Tom Hultgreen, Principal Geologist, AGR Reservoir Management, and Øystein Andersen, VP AGR Software, outline why true reservoir reconnaissance and accurate drilling budget are crucial to securing geothermal spending.
As the world seeks cleaner and greener energy sources to combat climate change, geothermal energy is forging its place amongst renewable solutions as a sustainable alternative to fossil fuels.
The advantages are obvious: there is enormous resource potential and – unlike the intermittency of wind and solar – geothermal is a constant, stable source of energy, so is easier to predict and manage. It is also one of the most convenient and cheapest electricity sources available today.1 Therefore, enabling its application worldwide is essential to hasten the energy transition and reinforce energy security (Figure 1).
However, while operational costs are low and consumer prices competitive, it requires mammoth investment to explore and drill for geothermal resources, as well as construct supporting power plants and infrastructure: considerably higher than coal, oil, and gas power plants.
Overcoming the technological and commercial challenges requires urgent innovation and collaboration if geothermal energy is to play a credible and cost-effective role in a low carbon future.
Considering uncertainty in geothermal reservoir modelling
Ranging from a few feet to several kilometres deep, geothermal wells – like oil and gas wells – are vertical or deviated and can be extended laterally over horizontal distances: up to about 1.5 km and dipping at angles of less than 45° as measured from the vertical.2 Having a comprehensive and real-time view of a geothermal reservoir gives investors in-depth and live analysis of the drill site, its environmental make-up, how it might respond when work begins, pressure and temperature over time, and, perhaps most importantly, its possibilities and profitability.
Constructing such reservoir models is a multidisciplinary effort between the fields of geophysics, geology, petrophysics, reservoir engineering, and reservoir modelling.
Today, AGR, a multi-disciplinary engineering consultancy and software provider, employs 3D and 4D static (or geological) and dynamic (or simulation) reservoir models to accurately deliver a complete view of reservoir’s potential with pinpoint accuracy.
The geothermal reservoir modelling process includes gravimetric, magnetic, seismic data, and well exploration and production data. These are analysed using both exploratory and confirmatory statistical methods and tools. Models typically show the crucial integration of the vital components and characteristics of the energy stored in the rock, and the fractures which form the connectivity or transportation ‘highway’ for energy in the reservoir.
In tandem, uncertainty and sensitivity reservoir analyses are also conducted to produce several stochastic model realisations using Monte Carlo algorithms. The output can include uncertainty ranges – from the most optimistic to most pessimistic outcomes – for example, P10-P50-P90 (a 10% chance becomes P10, a 50% chance P50, or a 90% chance P90) volumetric figures, or Tornado diagrams as shown in Figure 2. This data guides and supports decision-making processes relating to geothermal reservoir development and management.
Unravelling the complexity: What sets geothermal wells apart from conventional oil and gas wells
Rousing investor appetite and building trust in investment decisions is key to strengthening the business case for high-cost geothermal projects.
Geothermal wells have distinct differences in their design, function, and operation than oil and gas wells. Geothermal projects typically involve multiple investors and stakeholders. With multiple parties involved, decision-making can become complex and time-consuming. Each investor or stakeholder may want to have a say in project-related cost decisions, and achieving a consensus can be challenging.
All of this adds up to longer drilling days, operations in deeper and higher-temperature environments, and contend with low reservoir pressure, potential lost circulation, and more expensive equipment.
Probabilistic risk and reward analysis of geothermal wells
AGR’s drilling software, iQxTM was utilised by RED Drilling & Services GmbH (formerly RAG Energy Drilling) to enhance uncertainty understanding and improve geothermal drilling time and cost estimation. The Austria-based company switched from using a deterministic (Excel-based) approach to probabilistic well planning (often also called as Monte Carlo method).
iQx was developed in the early 2000s to improve time and cost estimation modelling for any type of hydrocarbon well drilling. It has recently been redeveloped to be applicable also in geothermal well drilling.
RED’s switch from using a deterministic (Excel-based) approach to probabilistic was game changing as the software offers a more complete and accurate view of time, cost, and risk estimation.
By applying the iQx Monte Carlo probabilistic simulation methodology, the rig and engineering specialist, can offer clients an assessment of cost range that will enable more accurate project budgets and avoid overruns. This approach is a compelling part of the proposition for investors.
The software provides answers that are not easily found in other planning tools, which struggle to map out all possible outcomes and risks that can arise during well operations or identify why a well may be more or less expensive than planned.
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For more news and technical articles from the global renewable industry, read the latest issue of Energy Global magazine.
The Winter 2023 issue of Energy Global hosts an array of technical articles weather analysis, geothermal solutions, energy storage technology, and more. This issue also features a regional report looking at the future of renewables in North America, and a report from Théodore Reed-Martin, Editorial Assistant, Energy Global, on how Iceland utilises its unique geology for renewable energy.
Read the article online at: https://www.energyglobal.com/special-reports/06022024/applying-lessons-learned-from-oil-and-gas-to-geothermal/
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