YANG_risk

Geologic risk analysis and resource assessment

Presented by Mr. Yang Dengwei2003.2.28

Part 1

Resource Assessment Principals

Contents

Four levels of petroleum resource assessment

Basic methods of petroleum resource assessment

Principals and procedures of play assessment

Principals and procedures of prospect assessment

Resource AssessmentGovernment

Long term energy policy Forecast discoveries/supply Environmental impact Future technical/capital needs Schedule lease sales etc. Economics of industry participation Political and regulatory options Exploration planning

Resource assessment

Industry Guide exploration by ranking opportunities Forecast rate of discovery and supply

( reserve/production ) Future technological/capital needs Schedule exploration activities Economic analysis to guide investment

decisions Future amount of exploratory drilling

1.1 Four Levels of Petroleum Resource Assessment

-Basin level-Petroleum system level-Play level-Prospect level

Four Levels of Petroleum Resource Assessment

Sedimentary basin investigation emphasize the stratigraphic sequence and structural style of sedimentary rocks.

Petroleum system studies describe the genetic relationship between a pod of active source rock and the resulting oil and gas accumulations.

Play investigations describe the present-day geologic similarity of a series of present-day traps.

Prospect studies describe the individual present-day trap.

Factor comparison in the four levels of petroleum resource assessment

-----------------------------------------------------Sedimentary Petroleum

Factor Basin System Play Prospect---------------------------------------------------------------------------------------------Investigation Sedimentary rocks Petroleum Traps TrapEconomics None None Essential EssentialGeologic time Time of deposition Critical moment Present-day Present-dayExistence Absolute Absolute Conditional ConditionalCost Very low Low High Very highAnalysis &Modeling Basin System Play Play--------------------------------------------------------------------------------------------------------

( from L.B.Magoon, 1994 )

1.2 Basic Assessment Methods

Arial and volumetric yield Delphi Geochemical material-balance Performance or behavioristic extrapolation

based on historical data Combinations of geological and statistical

models B.M. miller,1986

Basic Assessment MethodsBasin

Arial and volumetric yieldDelphiGeochemical material-balancePlay aggregation

Petroleum systemDelphiGeochemical material-balanceBasin modelingPlay aggregation

PlayReservoir engineering ( Trap volume )Discovery processDelphiGeochemical material-balanceAnalogProspect aggregation

ProspectReservoir engineering ( Trap volume )Three point method

Arial and volumetric yield Methods in Combination with Geologic Analogy

This method was one of the first to be used in petroleum resource evaluation (Weeks, 1950:Zapp,1962;Hendricks,1965;Meyer,1978;Miller,1979;etc.). Based on comparative study, geologist apply a yield factor from one known basin to an unknown basin having similar characteristics. For conceptual plays, this method provides some information about the richness of the unknown basin.


The advantages of this method are: (1) this method combines geochemical data and/or e4xperience from mature basins, (2) it is easy to understand,(3) it is suitable for the evaluation of conceptual plays.

The disadvantages are : (1) assessment obtained cannot be validated; (2) the information provided by this method is clearly inadequate for economic study


Jones 1975Y =a x R x T x S X MY is reserves per cubic milea is an experience-based parameter (26 bbls per cubic mile )R is the fraction of the basin that can contain petroleum T is the fraction of R that is in trap positionS x M is (producible petroleum in trap)/(trap capacity)


Q =KVBWhere:

Q---Petroleum resources of interest areaK---Reserve density factor of geologic analog

basin ( or area )V---Sedimentary volume of interest areaB ---Similarity factor between interest area and

analog basins

Reserve density factor

Basin (or region ) Reserve density factor (t/km3)----------------------------------------------------------------------Illinois basin 1100Mexico Gulf 1900Oklahoma 2300California 5800Texas 1200Michigan basin 200USA 1800

Delphi or Subjective Consensus Assessment Methods

DefinitionSeveral experts ( each of whom is considered

equally expert ) makes a resource assessment expressed in terms of a range of uncertainty . A consensus is achieved by averaging probabilities at specific resource sizes to derive a single curve reflecting the group opinion of the uncertainty.

Miller et al.,1975;Dolton et al.,1981; Nation Petroleum Council,1981


Procedure A group of experts usually reviews all the geologic

information available in an area or basin, which sometimes includes the results of any previous assessments by other estimators and/or by other methods.

Each member of the team constructs his or her own probability distribution of the estimated potential resources.

The group reviews all the individual results and makes modifications where considered necessary.

The final probability distribution are determined either by consensus of the group or by averaging the individual probability distributions


Main advantage:It can be used at all scales ( basin to prospect ) and

exploration maturities.It is basically a fairly rapid and simple procedure.The results can be expressed as probability distributions, which reflect the uncertainties in the estimates.

Disadvantage:-often no documentation of assumptions and reasoning-subjective estimates prone to personal and collective-who decides that all the experts are equally expert?

Geochemical Material Balance Methods

The geochemical material balance methods are a special type of volumetric resource appraisal procedure by which one can estimate the amount of hydrocarbons generated in the source rocks, the amount of hydrocarbons involved in migration, the probable losses of hydrocarbons during the migration process, and the quantity of hydrocarbons that have been accumulated in the deposits.Neruchev,1962;Semenovich,1977, Philippi,1955Ungerer,1984

Geochemical Material Balance Methods

Advantages of the method are:--It is deterministic--It provides a way of calculating an upper limit for the resources--It is suitable for plays or basin

The disadvantage are:--the determinstic approach may not be fully satisfactory--It is inapplicable for prediction of individual pool size

Chloroform Bitumen A Method

Q = H x S x R x B x KbWhere:

QTotal amount of hydrocarbon generated ( 108t )H--- Thickness of source rocks (km)S--- Area of source rocks (km2)R---Source rock density ( 108t/km3)B---Chloroform bitumen A content (%)Kh---Bitumen transformation factor ( commonly 15%-20% )

R = Q x K1 x K2Where

R---Hydrocarbon resourcesK1---the fraction of expelled hydrocarbon (%) that is in generated hydrocarbon amountK2---the fraction of accumulated hydrocarbon (%) that is in expelled hydrocarbon amount

Organic Matter Quality Balance Method

Q = H x S x R x C x KcWhere:Q--- Total amount of hydrocarbon generated( 108t)H---Thickness of source rock (km)S---Area of source rocks (km2)R---Source rock density (108t/km3)C---Organic matter content (%)KcOrganic matter transformation factor ( commonly 1.0%-

1.2% )

R =Q x K1 x K2

Statistical Table of Expelled and Accumulated Factor

Basin oil expelled & Basin gas expelled &accumulated accumulated factor (%) factor (%)

--------------------------------------------------------------------------------------Southern Songliao 12 Sichuan (J) 0.05North China 10 Sichuan (P) 0.20Ordos (Mz) 3.6 Sichuan (E) 0.24Jizhong sag 4 Qaidam 0.36East China Sea 3 Illinois 0.40 Junggar 1-9 Timan-Pechora 0.80Volga-Ural 2 Los-Angeles 0.10 West Siberia 2Persiam Gulf 3Permian 10

