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

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

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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

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SLIDE 1

The he c cor

  • rporate solutio

ion f for eval aluating, man manag aging, an and d repo porting r reserves

SPEE 2018

Petroleum Evaluation Software Symposium

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SLIDE 2
  • Us

Used ed b by over er 2 2700 700 cl clients

  • Ban

Banks, o

  • pe

perators & & majo major 3 3rd 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

  • r 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

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SLIDE 3
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SLIDE 4

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

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SLIDE 5

PHDWin Version 3

De Desi signed to

  • su

suppor pport i impr proved:

  • Sca

cala labi bility

  • Data disciplin

ine & & complian ance

  • Custom
  • mization &
  • n & flexib

ibility ity

  • Share

hared busine ness intelligence

  • Improved m

mytho hology

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SLIDE 6

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
  • rt for c

client nt/server d deployment nt

  • Be

Bett tter m r multi ti-user p performance

  • PHDW

DWin c n custom

  • m data

ata layer

  • Express o
  • r full v

versions

  • ns
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SLIDE 7

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

  • r run

un loca cally

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SLIDE 8

Scalability

MS S SQ SQL Se Server Logins ins prov rovide:

  • Datab

atabas ase s sec ecuri rity

  • Customiz

izab able in interfac ace

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SLIDE 9

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

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SLIDE 10

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

  • rmanc

nce

  • Improved

ed s speed eed o

  • f ca

calcu culations & & rep eporting

  • Im

Improved C Cas ash Formula s a scr cripting lan language

  • Uninterrupted wor
  • rkf

kflow wh w while repo porti ting

  • Run m

un mult ultiple i ins nstances

  • Run m

multiple r reports at at once ce

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SLIDE 11

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
  • rce c

cons nsistenc ncy

  • Reduce QC tim

time

  • Red

educe data en ata entr try err errors

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SLIDE 12

Data Discipline

Use ser De r Defined but lock d k down wn

  • product d

defin init itio ions

  • phas

hase conf nfigur urations

  • ns

for a all ll ca cases.

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SLIDE 13

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
  • spectiv

tive

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SLIDE 14

Data Discipline

Highl hly g granular I Investm stment t cat ateg egorie ies c can an be be li link 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

  • r

r co cost re reco covery.

  • to less g

s granular Investm stment R t Repor

  • rti

ting Categor

  • ries

On a a corporate bas bases t to force e stan andar ardiz izatio ion.

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SLIDE 15

Customization

Highly ly c customizable le i interface ce

  • Dat

ata “For

  • rms” ar

are user d definable

  • Multiple d

dat ata “ “For

  • rms” c

can an b be grouped to

  • create

“Views” t to

  • define your

ur w workspace

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SLIDE 16

Customization

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

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SLIDE 17

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

  • r econo

nomics

  • Re

Revenue, e expenses, , royal alties, , etc.

  • Gros
  • ss or
  • r net
  • Mon
  • nthly

ly or

  • r cumula

lative

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SLIDE 18

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 – ΔTime fr from f m first production (d (days) – ΔTime me2 from f first p production (day ays2

2 )

– Δ time me½ fr from f m first production ( (Days ys ½) – Δ time Mat aterial B Bal alan ance Ti Time (M (MBT ) T )

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SLIDE 19

Customization

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SLIDE 20

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

  • r

r stre ream

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SLIDE 21

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
  • nstrained 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

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SLIDE 22

Improved Mythology

  • Con
  • ntrol
  • l wha

what is is a approp

  • pria

iate

  • Chan

ange depr preciation me methods b by pu purpose.

  • Chan

ange investme ment d depr preciations b by fiscal mod model.

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SLIDE 23

Improved Mythology

Ne Nest sted GE GELs Ls

  • Group E

Eco conomic Lim imit (GE GEL) L) can n now be w be nest sted.

HUB Case Satellite Field 1 Child ECL Child ECL Satellite Field 2 Child ECL

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SLIDE 24

Shared Corporate Knowledge

Scena narios Rep eport with t with uniq ique

  • Repor

port t st start d dat ates

  • Max e

econ

  • nom
  • mic

ic y year ars

  • Disc

iscounting ra rates or me r methods

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SLIDE 25

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

  • s
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SLIDE 26

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

  • ther

er eco econom nomic qualif ifie iers

  • Share o

e or inh nher erit f from o

  • ther

er us user ers

  • User

ers ca can n wor

  • rk 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’

  • Pr

Projection

  • n Q

Qua ualifier er rep eplace ce 2. 2.9 9 “Arch chives es”

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SLIDE 27

Shared Corporate Knowledge

Scenario Controlled Data

Discounting Settings Incremental Tree Set Up Recompletion Tree Set Up Group Case Inclusion Fiscal Model settings Economic Options (i.e. Kill Dates or Cutoffs)

Qualifier Controlled Data

Price Expenses Investments Ownership Projections Shrinkage Multipliers

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SLIDE 28

Shared Corporate Knowledge

Link Sc Scenarios f for

  • r c

con

  • nsistent results:
  • Se

Sets o

  • f case

ases

  • In

Incre remental & recompl pletio ion t trees

  • Group c

case ase in inclusion

  • Disc

iscounting & & repo port se settings

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SLIDE 29

Shared Corporate Knowledge

Reservoir Engineer Scenario

Prices Expenses Projections Investments

Econ Team Scenario

Prices Expenses Projections Investments

Manager Approval Scenario

Prices Expenses Projections Investments

Reserves Scenario

Prices Expenses Projections Investments

Reservoir Engineer Scenario

Prices Expenses Projections Investments

Econ Team Scenario

Prices Expenses Projections Investments

Manager Approval Scenario

Prices Expenses Projections Investments

Reservoir Engineer Scenario

Prices Expenses Projections Investments

Econ Team Scenario

Prices Expenses Projections Investments

Reservoir Engineer Scenario

Prices Expenses Projections Investments

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SLIDE 30

Conclusion

  • MS

MS-SQL Ser Server i is faster er a and more reliab able

  • MS

MS-SQL L Server a allows very large e databases es (100,000 cases es)

  • MS

MS-SQL Ser Server is is a a true multi-user er environment

  • SQL

L all allows f for entire corporate as assets to b be in included in in a a sin ingle dat atabas ase

  • Scen

enarios allow f for mu multiple v e ver ersions t to be ea e easily ma maintained ed

  • Scenar

arios an and Qu Qual alifiers all allow for fas ast, seamless dat ata a shar aring.

  • New corporat

ate level f feat atures al allow great ater dat ata a discipline

  • Grap

aphing of an any s y stream wil ill l aid aid in QC QC an and an anal alysis is.

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SLIDE 31

The he c cor

  • rporate solutio

ion f for evaluat atin ing, man managing, an and d repo porting r rese serves

Thank You for Your Time