SMART MONEY

Col­lect­ing data from a re­fin­ery or oil field is one thing. But us­ing it prop­erly is an­other

Alberta Oil - - CONTENTS - BY IAN JONES

Col­lect­ing data from a re­fin­ery or oil field is one thing. But us­ing it prop­erly is an­other

HENRY FORD WOULDN’T HIRE AN

ex­ec­u­tive who salted his meal with­out tast­ing it first—or so the leg­end goes. True or not, his fo­cus on ef­fi­ciency helped his mo­tor com­pany per­fect its as­sem­bly line to pro­duce more with less. Oil and gas pro­duc­ers are now look­ing for the same level of ef­fi­ciency as they stream­line their busi­ness pro­cesses in a chal­leng­ing price en­vi­ron­ment. Advanced an­a­lyt­ics of­fers sev­eral in­roads to get more out of ex­ist­ing tech­nol­ogy in­vest­ments and to push back against low com­mod­ity prices.

The In­ter­na­tional Data Cor­po­ra­tion (IDC) es­ti­mates that the amount of data in the dig­i­tal uni­verse is dou­bling ev­ery two years. That re­al­ity is ob­vi­ous to any­one who in­ter­acts with the vol­ume of data pour­ing from ev­ery piece of equip­ment in the in­creas­ingly dig­i­tal oil field.

Yet anal­y­sis is the key to turn­ing this rapidly and con­tin­u­ally ac­cu­mu­lat­ing data into valu­able in­sights that can have a quan­tifi­able im­pact on a com­pany’s bot­tom line.

A good ex­am­ple of this is the quan­tity of real-time mea­sure­ments col­lected on a re­fin­ery floor by data his­to­ri­ans. This data­base of highly de­tailed process con­trol sys­tem data is gen­er­ally used only to look back­wards, an­a­lyz­ing how a pump failed or why pro­duc­tiv­ity de­clined. Months of spe­cific mea­sure­ments are stored at high cost while their po­ten­tial to be­come a valu­able cor­po­rate as­set is of­ten left un­re­al­ized.

Ap­ply­ing both pre­dic­tive and pre­scrip­tive an­a­lyt­ics con­verts this data his­to­rian into a fore­cast­ing dy­namo who can fore­see equip­ment fail­ure and ad­vise how to mit­i­gate against it. Us­ing the data in this new way can send rip­ples through an or­ga­ni­za­tion. The re­sult is un­planned equip­ment main­te­nance de­clines, parts in­ven­tory be­comes more ef­fi­cient and man­age­ment makes more ac­cu­rate and con­fi­dent pro­jec­tions based on solid ev­i­dence. The ef­fect on the bal­ance sheet is also mea­sur­able, to say the least.

Sim­i­lar ex­am­ples abound through­out the oil busi­ness. One large oil com­pany used advanced an­a­lyt­ics to ex­tend the op­er­a­tional life­time of low-vol­ume, steam-in­jected wells by op­ti­miz­ing its operations and main­te­nance sched­ules. An­a­lyt­ics en­abled the com­pany to mon­i­tor and ad­just its operations 24-7, lead­ing to an im­prove­ment in equip­ment re­li­a­bil­ity that helped lower costs and max­i­mize pro­duc­tion out­put. The com­pany es­ti­mates that its sub­se­quent abil­ity to pro­duce an ex­tra half-bar­rel per well per day, while re­duc­ing its en­ergy foot­print, adds hun­dreds of mil­lions of dol­lars to its an­nual rev­enues.

Ap­ply­ing advanced an­a­lyt­ics can also rev­o­lu­tion­ize oil and gas pipe­line fore- cast­ing. The pipe­line plan­ning process—a yearly reg­u­la­tory re­quire­ment—com­bines an ar­ray of eco­nomic as­sump­tions, such as com­mod­ity price trends, with large amounts of pipe­line data that demon­strate trends in sup­ply and de­mand. In­te­grat­ing data from well­heads, me­ter sta­tions and other sen­sors is a daunt­ing job, but an­a­lyt­ics au­to­mates and stream­lines the process with star­tling re­sults.

When these re­sults are com­pared to ex­ec­u­tives’ as­sump­tions about the most fea­si­ble mar­kets for the pipe­lines to ad­dress, the num­ber of po­ten­tial mar­kets is nar­rowed by one-third, as the il­lus­tra­tion shows. This speaks vol­umes about data’s abil­ity to be trans­formed into ac­tion­able in­for­ma­tion if the right anal­y­sis is ap­plied.

Ford, who liked no part of his operations to be wasted, would be pleased.

Ian Jones is Se­nior Strate­gist, En­ergy Risk Man­age­ment, at SAS

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