Sedimentary rate method

lgQ =2.183 +1.613lgvWhere:

Q---petroleum resource of sedimentary basinV---average sedimentary rate of a basin

Type I, average sedimentary rate > 14km3/MaType II, average sedimentary rate = 4-14km3/MaType III, average sedimentary rate = 1.5-4km3/MaType I, average sedimentary rate < 1.5km3/Ma

1.3 Principals and procedures of play assessment

1. 3.1 Play definition1.3.2 Play assessment methods-Reservoir engineering method (FASFUM)-Discovery process

1.3.3 Procedures of play assessment1.3.4.Application of play assessment in

WGRA and OGRA projects

1.3.1.Play Definition

A play is defined as a group of prospects within a geographically delimited area, where a set of mutually related factors must be present concurrently in order to permit the discovery of hydrocarbon.reservoir rocks, traps, mature source rocks,migration path, timing

( CCOP )

Play definition

An exploration play consists of a family of prospects and/or discovered fields that share a common history of hydrocarbon generation, migration, reservoir development and trap configuration

( Geological Survey of Canada , 1986 )

Play Definition

Play is the elemental part of a petroleum system, and a recognized as having one or more accumulations of hydrocarbons identified by a common geological character of reservoir, trap, and seal; timing and migration; preservation; a common engineering character of location, environment, and fluid and flow properties; or a combination of these.( Otis and Schneidermann, 1997 )

Play Definition

Prospects and fields in a play have similar structural configurations and structural histories.

Prospects and fields in a play have similar top seals and seat seals.

Fields in a play form a coherent lognormal distribution of ultimately recoverable reserves.

It is defined primarily by the present-day maximum extent of a potential reservoir facies

Play defined at early stages of exploration, are often refined and split into several plays as knowledge increase with continued exploration

1.3.2 Play assessment methods

-Reservoir engineering method (FASFUM)-Discovery process(PRASS1)

Play assessment methods

Reservoir engineering method (FASFUM)

)1()/1( gasohoil HCPVBFSHAIPR =

GORIPRIPR oilassgas =

gasghgas HCPVBFSHAIPR = )/1(

CGRIPRIPR gascond =

Calculation equation

Where:IPRoilin-place oil resourcesIPRgasin-place non-associated gasIPRassgasin-place non-associatedIPRcondin-place condensateAarea of closureHeffective reservoir thicknessHCPVgasprobability that accumulation in a gas accumulation

effective porosityShHC saturationFtrap fillBooil formation volume factorBggas formation volume factorGORgas oil ratioCGRcondensate gas ratio (condensate field)

Risk analysis

Play attributes

Four regional characteristics that describe a given plat, including:

-Hydrocarbon source (S)-Timing (T)-Migration (M)-Potential reservoir facies ( R)

These attributes determine whether conditions underlying the play are favorable for occurrence of oil or gas within it.

Marginal play probability=product of play attributes

Hydrocarbon source

Hydrocarbon source is the probability of occurrence of a rock unit that has generated and expelled oil or gas in sufficient quantity to form one or more accumulation within the play.Based on:Minimum source-rock criteria Organic richnessKerogen type Thermal maturity

When known hydrocarbon accumulations occur in the play, this play attribute probability is 1 by definition.

Source rock evaluationA source rock is the sedimentary rocks that are, or may become, or have been able to generate petroleum.An effective source rock is generating or has generated and expelled petroleum.A potential source rock contain adequate quantities of organic matter to generate petroleum, but only becomes aneffective source rock when it generates bacterial gas at lowtemperatures or it reaches the proper level of thermal maturity to generate petroleum .

Quantity, or amount of organic matter Quality, or type of organic matter Thermal maturity, or extent of burial heating

Geochemical parameters describing the petroleum potential of an immature source rock

Organic matter Bitumen HydrocarbonPetroleumPotential ----------------------------- -------------------------

TOC S1a S2b (wt.%) (ppm) (ppm)(wt.%)------------------------------------------------------------------------------------------Poor 0-0.5 0-0.5 0-2.5 0-0.05 0-500 0-300Fair 0.5 -1 0.5-1 2.5-1 0.05-0.10 500-1000 300-600Good 1-2 1-2 5-10 0.10-0.20 1000-2000 600-1200Very good 2-4 2-4 10-20 0.20-0.40 2000-4000 1200-2400Excellent >4 >4 >20 >0.40 >4000 >2400 ------------------------------------------------------------------------------------------amg HC/g dry rock distilled by pyrolysisbmg HC/g dry rock cracked from kerogen by pyrolysis

( from L.B. Magoon , 1994 )

Geochemical parameters describing kerogen type (quality) and the character of expelled productsa

HI Main Expelled Kerogen type (mg HC/g TOC) S2/S3 Atomic H/C Product at

Peak Maturity----------------------------------------------------------------------------------------------

I >600 >15 >1..5 OilII 300-600 10-15 1.2-1.5 Oil

II/IIIb 200-300 5-15 1.0-1.2 Mixed oil and gasIII 50-200 1-5 0.7-1.0 GasIV

Geochemical Parameters Describing Level of Thermal Maturation

---------------------------------------------------------------Maturation Generation

-------------------------------- ----------------------------------------------Stage of Thermal Ro Tmax Bitumen/ Butumen PIcMaturation for oil (%) (0C) TAIa TOCb (mg/g rock) {S1/S1+S2)}---------------------------------------------------------------------------------------------------------------Immature 0.2-0.6 470 >3.3 -- -- -----------------------------------------------------------------------------------------------------------------a TAL. Thermal alteration Index.b Mature oil-prone rocks with type I or II Kerogen commonly show bitumen/TOC ratios in

the range 0.05-0.25. Bitumen/TOC ratios over 0.25 can indicate contamination ormigrated oil or can be artifacts caused by ratios of small, inaccurate numbers.

c PL, production index. ( from L.B.Magoon,1994)

Geochemical parameters of source rocks incontinental beds in China

Source rock TOC Chloroform bitumen HC HC/TOCType (%) (%) A ( mg HC/g rock) (%)----------------------------------------------------------------------------------------------------------

Excellent >1 >0.1 >500 >5Moderate 0.6-1 0.05-0.1 100-500 1-5Poorer 0.4-0.6 0.02-0.05 60-100

------------------------------------------------------------------------------------------------------------

TimingTiming [fraction or %] is the probability of occurrence of a suitable relationship between the time of trap formation and the time of hydrocarbon movement into or through the play area. Based on:-the time of trap formation -the time of maturity of source rocks.


Migration

Migration is the probability of effective movement of hydrocarbons through a conduit that may be permeable, a fracture or a fault. Its evaluation is based on structural and stratigraphicinformation from which inferences can be drawn concerning the presence of a geologically favorable conduit. When known hydrocarbon accumulations occur in the play, this play attribute probability is 1 by definition.

Potential Reservoir Facies

Potential reservoir facies is the probability of occurrence of a rock that contain porosity and permeability capable of containing producible hydrocarbons. Based on:

-reservoir data from the play- projections from adjacent areas-analog comparisons


Marginal play probabilityThis term expresses the probability that all of the first four play attributes are concurrently favorable somewhere in the play.Marginal play probability = S x T x M x T

If oil or natural gas deposit has been found in the play, the marginal play probability is 1.

