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In this work we closely examine the overlap between (1) the computationally challenging problems in geophysical applications in the upstream business and (2) the capabilities of quantum annealing (QA) quantum processing units (QPUs). We analyze the strengths and limitations of the latter and we explain how and why QPUs need to be assisted with CPUs and GPUs to solve combinatorial optimization problems at industrial scale. We illustrate the discussion with three potential use cases: stack power maximization for residual statics estimation, “ray tracing” and compressive sensing.