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A U T H O R

Alton Brown Consultant, 1603 WaterviewDrive, Richardson, Texas, 75080;[email protected]

Alton Brown worked as a research geologist atARCOs Research Center in Plano, Texas, from1980 until ARCOs merger with BP Amoco. Sincethen, he has been an independent consultant.Research interests include petroleum migration,carbonate sedimentology and diagenesis, basinanalysis, and gas geochemistry.

A C K N O W L E D G E M E N T S

This work was completed at the ARCOResearch Center in Plano, Texas. I thank ARCO

and VASTAR for permission to release thisstudy. ARCO and VASTAR have subsequentlybecome part of BP Amoco, which is alsoacknowledged for its cooperation. AGIP andPetroecuador are gratefully acknowledged forreleasing Villano field pressure data. PaulWillette, Lee Russell, and Jim Twymanreviewed earlier drafts of the manuscript.AAPG reviewers Jim Puckette and Alain Hucare also acknowledged. David Novak, AndyHarper, Paul Willette, and Herb Vickers helpedwith the information-release process. A. F.

Veneruso kindly provided unpublished updatesto his pressure-gauge response model.Reference to any tool or gauge model ormanufacturer is not an endorsement orrecommendation for that product.

Improved interpretation ofwireline pressure dataAlton Brown

A B S T R A C T

Modern wireline pressure data can have resolution and reproduc-

ibility sufficient to detect small fluid-density changes and pressure

barriers, yet these features are commonly overlooked on conven-

tional pressure-depth plots. The large pressure variation caused

by weight of subsurface fluids hides these subtle features. Excess

pressure is the pressure left after subtracting the weight of a fluid

from the total pressure. This concept is applied to wireline pressuredata to remove effects of weight and emphasize subtle pressure

differences caused by density variations and pressure barriers. Fluid-

density changes of 0.02 g/cm3 or less can be resolved, and within-

well pressure barriers in the order of 5 kPa (0.7 psi) can be detected.

Using good-quality data, effects of reservoir capillary-displacement

pressure can be detected by offset of the free-water level from the

petroleum-water contact. This effect can be used to estimate reser-

voir wettability. Subsurface fluid-density measurements can also

be used to evaluate oil or gas quality on a bed-by-bed scale in traps

having variable oil or gas composition, to detect compartmental-

ization by small petroleum density differences, to verify quality of

samples for PVT (pressure, volume, temperature) analysis, and esti-

mate salinity or temperature of unsampled water zones.

Data quality limits barrier and fluid-contact resolution; thus,

quality control is essential. Pressure measurement errors on the

3-kPa (0.5-psi) scale can be detected from behavior of the buildup

pressure. Tests having the potential for small amounts of super-

charge are identified from the overbalance and formation mobility.

Examples illustrate identification of free-water levels and fluid con-

tacts, fluid identification, supercharge identification, and water-zone

compartmentalization.

INTRODUCTION

Pressure-depth plots have been used for the last quarter century

to evaluate fluid density, fluid contacts, and pressure compart-

Copyright#2003. The American Association of Petroleum Geologists. All rights reserved.

Manuscript received August 16, 2001; provisional acceptance March 22, 2002; revised manuscript

received July 8, 2002; final acceptance August 22, 2002.

AAPG Bulletin, v. 87, no. 2 (February 2003), pp. 295311 295

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mentalization from wireline pressure surveys (Pelissier-

Combescure et al., 1979). Over the last 10 years or so, a

new generation of temperature-compensated quartz

pressure gauges have increased within-well, wireline

pressuretest resolution andrepeatability to about 1 kPa

(0.2 psi; Veneruso et al., 1991). In many wells, total

pressure range of a wireline pressure survey is so large

that pressure-depth plots cannot take advantage of the

high resolution of modern pressure gauges.

This article uses a new interpretation technique

based on the concept of excess pressure. Data are trans-

formed to remove the effects of the weight of the static

fluid; thereby, small pressure differences can be visu-

alized. This technique enhances the measurement of

fluid densities and resolves small density changes and

pressure barriers that are not likely to be recognized on

standard pressure-depth plots. Poorly documented phe-nomena can also be detected, such as effects of capillary-

displacement pressures near fluid contacts. The high

resolution also allows new applications for wireline

pressure data. This technique was briefly described

on an earlier poster (Brown and Loucks, 2000). This

article presents the concept in more detail using examples

to illustrate its application. Wireline pressure data col-

lected after production indicates differential depletion;

thus, interpretation techniques are different from those

presented here.