If oil or natural gas deposit has not been found in the play, the marginal play probability is less than 1.

Prospect attributesThree local characteristics that determine the nature

of prospects within a play, including :-Trapping mechanism (TM)-Effective porosity (P)-Hydrocarbon accumulation (C)

Evaluation of these attributes is accomplished by recording a single value between 0 ( total certainty that the attribute is absent ) and 1 ( total certainty that the attribute is present ) for the probability that the attribute is generally favorable in a randomly selected prospect within the play area.

Trap occurrence

Trap occurrence is the probability of occurrence of a structural or stratigraphicconfiguration that provides a trap for migrating hydrocarbons.

Based on: -seismic or geologic mapping-projection from nearby areas-analog comparisons.

Effective porosity

Effective porosity is the probability of significant interconnected void space of a potential reservoirfacies capable of holding hydrocarbons. Evaluation of this attribute is recorded with an estimate of the probability that the porosity in the prospect is equal to or greater than the threshold porosity defined in the effective porosity volume parameter. Based on : measurement, calculation, projection

or analog comparisons.

Reservoir quality prediction

Predicting sandstone reservoir porosity-Porosity-depth plots-Equation for porosity prediction-Predicting effects of diagenesis on porosity-Estimating effect of near-surface diagenesis-Predicting sandstone porosity from burial history-Analog porosity

Related Technologies Used in Porosity Predictions

Technology Why is it important?----------------------------------------------------------------------------------Sedimentology Facies analysis,environment of depositionPetrography Microfacies,diagenesis, pore system descriptionFluorescence Depositional/diagenetic fabric recognition, pore

geometryLuminescence Depositional/diagenetic fabric recognitionGeophysics Facies analysis,unconformity recognitionCore analysis Porosity, permeability, pore geometryInorganic geochemistry Diagenetic interpretations, unconformity recognitionOrganic geochemistry Source rock quality, migration timingFluid inclusion thermometry Migration timing, diagenesis,thermal maturityThermal maturity analyses Indirectly related to porosity, hydrocarbon phase preservedBasin modelling Timing of porosity creation/destruction events, depth of

burialCompaction simulation Prediction of past burial depth and depth to porosity

basementRock mechanics Probability of fracturing

Equation for porosity predictionPorosity = 18.60 +(4.73 x in quartz) + (17.37/sorting )

- (3.8 x depth x 10-3 ) (4.65 x in age )Where:

Porosity = percent of bulk volumeIn quartz = percent of solid-rock volumeSorting = Trask sorting coefficientDepth = matersIn age = millions of years

Use 75% for percent solid volume quartz and 1.5 for sorting when these values are not known.

( from Scherer , 1987 )

Using burial history to predict porosity

Step 1. Construct a burial history diagram for the formation of interest in the prospect area.Step 2. Plot the tectonic history of the basin in the prospect area along the lower x-axis.Step 3. Plot the hydrologic history of the prospect area along the lower x-axis. Use the tectonic history to infer the hydrologic history of the prospect.Step 4. Plot the porosity curve by combining concepts of diagenetic processes with burial and hydrologic of the prospect.

Analog porosity

Analog porosity values for different depositional environments can help us predict the porosity of reservoir system rocks when the target formation is unsampled within the basin. Analog values, however, may have wide ranges within facies and subfacies of depositional environments. Therefore, we should use care when applying analog data.

Predicting sandstone permeability from texture

Pore type, pore geometry, and fluid properties are critical factors affecting permeability. Sandstone texture directly affects pore type and geometry,. Knowing what textures and fluids to expect, as well as what authigenic clays might be present, can help us predict permeability.

Effects of pore type and geometry

Pore type, defined by pore throat size ( I.e.,macroporosity), directly controls rock permeability. Pore throat size limits flow capacity. Pore geometry also affects permeability, but not as much. The rougher the surface of the pore, the more difficult for fluid to flow through the pore and the lower the permeability.

Effects of texture

Decreasing grain size decreases permeability

Increasing grain sorting increases permeability.

Increasing grain rounding increases permeability.

Effect of authigenic clays

Pore-bridging clays, like illite, decrease porosity slightly but can destroy sandstone permeability. Discrete particle clay, like kaolinite, lowers porosity and permeability only slightly.

Detrital clay and permeability

Detrital clays can be part of sandstone matrix or grains. As matrix, detrital clays can obliterate permeability. Detrital grains of clay are often ductile and can be compacted into pore spaces during burial. The percentage of detrital clay in a rock determines permeability.

Predicting sandstone permeability from texture

Step 1, Estimating grain size, sorting, and porosity using the depositional environment. For example, if a reservoir is a beach sand, it should be fine-to medium-grained and well sorted with well-rounded quartz grains.

Step 2, Apply information from Step 1 to the porosity-permeability-grain size plot. Use porosity and grain size from sandstone to estimate the permeability on the chart.

Step 3, If the sandstone is poorly sorted or is cemented, then discount permeability downward.

Step 4, Determine if authigenic clay is present,. If so, what kind: pore lining,discrete particle , or pore throat bridging? Adjust permeability downward according to clay type present.

Step 5, Determine if detrital clay is present using depositional environment (i.e. high energy= low clay content ). If detrital clay is likely, then expect permeability to be low.

Discovery process modelsThese methods project future discoveries from statistical analysis of discovered field-size distributions. The basic assumptions are that discovery is both proportional to pool size and to sampling without replacement.

Number of prospect distribution Number of pool distribution Play resource distribution Pool size by rank Generation of reservoir parameters This approach is applicable only in areas where

considerable discoveries have been made

Hydrocarbon accumulationHydrocarbon accumulation is the conditional

probability of occurrence in a randomly chosen prospect in the play of the combination of hydrocarbon source and migration necessary for the formation of hydrocarbon charge equal or larger than the minimum size.

Based on :the structural, stratigraphic and thermal

history of the play.

Conditional deposit probabilityConditional deposit probability is the probability that a

randomly chosen prospect in the play is an accumulation, given that the play is favorable for hydrocarbon accumulation ( i.e. marginal play probability is 1 )

Conditional deposit probability = TM x P x C

As a guide, the conditional deposit probability should not exceed the success ratio calculated from the drilling results so far.Usually the drilling starts in the most promising parts of the play. It is necessary to evaluate if the remaining parts of the play is better or worse than the explored part.

Unconditional play probability

Unconditional play probability ( discovery probability )is the probability that at least one undrilledprospect in the play is hydrocarbon accumulations of minimum size.

Unconditional play probability = play marginal probability x conditional deposit probability

Play resource estimates1. Reservoir parameters

Reservoir lithologyHydrocarbon mix

2. Hydrocarbon volume parametersarea of closurereservoir thicknesseffective porosityhydrocarbon saturationtrap fillreservoir depthrecovery rate oilrecovery rate gas

Play resource estimates

3. The number of prospects4. Reservoir parameters

original reservoir pressurereservoir temperaturegas-oil ratiooil formation factorgas compressibilitycondensate yieldoil floor depth

Minimum threshold valuesUSGS

Area of closure 2.4 km2 ( 600 acres )Reservoir thickness 1.6 m (5ft )

Effective porosity 3%Trap fill 1%Reservoir depth 30m ( 100 ft)

These minimum values are used at the 100th fractile unless a higher value is selected.

