© 2009 chevron corporation confidential – this information is proprietary to chevron and is to be...

© 2009 Chevron Corporation

CONFIDENTIAL – This information is proprietary to Chevron and is to be used, disclosed or reproduced only under permission granted by Chevron. All rights reserved.

Compartments for Beginners: Wellbore Formation Testing in the Real World

SPWLA WFT SIG

Houston, TexasSeptember 27, 2011

© 2009 Chevron Corporation CONFIDENTIAL – This information is proprietary to Chevron and is to be used, disclosed or reproduced only under permission granted by Chevron. All rights reserved.

2

Why are we talking about this?

• What has been the outcome of the last few years of data collection?

Compartments, Compartments and … more Compartments

• How do we define the Value Proposition?

Importance of Sample Quality and Volume

Value of Information vs cost and risk

• How do we plan and run the job?

Practical tips for adding value with new technology


The deepwater Appraisal problem: Reduce Subsurface Uncertainty in a cost-effective manner

Industry moving towards:

Ultra deepwater, deeper objectives Non-amplitude and subsalt prospects Less forgiving smaller targets

Appraisal problem is getting more difficult

Increased subsurface uncertainty High appraisal costs makes reducing uncertainty expensive

• $10MM to $30MM/well in deeper waters (data collection only).

Need to reduce subsurface uncertainty in a cost-effective way

Combining reservoir engineering and geochemistry in a valuable way to decide what data to collect for what cost and what is the acceptable risk to get this data


2009 DEEPSTAR 9702 Appraisal Lookback: 28 DWGOM FieldsTwo fields significantly outperformed expectations

Six fields significantly underperformed expectationsOf the remaining 22 fields 75% marginally underperformed and 25% marginally outperformed

In general, fields showed more complexity than anticipated

GOOD

UGLY BAD PRODUCTION OUTCOME

BAD RESERVES OUTCOME


Key Tools for Appraising New Fields

5


6

Looking for Value

Why are we talking about this?

• Optimize Cost and Maximize Value• Apply Appropriate FEL

For a new field discovery • Uncertainty Management Plan • Assess the impact of fluids properties on project execution• Impact of compartments on Appraisal program

IMPACT

Exploration: • What is the likely value of this discovery? (oil quality and continuity)• How high a priority should this prospect get in the Appraisal Queue?

Development: • What are the “game changers”?• Effect on project architecture and selection of development options?


7

Compartments, Compartments and More Compartments

Compartment Risk will be determined based on how well:

Pressure trends for major and minor sands correlate over the field,

Pressure trends correlate vertically within each zone in each well,

How measured and theoretical fluid gradients compare,

How fluid properties correlate over the field (both PVT and bulk properties), and

A review of geochemical marker results.

Oil Fingerprinting

Mud gas Isotope Analysis

Solution Gas Isotope Analysis

Sulfur Isotope AnalysisReal-time techniques that are useful in the timeframe needed to make decisions to complete or sidetrack are limited.


8

Exploration and Appraisal Activities Data Collection and Integration Toolkit

Distance ofinvestigation

Dyn

amic

Sta

tic

WFT PRESSURES

TRACERS

WELLTEST

GEOLOGY

SEISMIC

CORES

LOGS

1 cm 1 m 1 km

10-2 m 10-1 m 1 m 10 m 102 m 103 m 104 m

Courtesy Arild Fossa, PowerWell Services

FLUID PROPERTIES & GEOCHEMISTRY

NEW PARADIGM: THE DISTRIBUTION OF PRESSURE AND FLUIDS IN THE RESEVOIR REPRESENTS A TYPE OF DYNAMIC DATA!


9

In the Appraisal and Development Phase How much sample do we need and why?