High-resolution analysis requires tighter quality con-

trol, because small pressure-measurement errors cangreatly reduce interpretationstrength.Established quality-

control techniques (e.g., Dewan, 1983) are adapted to re-

solve more subtle test problems. Supercharged tests (tests

having anomalously high reservoir pressures) can be iden-

tified by new simplified relationships to overbalance,

filter-cake properties, and formation permeability.

PRESSURE ANALYSIS METHODOLOGY

Dewan (1983) and other wireline-log-analysis textbooks

present basic wireline pressure collection, quality con-trol, and interpretation methods. The wireline pres-

sures discussed in this article are pretest pressures;

that is, the static formation pressures are collected be-

fore wireline sampling. Data are collected in the fol-

lowing manner (Pelissier-Combescure et al., 1979). The

tool probe is pressed through the filter cake to the

borehole wall. A small volume of fluid is withdrawn

from the formation, and thus, the pressure drops (draw-

down). Pressure then builds as fluids in the formation

flow towardthe borehole (buildup). Drawdown volume

is normally so small that the pressure stabilizes within

a few minutes. In good tests, pressure stabilizes at the

formation pressure and the pretest ends. The mud pres-

sure at the test depth is recorded prior to setting the

probe and after withdrawal of the probe. These are re-

ported as hydrostatic or mud pressures. The other re-

ported pretest result is thedrawdown mobility (formation

permeability/filtrate viscosity). It is calculated from the

pressure drop during drawdown.

The most commonly used wireline pressure

interpretation technique is the pressure-depth diagram,

a plot of stabilized formation pressure against true ver-

tical depth (Figure 1). If the total pressure variation is

large, pressure-depth diagrams do not have resolution

sufficient to take advantage of the resolution of mod-

ern wireline pressure gauges. For example, the pres-

sure data in Figure 1 appear to be of quite high quality(low scatter), but the fluid contact is hard to identify,

even where contact elevation is identified. Water and

oil in this example have a relatively small density dif-

ference, and thus, the pressure-depth trends of the two

fluids are nearly parallel. One way to visualize small

density differences is to expand the pressure scale. The

slope difference is greater, but the contact may still

296 Improved Interpretation of Wireline Pressure Data

Pressure (MPa)

Subseadepth(m)

3040

3060

3080

3100

3120

33.8 34 34.2 34.4 34. 6

20 psi

free-water level

oil

water

oil-water contact

Figure 1. Conventional pressure-depth plot for the Villanooil accumulation, Ecuador. The diagonal line fits the waterpressures from the lower part of the survey. Data in the upperpart of the section deviate from the line owing to the presenceof oil. Horizontal lines show elevations of the free-water leveland oil-water contact.

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be difficult to recognize. In addition, scale expansion

increases the size of the diagram, and large diagrams are

cumbersome.

Excess-Pressure Definition and Construction of

Excess-Pressure Plots

Much of the pressure variations in pressure-depth plots

are caused by the weight of the fluids themselves. By

removing effects of the weight of one of the fluids on

pressure, small pressure differences caused by density

variations and pressure barriers can be enhanced. This

approach is referred to as the excess-pressure method

(Brown and Loucks, 2000). Excess-pressure estimation

is a common technique used elsewhere to analyze basin-scale water flow and geopressure development (e.g., over-

pressure of Mann and Mackenzie, 1990). In hydrologic

applications, freshwater or native-water density is used

for excess-pressure calculation. For wireline pressure

analysis, the density of any fluid in the reservoir is used.

Excess pressure is calculated from an assumed fluid

density, gauge depth, and measured pressure. Excess

pressure is the difference between the measured pressure

and the pressure expected from the weight of a fluid

between the datum and the depth of pressure mea-

surement (Figure 2A). The quantitative form of this

relationship is the following (Hubbert, 1956):

excess pressure rgz Pmexcess pressure 0:4335rz Pm

ft; g=cm3; and psi

excess pressure 9:8067E 6rz Pmm; kg=m

3; and MPa 1

wherePmis the measured pressure at depthz relative

to the datum (negative downward), U is the density of

the fluid at reservoir conditions, and gis the pressure

gradient for fluid having a density of 1 g/cm3. Excess

pressure can be calculated using any datum. The mag-

nitude of the excess pressure has less meaning than

excess-pressure differences calculated using the same

datum and fluid density. Excess pressure is easiest tointerpret if the chosen fluid density is the dominant

reservoir fluid density. A single static fluid having con-

stant density and free communication with itself (no

barriers) has the same excess pressure at all elevations

if density is chosen correctly (Figure 2B). Excess pressure

is constant because fluid potential is uniform (Hubbert,

1956).

