How IoT, Data, and AI Can Drive Process Efficiency in the Energy Sector

The energy industry is navigating a complex landscape shaped by geopolitical factors, macroeconomic headwinds, evolving regulations, and rapid technological change.

To thrive in this environment, leaders are increasingly turning to artificial intelligence (AI), Internet of Things (IoT) sensors, and advanced data analytics to optimize processes, reduce costs, and mitigate risks. 

However, they face foundational limitations in their space compared to other industries:

1. Connectivity constraints: Upstream operations (often located in remote or offshore areas) struggle with limited connectivity, hindering the seamless integration and real-time data exchange essential for digital transformation.
2. Hardware and IoT limitations: The harsh and hazardous environments in which the equipment operates pose challenges to the deployment and reliability of IoT devices and advanced hardware, limiting the scope of technological adoption. Additionally, the reliance on third-party dependencies for hardware and software components introduces potential vulnerabilities and compatibility issues that can further complicate implementation.
3. High-performance computing in remote locations: The need for powerful computing resources in distant, off-grid locations presents logistical and technical difficulties, making it harder to process and analyze vast amounts of data on-site.
4. Dependency on external technological readiness: Even if you’re at the forefront of technological adoption, progress can be impeded by the technological maturity of your partners, suppliers, and other stakeholders in the ecosystem.
5. Significant change management: The shift towards digitalization and advanced technologies is a substantial undertaking that requires a committed, industry-wide effort to transform established processes, practices, and mindsets.

These foundational limitations underscore the need for a collaborative, ecosystem-wide approach to drive digital transformation in the oil and gas sector, addressing unique challenges through tailored strategies and solutions.

Working with our clients in this sector, two key themes have emerged:

1. Improving process efficiency
2. Ensuring high-quality, "clean" data to enable advanced analytics. 

Let's dive deeper into each of these priorities.

Boosting Process Efficiency with AI and Automation

Many energy processes today remain highly manual and prone to human error. Even small mistakes, like a technician inputting an incorrect equipment reading, can cascade into major issues downstream. AI and machine learning offer immense potential to automate and optimize these processes.

Computer vision algorithms can analyze video feeds to ensure proper safety protocols are being followed on rigs and in refineries. Natural language processing can extract insights from unstructured data like maintenance logs and inspection reports. Machine learning models can predict equipment failures weeks in advance, enabling proactive maintenance.

The tech is far more accessible than you might believe, and the key to success lies in starting small. As you embark on these initial initiatives, seize the chance to lay the groundwork for tackling fundamental challenges, such as ensuring your data is primed and ready for AI consumption.

Experience has shown that grand-scale projects often falter right from the start, as they demand an overwhelming level of change that can strain your organization's capacity to adapt while maintaining ongoing operations. By opting for a more gradual approach, you can navigate the transformative process at a pace that allows for seamless integration without compromising your day-to-day activities.

With the right data infrastructure and governance in place, the opportunities to drive efficiency through AI are nearly limitless.

Ensuring Data Quality & Integrity

Much of the data generated by energy assets is noisy, incomplete, or siloed across legacy systems. Before investing heavily in AI, companies need to ensure they have clean, integrated data pipelines in place. This requires bringing together IT and OT, harmonizing data models, and establishing strong data governance.

Cloud platforms like AWS provide the foundation for breaking down data silos and enabling advanced analytics at scale. With tools for data warehousing, ETL, and data lakes, oil and gas companies can more easily integrate disparate data sources and make quality data available for AI/ML. 

Of course, moving sensitive exploration and production data to the cloud requires careful planning around data security, residency, and compliance. This is where having an experienced partner is key.

How Protagona Partners with Energy Sector Leaders:

At Protagona, we’re proudly rooted in Texas and greatly enjoy working with those in the energy sector to help with their modernization efforts.

Here’s how we successfully engage with our partners in the energy sector to implement solutions powered by AI, IoT, and clean data:

1. We begin with an ideation workshop, collaborating closely with our clients to understand their specific challenges and objectives. The key to successful ideation is to dream big while staying grounded in reality. We encourage our clients to 'start small' by identifying the most critical pain points and opportunities within their value stream. By employing Value Stream Mapping (VSM) techniques, we help our clients visualize and prioritize the areas where technological interventions can deliver the greatest impact.

2. We combine deep industry expertise with cutting-edge data science. Our teams bring together decades of experience in upstream, midstream and downstream operations with advanced capabilities in machine learning, computer vision, natural language processing and edge computing. This allows us to develop fit-for-purpose solutions that drive measurable impact.

3. We put data at the center. We help energy companies break down silos and establish a strong data foundation to power AI and analytics. Our data engineers and architects work hand-in-hand with client teams to integrate disparate data sources, ensure data quality and integrity, and implement robust governance frameworks. We also bring deep knowledge of industry data standards like OSDU and PPDM.

4. We leverage the power of the cloud. We help energy companies harness the scalability, flexibility, and advanced capabilities of platforms like AWS to accelerate their digital initiatives. With strong partnerships across the cloud ecosystem, we enable clients to tap into the latest innovations in areas like IoT, edge computing, digital twins and advanced visualization.

5. We prioritize security and compliance. We understand the critical importance of data security and privacy for oil and gas companies. We bake in comprehensive controls and safeguards to ensure sensitive information remains protected while maintaining compliance with complex industry regulations.

6. We focus on empowering people. While AI and automation are incredibly powerful, we never lose sight of the human element. We put significant emphasis on change management, training, and upskilling to ensure that client teams are able to fully leverage new tools and capabilities. Adoption and sustainability are always top of mind.

Eyes on the Prize

Energy leaders have a tremendous opportunity to leverage AI, IoT, and data to drive step-change improvements in efficiency, agility, and risk management. But success requires more than just investing in the latest digital technologies. It demands fundamental operational shifts, a commitment to data excellence, and strong alignment between business and IT units.

Leaders that get this right will be well-positioned to navigate the uncertain road ahead. By harnessing data to work smarter and faster, they'll be able to optimize production, reduce downtime, enhance safety, and consistently deliver to the bottom line.