Lat­est Dig­i­tal Tech­nolo­gies to Cre­ate Par­a­digm Changes in the En­ergy Sec­tor

Chemical Industry Digest - - News & Views -

The en­ergy sec­tor has long pi­o­neered the use of trans­for­ma­tional tech­nolo­gies. And now with the in­creas­ing po­ten­tial of AI that en­ables un­lim­ited amount of data to be in­gested, in­ter­preted and acted upon, this sec­tor faces a wave of change. With such po­ten­tial, AI will en­able op­er­a­tions to run the en­ergy sec­tors more ef­fi­ciently and pro­duc­tively at an ever lower cost. Mckin­sey es­ti­mates that by 2035,data an­a­lyt­ics and ro­bot­ics alone could pro­duce be­tween $290m and $390bn in an­nual pro­duc­tiv­ity sav­ings for oil, nat­u­ral gas, ther­mal coal, iron ore and cop­per pro­duc­ers across

the globe.

In­flec­tion point

“A cou­ple of years ago what we’re do­ing now would have been very ex­pen­sive be­cause com­puter stor­age and pro­cess­ing power was cost pro­hib­i­tive. A re­duc­tion in the cost of tech­nol­ogy and an in­crease in the avail­abil­ity of data is a key fac­tor here,” says Harry Bloch, CFO of start-up VROC AI which pro­vides pre­dic­tive main­te­nance so­lu­tions to the oil and gas sec­tor. With cost fall­ing rapidly and easy avail­abil­ity of data pro­cess­ing para­pher­na­lia, new area of com­puter sci­ence has emerged- from sym­bolic learn­ing in­volv­ing im­age pro­cess­ing and ro­bot­ics to more com­plex al­go­rithm-based pat­tern recog­ni­tion and re­in­forced ma­chine learn­ing us­ing neu­ral net­works—that will lead to a rapid ac­cel­er­a­tion in the use of AI across the sec­tor. De­vel­op­ments in quan­tum com­put­ing are set to take cog­ni­tive com­put­ing to an even more ad­vanced level.

For an in­dus­try based on tech­no­log­i­cal trans­for­ma­tion, en­ergy com­pa­nies have been sur­pris­ingly slow to recog­nise the po­ten­tial of AI.Ac­cord­ing to Global Hu­man Cap­i­tal Trends 2018 re­port , Deloitte notes that AI, ro­bot­ics and au­to­ma­tion alone are still rated rel­a­tively low by the en­ergy in­dus­try, de­spite ro­bot­ics in par­tic­u­lar tak­ing a sig­nif­i­cant foothold over the past 1218 months.

Ta­lent short­age

One of the ma­jor fac­tors that con­strains the use of AI in the oil and gas sec­tor is the short­age of qual­i­fied in­di­vid­u­als. Ac­cord­ing to El­e­ment AI, fewer than 10,000 peo­ple glob­ally have the re­quired skills to un­der­take sig­nif­i­cant re­search in this area.As AI evolves, the skill sets re­quired to drive it into the fu­ture will also ad­just. “The in­dus­try is chang­ing from be­ing one that had an el­e­ment of hu­man cap­i­tal to one that now has cen­tral pro­cess­ing unit (CPU) power. AI com­bined with ma­chine learn­ing and al­go­rithms means the roles for data sci­en­tists are rapidly chang­ing,” VROC’s Bloch says. Cur­rently to over­come the im­me­di­ate re­cruit­ment hur­dles, many en­ergy com­pa­nies are opt­ing to out­source AI work.

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