Excess-pressure plots are constructed by identify-

ing the density that equalizes excess pressure of the

fluid of interest at all depths. Start by choosing a depth

interval in the pressure survey that has a single fluid

and no potential sealing lithologies. Excess pressuresare calculated and plotted against depth using an arbi-

trary fluid density. If the excess-pressure-vs.-depth trend

is rotated clockwise from vertical, the chosen density

is too high and a lower density value is substituted.

The assumed density is iterated until excess-pressure

variance is minimized and the excess-pressure trend is

vertical.

Data in Figure 1 are used as an example. The water-

saturated zone below the shale was chosen for analysis

and 1 g/cm3 density was assumed. This excess-pressure

trend slopes clockwise from vertical and the density

is slowly reduced until the excess-pressure trend isvertical at 0.966 g/cm3 (Figure 3). Tilt to the excess-

pressure slope is evident with only 0.006-g/cm3 change

in assumed water density (Figure 4). Excess pressure

in the water column ranges from 5023 to 5026 kPa

(728 to 728.5 psi), a range of 3 kPa (0.5 psi). In com-

parison, formation pressure over the same interval

ranges from about 34,160 to 34,560 kPa (4954.5 to

5012.5 psi), a range of 400 kPa (58 psi). Pressure bar-

rier and fluid contact are evident above the analyzed

interval, whereas these features are difficult to recognize

Brown 297

Pressure Excess pressure

assumed fluid-pressuretrend

excess

pressure

pressure

analyses

Depth

Depth

(A) (B)

Figure 2. Excess-pressure concept. (A) Pressure-depth diagram,showing pressure analyses (dots), pressure trend assumed forexcess-pressure calculation (diagonal line), and excess pressure(difference between expected and measured pressure, horizontallines). (B) Excess-pressuredepth diagram. The vertical datatrend in the lower part of the survey indicates that data matchthe assumed fluid density. Excess pressures for the shallowerpoints (horizontal lines) increase up section, indicative of a fluidhaving lower density.

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on Figure 1. The shallower data can be analyzed by using

excess pressure calculated from the oil density of 0.91 g/cm3 (Figure 5).

Interpretation Using Excess Pressure

Fluid density, fluid contacts, and pressure barriers can be

interpreted from excess-pressure plots. Fluid density is

estimatedby rotating theexcess-pressuretrend to vertical,

as discussed previously. Selection of fluid density is an

iterative process; thereby, barriers and slope changes can

be detected during the density-estimation process. If a

possible barrier or contact is identified, the depth range

of analyzed samples is narrowed so that only a singlefluid is evaluated. In contrast, fluid density is calculated

from pressure-depth plots by regression. Pressure-barrier

or small density changes may not be noticed before

regression; thus, the density calculated from the trend

may not represent the actual fluid density.

Slope change indicates fluid-density change. Fluid-

density changes at fluid contacts and across petroleum

seals (Figure 6). On excess-pressure plots, clockwise tilt

from vertical indicates a density that is lower than mod-

eled. Expanding the scale increases the excess-pressure


0.966 g/cm0.960 g/cm0.972 g/cm

(A)

5030 50405210 52204840 4850 4860

Excess pressure (kPa)

Subseadepth(m)

3040

3060

3080

3100

3120

B( ) C)(

shale bed

3 3 3

Figure 4. Sensitivity of excess-pressure density estimation.Excess-pressure-vs.-depth plot for assumed fluid densities of(A) 0.972, (B) 0.960, and (C) 0.966 g /cm3. Fluid-density changeof 0.006 g/cm3 is evident in the lower water-bearing sandstonefrom the excess-pressure slope. Same data are shown inFigures 1 and 3. Shaded zone is the shale bed.


water gradient

oil gradient

FWL

oil mobile

oil immobileSubsea

dept

h(m)

3040

3050

3060

3070

6710 67156705

OWC

0.5 psi

Figure 5. Excess pressure calculated using oil density (0.91g/cm3), using data from Figure 1 shallower than 3072 m.Intersection of oil and water trends is the free-water level(FWL), the elevation where capillary pressure is zero. Oil-watercontact (OWC) elevation lies between the highest data on thewater trend and lowest data on the oil trend. The free-waterlevel is lower than the oil-water contact due to water-wetconditions in the reservoir.