The probabilities that these threshold values are achieved are incorporated in the prospect attribute judgements and the number of drillable prospects distribution.

The minimum threshold values are selected to be less any reasonable economic limit in order to prevent economic considerations from influencing the evaluation procedure.

Area closure

Area of closure is the distribution of the mean area within a trap above the spill point. A minimum threshold value is required. Data used in the evaluation of this parameter may include seismic mapping, surface geologic mapping, or analog comparison.

Reservoir thickness Reservoir thickness is the possible range for the

mean thickness of the reservoir, or the amount of vertical closure in the situation where structural amplitude is less than individual reservoir thickness. Thickness values describe the maximum reservoir thickness for a single reservoir or for stacked multiple reservoirs with effective porosity of a minimum threshold value. Data used in the evaluation of this parameter may include seismic mapping, surface and subsurface geological measurements, projection from nearby areas, or analog comparison

Effective Porosity Porosity is the distribution of the mean

amount of interconnected void space in the reservoir rock. A minimum threshold value is used at the 100th fractile, and the probability that this minimum value is achieved is incorporated into the probability of effective porosity judgement. Data used in the evaluation of this parameter are based on measurement, calculation, projection, or analog comparison.

Trap fill Trap Fill [fraction or %] is the distribution of

the mean trapped hydrocarbon volume as a percentage of the porous volume under closure. A minimum threshold value is used at the 100th fractile. The probability that this minimum value is achieved is incorporated into the probability of hydrocarbon accumulation judgement. Data used in the evaluation of this parameter is based on source-rock richness and thermal maturation, hydrocarbon drainage area, size of structure, porosity and permeability of reservoir rock, or analog comparison.

HC Saturation

HC Saturation [fraction or %] is the distribution of the mean hydrocarbon saturation for the prospects in the play. The hydrocarbon (HC) saturation is 1 minus the water saturation

Reservoir Depth

Reservoir depth [meters or feet] is the distribution of the mean depth that must be drilled to penetrate potential reservoir facies. A minimum threshold value is used at the 100th fractile. Data used in the evaluation of this parameter may include seismic mapping, projection from nearby areas or analog comparison

Number of drillable prospectsThis play characteristic describes the range of

possible values for the number of valid targets that would be considered for drilling if the play were to be fully explored.

Only prospects with the minimum accumulation size are considered.May be estimated by using :

seismic mapping surface and subsurface mapping prospect density scaled to the area of the area

of the play based on mature part of play or analogue

Recovery Rate

Recovery Rate Oil is the distribution of the mean amount of oil in-place that can be recovered.

Recovery Rate Gas is the distribution of the mean amount of gas in-place that can be recovered

Probability of gasProbability of gas ( Hydrocarbon mix ) is the

probability that an accumulation is a gas accumulation. 1 minus this probability is the probability that the accumulation is an oil accumulation.

Based on: -thermal maturity-type of organic material -the type of hydrocarbon observed in wells and seeps

-seismic observation

Geological variables as a function of depthOriginal reservoir pressure [bars or psi]Reservoir temperature [Deg K or R]Gas-Oil Ratio [ sm3/sm3or scf/STB]Oil Formation Factor [sm3/sm3or bbl/STB]Gas Compressability factor [real]Condensate Yield [sm3/1000 sm3 or STB/1000 scf]

(Zoned ) linear functionA x Depth +B

Exponential functionPower functionLogarithmic function

Original reservoir pressure

PRES = PINT + (PGRAD)Dwhere

PRES---reservoir pressure(bar)PINT---surface pressure (bar)PGRAD---pressure gradient (bar/m)

If the original reservoir pressure is equal to the hydrostatic pressure, the function could be written as :

PRES = 0.1 x depth + 1If the original reservoir pressure is 30% higher than the

hydrostatic pressure, the function could be written asPRES = 0.13 x depth +1

Reservoir temperature

TRES = TINT + (TGRAD ) DWhere:TRES---reservoir temperature (K )TINT---surface temperature( K )TGRAD---temperature gradient ( k/m )D---depth ( m)

Gas-oil ratio

May be estimated by using: Local data Basin modelling Standing chart for saturated oils (input: pressure, temperature, oil and gas gravities ) Vasquez-Beggs equations (Empirical) (input:as above)

Oil formation volume factor

Local dataStanding chart for saturated oils(Input: GOR, gas and oil densities,

temperature)Vasquez-Beggs equation (empirical)(input: as above)

Gas Compressability factor

Local measurements Analog analysisEmpirical equation

Z= 0.000099 x depth + 0.68Abrahamsen (1989)

FASPUM output Number of accumulations is the number of accumulations

of the relevant hydrocarbon type. Accumulation size is the amount of in-place hydrocarbons

in an accumulation. Conditional prospect potential is the risked amount of in-

place hydrocarbon in a randomly selected accumulation under the assumption that the marginal play probability is 1.

Conditional B play potential is the risked amount of in-place hydrocarbon expected to be found in the play under the assumption that the marginal play probability is 1 and that there exists at least one undrilled accumulation of the relevant type in the play. This estimate of play potential therefore ignores that there are a finite number of prospects available for drilling.

Faspum output Conditional A play potential is the risked amount

of in-place hydrocarbon expected to be found in the play under the assumption that the marginal play probability is 1. This estimate of play potential should be close to the B potential when there are a large number of prospects in the play.

Unconditional prospect oil potential is the amount of in-place oil in the accumulation given the estimated value of the unconditional prospect probability. If the marginal play probability is 1 then the unconditional prospect potential and the conditional prospect potential are identical.

1.3.3 Principals and procedures for play assessment

Play definition Information-or data gathering Construction of play model Play geologic risk assessment Play resource estimates Delineation of permissive areas Play economic analysis Reporting of assessment results

Information or data gathering

Types of information and data compiled relate to the following :1. Petroleum geology2. Exploration history3. Seismic exploration4. Production and reserves statistics5. Analog basins or information

Construction of play modelSynthesize geologically related factors to represent a certain

type of hydrocarbon prospectivityFactors to be considered:

1.sedimentation and tectonic evolutionsource rockdevelopment and configurationhydrocarbon generation/migration/accumulationreservoir characteristicsseal characteristics

2. sea level changes3.heatflow/geothermal gradient

Delineation of permissive areas-to define areas which are economically, technically and

politically feasible for petroleum explorationFactors to be considered: exploration density

seismic coveragewells drilledgeological mapping

geologic faciesareal distribution of playgeothermally favorable area extent of stratigraphic units and their thicknessadequate trap and sealpresence of mature source rockcontamination-N2, CO2migration patternsporosity and permeability

geographical limitoffshore-water depth, block or country boundaryonshore-block or country boundary, topography

Reporting of assessment results- Present values realistically and minimize risks and to identify economically feasible work program

Factors to be considered: purpose of assessment methodology and data sets used remaining plat potential expressed as P95/expected

value/P05 values total play potential ( remaining potential combined

with produced, developed and discovered resources ) hydrocarbon accumulations

accumulation size distributionnumber of accumulationoil and gas distribution

risk factor ranking of plays, areas, etc.