We need multiple fluid samples from different wells because spatial variations in fluid composition can reflect:

• Faulting, compartmentalization and reservoir architecture

• Filling history as an indication of geologic complexity

• Proximity to fluid contacts and gravitational grading

• Biodegradation, tar mats, loss of light ends and mixing events

• and allow production allocation or mechanical troubleshooting with fingerprints

Water Samples: (500 to 1,000 cc per zone)

• Hydrate formation, Scale, Souring and Corrosion potential, Salinity

Geochemical allocation of fluids during the Tahiti Well Test by Russ Kaufman and

Stan Teerman

Tahiti Field: Four conventional cores, over 500 pressure points, 33 fluid samples, M-21 Well Test

OWC

3 miles

24500

25000

25500

26000

26500

27000

27500

0.0 0.5 1.0 1.5 2.0 2.5

Optical Density

TVD

(ft)

M21A

M21B

M21A-10

M21A-20

North

South

Center

24500

25000

25500

26000

26500

27000

27500

0.0 0.5 1.0 1.5 2.0 2.5

Optical Density

TVD

(ft)

M21A

M21B

M21A-10

M21A-20

North

South

Center

Relationship of optical density during Tahiti sample pumpouts with column height by Soraya

Betancourt (SLB)


10

In the Exploration and Appraisal Phase How much sample do we need and why?

We need multiple sample bottles at each sample point because:

• 300 cc sample => minimum evaluation

• Samples compromised during transfer or leakage during storage

• Custody transfer and inventory mistakes

• Multiple measurements required for confidence

Studies that usually require substantial volumes of oil (gallons, barrels):

• Restored state core floods for SCAL

• Completion/stimulation fluid compatibility

• Flow loop testing

• Emulsions key for oils <20 deg API

Larger volumes needed (1 Bbl)

0.1 1 10 100

Recombination

Dew point, Pd

Monophasic Z

DS Z at Pd/2

Maximum rld

DS mass balance

Flash GOR

Flash liq. shrinkage

Methane mol%

Cn at 1 mol%

Cn at 0.001 mol%

Cn+ molar mass

Bubble point, Pb

Oil compressibility

Bo factor

DV mass balance

Oil viscosity

Relative Error (%)

Worst Cases

Ranges OverlapTarget Accuracy

Deepwater Project Learning: Major Capital Projects relying on Wellbore Formation Tester sample volumes are typically short of STO and live fluid prior to completion of all desired experiments..

From SPE 49067: “Identifying and Meeting the Key Needs for Reservoir Fluid Properties A Multi-Disciplinary Approach” B.J. Moffatt and J.M. Williams


11

In the Exploration and Appraisal Phase How much sample do we need and why?

Optimum Samples Volume needed for: Target:

• PVT for reservoir and fluid flow simulation: GOR, Bo, density, viscosity

Volume: 1,000 cc Res Fluid / zone affect OOIP, rate and recovery

• Geochemistry fingerprinting: Reservoir continuity and variability

Volume: 50 cc STO / zone Source rock typing, analogs

• Hydrates, wax & asphaltene potential: Operability, cost,

Volume: 100 to 200 cc Res Fluid / zone development options

• Crude Value: Market Value, STO properties

Volume: 10 gallons STO / zone and character, refinery options

• Emulsion / Foaming: Viscosity variation with water cut;

Volume: 10 gallons STO / zone separation time; foam stability

• Chemical Screening: Effectiveness of

Volume: 10 gallons STO select chemicals


12

How clean does it need to be?Oil Based Mud Contamination

Oil-based mud and hydrocarbon additives to water based muds can contaminate fluid samples, affecting the results of PVT and STO testing.

• Dew point and bubble point decrease

• GOR decreases

• Liquid density generally decreases

• Viscosity increases

• Pour point decreases for some oils

• Wax appearance point decreases slightly (may be within meas. uncertainty)

• Saturates increase (n-Paraffins)

• Asphaltenes become more stable

Fraction OBM Determination

0.1

1.0

10.0

100.0

We

igh

t %

0

10

20

30

40

50

60

70

80

90

100

Clean Oil

Oil

OBM

Trend Line

Tahiti Field: OBM contamination corrections• Plan sampling program to minimize contaminants.

• Quantify the OBM components and correct for their effect.

• Make sure you capture relevant OBM samples. Consider contamination of your sample from other zones (or other wells).

• Until recently most OBM were 2-3 component mixtures. NovaPlus, Petrofree, Petrofree LE were C14,C16,C18, C20 mixes. Current use of ‘fillers’ makes filtrates more ‘complicated’. These are now multi-component fluids in the C7-C30 range and this makes corrections more difficult.