shale bed(pressure barrier)


5020 5030 5040 5050

Su

bsea

dep

th(m

)

3040

3060

3080

3100

3120

1 psi

oil

water

free-water level

Figure 3. Excess pressure vs. depth plotted for the Villano

field data shown in Figure 1. A density of 0.966 g/cm3

wasused to calculate excess pressure. Three trends are evident: avertical trend below the shale bed (main aquifer), a shortvertical trend above the shale bed (aquifer having slightlyhigher pressure), and a diagonal trend (oil column). Theshaded zone is a shale bed that acts as a barrier betweenthe aquifers with different pressure. The rest of the reservoiris sandstone.

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slope of fluids having a density different from modeled

density, but vertical excess-pressure trends do not change

as the scale expands. Scale can be expanded as much asneeded to detect small density changes. Once a different

slope indicates a different fluid, fluid density can be cal-

culated iteratively, just like the density of the first fluid

(Figure 5). In contrast, all trends are tilted on pressure-

depth plots, and thus, expanding the pressure axis changes

the slopes of both lines. Even after expanding the pres-

sure scale, minor slope changes may not be recognized.

Pressure-depth plots of most data lack sufficient res-

olution to differentiate betweenfree-water level (elevation

where capillary pressure is zero) and petroleum-water

contact (elevation with lowest moveable petroleum),

but these surfaces can be distinguished using excess-pressure plots. Intersection of the petroleum and water

trends is the free-water level, because at this eleva-

tion, the petroleum and water pressures are the same.

Petroleum-water contact occurs at or below the lowest

test that lies on the petroleum-density trend. The dif-

ference in petroleum-water contact elevation and free-

water level indicates wetting conditions in the reservoir

(Desbrandes and Gualdron, 1987). Reservoir-saturation

history can be evaluated by comparing petroleum-water

contact estimated from porosity-resistivity logging to

the contact estimated from wireline pressure data. If

porosity-resistivity logging indicates a deeperpetroleum

contact than estimated from wireline pressure data,the petroleum-water contact has probably moved up-

ward since trapping. The deeper petroleum is residual,

and the permeability-saturation relationship may fall

on the imbibition curve higher in the reservoir.

Abrupt offsets of pressure-depth trends indicate

pressure seals. Pressure seals plot as offsets between

tilted trends on pressure-depth diagrams (Figure 6A).

These offsets may not be recognized where the magni-

tude of the offset is small compared to the total pressure

change across the barrier. Excess-pressure plots remove

most of the total pressure change across the barrier, and

thus, excess-pressure scale can be expanded to visualizethe small excess-pressure difference (Figure 6B). If fluid-

density changes across a pressure barrier (such as the

top seal), the excess-pressure slope as well as the mag-

nitude of the excess pressure differs.

DATA-QUALITY CONTROL

The standard deviation of water-leg excess-pressure data

in Figure 3 is 0.65 kPa (0.09 psi). This is comparable

Brown 299

Pressure

fluid contacts

GOC

FWL

pressure barrier

seal

OWC

Depth

(A)Pressure

fluid contacts

GOC

FWL

pressure barrier

seal

OWC

Depth

(B)

oil

gas

water

Water with lower density

oil

Figure 6.Identification of fluid contacts and pressure barriers using pressure plots. (A) Pressure-depth plot showing characteristics offree-water level (FWL), oil-water contact (OWC), gas-oil contact (GOC), a pressure barrier, and a seal. (B) Excess-pressure plot calculatedfor oil density showing excess-pressure characteristics of free-water level (FWL), oil-water contact (OWC), gas-oil contact (GOC), apressure barrier, and a seal. Gas trend is rotated clockwise from vertical (lower density), whereas water trend is rotated counter-clockwise (density greater than oil). Water above seal has lower density than water below the OWC; thus, its slope is different. Excess-pressure scale is expanded by a factor of about seven relative to the pressure scale; thus, contacts and barriers are more obvious.

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to the within-well reproducibility of the temperature-

compensated quartz-gauge response (Veneruso et al.,

1991). Many data sets collected under good logging con-

ditions show low scatter, but some surveys show sig-

nificantly larger pressure scatter. For example, Fraisse

et al. (1987) report that 32% of repeated quartz-gauge

formation pressures have a pressure difference of 50

kPa (7 psi) or greater. The quality of the interpretation

is only as good as the quality of the data, and thus, data-

quality evaluation becomes essential.

