Maria PesantezThe power of artificial intelligence (AI) is impacting different industries, including oil and gas. Despite this trend, many oil & gas operators remain hesitant to leverage machine learning capabilities. Various misconceptions are keeping many companies on the sidelines as their competitors run with the opportunities AI presents including analyzing acquisition opportunities, making investment allocation decisions, and optimizing drilling programs.
In this blog, we’ll debunk some of the most popular myths about artificial intelligence in oil and gas that we have learned working with top operators.
Myth 1: AI will replace your job…
Reality: Contrary to popular belief, AI is not here to replace your job but rather to augment your capabilities. AI technology is designed to automate repetitive tasks, process vast amounts of data, and generate valuable insights. This enables workers to focus on more complex decision-making processes and strategic planning. AI serves as a powerful tool that enhances efficiency, productivity, and overall operations, while the employee’s expertise remains irreplaceable.
Numerous studies and reports support the idea that AI complements workers rather than replacing them. According to a report by the World Economic Forum (WEF), by 2025, automation and a new division of labour between humans and machines will globally add 97 million jobs, while disrupting 85 million jobs. (Source: weforum.org/) This indicates that AI will contribute to job creation and the reshaping of roles rather than causing widespread unemployment.
Furthermore, as covered in a previous blog post, AI systems fall short in replicating the creativity, critical thinking, and problem-solving abilities of human employees. While they excel at processing vast data, human input remains essential for validating results and making complex judgments. Engineers in the oil and gas industry possess invaluable domain knowledge and adaptability, playing a crucial role in ensuring successful operations.
Myth #2: AI is too expensive for small/medium-sized E&P companies
Reality: Not true! The cost of implementing AI solutions has come down significantly in recent years, making it more accessible for oil and gas companies of all sizes. In fact, Novi Labs offers an off-the-shelf SaaS (Software as a Service) solution that can be up and running in just a few hours.
Traditionally, the perception has been that AI implementation comes with exorbitant costs, making it a luxury only affordable for large corporations. However, this is no longer the case. Advancements in technology and increased competition in the AI market have driven down costs, making AI solutions more affordable and attainable for small and medium-sized E&P companies.
To give you one example in the language modeling space, training costs for a large language model, similar to GPT-3 level performance, have significantly declined by 70% per year. This indicates a substantial annual reduction in costs. (Source: research.ark-invest.com)
This cost reduction can be attributed to factors such as improved hardware affordability, the availability of open-source AI tools and frameworks, and advancements in cloud computing.
Myth #3: Only big data projects can benefit from AI
Reality: Nope! There’s a common misconception that only large-scale, big data projects can benefit from AI. However, this notion overlooks the fact that AI can deliver valuable results with a relatively small amount of data. While having a large dataset can be beneficial for certain AI applications, such as deep learning or complex natural language processing, many AI techniques, including machine learning, can be effectively applied with modest amounts of data.
Forecasting solutions like Novi Labs, provide comprehensive data without requiring users to source data from external providers. Novi comes pre-loaded with its own proprietary data, which combines public data and data from top L48 operators. This eliminates the need for users to gather and integrate data from various sources, ensuring that even small and medium-sized companies can benefit from AI-powered forecasting without extensive data-sourcing efforts.
Myth #4: AI lacks transparency and cannot be trusted
Reality: Not true! The transparency of AI algorithms has been a topic of concern, as the black-box nature of some AI models can make it challenging to understand the reasoning behind their decisions. However, the AI community recognizes the importance of transparency and has been actively working towards developing explainable AI models that can be trusted.
For example, Novi Labs forecasting solution provides a fully automated, self-serve, and configurable machine learning platform. Users can configure the model’s inputs and features, analyze model performance and then generate a wide range of potential development scenarios with easy-to-understand explainability datasets that show you HOW the model came up with its forecasts.
This level of configurability empowers users. By prioritizing transparency and explainability, AI models can gain the trust of users and stakeholders.
Myth #5: You need to be a data scientist to use AI
Reality: You don’t need to be a data scientist to use AI tools. Many ML software vendors offer user-friendly interfaces that don’t require any coding.
In fact, advancements in AI technology have led to the development of user-friendly tools and platforms that enable professionals. Many machine learning software vendors now provide intuitive interfaces that allow users to interact with AI models and perform tasks without writing complex code. These user-friendly platforms typically offer drag-and-drop functionalities, visual workflows, and pre-built templates that simplify the process of data preparation, model training, and result analysis.
In the context of reservoir engineering, having a basic understanding of key concepts like well logs, production data, and reservoir behavior is sufficient to utilize AI tools effectively, you’ll be able to get started right away.
Conclusion
E&P companies need to be ready to thrive in an AI-powered energy industry, and that starts with shaking off the assumptions that may be holding them back. Contrary to the misconceptions discussed, AI offers numerous opportunities for optimizing and driving business success.
If you’re interested in learning more about how AI can specifically help you in the oil and gas industry, we’d be more than happy to discuss it further. Whether you have questions, want to explore potential use cases, or require guidance on implementing AI solutions, we’d be happy to chat with you about it. Shoot us an email at intro@novilabs.com
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