Speaking at an event hosted by BPI France, Total’s seismic and high-performance computing guru Henri Calandra explained how his company was supporting various lines of research into quantum computing. Today’s HPC is looking for new approaches, as conventional approaches ‘run out of steam’. Moore’s law is to end by 2025 and parallelism is limited by Amdahl’s law. Energy is also getting to be a big issue (a subsequent speaker opined that a ‘post exaflop’ conventional HPC computer would need a 900 MW power station to run). Oil and gas needs HPC for seismics, reservoir simulation on heterogeneous, complex reservoirs, uncertainty management and, increasingly, for machine learning and high-performance data analytics. Other fields requiring HPC include MINLP (mixed integer non-linear programming) problems including refinery blending, scheduling, production, shipping and oil field/reservoir optimization. Possibly closer to the quantum bailiwick we have computational material science, where the ability to accurately model ground states of fermionic systems would have significant implications for many areas of chemistry and materials science such as catalysis, solvents, lubricants and batteries.
Total is therefore exploring quantum technology as a potential groundbreaking new approach to pave the way to a ‘beyond exascale’ future. Quantum is however, ‘very challenging technology’ and is currently limited to a few tens of qubits on a ‘Nisq’, a ‘noisy, intermediate scale quantum device’. Total’s objectives are to understand and track the evolution of quantum computing across initiatives such as Quantum Computing’s D-Wave, IBM Q, Google’s Bristlecone and Rigetti Computing’s 16Q Aspen.
In addition to the novel hardware, quantum algorithmics is a ‘brand new science’. Total is working to accelerate and build in-house competencies, working with research partners and an ecosystem of hardware providers to develop algorithms for Total business use cases, and to be ready when industrial quantum computers become available and quantum supremacy is demonstrated. Total acquired a 30 qbit ATOS QLM 30 in 2018 and is currently upgrading to a QLM 35 system*.
We chatted briefly with Caldera and asked what were the most promising short(ish) term applications of QC. He confirmed that chemistry and combinatorial optimization were the most promising areas. We asked for more specifics on potential geophysical applications. QC has potential application in some geophysical modeling problems. Full waveform inversion? ‘Yes, but easily 5 to 10 years out’. Caldera was circumspect as to the likelihood of QC having oil and gas application any time soon.
* More on Atos’ quantum initiatives.
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