OBM Contamination effects:


13

How clean does it need to be? For Black Oils:

PVT relationships, Density, GOR

• No analogs: Target 5% OBM

• Analogs available: Target 10% OBM, preferably <5% OBM. These properties can be modeled with some confidence up to 20% OBM. However, note that many labs have difficulty quantifying OBM contamination amounts above 15% OBM.

Volumetric Properties readily corrected (Rs, Bo, Do)

Saturation Pressure correction difficult (Pob, Pod)

Viscosity

• Correction for OBM complicated

• Experimental error with perfect sample is +/-15%.

• Consider making several determinations with different OBM amounts

Flow Assurance

• Wax appearance typically invariant up to 25% OBM

• Asphaltene Onset Pressure variation can be significant above 10% OBM.

Tahiti Field: Fluid modeling of OBM contamination effects by Kathy Greenhill and Jeff Creek

0.000

0.2000.400

0.600

0.8001.000

1.200

1.400

1.6001.800

2.000

0 10 20

Co

rrec

tio

n F

acto

r

Pb

Uo @ Pb

Uo @ 13698

Rs

Bob

API Gravity

Bo @ 149300.000

0.2000.400

0.600

0.8001.000

1.200

1.400

1.6001.800

2.000

0 10 20

Contamination (% OBM)


14

How clean does it need to be? For Black Oils:

Bulk fluid properties (viscosity, emulsions, assays)

• Volumetric property correction for contamination is generally straightforward.

• Affect on emulsions and rheology are less predictable and typically require physical testing.

Geochemistry

• OBMs alter Vitrinite reflectance, TOC, density, isotopes, SARA and biomarkers.

• For Black Oils, high definition studies work best when less than 10% OBM. Recent results indicate much improved results below 5% OBM.

• Useful information can be obtained up to 30% OBM contamination.

For Light Oils and Gas Condensates:

• OBM contamination may interfere with critical light components making the acquisition of cleaner samples necessary. For difficult sampling operations, a well test may be required.


15

What's the best way to get the sample we need? (highest Possibility of Success, Lowest Cost)

Determine what is the likely pump-out duration

What is the overbalance?

What is the mud system (invasion profile)?

What is the expected formation / fluid mobility?

What is the anticipated fluid type (viscosity and GOR)?

Determine sampling strategy

Plan pump-out until we get to below 5% OBM contamination? Would 10% OBM be acceptable?

Consider setting maximum pump-out time (5 to 8 hours?)

Consider contingency plan

• How long to pump at one station before moving?

• How many attempts will be made?


16


Define Risk:

Determine probability of getting tool differentially stuck

How long has the hole been open?

What is the well angle to the angle of formation bedding dip?

What is the mud system?

What is the overbalance pressure?

Indicators

• Did the drill pipe take any drag on the trip out?

• What does the caliper show? Does the hole have ledges or breakouts? Hole geometry is your biggest concern!

Determine the probability of getting line stuck (key seated)

What is the dog leg severity of the hole above the sampling interval?

How much formation is open above the sampling interval?

What is the overbalance in these shallower zones?


17


VOI Example: Knotty Head Exploration Sampling

Exploration prospect, some well sampled zones, some under sampled zones. Developed sample acquisition hierarchy, sampling fluids in sidetrack.

Strategy – pump-out until <5% OBM contamination

Conditions…

MDT tool selection

Sampling Strategy

Fish or no Fish

Successful fish

Tool Stuck

Decision

Uncertainty

MRPQ

Norm probe

Off wall after 6hrs

<5%OBMNo

Yes No

Yes No

Yes

$3.1 Million

$4.3 Million

$1.7 Million

$0.5 Million

$0.35 Million

* Loss of wellbore for further Data acquisition

*

*** Would you do a VSP or RSWC ops in the same hole you just fished?

**


18

Chevron provided both live and dead M21 Sand oil samples and the conceptual geologic framework models for each sand.

Schlumberger conducted Lab VIS-NIR (using the world’s best mass spectrometer at Florida State University) and fluorescence spectroscopy (with Wood’s Hole Oceanographic Institute) on live and dead oil samples, then compared the results with field Downhole Fluid Analysis optical data.