1.3.4 The Discussion on input & output data of resource assessment in WGRA and

OGRM projects

Discussions on input data Discussions on output data

Discussions on input data

Marginal play probability Conditional deposit probability Possible guideline for success ratio Prospect risking guide Possible guidelines for prospect densities Geometric factor Recovery rate

Marginal play probability

If oil and gas field ( or fool ) has been found, in the play, the marginal play probability is 1.

If oil and gas field ( or pool ) has not been proven by drilling in the play, the marginal play probability should be less than 1.

Marginal play probability 0.4-0.6 : Little or no available data on which to base a geological

model; play may with equal likelihood eventually be vindicated or denied.

0.6-0.8: Sufficient data on which to base a geological model which predicts that play may possibly be affirmed by subsequent data acquisition, including drilling.

0.2-0.4 : Sufficient data on which to base a model which predicts that play possibly be denied by subsequent data acquisition, including drilling.

0.8-1.0: Further data which strengthen the model prediction to : play will probably be affirmed by drilling.

0.0-0.2: Further data which strengthen the model predictions to: play will probably be denied by drilling

( From B.A Duff and D.Hall, 1996 )

Marginal play probability

Play play probability ranges from zero in hopeless plays to 1.0 in the assured extensions of existing productive plays or established plays. Average plays chance in a group of 1150 plays in 80 productive basins was 0.35 ( white, 1980 ), but new plays generally are becoming riskier.

Average marginal play probabilityChance of at least one major field:for sandstone plays=0.38for carbonate lays=0.30for all plays=0.35

(1150 plays in 80 productive basins---White, 1980 )

Probability of hydrocarbon accumulation

Step 1: Calculating the primary feature value of hydrocarbon accumulationNo.discoveries / No. drilled prospects with effective porosity and trap mechanism

Step 2 : Making a judgement for the whole play area based on regional conditions of hydrocarbon accumulation

Conditional deposit probabilityAs a guide, the conditional deposit probability should not

exceed the success ratio calculated from the drilling results so far.Usually the drilling starts in the most promising parts of the play. It is necessary to evaluate if the remaining parts of the play is better or worse than the explored part.

Possible guideline for success ratios

The success ratio in a play is the number of expected fields exceeding minimum size divided by the number of prospects large enough to hold fields of at least that size.

Success ratios reflect independent individual prospect risk. They are highly influenced by the selected population of prospects.

Possible guideline for success ratios Ratios may be very high for a high-graded

group of prospects in the best part of a productive trend. They may be much lower if a large number of fringing poor prospects are included in the group.

Success ratios range from zero in nonproductive plays to 1.0 in exceptionally productive plays (e.g.,heart of the Los Angeles basin ). More typically, success ratios range from near zero to 0.5 and average about 0.25.

Prospect risking guide

Extensions of producing plays0.3-0.5 ( play success ratio ) x 0.8-1.0 ( common play chance )=0.24-0.50 (average prospect chances )

Good-looking new plays0.2-0.3 x 0.3-0.4=0.06-0.12

Poorer-looking new plays0.1-0.2 x 0.1-0.2=0.01-0.04

( White,1993 )

Prospect risking guide

1.Very low risk ( Pg between 0.5 and 0.99 )All risk factors are favorable. This category is associate with wells that test proven plays adjacent to ( 10km) existing production.

Prospect risking guide 4.High risk ( Pg between 0.063 and 0.12 )One or two risk factors are encouraging

Two or three factors are neutral or encouraging to neutral. This category is often associated with wells testing new plays in producing basins far from( >20km) existing production or proven plays in an unproved area

(from B.A.Duff and D.Hall,1996)

Prospect risking guide 5. Very high risk (Pg between 0.01 and

0.063 ) Two to three risk factors are no better than

neutral, with one or two factors questionable or unfavorable. This category is usually associated with wells testing new plays in an unproved area far from (>50km) existing production.

(from B.A.Duff and D.Hall,1996)

Probability factorGeox Guideline of CCOPHydrocarbon source ReservoirTiming TrapMigration Petroleum ChargePetroleum reservoir Retention afterFacies AccumulationTrapping mechanismEffective porosityHydrocarbon accumulation

The CCOP Guidelines for Risk Assessment of Petroleum Prospect

Probability Marginal play probability Conditional prospectprobability

Reservoir probability of existence of probability of effectiveness(P1) reservoir facies (P1a ) Of the reservoir (P2b)

Effective trap probability of effective probability of presence of the (P2) seal mechanism ( P2b ) mapped structure (P2a)

Petroleum probability of effective probability of effective charge migration

(P3) source rock (P3a ) migration (P3b )Retention probability of retention

(P4) after accumulation (P4

Estimating remaining number of drillable prospects in a play

Prospect density:=No. of prospects+ No. of wells ( discoveries & dry wells)

area of mature acreage

No.of remaining drillable prospects:=prospect density x total acreage- drilled wells

Problem:analogs for prospect densities of stratigraphic traps

Possible guidelines for prospect densities

Prospect densities number per 1000 sq mi or 1000sq km ) are used to help postulate number of likely but unseen prospects, by comparing what is known about the area being assessed with the density of a thoroughly drilled or mapped look-alike area .

Prospect densities depend on the minimum field size being assessed. A very rough rule of thumb is that it takes about 1 sq mi (2.6 sq km ) closure area to hold a 10 x106 bbl (1.6 x 106m3) oil field, but there is great variation depending on pay thickness, porosity, etc.


Prospect densities vary with structural and stratigraphic trap style.--for large prospects ( 5 sq mi or 13 sq km ) that might hold a major field ( 50 x 106 bbl or 8 x 106m3 ), the density may range from 1 to about 30 per 1000 sq mi (0.4 to 12 per 1000 sq km ).--smaller densities are typical of simple structural deformations such as normal-faulted blocks, and larger ones characterize complex deformations such as wrench styles, foldbelts, or intermixed salt and glide features.--prospect densities for stratigraghic traps are very uncertain, except perhaps for some reefs


Studies of local conditions and good geologic look-alikes are essential, based on the particular minimum field size being assessed. The best look-alike is the thoroughly drilled extension of an assessed play.

Geometric factor

Geometric factor is a correction factor that accounts for the thinning of a full hydrocarbon column at the edge. Data used in the evaluation of this parameter may include seismic mapping, surface and subsurface geologic measurements, projection from nearby areas, or analog comparisons.

Recovery rate

The recovery factor is often the most important and the most difficult parameter to establish with confidence at any stage.

The recovery factor is dependent on many aspects which range from reservoir drive mechanisms, fluid viscosity, reservoir thickness, rock permeability, porosity, rock type right down to the abandonment conditions

In prospect evaluation the reserves are recoverable using good oilfield practices .

