ClassificationClassification for Gas for Gas ReservesReservesapplicableapplicable inin Poland Poland

PGNIG - Sanok Branch, Department of Geology & Geological Concession - Urszula Gawlik

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ReservesReserves ClassificationClassificationrankedranked by by thethe degreedegree of of explorationexploration

In Poland, Minister of In Poland, Minister of thethe EnviromentEnviroment’’ss Resolution (Resolution (JournalJournal ofof LawsLaws No No 136, 136, itemitem 1151 1151 ofof 6 6 JulyJuly 2006) 2006) isis definingdefining thethe explorationexploration categoriescategories for for

oil & gas oil & gas reservoirsreservoirs, , whichwhich areare requiredrequired by by thethe GeologicalGeological Report.Report.

AccordingAccording to to SectionSection 5.1 5.1 ofof thethe aboveabove Resolution Resolution thethe followingfollowing threethreecategoriescategories of of explorationexploration: C, B &A : C, B &A areare determineddetermined for natural gas, for natural gas, crudecrude oil & oil & methanemethane fromfrom hardhard coalcoal reservoirsreservoirs..

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Category C

boundaries of reservoir estimated as a result of geophysical research & geological interpretation.

The data obtained are used to continue more detailedexploration works or field development after obtaininga hydrocarbons inflow of commercial interest fromAT LEAST ONE WELL

The most important for category C is that: The range of statistical estimation of average reservoirfeatures and reserves MUST NOT EXCEED 40%

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Category B

The geological model of the reservoir is quite good and correct to define its boundaries (shape, size, structure of hydrocarbon trap) and to estimate reservoir parameterswith theirs vertical / horizontal variance.

Category B is based on results of the detailedexploration.

The most important for Category B is that: The range of statistical estimation of avarage reservoirfeatures and reserves MUST NOT EXCEED 30%

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Category A

requirements as for Category B but complying with PRODUCTION DATA from oil/gas field exploitation.

The most important for Category A is that: The range of statistical estimation of avarage reservoirfeatures and reserves MUST NOT EXCEED 15%

PGNIG - Sanok Branch, Department of Geology & Geological Concession - Urszula Gawlik

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Basic Basic methodsmethods of of reservesreserves estimationestimation

•• volumetricvolumetric

•• materialmaterial balancebalance

•• productionproduction declinedecline curvescurves analysisanalysis

•• statisticalstatistical

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VolumetricVolumetric –– basicbasic methodmethod mainlymainly usedused atat thethegeneralgeneral & & detaileddetailed reservoirreservoir

explorationexploration stagestage

gB

SGPHIEHNETAQ 1⋅⋅⋅⋅=

• Q - original gas in place (geological reserves) • A – reservoir surface• HNET– average effective thickness• PHIE – average effective porosity• SG – average gas saturation• Bg – gas formation volume factor

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Multiplication of reservoir parametersmaps:• Effective porosity – PHIE • Net/gross thickness - HNET• Gas saturation – SG

∑ ⋅⋅= iig

qaB1Q

• Q = original gas in place• ai – surface of every map cell• qi – hydrocarbon pore thickness in every map cell

qi = PHIEi * HNETi * SGi

• Bg – gas formation volume factor

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Effective thickness mapEffective porosity map Gas saturation mapHydrocarbon pore thickness map

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MaterialMaterial BalanceBalance –– dynamicdynamic methodmethodisis usedused onlyonly atat thethe reservoirreservoir exploitationexploitation stagestage

wefwgwtot BWEEGBtPUSGEF ++=+= )(),(

GasGas materialmaterial balancebalance equationsequations: :

• F - Total production (withdrawal) gas or gas & water• G – Original gas in place• Etot– Total expansion of reservoir Etot = Eg + Efw

• Eg – Expansion of gas• Efw – Expansion of connate water and reduction in the pore volume• U – Aquifer constant• S(P,t)– Aquifer function ( depending on model, pressure and time) • We - Cumulative natural water influx• Bw – Expansion of water

PGNIG - Sanok Branch, Department of Geology & Geological Concession - Urszula Gawlik

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TheThe fourfour most popular most popular graphicgraphic solutionssolutions ofof gasgasmaterialmaterial balancebalance equationsequations

•• P/Z P/Z methodmethod

•• HavlenaHavlena -- OdehOdeh methodmethod

•• Cole Cole methodmethod

•• PressurePressure MathMath methodmethod

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P/Z method – Pressure / Z- factor vs Cumulative Gas Production

Original Gas in Place (OGIP) = 200 mln nm3

= 7,2 BCF

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Havlena – Odeh method for gas reservoir with water influx

Original Gas in Place (OGIP) = 160 mln nm3

= 5,6 BCF

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Production decline curve analysis – successful dynamic method

Remainig reserves= 0,65 mln nm3 = 0,2 BCF

EOL – reservoir end of life

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nsz ⋅±

2α

range of expectedreserves value

Range of reserves estimation• Many wells (>20) in the reservoir

ααα −=⋅+<<⋅− 1)(22

snszQQ

nszQP

0

0.002

0.004

0.006

0.008

0.01

0.012

0.014

0.016

0.018

0.02

100 120 140 160 180 200 220 240 260 280 300

Reserves

Prob

abili

ty d

ensi

ty

Q

Q

α

s

nz

reserves expected valuereserves average value (based on well data)

reserves standard deviation (based on well data)

confidence factor from Gaussian distribution

number of wells

significance level (1-α – confidence level; 1-α =0.9)

reserves average value

P=0.9

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ααα −=−

⋅+<<−

⋅− 1)11

(22 n

stQQnstQP

Q

Q

α

s

nt

reserves expected valuereserves average value (based on well data)

reserves standard deviation (based on well data)

confidence factor from t-Student distribution

number of wells

significance level (1-α – confidence level; 1-α =0.9)

•several wells (4-20) in the reservoir

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1-3 wells – Monte Carlo simulation• Assumption of data intervals and type of datadistribution for independent reservoir parameters:

- surface A- effective thickness THNET- effective porosity PHIE- gas saturation coefficient SG

• Values sampling – random sampling from definedabove data populations of every parameter – many, many times

• „reserves” population set up – every reserves valuecalculated from set of sampled data

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Cumulant of reserves distribution estimated in Monte Carlo simulation

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

100 150 200 250 300 350 400 450 500

Gas reserves [mln nm3]

Prob

abili

ty t

hat r

eser

ves

are

grea

ter t

han…

• Reserves expected value estimation based on staticticalparameters of „sampled reserves” population

P 90proved

P 50probable

P 10possible

ααα −=⋅+<<⋅− 1)(22

szQQszQP

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Thank youfor your attention !

PGNIG - Sanok Branch, Department of Geology & Geological Concession - Urszula Gawlik