Uncertainty Analysis 2009

Reserves Estimation & Uncertainty analysis

Johny Samaan

Reservoir engineer

18 Dec-2009

Introduction

TargetEverybody involved in the actual generation of data for hydrocarbon resource volume management (HCRVM), e.g. Geoscientists, Subsurface Engineers, Economists, Planners.

ObjectiveDescribe the main procedures & definitions related to the subject

List and apply the main estimating techniques used.

Key messagesSome best practices in dealing with uncertainty and reserves estimating

– Volumetric & performance based estimating methods, probabilistic & deterministic

– Use “old-fashioned” res eng practice to back-up/validate simulation results

– Module is not meant to replace general foundation courses

Performance Based Reserves Estimation

Used once sufficient production data available

(Material Balance) p/Z plots

Decline curves

Analytical calculation

History matched simulation

Each has its uses, but the limitations of each need to be properly understood; need to understand the physics.

Reality checks

Forecast should seamlessly match historical production trends

Remaining field life duration must be realistic.

Can deal with uncertainty.

Measured Low case ?

High case ?

Uncertainties make resource volume estimates ambiguous

All affect the level of certainty of estimated volu mes

• Mapping/Gross Rock Volume• Hydrocarbon fluid contact levels• Net sand ratio, porosity, HC saturation • Reservoir drive mechanisms• Recovery techniques, Recovery

Factors• Development Scheme, Infrastructure• Market availability (Gas)• Oil and gas prices, fiscal terms, etc.

Dealing with uncertainty

“Subsurface Uncertainty” is often quoted in FDPs.

• How many pens are in my briefcase?

“Uncertainty” is caused by our inability to quantify exactly the static properties and exactly predict the dynamic behavior of the subsurface

• We are often optimistic about our ability to predict the level of uncertainty

• Reserves prediction is influenced by the decisions we take during the course of a field life-cycle

Once we have “a number”, we sometimes believe it to be “correct”, then use it unwisely.

Judgments & Interpretation, dealing with uncertainty • There is no “one number” for reserves

1.0

0.5

0

Reserves (MMm 3)0 50 100

?

?

P90

P85

Proved

Low

downside

P15

P10

High

upside

P50 Most Likely

Mid

Base

?

?mean, Expectatio

n

variety of qualifier creates confusion !

How to ensure consistency ?

Resource Volume Determination Methods over Field Life

TIME

Volumetric Estimates(or Analogue Recovery)

Discovery Production Abandon

Performance Based Estimates

Probabilistic

Deterministic multi-scenario

Ways to deal with uncertainties:

Deterministic - multi-scenario method

Model

Scenario A Scenario B Scenario C

Realization 1 Realization 2

Using flow simulator tohistory match

Realization 3

Forecast & reserves

Forecast & reserves

Forecast & reserves

Hydrocarbon Initially in Place (HCIIP) Calculation

HCIIP = GRV x N/G x ΦΦΦΦ x SHC / FVFHCIIP = GRV x N/G x ΦΦΦΦ x SHC / FVF

Area/depth data, Fluid contacts,

Gross thicknessStructure model

HC Charge modelReservoir model

Seismic mapping & well data

Area/depth data, Fluid contacts,

Gross thicknessStructure model

HC Charge modelReservoir model

Seismic mapping & well data

Net-to-gross ratio, PorosityReservoir model

(HC charge history)Well data

Net-to-gross ratio, PorosityReservoir model

(HC charge history)Well data

Formation volume factorHC modelPVT data

Formation volume factorHC modelPVT data

HC saturationReservoir model

HC models(HC charge history)

Well data

HC saturationReservoir model

HC models(HC charge history)

Well data

Volumetric Probabilistic Approach

GRV

ΦΦΦΦ

N/G

Shc

(1/Bo)

RFo

Pro

babi

lity

Den

sity

Fun

ctio

ns

Monte Carlo or Moment Processing

P15

P85

P50

Ultimate Recovery

Cum

ulat

ive

Pro

babi

lity

100

0

Expectation: probability-weighted

average

Ultimate Recovery = GRV x ΦΦΦΦ x N/G x Shc x (1/Bo) x RF

1600

1500

1400

1300

1200

GOC 1230

OWC 1

520

1700

1600

1400

OWC 15

20

1500

GOC

OWCOWC

Schematic Cross Section A-A'