Pressure-measurement problems, supercharging,

or depth errors may cause bad data. In most cases, bad

data cannot be corrected. Thus, the best strategy is the

identification of bad or suspect data and its elimina-

tion from the data set. The data normally supplied to

the geologist is a table of summary pretest formation

pressures, their depths, hydrostatic pressures, and draw-down mobilities (formation permeability/fluid viscos-

ity). Tests with suspect pressures may also be identified.

These data are insufficient to detect subtle data prob-

lems. Quality must be assessed from the transient pres-

sure data and other data available on the pressure-test

logs.

Pressure-Measurement Errors

Pressure-measurement problems have been recognized

since the introduction of multiple-testing tools (e.g.,Dewan, 1983). Traditional criteria identify data with

tens to hundreds of psi errors. These buildup criteria

have been modified to detect problems in the psi range

desired for high-resolution pressure analysis.

The pressure buildup during a good test is smooth,

with the rate of pressure increase decreasing with time

(Figure 7). The pressure appears stabilized at the end

of a good test; thus, the final pressure is very close to

the formation pressure. Random pressure fluctuations

during the latter part of the buildup are very small (

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during the entire buildup period or during the early or

late parts of the buildup. Pressure spikes or drops on the

buildup curve identify subtle seal leakage (Figure 8). In

some tests, the rate of pressure increase increases with

time, opposite from normal test behavior (Figure 8). A

plugged probe may be interpreted as equilibrated pres-

sure, because pressure buildup stops. Late-test plugging

causes an abrupt flattening of the pressure plotted against

Horner- or spherically normalized time. Most tests with

plugging or leaking during buildup must be discarded.

Stabilized pressure can be interpreted from tests where

probe plugging or seal leakage only affects the last part of

buildup. Horner- or spherically normalized time plots

from the earlier parts of the buildup project to the sta-

bilized pressure. Likewise, tests with good probe sealing

during the later part of the buildup may indicate static

reservoir pressure even where earlier parts of the testwere affected by probe-seal leakage.

In some settings, the temperature-compensated

quartz gauge shows an anomalous pressure response.

Pressure rises above the formation pressure during the

middle part of the buildup and then asymptotically

decreases with time (Figure 9). The cause of this phe-

nomenon is not clear. If the test is terminated too soon,

the pressure decrease is not recorded and the reported

pressure is slightly high (0.72 kPa [0.10.3 psi]) tothe static pressure. Where the pressure decline is re-

corded, interpreters may extrapolate reservoir pres-

sure from the part of the buildup curve where pressure

is falling. This extrapolation is not theoretically jus-

tified. It may lead to extrapolated equilibrium pres-

sure as much as 7 kPa (1 psi) lower than actual static

pressure. If this effect is observed during data collec-

tion, the best approach is to allow longer buildup

periods to allow the gauge to stabilize at static for-

mation pressure.

Brown 301

0 10thousand psi

10 psi 1 psi

Time

(s)

0

360

120

480

240

Drawdown

Buildup

Probe set

Full-scalepressure

CQGpressure

Straingauge

pressure

Pressurespike

Pressuredrop

-

Figure 8.Wireline pretest pressure variation for a test havinga small amount of seal leakage. Tracks and scales are the sameas those in Figure 7. Seal leakage is indicated by small (

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Depth Errors

A depth error of 0.3 m will result in approximately

3 kPa (0.4 psi) excess-pressure error in water-bearing

sections;thus, depth errors decrease excess-pressure data

quality. Depths must be adjusted to true vertical depth

for proper analysis. If the depth datum is adjusted during

the pressure logging run, pressure tests before and after

depth adjustment should be compared to see if there is

a systematic pressure difference caused by the depth

adjustment. Pulling stuck tools is likely to stretch the

cable, and logging runs with tool sticking may have higher

scatter than other data.

Within-well depth errors are difficult to detect or

correct. Theoretically, the mud pressure can be used

to correct the depth, but this has not proved useful

unless depth errors are great. Hydrostatic (mud) pres-sure measurements are rarely allowed to stabilize be-

fore or after the pretest; thus, reported before- and

after-test hydrostatic pressures may differ by as much

as 10 kPa (1.5 psi). Mud density changes during log-

ging as mud changes temperature; thus, a slight drift

to the mud pressure at a fixed depth is present. Mud

pressure also changes as mud level in the borehole varies

while logging.

