Quantitative Interpretation (QI) is the commonly used name for an integrative geoscience discipline that connects seismic data with other data from a variety of different sources and different scales to allow geoscientists to derisk the subsurface. Historically, the majority of the energy industry's QI work was performed to support the exploration for hydrocarbons, the cost-effective hydrocarbon resource development, and hydrocarbon production monitoring. In recognition of the role hydrocarbon related CO2 emissions play with accelerating global warming, the energy industry and supporting stakeholders have embarked on an ambitious journey to supply the global economy with energy with increasingly lower carbon dioxide emissions. The energy transition that leads us from a past focused on fossil fuels to a future dominated by a variety of low- or zero-carbon emission technologies provides for plenty of challenges and opportunities – this also holds true for the QI community of practice that is eager to become a relevant and supportive partner in this transition. Here, we describe differences and similarities between QI for the hydrocarbon E&P lifecycle and in support of CCUS and renewable energy resources. While it is indeed possible to adapt existing QI workflows for subsurface exploration, characterization, and monitoring to several of the energy transition challenges, some effort is needed to do so successfully.

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