Permian Wastewater Could Offer Cooling Solution for AI Data Centres

The rapid expansion of artificial intelligence (AI) data centres is placing significant pressure on global water and energy resources, according to a report by OilPrice.com. A study by researchers at the University of Texas at Austin (UT Austin) proposes using wastewater from the oil and gas industry, specifically from the Permian Basin, as a sustainable water source for cooling these facilities.

AI data centres are known for their substantial water and energy consumption. Large data centres can directly use up to 5 million gallons of water daily, according to figures cited by the Environmental and Energy Study Institute. However, research from the University of Michigan indicates that indirect water usage, stemming from the energy generation required to power these centres, can significantly increase their overall water footprint. One study from the University of Michigan calculated that including offsite water usage for power generation increased the water footprint of three planned data centres in Michigan by 14 billion gallons.

Shaolei Ren, a professor at the University of California, Riverside, noted that this indirect water usage often receives less attention, despite its substantial impact on watersheds and regional water resources. The need to find sustainable solutions for data centre water consumption is therefore paramount.

Permian Basin Wastewater as a Resource

Researchers at UT Austin have modelled methods for desalinating oilfield wastewater for data centre cooling. Lead researcher Vaibhav Bahadur highlighted that the Permian Basin generates approximately 1,200 Olympic-sized swimming pools worth of wastewater daily. This water is predominantly injected underground, and current projections suggest that burial space could become scarce as early as 2030.

Treating this produced water for beneficial reuse could offer a dual benefit: providing a new, non-potable water source for industrial applications like data centre cooling, and alleviating the environmental and logistical challenges associated with wastewater disposal in the Permian Basin.

Desalination Methods Explored

The UT Austin study, published in the scientific journal *Water Research*, explored different desalination techniques. Reverse osmosis was identified as the most energy-efficient method. However, its effectiveness is limited when water salinity exceeds that of seawater. For highly saline wastewater, heat-based distillation processes were considered, though these methods are notably more energy-intensive.

The findings suggest that while technical challenges remain in treating and utilising this specific type of industrial wastewater, it presents a potential avenue for addressing the mounting water scarcity concerns exacerbated by the growth of energy-intensive AI infrastructure. The approach could offer a sustainable alternative to using freshwater resources for industrial cooling requirements.