Empirical value of recovery rate

Gas pool Oil pool Strongly water drive 30%-40% 45%-60% Partly water drive 40%-50% 30%-45% Gas- top drive 50%-70% 20%-40% Solution gas drive 50%-70% 10%-20%

Empirical equation

Er=21.4287(K/o)0.1316

Er=recovery rateK=permeability

0=oil viscosity

Geological variables as a function of depthOriginal reservoir pressure [bars or psi]Reservoir temperature [Deg K or R]Gas-Oil Ratio [ sm3/sm3or scf/STB]Oil Formation Factor [sm3/sm3or bbl/STB]Gas Compressability factor [real]Condensate Yield [sm3/1000 sm3 or STB/1000 scf]

(Zoned ) linear functionA x Depth +B

Exponential functionPower functionLogarithmic function

Original reservoir pressure

PRES = PINT + (PGRAD)Dwhere

PRES---reservoir pressure(bar)PINT---surface pressure (bar)PGRAD---pressure gradient (bar/m)

If the original reservoir pressure is equal to the hydrostatic pressure, the function could be written as :

PRES = 0.1 x depth + 1If the original reservoir pressure is 30% higher than the

hydrostatic pressure, the function could be written asPRES = 0.13 x depth +1

Reservoir temperature

TRES = TINT + (TGRAD ) DWhere:TRES---reservoir temperature (K )TINT---surface temperature( K )TGRAD---temperature gradient ( k/m )D---depth ( m)

Gas-oil ratio

May be estimated by using: Local data Basin modelling Standing chart for saturated oils (input: pressure, temperature, oil and gas gravities ) Vasquez-Beggs equations (Empirical) (input:as above)

Oil formation volume factor

Local dataStanding chart for saturated oils(Input: GOR, gas and oil densities,

temperature)Vasquez-Beggs equation (empirical)(input: as above)

Gas Compressability factor

Local measurements Analog analysisEmpirical equation

Z= 0.000099 x depth + 0.68Abrahamsen (1989)

Oil floor depth

Oil floor depth = Critical reservoir temperature / geothermal gradient

Discursion of output dataYield factorAccumulation SizeProspect evaluation

Yield factor

In the Southeast Asia and East Asia plays evaluated in WGRA and OGRM projects , the yield factors commonly range from 0.03 to 0.09 tons/ m^3 pore space for oil, from 3 to 33 m^3/ m^3 pore space for non-associated gas, and from 0.0059 to15.759 m^3 / m^3 pore space for associated gas.

25.5425.110.064Miocene sandstone ,Nam Con Son Basin

0.7630.120.033Oligocene sandstone, Andaman Sea

0.0929.610.09Miocene carbonate, North Sumatra Basin

4.8615.050.058Miocene Turbidite sandstone, North Sumatra Basin

/2.09/Miocene sandstone , Ullenung Basin

/38.65/Miocene carbonate , Sarawak Basin

13.145.380.059Miocene carbonate, Nam Con Son Basin

12.3223.220.07Tertiary sandstone, Subei-South Yellow Sea Basin

12.5824.950.09Lower Paleocene sandstone, East China Basin

Associated gas (t/m3 pore space)

Non associated gas(t/m3 pore space)

Oil(t/m3 pore space)

Plays

Yield factors in Southeast and East Asia plays

Accumulation Size

In the Southeast and East Asia plays evaluated in WGRA and OGRM projects, the accumulation size usually ranges from 13 to 43 x 106 t for oil pool and from 10 to 50 x 10 9 m3 for non-associated gaspool.

Resource assessment

In general, geologists tend to overestimate with a factor of 2-2.5. This is mainly because of :

Subjective judgments, and The multiplicative nature of the calculation.

OverestimatesBecause of the multiplicative nature of the calculation, even an average overoptimism of each parameter with 20% given an overestimate of recovarable resourceswith a factor of 3.0!

Gross rock volume 100% 112.5% 116.5% 120%Net/gross ratio 100% 112.5% 116.5% 120%Porosity 100% 112.5% 116.5% 120%HC-saturation 100% 112.5% 116.5% 120%FV-factor 100% 112.5% 116.5% 120%Recovery factor 100% 112.5% 116.5% 120%

---------------------------------------------------------------------Product 100% 200% 250% 300%

How can we improve ?

Internal guideline andprocedures for resourceassessment

post-mortem evaluation;compare drilling results withpre-drill estimates

Improve internal guidelinesand procedures

Discovery process modelsThese methods project future discoveries from statistical analysis of discovered field-size distributions. The basic assumptions are that discovery is both proportional to pool size and to sampling without replacement.

Number of prospect distribution Number of pool distribution Play resource distribution Pool size by rank Generation of reservoir parameters This approach is applicable only in areas where

considerable discoveries have been made ( Kaufman,1975; Roy and Ross,1980;Lee and wang, 1986

1.4 Prospect assessment

1.4.1 Prospect definition

1.4.2 Prospect resource assessment

Reservoir engineering ( Trap volume )

Three point method

Prospect portfolio (aggregation )

1.4.3 Principals and procedures of prospect assessment1

1.4.1 Prospect Definition

A prospect is a trap that may contain a petroleum deposit, and is mapped in three dimensions

( STATOIL )

1.4.2 prospect resource assessment

Three-point method ( J.E. Warren 1980-1984 )

Basic equation

Roil=7758AhSh(1/Bo)RfoR(gas)=43560AhSh(1/Bg)RfgR(condensate)=43560AhSh(1/Bg)

RfgCGR

Where:A = areal extent of prospect in acresH = average net pay in feet = average porositySh = hydrocarbon saturationBoil =initial oil formation volume factor in reservoir barrels/stock

tank barrels ( STB )Bg = initial gas formation volume factor in reservoir cubic

feet/surface cubic feetRfo = recovery factor for oilRfg = recovery factor for gasCR = condensate recovery factor in STB/ft3

7538 = conversion factor from acre-feet to barrels43560 =conversion factor from acre-feet to cubic feet

Calculation stepsStep 1

Specify the parameter ranges ( 5%, 10% and 95% probabilities of occurrence of each parameter )

Step 2Calculate a mean and variance for each parameter

m(v) = 0.185P5(v) + 0.63 P50(v) + 0.185 P95(v) m2(v) = 0.185 P5(v)2 + 0.63 P50(v)2 + 0.185

P95(v)2

2(v)=In[m2(v)/m(v)2]

Where

m(v)the mean of the natural logarithm for each parameter

If calculating the mean of areav = A, i.e. m(V) = m(A)2(v)the variance of the natural logarithm for each parameterP5(v)the 5% probability of occurrence for each parameter

P50(v)the 5% probability of occurrence for each parameter P95(v)the 5% probability of occurrence for each parameter

For example, the mean and variance of area in the table are:

m(A)=0.185225+0.63900+(0.1853300)=12192(A)=ln[(0.185225)2+(0.63900)2+

(0.1853300)2]/(1219)2=0.5337

Step 3 Multiply the parameter means and sum the variance to obtain the mean and variance of the reserve distribution

2[R(oil)] = 2(A) + 2( h ) + 2()+2( Sh ) + 2( 1/Bo ) + 2( Rfo )

m[R(oil)] = 7758 m(A) m(h) m(p) m(Sh) m(1/Bo) m(Rfo)

