This paper examines the potential of nuclear logging techniques, ubiquitous in the petroleum industry, to extract geological information needed to support the transition to the low-carbon energy future being envisioned to replace fossil fuels and explores the technological advances needed. Assessment to date, using Monte Carlo modeling and available measurements shows promise in (1) monitoring injected CO2 for carbon capture and sequestration (CCS) to mitigate climate change, (2) assessing sites to bury high-level waste to support nuclear power generation and later monitor buried radioactive waste, and (3) in geothermal, a renewable option. For each case, standard techniques, while promising, also show technological gaps. Additionally, two postulated low-carbon areas supporting renewable energy generation are briefly examined—downhole quantification of strategic minerals and prediction and detection of naturally occurring hydrogen in the geology.

Three related technology areas are also examined: transition from the current dual-track philosophy of nuclear logging tool design to a compact, more universally applicable advanced accelerator-based multiple-parameter tool concept, incorporation of artificial intelligence-guided physical health management systems to minimize generator failure, and advances in generation/detection hardware and software. Software advances would include codes with dynamic visualization and improved nuclear data libraries to design, calibrate, and assess tools, especially to provide a priori space-time profiles of attendant multiple radiation types, which would arise in the novel systems being postulated.

Two exotic concepts, recently suggested also for downhole use, associate-particle imaging to monitor casing integrity of wells storing methane and hydrogen and muon-based deep density probing, are briefly explored.

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