The Team successfully defined the asphaltene gradient in the oil column and tested for compartmentalization. We found small variations in GOR but large variations in Color that correlate very well with SARA Asphaltene content. Also, we found that the two-fold variation in color is a reflection of an asphaltene gradient in the oil column. The M21A and B Sands had different trends, but no clear indication of lateral compartmentalization was found.

Chevron/Schlumberger Compartmentalization Study using Downhole Fluid Analysis at Tahiti

y = 0.3402x + 0.2133

R2 = 0.8665

0.0

0.5

1.0

1.5

2.0

2.5

0 1 2 3 4 5 6 7

SARA Asphaltene Content (%w/w)

OD

@1

07

0n

m (

OB

M c

orr

ec

ted

)


19

Tahiti Field: Compartmentalization Analysis

North

South

North` South

GC 641 1ST1

GC 640 1

~2900 feet

West (Updip)

East (Downdip)~4300 feet~2400 feet

West (Updip)

East (Downdip)

~2300 feetWest (Updip)

East (Downdip)

GC 596 1ST1

GC 596 1GC 640 1ST2 BP1

GC 640 2ST1

GC 640 2BP1

GC 640 2BP2

M21 A-10

M21 B-40

M21A:TST = 70 ftM21B:TST = 48 ft








~70 feet

M-21 TST Cross SectionDatum = M21B_Base

How consistent are these stratigraphic units laterally?Are there sub-compartments vertically that have not been identified?

M21 A-20

M21 B-50

N S

Stratigraphy and StructureM-21A Sand

24,200

24,700

25,200

25,700

26,200

26,700

27,200

27,700

28,200

28,70018,900 19,100 19,300 19,500 19,700 19,900 20,100 20,300 20,500 20,700 20,900

Formation Pressure, psia

Dep

th, S

ST

VD

640_1OH

641_1ST1

640_1ST2BP1

596_1OH

0.455 gradient

640_2OHBP2

596_1ST1

640_2ST1BP1

PS002

Theo Grad

Oil Gradient 0.343 psi/ft

Oil Gradient 0.360 to 0.374 psi/ft

Meas. Water Gradient 0.442 psi/ftfrom M-21B Sand

OWC based on measured waterGradient 27,312' SSTVD

OWC based on theoretical waterGradient 27,570' SSTVD




M-21A SandM-21A Sand24,200

24,700

25,200

25,700

26,200

26,700

27,200

27,700

28,200

28,70018,900 19,100 19,300 19,500 19,700 19,900 20,100 20,300 20,500 20,700 20,900

Formation Pressure, psia

Dep

th, S

ST

VD

640_1OH

641_1ST1

640_1ST2BP1

596_1OH

0.455 gradient

640_2OHBP2

596_1ST1

640_2ST1BP1

PS002

Theo Grad


Oil Gradient 0.360 to 0.374 psi/ft

Meas. Water Gradient 0.442 psi/ftfrom M-21B Sand

OWC based on measured waterGradient 27,312' SSTVD

OWC based on theoretical waterGradient 27,570' SSTVD




Pressures

12Tahiti Project Confidential© Chevron 2005

0

200

400

600

800

1,000

1,200

M-2

1C

*

M-2

1B

M-2

1 B

-40*

M-2

1 B

-40*

M-2

1 B

-40*

M-2

1 B

M-2

1 A

-10*

M-2

1 A

-20*

M-2

1 A

-10*

M-2

1A

*

M-2

1A

M-2

1 A

-10*

M-2

1 A

-10

M-2

1 A

M-1

8C

M-1

8B

M-1

8B

M-1

8A

*

M-1

8A

*

M-1

8A

*

M-1

8A

M-1

7B

M-1

7B

M-1

5A

*

M-1

5A

*

M-1

5A

*

M-1

5A

M-1

4D

M-1

4B

M-1

4A

M-1

3C

Stra

y G

as

M-6

A

La

b G

OR

, s

cf/

stb (

co

rre

cte

d f

or

OB

M %

)