Top Reservoir Map Base Reservoir Map

Volumetric Method

Ultimate Recovery =

GRV x N/G x ΦΦΦΦ x Shc x (1/Bo) x RF

GRV =gross rock volume

net

rock

vol

ume

Pore space

water

oil

gas

Net/gross ratio porosity saturation shrinkage recovery factor

1700

1600

1400

–OWC 1520

1500

The Area/Depth Graph – GRV Calculation

Interface between upper and lower reservoir unit

(Range of possible) GOC

(Range of possible) GOC

(Range of possible) OWC

(Range of possible) OWC

� Area/depth data, Fluid contacts, Gross

thickness

Gross Thickness Lower Unit

Reservoir unit geometry “Reservoir Units Parallel t o Bottom”

AREA

DE

PT

H

60°

Base Case

70°

Minimum

50°

Maximum

20°

25°15°

GRV – Combined Uncertainties

Reservoir Properties – Sources of uncertainty

Core data, sidewall samples, cuttingsCore N/G uncertainty in the order of 5-10%

Core porosity uncertainty +/- 1 p.u.

Well logs – tool resolution, qualityLog N/G uncertainty in the order of 10-20%

Log porosity uncertainty +/- 2 p.u.

Geological Model – applicabilityRepresentative ness of cores and logs

Reservoir model and mapping of trends

Seismic attributes – seismic resolution

Hydrocarbon saturation - Process

Use wire line log measurements.

Calibrate with core data – in doubt logs have preference

Calculate volume weighted average of Sh

water

air

free waterlevel

pressure

height

h g∆ρ

A

A1

B

B1

C

C1 C1

B1

A1

Pnw-Pw

air

water

Relation between Capillary Pressure and Water Saturation

Capillary Pressure and Fluid Distribution

GGGGGWGGGWGGGGGWWGGGGWGGGGWGGGGGGGGWGGGWGGGWGGGGGGWGGWOGGWGGOGGGOGWGGGWOGGWGOGGGWGOGOGOGWGWGOGWGOOWGGOOWOWGGOWGOOGOGWOGOWOOOGOWOGOOWOOGOOOWOWGOOWOOOOWOOGOOWOOGOOOOOWOOOOWGOOOOWOOWOOOOWOOOOWOOOOOOOOOWOOOOOWOOOWOOOOOOOWWOOWOOWOOOWOOOOWOOOOOWOOOOOOOOWOOOOOWOWOOOOWOOOOWOOOOWOWOOWOOOOOOOWOOOWOOOWOOOOWOOOOWOOWOOOOWOOOOOWOOOOWOOOOWOOOOWOOOOOOOOWOOOOWOOOOWOOOWOOOOWOOOOWOOWOOOOWOOOWOOOWOOOWWOWOOWOOWOOWOOWOOOWOOWOOWOOWOOWOWOOWOOWOOWOOWOOWOOWOOWOOWOOWOOWOWOWOWOWOWOWOWOWOWOWOWOWOWOWOWOWWOWOWWOWWOWWOWWWWOWWWOWWWOWWWOWWWWWOWWWWWOWWWWWWOWWWWWWOWWWWOWWWOWWWWOWWWWWWWOWWWWWWWOWWWWWWWOWWWWWWWWW

Swc

region ofirreducible

water saturation

transition zone

water saturation0 100

Pcorh

Fluid Properties are used to:

To estimate hydrocarbons in place and reserves

To understand reservoir processes and predict reservoir

behavior

To identify processing requirements

To identify markets

Reservoir and Surface Volumes

Rs

Rp

m3

Bo

Bw

Bg

m3

m3

1 m3

m3

m3

1 m3

1 m3

SURFACERESERVOIR

Fluid Properties Uncertainties

Compositional variation with depth or lateral variations can be

complicating factors, necessitating volume weighted

averaging

Uncertainty ranges can be based on range of validated

samples or the use of PVT correlations

Methods for Determining Ultimate Recovery

No physicsIndustry or analog correlation

Performance extrapolation

Decline curve ‘analysis’

