SPE-ATW Dubai-EOR Lab QA/QC

SPE Workshop:Petrophysical Challenges in Reservoir Life Management

27 – 29 April 2015Dubai, United Arab Emirates

LABORATORY QA/QC – ITS IMPORT ON EOR FEASIBILITYJules ReedLR Senergy

Objectives

15ADU5 - SPE WORKSHOP: Petrophysical Challenges in Reservoir Life Management

Proper QA/QC of laboratory EOR feasibility studies is more important than QA/QC of more routine and/or special core analysis results because economic margins are tighter

• Data for decision making

• Cost of EOR

• EOR feasibility study objectives

• QA versus QC – what’s the difference?

• QA/QC in EOR studies – sources of error

Data Quotes


A theory is something nobody believes, except the person who made it.

An experiment is something everybody believes, except the person who made it.

- Albert EinsteinYou can use all the quantitative data you

can get, but you still have to distrust it and use your own intelligence and judgment.

- Alvin Toffler

You can have data without information, but you cannot have information without data.

- Daniel Keys MoranData is not information,

Information is not knowledge, Knowledge is not understanding,

Understanding is not wisdom.- Clifford Stoll

EOR Costs

IEA 2008

EOR economic return is more marginal due to higher investment and production costs over primary and secondary production techniques

EOR Feasibility Study Objectives

• Assess potential incremental recovery• Improve microscopic sweep efficiency• Can remaining oil saturation be moved towards residual?

• Requires accurate understanding of true Sor

Np = OOIP · ER

Np = Cumulative oil produced (STB)OOIP = Original oil in place (STB)ER = Recovery Efficiency (fraction)

ER = EA·EI·ED = EV·ED

EV = Volumetric sweep efficiency (fraction)EA = Areal sweep efficiency (fraction)EI = Vertical sweep efficiency (fraction)ED = Displacement sweep efficiency (fraction)

QA vs QC


• Quality Assurance (QA) – ensuring the process is fit for purpose• Quality Control (QC) is preventing/identifying defects and removing

• QA includes test design to fit objectives, to represent the reservoir

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

0 0.2 0.4 0.6 0.8 1

Res

idua

l Oil S

atur

atio

n (v

/v)

Initial Oil Saturation (v/v)

Clean State

Fresh State

Restored State

C = 0.6

C = 1.5

C = 2.5

C = 10

QA vs QC


• Numerous labs do not have a traceable/accredited QC system• Labs with QC accreditation, most often merely focus on calibration, i.e. the

equipment reads correctly– Few labs focus on finding/eliminating defects in results, thus results may

contain errors– Few labs report the supporting data to allow full quality review

• Data results come from experiments - defects always occur

Some data errors can be interpreted and corrected

Others may not. Data must be ignored.

EOR QA/QC – sources of error


• Poor sample selection

• Incorrect basic rock properties

• Incorrect conditions (wetting, fluids)

• Improper QC during testing, only performed retrospectively (if at all)

• Inappropriate experimental procedures/ methods

• Not accounting for method sensitivities

Sample ID 1AExpected K 700 mDMeasured K 15 mDPore Volume 11.43 mlFluid volumes measured 12.52 ml Volume error 10%



0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 10.00001

0.0001

0.001

0.01

0.1

1

Relative Permeability Curves per Methodology

Steady State Unsteady State Centrifuge

Water Saturation [fraction]

Rela

tive

Perm

eabi

lity

• Results can be method sensitive• Flooding methods do not provide accurate residual answers• Most EOR studies require flooding• Few labs understand the

impact of this and fail to make the necessary corrections

• This is one of the most common sources of error in EOR flood tests



• Capillary end effects may not be negligible (as is assumed)• Capillary end effects are not present deep reservoir• Certain EOR tests may mostly measure removal of end effects

0 1 2 3 4 5 6 7 80.75

0.8

0.85

0.9

0.95

1

Swi Sor -water Sor-polymer Sor W-realSor-P real

Sample Length [cm]

Wat

er sa

tura

tion

[fra

ction

]

Recovery Factor (%OOIP) measured directly (solid lines) 72% 83%EOR = 11 %OOIP

More realistic deep reservoir84% 87%EOR = 3.2 % OOIP

Invest in data quality


Please keep all your pictures, graphics, charts and/or inserted shapes within the white area to obtain best clearance for the information provided.

Summary


i. Data > Information > Knowledge > Understanding > Wiser investment choices

ii. Laboratory feasibility studies provides information towards this goal

iii. Study processes/procedures must be quality assured

iv. Results must be simultaneously quality controlled as testing is ongoing

v. Data corrections will be necessary for all flooding analyses

Science

SPE-ATW Dubai-EOR Lab QA/QC