Tahiti Fluid AnalysisM-21 A & B Fluid Properties

0

5

10

15

20

25

30

35

40

45

M-2

1C

*

M-2

1B

M-2

1 B

-40*

M-2

1 B

-40*

M-2

1 B

-40*

M-2

1 B

M-2

1 A

-10*

M-2

1 A

-20*

M-2

1 A

-10*

M-2

1A

*M

-21A

M-2

1 A

-10*

M-2

1 A

-10

M-2

1 A

M-1

8C

M-1

8B

M-1

8B

M-1

8A

*

M-1

8A

*

M-1

8A

*M

-18A

M-1

7B

M-1

7B

M-1

5A

*

M-1

5A

*

M-1

5A

*M

-15A

M-1

4D

M-1

4B

M-1

4A

M-1

3C

Stra

y G

as

M-6

A

Lab

AP

I (co

rrecte

d f

or

OB

M %

)

0

5

10

15

20

25

30

M-2

1C

*

M-2

1B

M-2

1 B

-40*

M-2

1 B

-40*

M-2

1 B

-40*

M-2

1 B

M-2

1 A

-10*

M-2

1 A

-20*

M-2

1 A

-10*

M-2

1A

*M

-21A

M-2

1 A

-10*

M-2

1 A

-10

M-2

1 A

M-1

8C

M-1

8B

M-1

8B

M-1

8A

*

M-1

8A

*M

-18A

*

M-1

8A

M-1

7B

M-1

7B

M-1

5A

*

M-1

5A

*M

-15A

*

M-1

5A

M-1

4D

M-1

4B

M-1

4A

M-1

3C

Stra

y G

as

M-6

A

% L

ab

OB

M C

on

tam

inati

on OBM Contamination - monophasic

OBM Contamination - STO

0.0

1.0

2.0

3.0

4.0

5.0

6.0

7.0

8.0

M-2

1C

*

M-2

1B

M-2

1 B

-40*

M-2

1 B

-40*

M-2

1 B

-40*

M-2

1 B

M-2

1 A

-10*

M-2

1 A

-20*

M-2

1 A

-10*

M-2

1A

*

M-2

1A

M-2

1 A

-10*

M-2

1 A

-10

M-2

1 A

M-1

8C

M-1

8B

M-1

8B

M-1

8A

*

M-1

8A

*

M-1

8A

*

M-1

8A

M-1

7B

M-1

7B

M-1

5A

*

M-1

5A

*

M-1

5A

*

M-1

5A

M-1

4D

M-1

4B

M-1

4A

M-1

3C

Stra

y G

as

M-6

A

Su

lfu

r a

nd

As

ph

alt

en

e P

erc

en

tag

es

Elemental SulfurPercentage

Asphaltene Percentage • M-21 A & B fluids are very similar and exhibit physical properties that are normal for the trend.

• Sulfur and Asphaltenes are very low for trend

• In general, API and GOR are consistent with measured gradients.

• OBM contamination is, in general, low enough to be successfully removed by EOS compositional modeling.