In the table 2[(oil)]=0.0000+0.5337+0.5591+0.0154+0.0360+0.0176

+0.0158+0.0075+0.0645=1.2496

m[R(Oil)=77581219870.81110.77780.25190.78520.70000.3182

=23106bbl

Step 4

Calculate values for different probabilities of occrrence

Rx = P50 (R) ez(x) whereP50(R)m(R) e-0.5 2

Z(x)the value or z factor corresponding

to the x-percentile of the standard normal distribution

In the table

Median (50% probability)=23e-0.51.2496=12106bblLow(10% probability)= 12e-1.2821.2496=3106bbl

TABLE 6-1 THE PETROLEUM RESOURCES CALCULATION TABLE OFTHREE-POINT METHOD

COUNTRY/CONCESSION/PROSPECTDEPTH TO OBJECTIVEWELL COSTEVALUATION

521231.249623RESERVE106 BBL0.370.310.260.06450.31820.450.320.18RECOVERY FACTOR

0.740.700.660.00750.70000.80.70.61/FVF

0.850.780.720.01580.78520.920.80.6HC SATURATION

0.270.250.230.01760.25190.310.250.2POROSITY

///0.03600.77780.980.80.5GEOMETRIC FACTOR

///0.01540.81710.960.830.63NET TO GROSS

///0.5591872406315GROSS PAYFT15339345690.533712193300900225AREAACRES

///0.00007758775877587758CONVERSION FACTORBBL/ACRE-FT

HIGH(90%)

MEDIAN(50%)

LOW(10%)

VARIANCEMEAN95%50%5%

OUTPUTINPUT

Prospect portfolio(Ed Capen, 1992)

Calculation step aDetermine 10% and 90% points for each prospect

in the portfolio with geological chance

bCompute mean and standard deviation of the natural loganithms for each prospect including truncation

corrections

= ln10%X + 0.5ln90%Xln10%X= (ln90%X) + ln10%X / 2

2 = (ln90%Xln10% / (2 1.28))22/2 += eM

( ) ( )[ ] ( ) ( )[ ]{ }LHLHHL zFzFzFzFMm lnlnlnln: /## =( ) /lnln = Lz L

= LL zz lnln#( ) /lnln = Hz H

= HH zz lnln#=1[1(0.6446930.161984z)4.874]6.158( ) .approxzF

2

e mole=

Commercial chance= CC = Cg[1F(L)]

Truncated var.= (0.894)(untruncated var. )e(-0.0187)(truncation pt.)

whereis the mean of that clear area between L and H i.e

the mean of truncated lognormal distribution H

10% X = the prospect reserve at 10% cumulated frequency

90% X = the prospect reserve at 90% cumulated frequency

HLm :

Figure Truncated lognormal c. Calculate mean and variance for the prospect portfolio M* = (piMi )/(1qi) V* = [1/(1qi)]{ piMi2ei2 } pi2Mi2[qi/(1qi)]( piMi)2} 2 = ln (V/M2 + 2) Where: M*and V* are the mean and variance of the resource distribution

of the prospect portfolio respectively Pi = Chance of success for each prospect, i = 1,2,3,n qi = Chance of failure for each prospect= 1Pi mi =Mean of resource distribution of each prospect I2 = Variance of resource distribution of each prospect dCalculate 10% and 90% points for the prospect portfolio 10% X = e 1.28* 90% X = e + 1.28*

1.4.3 Principles and procedures for prospect assessment

Play delineation Collect all relevant geophysical and geological

data Prospect identification and mapping Establish a geological model for the prospect Geological risk assessment Estimates of the prospects resource potential Calibration of the probability of discovery An analysis of potential interdependency on other

prospects Input to economic assessment

Part 2

The CCOP Petroleum Classification System The CCOP Guidelines for Risk Assessment of

Petroleum Prospects

2.1 The CCOP Petroleum Classification System

PurposeThis system is a supplement, and is not supposed to replace

any national classification system that is established in the CCOP member countries.

-act as a guide for those member countries that have not yet worked out their own system.

-contribute to a common understanding and future standardization of terms and definition used in resource classification in CCOP region.

-improve all communications on resource across borderlines and also be a vital tool for common promotion activities of CCOP region

The CCOP Petroleum Classification System

Basic Principles the petroleum resources should be considered as a

whole. possess clear and consistent definitions of the

terms. general and flexible guidelines. clear boundaries between different levels be easy to be used as well as for the governmental

agencies as for the petroleum industry.

The CCOP Petroleum Classification System

Framework of CCOP petroleum resource classification system

- be entirely based on recoverable petroleum resources.-comprises the two major parts: undiscovered recoverable and

discovered recoverable resources.-the undiscovered recoverable resources are further

subdivided into speculative and hypothetical resources-the discovered recoverable resources further subdivided intopotential recoverable resources and reserves.-for further subdivision of the reserves, the CCOP Petroleum

Classification System has adopted the Reserve Classification as described and published by the SPE and WPC in March 1997

Undiscovered petroleum resources

Speculative resourcesSpeculative resources is referred to the unmapped prospects that have not yet been mapped in the basin. The unmapped resources are estimated by play assessment methods.A statistical aggregation of all play assessments will give the estimate of the total undiscovered resources.

Hypothetical resourcesHypothetical resources comprise resources which are mapped in the form of prospects, but which have not yet been discovered by drilling.The resources are given a probability of discovery. The estimates of the total hypothetical resources are given by statistic aggregation of the risk-weighted resource estimate of each prospect in a play or an basin.

Discovered petroleum resources Potential Resources

Potential resources is defined as the discovered resources that are recoverable but not economically producible at a specific data due to economic, political, environmental or technological reasons.-Accumulations---such as marginal fields, relinquished fields, fields under dispute, or reservoirs with inconclusive data.- Accumulations that will probably be commercially recoverable in the near future/short term.-Accumulations that have no plans for developments in the near future/shore term.-Improved oil recovery-Non-producible reservoir

Discovered petroleum resources Reserves Unproved reserves Unproved reserves are based on geologic and/or

engineering data similar to that used in estimates of proved reserves, but technical ,contractual, economic, or regulatory uncertainties preclude such reserves being classified as proved

Possible reserves Possible reserves are those unproved reserves which

analysis of geologic and engineering data suggests are less likely to be recoverable than probable reserves.

Probable reserves Probable reserves are those unproved reserves which

analysis of geologic and engineering data suggests are more likely than not to be recoverable.

Discovered petroleum resources

Proved reservesProved reserves are those quantities of petroleum which , by analysis of geological and engineering data, can be estimated with reasonable certainty to be commercially recoverable, from a given data forward, from known reservoirs and under current economic conditions, operating methods, and government regulations

Discovered petroleum resources

Proved reserves Proved reserves are those quantities of petroleum

which, by analysis of geological and engineering data, can be estimated with reasonable certainty, to be commercially recoverable, from a given data forward, from known reservoir and under current economic conditions, operating methods, and government regulations.

