SPEE 2018 Petroleum Evaluation Software Symposium The he c cor - PowerPoint PPT Presentation

SPEE 2018 Petroleum Evaluation Software Symposium The he c cor orporate solutio ion f for eval aluating, man manag aging, an and d repo porting r reserves

• Us Used ed b by over er 2 2700 700 cl clients ◦ Ban Banks, o ope perators & & majo major 3 3 rd party re y reserve a auditors rs • Modelin ing e economic mics i s in over 3 35 countries w s worldwid dwide • Pr Providing pr proven an and d trusted d rese serve a and economic mic c calculat atio ions s for or alm lmost 3 30 years rs • Backed by a a k knowle ledgeable le su suppo pport, c consu sulting & & sal sales st staf aff

PHDWin Version 3 Design gned d to to move ve PHD HD Wi Win from m a projec ject base ses sy system to a a corporate syst stem. m.

PHDWin Version 3 De Desi signed to o su suppor pport i impr proved: • Sca cala labi bility • Data disciplin ine & & complian ance • Custom omization & on & flexib ibility ity • Share hared busine ness intelligence • Improved m mytho hology

Scalability MS MS-SQL L Serve ver • Indus ustry s y stand ndard • Stab table an and rel reliab iable p per erform rmance • Suppor ort for c client nt/server d deployment nt • Be Bett tter m r multi ti-user p performance • PHDW DWin c n custom om data ata layer • Express o or full v versions ons

Scalability MS MS-SQL Serve ver • Data tabase si e size e is s scala lable ble ◦ 100, 00,000 ca 000 case t e tes est D DBs ◦ Co Combine asse assets • Ope pen d dat ata structure • New ew i inputs ◦ dail daily dat data, sc scheduled pr projections, F Flow R Regime I ID • Uti Utilize e ent nterprise h hardware o or run un loca cally

Scalability MS S SQ SQL Se Server Logins ins prov rovide: • Datab atabas ase s sec ecuri rity • Customiz izab able in interfac ace

Scalability MS S SQ SQL Se Server Logins ins prov rovide: • User c chat hat • Private/Pu /Publ blic ic i items ◦ Sorts ts ◦ Fil Filter ers

Scalability New PHDWi Win Economics cs E Engi gine • Paralle llel l processing /M /Multi-thread aded e eco conomics ◦ Improved ed h hardware d direc ectly co correl elates es w with perfor ormanc nce ◦ Improved ed s speed eed o of ca calcu culations & & rep eporting • Im Improved C Cas ash Formula s a scr cripting lan language • Uninterrupted wor orkf kflow wh w while repo porti ting • Run m un mult ultiple i ins nstances • Run m multiple r reports at at once ce

Data Discipline Corporat ate C Cont ntrols ◦ Impos pose an and m main aintai tain c corporat ate stand ndards ◦ Ensu sure c re comparable, e, q quality r resu sults ◦ Enfor orce c cons nsistenc ncy ◦ Reduce QC tim time ◦ Red educe data en ata entr try err errors

Data Discipline Use ser De r Defined but lock d k down wn • product d defin init itio ions • phas hase conf nfigur urations ons for a all ll ca cases.

Data Discipline Create n nest sted libr ibrar aries fo for • fields ds, re , reservoirs rs and nd zo zones • PRM RMS c S cat ateg egoriz izatio ion ◦ Re Reserves • Pro rove ved • Pr Proba babl ble • Possib ssible ◦ Cont nting ngent nt ◦ Prospe ospectiv tive

Data Discipline Highl hly g granular I Investm stment t cat ateg egorie ies c can an be be link li nked • to us user d r define ned depr preci ciation me n methods f for r A- tax ca calcula lculations, b book a acco ccount unting o or r co cost re reco covery. • to less g s granular Investm stment R t Repor orti ting Categor ories On a a corporate bas bases t to force e stan andar ardiz izatio ion.

Customization Highly ly c customizable le i interface ce • Dat ata “For orms” ar are user d definable • Multiple d dat ata “ “For orms” c can an b be grouped to o create “Views” t to o define your ur w workspace

Customization Tail ailor “Vie iews ws” to sho how d data ata rel relevant t t to your r job. b.

