nekhaev eng 2
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SPE 149916Capit al Costs Estimat ion Method for Arct ic Off shore Oil Proj ects
M.A. Kuznetsov, K.K. Sevastyanova, P.A. Tarasov, S.A. Nekhaev
LLC «RN-SakhakinNIPImorneft»
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Challenges:
• The lack of cost-evaluation methods for the Arctic region
• The lack of input normals
• The absence of analogous fields
High risks:
• Harsh ice conditions• Reserves value uncertainty• The lack of geological data• The lack of coastal infrastructure
Prospective projects in the Russian ArcticProspective projects in the Russian Arctic
Actuality:
• Joint development of licensedareas in the Kara Sea with foreigncompanies
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Current status: Existing software products:
• do not support estimates for Arctic conditions
• require large amounts of input parameters
• use foreign costs structure for materials and equipment
Goal:
Evaluation of capital investments in the early stages of project analysis
Tasks:
• Identify a minimal set of informative parameters for costs modeling
• Development of econometric models for integrated structure of capitalcosts
ResearchResearch taskstasks
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Statistically marked outhomogeneous groups offields
Regression models were built for certaingroups
Method is based on real projectsMethod is based on real projects
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Topside costs are modeled by 2 parameters: peak oil (Qoil) andpeak gas (Qgas)
Scale effect: topside costs rise slower then facilities capacity
TopsideTopside
Real data Model
Mtopside Mtopside
Qoil Qoil
Qgas Qgas
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С t o p s i d e =
С 0 + C 1
Q o i l +
С 2 Q g a
s
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hwater
Mtopside
GBS costs are influenced by: Topside weight ( Mtopside) and water depth (hwater )at the installation point
GBS
GravityGravity BasedBased StructureStructure ((SubarcticSubarctic))
hwater
Мtopside
МGBS
)( 0
2СbhhaM water water topsideunit GBS unit GBS ++==
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GBS CAPEX in the Arctic depends on water depth (hwater ) atthe installation point
h=30m
h=60m
h=120m0
50
100
150
200
250
300
20 40 60 80 100 120
Глубина моря, м.
Массаоснования,тыс.т.
0h - Min water depth for GBS installation
GravityGravity BasedBased StructureStructure ((ArcticArctic))
0
lnh
ha
wa te r
uni t G B S uni t G BS ==
GBS
we
ight,‘000t
Water depth, m
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Subsea costs are determined by: the number of wells (Nwells) in cluster andwater depth (hwater ) at the installation point:
0
50
100
150
200
250
300
350
0 5 10 15 20Число скважин/ПДК
СтоимостьПДК,млн.$
Nwells/Cluster
hwater
SubseaSubsea facilitiesfacilities
water inst wellsunit subsea haN +=7,0
Subseaco
sts,mln.$
Nwells/Cluster
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Cumulative forecast error does not exceed 30% (permissible error for theconceptual design)
Ошибка модели ОГТ
30% интервал ошибки
Hibernia
ПА-БЛУН-А
Аркутун-Даги
0
50
100
150
200
250
0 20 40 60 80 100 120 140 160 180
Расчетные значения, V железобетона, тыс.куб.м.
Фактическиезначения
,V
желе
зобетона
,тыс.куб.м.
Ошибка модели ВСП
30% интервал ошибки
0
10
20
30
40
50
60
70
80
0 10 20 30 40 50 60
Расчетные значения, тыс.т.
Фактическиезначения,тыс.т.
ForecastForecast accuracyaccuracy
GBS model error
30% spacing error
Topside model error
30% spacing error
Realva
lue,‘000t.
Estimated value, ‘000 t. Estimated value, ‘000 cub.m.
Realv
alue,‘000cub.m.
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Tampico
Tamaulipas
Morgan CityDaewoo
Hyundai
Okpo
Verolme
Vlissingen
St.Wandrille
Algeciras
Puerto Real
Keppel
Labor
Matherials
Transportation
St. John’s
k 2
k 3
k 4
k 5
k 1
CAPEX = kiCAPEXtopside+ k jCAPEXGBS+ klCAPEXSubsea
RegionalRegional componentcomponent
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An example ofAn example of a typicala typical platform evaluationplatform evaluation
Unit capex >15 $/bbl (reserves 90 mln.t)
The minimum set of parameters:
Result:
Peak oil, '000t/d 24
Peak gas, mln.cub.m. d 2,88
Water depth, m 60
Topside CAPEX, mln.$ 3477GBS CAPEX, mln.$ 1348
GBS CAPEX DRILLEX
Topside CAPEX
Other
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-20 000
-10 000
0
10 000
20 000
30 000
40 000
50 000
60 000
70 000
Валовая
выручка
Транспортные
расходы
Платежии
налоги
OPEX
CAPEX
млн.руб
30% error in estimating capital costs leads to a shift in the NPV assemblyaverage at 28%
100% -4%-77%
-18%-4%
-условно-постоянный CAPEX
-60%
-30%
0%
30%
60%
-30% 0% 30%
Δ NPV
Δ CAPEX
-15%
0%
15%13%
18%
23%
28%
33%
38%
43%
+30%-30%
EconomicsEconomics
-52%
-40%
-28%
-16%
-4%
Mln.rub
Revenu
e
Transportat
ion
costs
Royaltiesa
nd
taxes
conditional permanent CAPEX
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Results
1. Identified a minimal set of informative parameters for capital costs modeling with an accuracy of 30%
2. Unit capex for the Russian Arctic region is estimated
3. Practical application:
• investment committee
• preparation of proposals on tax optimization
• development of the Declaration of Intent to developfields
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Thank you!
Capital Costs Estimation MethodCapital Costs Estimation Methodfor Arctic Offshore Oil Projectsfor Arctic Offshore Oil Projects