Fluid Properties

Oil Geochem

0.00

1.00

2.00

89/ 91

61/ 63

86/ 87

74/ 75

116/ 115

39/ 38

85/ 8457/ 58

33/ 32

42/ 40

103/ 104

143/ 142

152/ 153

596_1OHST1 M21-A10

M-21A

M-21B

M-21 A

M-21 B

StarplotStarplot of Peak Height Ratiosof Peak Height Ratios

MM--14B14B

596_1ST1/M596_1ST1/M--15A15A

MM--21B21B

MM--21C21C

640_1ST2BP1/M640_1ST2BP1/M--15A15A

MM--21A21A

640_2OHBP1/M640_2OHBP1/M--15A15A

Cluster Analysis of Peak Height RatiosCluster Analysis of Peak Height Ratios

0.00

1.00

2.00

89/ 91

61/ 63

86/ 87

74/ 75

116/ 115

39/ 38

85/ 8457/ 58

33/ 32

42/ 40

103/ 104

143/ 142

152/ 153

596_1OHST1 M21-A10

M-21A

M-21B

596_1OHST1 M21-A10596_1OHST1 M21-A10

M-21AM-21A

M-21BM-21B

M-21 A

M-21 B


MM--14B14B

596_1ST1/M596_1ST1/M--15A15A

MM--21B21B

MM--21C21C

640_1ST2BP1/M640_1ST2BP1/M--15A15A

MM--21A21A

640_2OHBP1/M640_2OHBP1/M--15A15A


0.00

1.00

2.00

89/ 91

61/ 63

86/ 87

74/ 75

116/ 115

39/ 38

85/ 8457/ 58

33/ 32

42/ 40

103/ 104

143/ 142

152/ 153

596_1OHST1 M21-A10

M-21A

M-21B

M-21 A

M-21 B


MM--14B14B

596_1ST1/M596_1ST1/M--15A15A

MM--21B21B

MM--21C21C

640_1ST2BP1/M640_1ST2BP1/M--15A15A

MM--21A21A

640_2OHBP1/M640_2OHBP1/M--15A15A


0.00

1.00

2.00

89/ 91

61/ 63

86/ 87

74/ 75

116/ 115

39/ 38

85/ 8457/ 58

33/ 32

42/ 40

103/ 104

143/ 142

152/ 153

596_1OHST1 M21-A10

M-21A

M-21B

M-21 A

M-21 B


MM--14B14B

596_1ST1/M596_1ST1/M--15A15A

MM--21B21B

MM--21C21C

640_1ST2BP1/M640_1ST2BP1/M--15A15A

MM--21A21A

640_2OHBP1/M640_2OHBP1/M--15A15A


0.00

1.00

2.00

89/ 91

61/ 63

86/ 87

74/ 75

116/ 115

39/ 38

85/ 8457/ 58

33/ 32

42/ 40

103/ 104

143/ 142

152/ 153

596_1OHST1 M21-A10

M-21A

M-21B

596_1OHST1 M21-A10596_1OHST1 M21-A10

M-21AM-21A

M-21BM-21B

M-21 A

M-21 B


MM--14B14B

596_1ST1/M596_1ST1/M--15A15A

MM--21B21B

MM--21C21C

640_1ST2BP1/M640_1ST2BP1/M--15A15A

MM--21A21A

640_2OHBP1/M640_2OHBP1/M--15A15A


11Tahiti Project Confidential© Chevron 2005

-41.0

-40.5

-40.0

-39.5

-39.0

-38.5

-38.0

-37.5

-37.0

-36.5

-36.0

-65.0-64.0-63.0-62.0-61.0-60.0-59.0-58.0-57.0-56.0-55.0

13C Methane

13C

Etha

ne

M-15A M-21A M-21B

Tahiti MDT Solution Gas Results

• Isotopic composition of MDTsolution gas indicates M-21A and B represent separatereservoir groups.

• Isotopic differences in the M-21A & B may suggest perm barriers between the Tahiti South wells and the rest of the field.

• Isotopic differences in the M-15A gases show separation consistent with oil fingerprinting.

640_2OHBP2

596_1ST1

640_2OHBP1 640_2ST1BP1

596_1A20

596_1ST1

596_1A10

640_2ST1BP1

Tahiti South M21-A and

South Updip Stk M-21B

Solution Gas Geochem

Mud Gas IsotopesAll these methods all seem to agree that for the main Tahiti All these methods all seem to agree that for the main Tahiti reservoir, compartments either do not exist or are limited to reservoir, compartments either do not exist or are limited to “baffles” “baffles”

• After the field came on production in April, 2009 interference was seen After the field came on production in April, 2009 interference was seen between all six wells within about 12 daysbetween all six wells within about 12 days


Tahiti Asphaltene Concentration Model

PS03Asphaltene Content %w/w

Schlumberger: Nicolas Ebele, Sandra Quental, Francois Dubost, Soraya Betancourt

z=1870’

=45o

640#2 ST0 BP2

M21B

M21A

640#2 ST1 BP1 -

+

N

640#2 ST0 BP2

640#2 ST1 BP1

Calibrated model with existing wells

Predict DFA Optical Densities and Asphaltene Concentration in new wells drilled updip

Existing Wells

PS002New Wells

PS003

PS003PS002


21

Sampling Best Practices

1) Early Involvement in sample planning!!!