Customization Improved G Graphing ng • Create unli limited grap aphs on e each ach cas cases • Show multiple g grap aphs at at a a time • Creat ate an and ap apply Grap aph templat ates with co corporat ate co control • Plot M Monthly, Dai aily an and T Test D Dat ata • Plot an any p product v volumes o or econo nomics ◦ Re Revenue, e expenses, , royal alties, , etc. ◦ Gros oss or or net ◦ Mon onthly ly or or cumula lative

Customization • More gr graph phing o g opt ptions ◦ New projection m methods • Sch ched eduled ed • SED EDM ◦ New p plotting ng methods • Cartesian ian, s , semi-lo log a and lo log log log – Abs bsolu lute tim ime – Δ Time fr from f m first production (d (days) – Δ Time me 2 from f first p production (day ays 2 2 ) me ½ fr – Δ time from f m first production ( (Days ys ½ ) – Δ time Mat aterial B Bal alan ance Ti Time (M (MBT ) T )

Customization

Customization Better R Reporti ting • Create custom r report tables s • Dis isplay an any in inter erim cal alculat ation • Report a any y product ct o or r stre ream

Improved Mythology Impr proved E d ECL calcu cula lation • econo nomic li limit calculation find nds t the date in in which cumu mulative cash fl h flow i is Max aximize zed ◦ Id Ideal al f for acco accounting for: • Shut ut i in n per eriods • Con onstrained w wells lls • Pr Price ce f fluct uctuations • Recurring annual l expens nses ◦ Pr Previously y used ed i in 2.9 for groups. ◦ Now used f for al all e eco conomic limits

Improved Mythology • Con ontrol ol wha what is is a approp opria iate ◦ Chan ange depr preciation me methods b by pu purpose. ◦ Chan ange investme ment d depr preciations b by fiscal mod model.

Improved Mythology Ne Nest sted GE GELs Ls • Group E Eco conomic Lim imit (GE GEL) L) can n HUB Case now be w be nest sted. Satellite Satellite Field 1 Field 2 Child ECL Child ECL Child ECL

Shared Corporate Knowledge Scena narios Rep eport with t with uniq ique ◦ Repor port t st start d dat ates ◦ Max e econ onom omic ic y year ars ◦ Disc iscounting ra rates or me r methods

Shared Corporate Knowledge Scenar arios & s & Qualif ifie iers Seaml amless ss d dat ata shar sharing g be between een vasio ious need needs • ◦ imp mproves es busines ess intel elligen gence ◦ Imp mproves es e efficien ency Similar t to Aries es but but more s e struct uctured ed • ◦ Dat ata q a qual alified by q y qual alif ifier or scenario Incl ncludes es h hier erarch chal q qua ualifier ers • Nea Nearly unli limited s scenarios os •

Shared Corporate Knowledge Scenar arios & s & Qualif ifie iers Added Pr Price, e, Ex Expens ense, e, I Inves estmen ent a and nd o other er eco econom nomic • qualif ifie iers Share o e or inh nher erit f from o other er us user ers • User ers ca can n wor ork concur concurren ently w within s same o e or differen ent • scena cenarios Arrange q e qua ualifier ers i in a n a hier erarchy • Owner nership q qua ualifier er R Rep eplace 2. e 2.9 “ 9 “Partner ers’ • Projection Pr on Q Qua ualifier er rep eplace ce 2. 2.9 9 “Arch chives es” •

Shared Corporate Knowledge Scenario Qualifier Controlled Controlled Data Data Price Discounting Settings Expenses Incremental Tree Set Up Investments Recompletion Tree Set Up Ownership Group Case Inclusion Projections Fiscal Model settings Shrinkage Economic Options (i.e. Multipliers Kill Dates or Cutoffs)

Shared Corporate Knowledge Link Sc Scenarios f for or c con onsistent results: ◦ Se Sets o of case ases ◦ In Incre remental & recompl pletio ion t trees ◦ Group c case ase in inclusion ◦ Disc iscounting & & repo port se settings

Shared Corporate Knowledge Reservoir Reservoir Manager Reservoir Reservoir Manager Econ Team Econ Team Reserves Econ Team Engineer Engineer Approval Engineer Engineer Approval Scenario Scenario Scenario Scenario Scenario Scenario Scenario Scenario Scenario Scenario Prices Prices Prices Prices Prices Prices Prices Prices Prices Prices Expenses Expenses Expenses Expenses Expenses Expenses Expenses Expenses Expenses Expenses Projections Projections Projections Projections Projections Projections Projections Projections Projections Projections Investments Investments Investments Investments Investments Investments Investments Investments Investments Investments