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    SPE 149916

    Capital Costs Estimation Method for Arctic Offshore Oil Projects

    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 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

    Research tasks

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    Statistically marked out

    homogeneous groups offields

    Regression models were built for certaingroups

    Method 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

    Topside

    Real data Model

    Mtopside Mtopside

    Qoil Qoil

    Qgas Qgas

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    hwater

    Mtopside

    GBS costs are influenced by: Topside weight (Mtopside) and water depth (hwater)at the installation point

    GBS

    Gravity Based Structure (Subarctic)

    hwater

    topside

    GBS

    )( 02

    bhhaM waterwatertopsideunitGBSunitGBS

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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

    , .

    ,..

    0h - Min water depth for GBS installation

    Gravity Based Structure (Arctic)

    0

    lnh

    ha waterunitGBSunitGBS

    GBS

    weight,

    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 20 /

    ,.$

    Nwells/Cluster

    hwater

    Subsea facilities

    waterinstwellsunitsubsea haN 7,0

    Subseacosts,m

    ln.

    $

    Nwells/Cluster

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    Cumulative forecast error does not exceed 30% (permissible error for theconceptual design)

    30%

    Hibernia

    --

    -

    0

    50

    100

    150

    200

    250

    0 20 40 60 80 100 120 140 160 180

    , V , ...

    ,

    V

    ,...

    30%

    0

    10

    20

    30

    40

    50

    60

    70

    80

    0 10 20 30 40 50 60

    , ..

    ,..

    Forecast accuracy

    GBS model error

    30% spacing error

    Topside model error

    30% spacing error

    Realvalue,

    000t.

    Estimated value, 000 t. Estimated value, 000 cub.m.

    Realvalue,

    000cub.m.

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    Tampico

    TamaulipasMorgan City

    Daewoo

    Hyundai

    Okpo

    Verolme

    VlissingenSt.Wandrille

    Algeciras

    Puerto Real

    Keppel

    Labor

    Matherials Transportation

    St. Johns

    k2

    k3

    k

    4

    k5

    k1

    CAPEX = kiCAPEXtopside+ kjCAPEXGBS+ klCAPEXSubsea

    Regional component

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    An example of a typical platform 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.$ 3477

    GBS 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

    OPEX

    CAPEX

    .

    30% error in estimating capital costs leads to a shift in the NPV assemblyaverage at 28%

    100% -4%-77%

    -18%-4%

    -- CAPEX

    -60%

    -30%

    0%

    30%

    60%

    -30% 0% 30%

    NPV

    CAPEX

    -15%

    0%

    15%13%

    18%

    23%

    28%

    33%38%

    43%

    +30%-30%

    Economics

    -52%

    -40%

    -28%

    -16%

    -4%

    Mln.rub

    Revenue

    Transportation

    costs

    Royaltiesand

    taxes

    conditional permanent CAPEX

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    Results

    1. Identified a minimal set of informative parameters forcapital 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 develop

    fields

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    Thank you!

    Capital Costs Estimation Methodfor Arctic Offshore Oil Projects