Some physicsMaterial balance

Analytical calculations

Full physicsNumerical simulation

RANGE OF PRIMARY RECOVERY FACTORS

Low natural energyFair reservoir quality

Average conditions

High natural energyGood reservoir quality

Typical maximumachievable

20 - 35%

5 - 20%

> 35%

65 - 70%

OIL RESERVOIRS:OIL RESERVOIRS: % STOIIP% STOIIP

Simulation Uncertainty - Introduction

Focus on Reservoir Engineering uncertainty

• Fault Analysis

• Aquifer volume and productivity index

• Fluid models-contact levels

• Well completions

Selection of uncertainty parameters

In our project we will investigate the

effects of structural uncertainty on our

simulation results:

•Fault transmissibility

•2 Oil Water Contacts for different

initialization regions

•Fetkovich Aquifer volume and

productivity index

•Well perforation bottom depth

Fault analysis: Fault transmissibility

Study the effect of that structural uncertainty in combination

with a varying fault transmissibility multiplier on the e.g. the

water breakthrough in one or more wells

These are then used as input to the simulation or simply as a

visual assessment of the sealing potential of faults.

The Fault analysis process in Petrel allows you to generate

fault transmissibility multipliers, either directly or by modeling

fault properties based on grid properties (e.g. fault throw)

Task: Based on the structural uncertainty, the positions of the

horizons were varying due to changes in depth conversion.

This could change the Fault transmissibility

Fault transmissibility uncertainty Workflow

• Use the existing workflow

“Structural Uncertainty” and

create new.

• Add the Fault analysis and

the define simulation case

processes

• Disable the volume

calculation process

Uncertainty task: Fault transmissibility

• Use a Uncertainty task

• Add results to Folder

• Set Number of samples to 5

• Save the workflow by pressing Applyand

press Run to execute it

Fault transmissibility uncertainty: Results

After 5 runs

Field Water cut

Make Fluid Model process: Contact levels

Task: Add to the existing workflow

“Contact uncertainty” the execution of

a simulation case where the “Make

fluid model” depends on the varying

water contact

The case:

• Previously we studied the

effect of a fluctuating fluid

contact in the Make contacts process

• The same uncertainty could

be used to define the

initialization of our

simulation model in the

“Make fluid model”


The oil water contact is

made uncertain in the

“Make Fluid model”

process instead of in the

“Make contacts” process


1) Define variables:

=> Number of contacts to

investigate

2) Define the distribution for

the uncertain variables

500 picks from the above distributions would yield the following distributions for C1 and C2

Fluid model uncertainty: Results after 5 runs

The oil water contact is

made uncertain in the

“Make Fluid model”

process

Field Oil production

cumulative after 5 runs

Task:

• By varying the aquifer volume and the productivity index, the Fetkovich model can

encompass a range of aquifer behaviour from

steady state to the ‘pot’ aquifer.

• The aquifer volume and productivity index are

made uncertain in order to see how much

modelling the aquifer improves the oil recovery

Aquifer uncertainty - Introduction

The case:

• A reservoir with a large aquifer

• The Fetkovich aquifer model uses a simplified

approach based on a pseudosteady-state

productivity index and a material balance

relationship between the aquifer pressure and the

cumulative influx.

Aquifer Modelling: Fetkovich Aquifer Volume and productivity index

The large aquifer around the

reservoir is modelled by a

Fetkovitch aquifer. The volume

and productivity index are

uncertain parameters

Aquifer Modelling Workflow: Variables

1. Define the variables under the Variables tab (i.e. their uncertainty

ranges)

2. Define $AQ_PI and $AQ_VOL as being a list of 5 values. $AQ_PI=

list(100, 400, 600, 800, 1500, 2000) and $AQ_VOL=list(20000000,

100000000, 150000000, 200000000, 20000000000, 200000000000)

Aquifer modelling uncertainty: Results after 5 runs


cumulative after 5 runs

Uncertainty by shifting Completion Intervals

Task: This short workflow

shows how to perform a

sensitivity analysis by shifting

the perforations vertically

(bottom depth).

The Well Completion design is

used in a workflow, thus it is

possible to assess the impact of

the perforation interval on the

production/injection scheme.


This workflow can be used

for a variety of completion

items and cases; the

following steps only give one

example of usage.



rate after 5 runs

Thank you

Documents

Uncertainty Analysis 2009