• Try to influence mud selection and encourage minimum overbalance. Overbalance influences pump selection and pump stroke volume (which can lead to significantly longer pumpout times to displace the same volume).

• Set casing over any low pressure sands, if practical. If not practical, consider conducting contingent wireline runs prior to reaching TD.

• Quartz pressure gauges are very accurate. Depth control isn’t. Plan accordingly.

2) Consider likely mobility and possible pump out times.

• In general, OBM contamination is directly proportional to pumpout volume. Real-time optical analyzers are necessary to develop a feeling for sample quality and determine that pumpouts are proceeding as planned. Don’t waste rig time.

• Make sure you capture a set of relevant OBM samples.

3) Construct sampling strategy and consider the probability of tool sticking.

• Consider tool selection and string weight. Build a flexible plan. Monitor drilling and consider how changing hole conditions may change risk leading up to job.

• Define back-off points as clearly as possible before the job and have a clear chain of command relationship defined with Drilling.

4) Immediately after the job, QA/QC the data and properly archive the run.


22

Notable References for further reading:

Brown, Alton “Improved Interpretation of Wireline Pressure Data” AAPG Bulletin, v. 87 No 2 (February 2003), pages 295-311.

Brooks, A., Wilson, H., Jamieson, A., McRobbie D.,Holehouse, S.G., “Quantification of Depth Accuracy”, Paper SPE 95611 presented at

the 2005 SPE Annual Technical Conference and Exhibition, Dallas, TX, U.S.A., 9-12 October.

Hashem, M., Elshahawi, H., Ugueto, G., “A Decade Of Formation Testing – Do’s and Don’ts and Tricks of the Trade”, SPWLA Paper

2004L, presented at the SPWLA 45th Annual Logging Symposium Noordwijk, The Netherlands, 6-9 June, 2004.

Kabir, C.S., Pop, J.J., “How Reliable is Fluid Gradient in Gas/Condensate Reservoirs?”, Paper SPE 99386, presented at the SPE Gas

Technology Symposium held in Calgary, Alberta, Canada, May 14-17, 2006.

Lee, J., Michaels, J., Shammai, M., Wendt, W., “Precision Pressure Gradient Through Disciplined Pressure Survey”, SPWLA Paper

2003EE, presented at the SPWLA 44th Annual Logging Symposium, Galveston, Texas, U.S.A., 6-9 June, 2003.

Mullins, Oliver C., Betancourt, Soraya S., Cribbs, Myrt E., Creek, Jefferson L., Dubost, Francois X. Dubost, Andrews, A. Ballard and

Venkataramanan, Lalitha, “Asphaltene Gravitational Gradient in a Deepwater Reservoir as Determined by Downhole Fluid Analysis” SPE

102571 presented at the SPE International Symposium on Oilfield Chemistry held in Houston, Texas, U.S.A., 28 February–2 March 2007.

Charles Collins, Mark Proett, Bruce Storm and Gustavo Ugueto, “An Integrated Approach to Reservoir Connectivity and Fluid Contact

Estimates by Applying Statistical Analysis Methods to Pressure Gradients”, paper presented at the SPWLA 48th Annual Logging

Symposium held in Austin, Texas, USA, 3-6 June, 2007.

Elshahawi, M. Hashem, D. McKinney and M. Flannery, Shell, L. Venkataramanan and O. C. Mullins, Schlumberger, “Combining

Continuous Fluid Typing, Wireline Formation Tester and Geochemical Measurements for an Improved Understanding of Reservoir

Architecture”, SPE 100740, paper presented at the 2006 SPE Annual Technical Conference and Exhibition, San Antonio, Texas, U.S.A., 24-

27 September.

Elshahawi, H., Samir, M., Fathy, K.,, “Correcting for Wettability and Capillary Effects on Formation Tester Measurements”, SPWLA Paper

2000R, presented at the SPWLA 41st Annual Logging Symposium, June 4-7.

Asphaltenes, Heavy Oils, and Petroleomics, Oliver Mullins, et al. (eds.), Springer, 2007

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