AI in Petroleum Industry

Whether AI could play a crucial role, when the pressure profiles as a function of depth from various wells remain not superimposed (which indicate the presence of non-communicating regions such as clay, shale and/or fractures); and whether, AI could provide deeper insights on reservoir compartmentalization?

Given the reservoir compartmentalization, whether AI would really help in deducing precise locations of (a) free water level; and (b) free oil level; and, in turn, (c) the height of the oil column – that could be used to estimate the initial oil in place?

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AI would also make use of ‘log measurements (based on resistivity and density)’ - on top of ‘pressure measurements’?

What would be the role of AI – in deducing ‘capillary pressure’ - when the data on both ‘log & pressure measurements’ are coupled together?

Will AI get rid-off - the various interpretations - usually provided from different data sets, in the event, when the wells do not penetrate OWC or GOC directly?

Whether the role of arriving at the appropriate composition of ‘drilling mud’ (as a function of various depths) using AI - could ensure that ‘there will be no more blowout’ - resulting from the enhanced pressure in the oil- or gas-bearing zone (with reference to a water-column at the same depth)?