Unlocking geothermal potential with AI and data science

Harnessing AI in the Pursuit of Geothermal Power - Enovate AI

Carlo Cariaga 26 Jun 2024

Geothermal power has emerged as a promising solution in the pursuit of cleaner and more sustainable energy sources. However, maximizing the potential of geothermal energy requires strategic planning and advanced technologies. One such technology that is transforming the way to approach geothermal power plant development is Enovate’s Advanced Artificial Intelligence (AI).

AI as part of geothermal project development

The integration of Advanced AI into geothermal power plant planning represents a paradigm shift in energy development. By harnessing the power of AI for site selection, resource assessment, operations optimization, and risk management, unlocking the full potential of geothermal energy while minimizing risks and maximizing efficiency is attainable.

Advanced AI provides significant benefits in several stages of geothermal project planning, development, and operations:

Enhanced Site Selection and Resource Assessment – The success of a geothermal power plant heavily relies on selecting the most viable sites with optimal resource potential. The software analyses vast amounts of geological data, including subsurface temperatures, rock permeability, and seismic activity, to identify ideal locations for geothermal development. By accurately assessing geothermal resources, the solution minimizes the risk of investing in suboptimal sites and maximizes energy production efficiency.

Precision Drilling and Operations – Geothermal drilling is a complex and costly process. The industry leading AI-driven algorithms can optimize drilling operations by predicting subsurface conditions and recommending the most efficient drilling paths all in real-time. This precision minimizes drilling risks, reduces downtime, and lowers operational costs. Additionally, the process involves a continuously monitor plant operations, optimizing parameters in real-time to enhance efficiency and lifespan.

Optimized Resource Utilization – Geothermal reservoirs are finite resources that require careful management to ensure long-term sustainability. The AI models can simulate reservoir behaviour under different extraction scenarios, enabling optimized resource utilization while preserving reservoir health. This ensures that geothermal energy remains a reliable and sustainable energy source for years to come.

Improved Economic Viability – AI-driven economic modelling provides insights into the financial implications of geothermal projects. By analysing various scenarios and market conditions, the process helps stakeholders make informed investment decisions and develop robust business strategies. This transparency enhances project viability and attracts investment in geothermal energy development.

Environmental Stewardship – Geothermal energy is renowned for its low environmental impact, but responsible development is essential. The algorithm developed aids in assessing and mitigating environmental risks associated with geothermal projects, ensuring compliance with regulations and minimizing ecological disturbances. This contributes to maintaining a positive environmental footprint and fostering public acceptance of geothermal energy.

Case study

A recent geothermal feasibility study clearly demonstrated the potential to use a hybrid model, integrating first principles and data science, to better understand the entire geothermal heat extraction and utilization process, thereby optimizing its electricity generation costs.

The study was based on a deep exploration well drilled back in the 80s, which showed excellent geothermal potential based on its temperature log and its calculated geothermal gradient. The OH log with the porosity, permeability results plus the lithology description by the coring program described the subsurface geology and reservoir properties in detail, which could be used to infer the heat transfer properties of the sedimentary rocks. An unconventional closed-loop geothermal well is considered an ideal candidate for geothermal resource development in this area.

To further enhance the accuracy of heat transfer models, deployment of the latest optical fiber sensor technology was proposed to collect distributed temperature data along the wellbore of a new drill. Utilizing first principles models—traditional engineering design models that reflect physical laws such as mass balance and energy balance — will help to understand the heat transfer mechanisms in an unconventional closed-loop geothermal well.

Additionally, advanced data science processing and machine learning algorithms could be applied to analyse data and uncover patterns not evident in first-principles models. Techniques like convolutional neural networks (CNN), recurrent neural networks (RNN), and long short-term memory networks (LSTM) are being used to evaluate the impact of well design, construction material selection, and sedimentary rock characteristics on geothermal heat extraction.

Almost-instantaneous transmission of temperature data allows high-power computation systems to test this hybrid model with real-time data. This iterative process enhances the model’s accuracy and reliability, optimizing the daily geothermal plant operation and effectively reducing the cost of generating geothermal electricity.

Ultimately, this approach enables the creation of a real-time IoT and AI pattern recognition system to effectively extract the geothermal resource and electricity generation with a capacity to supervise the plant remotely.

This transformative technology not only accelerates the adoption of sustainable energy solutions but also paves the way towards a greener and more resilient future. As continuing to leverage AI advancements, the outlook for geothermal energy remains bright, offering a reliable and renewable energy source to power the world sustainably.

About Enovate AI

Enovate AI delivers business and operational process optimization for decarbonization and energy independence through digital engineering and automation. Enovate AI’s proven technology model is enabled by the capacity to deliver digital solutions that accelerate a clean, efficient, and diversified energy supply. Enovate AI supports oil and gas, renewables, and CCS operations with an end-to-end digital package from optimization to monetization.

Enovate AI supports a cleaner, more efficient, and diversified energy industry through the deployment of effective AI solutions. At Enovate AI we realize the full potential of process autonomy to create a more profitable, sustainable, and environmentally responsible energy industry across the globe.

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Rebecca Nye
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contactus@enovate.ai

Carlo Cariaga

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