over $150 billion by 2030. In the early days of the technology, digital twins were used in capital-intensive operations to streamline processes, save money, and control emissions.

Since then, companies have seen the benefits of making digital twins of entire operations, including refineries, terminals, pipelines, plants, offshore platforms, and more.

The benefits of accessing real-time data, analytics, and simulations allow operations to optimize each step and catch issues before they cause problems.

In this article, we examine how the technology is being implemented in North American energy operations to gain some insights into the future.

How The Technology Works

To understand the benefits, it is worth briefly explaining how the technology works.

A digital twin is a virtual replica of a physical process, asset, or system. It is often equipped with high-tech sensors to gather real-time data and advanced analytics to mirror the physical world in a digital format.

digital twinning in the energy industry

With this tool, energy companies can conduct simulations, analysis, and control of the physical counterpart. The technology’s components include:

  • An interconnection of sensors and IoT devices
  • Data integration platforms like OSIsoft PI System or AVEVA’s Unified Engineering
  • Data processing and storage
  • Cloud computing
  • Modeling and simulation with hyper-detailed 3D models of physical assets
  • Simulation tools like Simulink or ANSYS to run scenarios and predict the behavior of assets
  • Analytics and machine learning capabilities to crunch data and predict future events
  • Augmented Reality (AR) and Virtual Reality (VR) provide immersive and interactive interactions

The technologies come together to offer several benefits, which we discuss below.

The Reported Benefits of Digital Twins in Energy Industry Operations

Companies that have implemented digital twin technology report benefits that fall into the following categories:

1.    Operational Efficiency

Digital twins can be used to predict equipment failures and schedule maintenance proactively, reducing unplanned downtime by a significant percentage. By simulating various operational scenarios, digital twins can lead to a 10 to 15% increase in production efficiency.

2.    Cost Savings

Energy companies can save a lot of money by monitoring issues and mitigating them before they become serious through what is called predictive maintenance. It is also a great way to pre-plan the projects for the best execution which, over time, leads to reduced capital expenditures.

3.     Safety and Reliability

Real-time monitoring and predictive analytics improve safety by identifying potential hazards and correcting them before people work in the area. Digital twins can drastically reduce accidents and incidents related to safety standards.

Additionally, continuous monitoring and simulation can enhance operations reliability, with fewer unexpected failures.

digital twins in the energy industry

4.    The Environmental Impact

With the sensors you can post everywhere to view, record, or track emissions, energy companies can monitor flaring and other emissions to not only reduce equipment failures, but also have an informed way of how to do so.

The companies can also improve the efficiency of carbon capture and storage, helping reduce their carbon footprint.

5.    Time-to-Market

All the benefits of a speedy, less glitchy operation do not just mean cost savings; it also means energy companies can efficiently and quickly get their products to market. The digital twins provide accurate simulation and real-time data, allowing the operators to get their processes right from the beginning.

6.    Enhanced Decision-Making

The best decision-making is dependent on how much you know about the situation. With the implementation of digital twins, a lot of guesswork or lengthy processing is taken out of the equation.

This leads to better strategic planning and operational adjustments to meet the changes as they come.

7.    Resilience Improvement

The ability to simulate different scenarios allows companies to plan for various contingencies. It also improves resilience across the systems, ensuring that downtime is not a big issue and that taking a hit in any given area can be addressed quickly.

8.    Training and Development

Due to the highly detailed nature of well-made digital twins and with the aid of AR and VR, new recruits or people looking to improve their skills or implement new efficient processes to the existing workflow can benefit from the training it offers.

They do not just have to rely on the theoretical aspects of what they need to learn; they can see it in action without taking up space anywhere near physical assets or installations. It also means that they can be trained from anywhere in the world with an Internet connection.

9.    Supply Chain and Inventory Management

By providing a comprehensive view of the supply chain, digital twins help in optimizing logistics and reducing delays. With the implementation of real-time tracking of products and materials, companies can ensure timely availability and reduce inventory expenses.

Which Companies are Leading The Charge In North American Digital Twin Implementation?

In North America, the following energy companies have digital twin implementations with the expectation more will join in the coming years.

BP’s Argos Floating Production Unit

From its inception, this operational unit was meant to be high-tech and implemented a dynamic visual twin with real-time data and machine learning, training programs with HoloLens smart glasses, and more.

Chevron

As part of the Permian Basin-based Project Astra led by the University of Texas at Austin, Chevron is developing a digital twin of the pilot region with a methane sensor network to simulate and predict emissions.

The company also uses digital twins to facilitate remote collaboration, connecting teams in Houston to platforms in Australia as a demonstration of the technologies’ capabilities.

Equinor

Equinor has implemented digital twins in the Bakken Formation to optimize shale oil and gas operations and in the Marcellus Shale to improve well performance and reduce environmental impact. It also uses the technology in the Gulf of Mexico to enhance safety and efficiency in offshore operations.

Looking to the Future

The future of the energy industry’s relationship with digital twins looks bright. The technology has shown many companies that they can enhance maintenance and reduce downtime, increase operational efficiency and optimization, experience better asset performance and higher extraction rates, and enhance safety standards.

The technology implementation will continue to integrate with emerging technologies such as IoT, machine learning, artificial intelligence, and advanced analytics.

Looking to learn more about digital engineering and how it can help your business thrive?

Vista Projects is an integrated engineering services firm able to assist with your system integration and digital engineering projects. With offices in Calgary, Alberta, Houston, Texas, and Muscat, Oman, we help clients with customized system integration and engineering consulting across all core disciplines. Contact us today!



source https://www.vistaprojects.com/digital-twins-in-the-energy-industry-transforming-operations-in-north-america/

source https://vistaprojects2.blogspot.com/2024/12/digital-twins-in-energy-industry.html

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