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To meet future energy demand a significant increase in production from primary energy sources of a wide variety from renewables to fossil-based in a context in which environmental concerns are growing. However, the role of hydrocarbons for a good part in this century will remain important- in particular the role of natural gas may in fact be crucial for the coming decades. Hence there is growing need for technology innovation for efficient hydrocarbon production with smaller foot prints and with an emphasis on gas. In turn, more accurate geoscience technology and monitoring and management of operations will be needed, enabled by more accurate measurements made possible through ubiquitous large scale sensor networks. Thus, in future subsurface characterization and field management may require the processing and interpretation of PByte scale data sets acquired in a more or less continuous fashion. Furthermore, the need to understand more fundamentally rock and fluid interactions often require techniques very similar to quantum-chemistry technologies used in catalysis used in large scale gas to liquid applications. As a result now, more than ever, the need for high performance computing driven by large scale data processing and interpretation needs of a wide variety is key enabler to meet future energy demand in almost any scenario. In this talk some of the geoscience challenges will be illustrated as well as some in computational chemistry and some views will be presented on how these challenges may be met by innovations in computing.