2.2 The CCOP Guidelines for Risk Assessment of Petroleum Prospects

Introduction The probability concept Individual prospect probabilities Conditional probabilities Play probabilities Calibration of probability factors

Purpose for risk assessment

The purpose of risk assessment in petroleum exploration is to estimate the probability of discovery prior to drilling of a mapped prospect.

economic evaluationprofitability studiesexploration strategyassessment of undiscovered resources

The CCOP risk assessment guidelines provide general procedures for how to perform risk assessment

Principles for risk assessment

Geochronological risk assessment is achieved by evaluating the relevant geological processes and events in a logical time sequence.

In some cases, adjustments to the guidelines may be necessary in light of local geological knowledge of relevant areas and according to national requirements

Principles for risk assessment

In the risk assessment it may be useful to establish a set of general qualitative description for the relative probability scale.

Risk assessment

The probability of discovery is defined as the product of the following major probability factors, each of which must be evaluated with respect to presence and effectives:

Probability of reservoir Probability of trap Probability of hydrocarbon charge Probability of retention of hydrocarbon after

accumulation

Probability of effective reservoir

P1=P1a x P1bP1a: Probability of existence of reservoir facies with

minimum net thickness and net/gross-ratioImportant factors:depositional environmentdata reliability

P1b: Probability of effectiveness of the reservoir, with respect to minimum porosity, permeability and hydrocarbon saturation

Probability of effective trap

P2=P2a x P2bP2a: probability of presence of the mapped

structure with a minimum rock volume as applied in the volume calculation

P2b: probability of effective seal mechanism for the mapped structure

Petroleum charge

P3 =P3b x P3bP3a: probability of effective source rock in

term of the existence of sufficient volume of mature source rock of adequate area of the drainage area of the mapped structure.

P3b: Probability of effective migration of hydrocarbons from the source rock to the mapped structure.

Retention after accumulation ( P4 )

In order to avoid double-risking, we have to distinguish carefully between which factors affect the sealing mechanism and which affect retention after accumulation

Risk assessment procedure Collect all relevant geophycical and geological data. Prospect identification and mapping. Establish a geological model for the prospect Estimates of the prospects resource potential. Each prospect is given a value of probability of

discovery. Calibration of the probability of discovery on the basis of

success ratios, previous exploration history, etc. Presentation and discussion with an internal expert panel is

desirable . An analysis of potential interdependency on other

prospects under evaluation should also be carried out (Bayes equation or theorem)

Input to economic assessment

2.3 Other Guidelines for risk assessment

Risk factors

CCOP reservoir, trap, charge,retention after accumulation

NPD reservoir, trap, source and accumulation,retention after accumulation

Fina closure,seal, reservoir,chargeUSGS hydrocarbon source, timing, migration, potential

reservoir facies,tapping mechanism,effective porosity,hydrocarbon accumulation

Chevron source rock, reservoir,trap,timing/migrationD.A. White trap-seal-timing

reservoir-porosity-permeabilitysource-maturationpreservation-HC quality-recovery

The Chevron guideline for risk assessment

The probability of geologic success (Pg ) is obtained by multiplying the probabilities of occurrence of each of the four factors of the play concept

Pg=Psource x Preservoir xPtrap x Pdynamics(Otis and Schneidermann, 1997 )

Probability Factors

A. Source Evaluation1.Capacity for HC charge2. Source rock maturity3. Other

B. reservoir quality1.Presence2.Quality (for stab.flow)3.Other

Probability Factors

C. Trap integrity1. Trap definition2. Trap characteristics3. Seal- vertical&lateral

D. Timing/migration1. Timing2. Migration pathways3. Preservation4. other

Five broad categories

1.Very low risk ( Pg between 0.5 and 0.99 )All risk factors are favorable. This category is associate with wells that test proven plays adjacent to ( 10km) existing production.

Five broad categories4.High risk ( Pg between 0.063 and 0.12 )One or two risk factors are encouraging

Two or three factors are neutral or encouraging to neutral. This category is often associated with wells testing new plays in producing basins far from( >20km) existing production or proven plays in an unproved area

Five broad categories

5. Very high risk (Pg between 0.01 and 0.063 )

Two to three risk factors are no better than neutral, with one or two factors questionable or unfavorable. This category is usually associated with wells testing new plays in an unproved area far from (>50km) existing production.

Geologic risking guide for prospects and plays

David A. White1993

Adequacies of essential geologic controls of oil & gas for play/prospect

PLAY------ ----- PROSPECTa.--- trap seal - timing h.---x a=---p.

closure volume ( area and corrected height, structuralor stratigraphic)

seal ( top, lateral; no serious leakage by faults, fracture)timing ( particularly relative to migration)

b.--- reservoir porosity- permeability i.--- x b=---q.reservoir facies thickness ( no nondeposition, facies changetruncation,or faulting; adequate net/gross)porosity ( primary or secondary, not plugged or cemented)permeability & continuity

c.--- source maturation - migration j.--- x c=---rorganic quantity ( area,thickness, total organic carbon)& quantity (organic-matter type)maturation (sufficient time,temperature; not overcooked )migration (primary or expulsion; secondary,source to trap)

d.--- preservation HC quality recovery k.---x d=---s.preservation ( no bad flushing, biodegradation, diffusion)hydrocarbon quality & concentration ( oil not too viscous or of too low a saturation; gas not too dispersed or diluted by inerts:oil or gas column not too thin)recovery( drive, pressure, depth)

e.---play chance = a x b x c x df.---play success ratio( from grading, history, or look-alike)g. average prospect chance = e x f =---Conditional prospect success factor = h x i x j x k =---m.Overall prospect chance of adequacy = e x m = p x q x r x s =---t

Geological risk analysis of individual prospects

-the NPD procedure

The probability of discovery ( POD )

POD=P1 x P2 x P3 x P4P1-Probability of efficient reservoirP2-Probability of efficient trapP3-probability of efficient source and accumulationP4-Probability of efficient retention after accumulation

Probability of efficient reservoir ( P1 )

P1=P1a (modified by P1b)P1a = probability of existence of efficient reservoir facies

with minimum net reservoir thickness ( net/gross-ratio, thickness ) as applied the the resource assessment

P1b = probability of efficient porosityImportant factors

well datatype of facies and facies changesdepth and diagenesisporosity and permeability plotporosity mapsseismic velocities

Probability of efficient trap ( P2 )P1a= P2b x P2b

P1a= probability of existence of the mapped structural/geometrical body with a minimum rock volume as presented the resource assessment.

P2b = probability of efficient seal of the mapped structural/geometrical body

Probability of efficient source and accumulation ( P3 )

P3 = P3a x P3bP3a = probability of existence of sufficient volume of mature source rock of necessary quality located in the drainage area for the mapped structure.

P3b = probability of efficient migration of hydrocarbons from the source rock to the mapped structure.

Efficient retention after accumulation ( P4 )

Probability of effective retention of hydrocarbons in the trap from the time of migration and until today.

Important factors:biodegradationerosion of the subsurfacetiltingreactivation of related faults

A modal-based approach to evaluation of exploration

opportunities

B.A.Duff and D.hall

Documents

YANG_risk