Supercharging

Supercharging results from leakage of mud filtrate

through the filter cake (Figure 10). All filter cakes

that developed from water-based muds are perme-

able; thus, filtrate from overbalanced mud leaks into

the formation. If the filter cake has high permeability

or if the formation has low permeability, leakage into

the formation is faster than dispersion into the for-

mation. Pressure rises above the formation pressure

near the borehole wall. The probe measures pressure

at the borehole wall; thus, tests have high pressures

unrepresentative of the formation. All wireline pres-

sure tests in water-based muds are supercharged becausefiltration through the filter cake always occurs. Under

good logging conditions, supercharging is too small to

measure.

Where supercharging is hundreds to thousands

of kilopascals in excess of formation pressure, super-

charging can be identified solely on the basis of its high

pressure (e.g., Pelissier-Combescure et al., 1979). Super-

charging on the 110-kPa (0.11.5-psi) scale cannot

be reliably identified by higher pressure because den-

sity changes or compartmentalization may cause this

pressure difference. Numerical and analytical solutions

to supercharging provide a basis for predicting super-

charged tests (Pelissier-Combescure et al., 1979; Ste-

wart and Wittmann, 1979; Phelps et al., 1984; Waidet al., 1992). These models are rarely used with field

data.

Instead of these complex models, a simple model

is used to approximate conditions where supercharg-

ing is significant. During filtrate loss, water flows radially

through two concentric zones of differing permeability:

the filter cake and the formation. In each radial zone,

the pressure drop can be calculated as a function of the

permeability and the radial distance, assuming the Dupuit

assumptions of steady, incompressible, radial flow into


Borehole

Filter cake

formation

(A)

Mud pressure

Staticformation

pressure

Supercharge

Borehole Formation

Pressure dropacross filter cake

Radial distance

Pressure drop information

Pressure

(B)

Figure 10. Supercharge development. (A) Supercharge re-sults from radial filtrate flow from the borehole (left) intothe formation (right) through the permeable filter cake. Pres-sure near the borehole must exceed static formation pres-sure to accommodate flow. (B) Pressure profile across theborehole, filter cake, and formation. Where the filter cake hashigh permeability relative to the formation, pressure nextto the borehole is significantly higher than static forma-tion pressure. Pressure is measured at the borehole wall;thus, the static test pressure is higher than the static forma-tion pressure. This is the supercharge. Supercharge increaseswith increasing mud overbalance and increasing filter-cakepermeability.

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an infinite confined reservoir (modified from Viessman

et al., 1977):

p Pi P Qm

2pgrkln

r

ri2

where p is the pressure difference measured at radius

rfrom the reference pressurePimeasured at radiusri,

Qis the fluid flux through the borehole wall per unit

depth, k is the permeability, g is the gravitational ac-

celeration, Uis the fluid density, and Ais the viscosity.

Equation 2 can be used to describe the flow through

both the filter cake and the formation near the borehole.

The supercharge-plus-pressure drop across the filter cake

is the overbalance; that is, the mud pressure in excess of

the formation pressure. The ratio of supercharge to over-

balance can be determined by dividing the pressure dropin the formation by the total pressure drop (over-

balance). By taking the ratio,Q, A,g, 2, and Ucancel:

supercharge

overbalance

kfc ln rr

rb

kfc ln rr

rb

kfln

rbrbxmc

3

where permeability (k) subscripts fc and f refer to filter

cake and formation, respectively, and radius (r) sub-

scripts b and r refer to borehole and radius of influence,

respectively. The filter-cake thickness isXfc. The flow

model assumes that filtration has reached a steady flow,and thus, filtration history is ignored (except for calcu-

lation of filter-cake properties). The variables in equa-

tion 3 can be evaluated from well data. Borehole radius

is determined from caliper logs. Filter-cake properties

can be calculated from high-temperature, high-pressure

mud-filtration test, mud-solids test, and time since the

last wiper trip, all of which are in daily drilling and

mud reports. The filter-cake properties are calculated

by assuming static filtration since the last wiper trip.

Formulas for calculating the filter-cake properties from

test data are described in textbooks on drilling fluids

(e.g., Gray and Darley, 1980). Formation permeabilityis estimated from the mobility (permeability/viscos-

ity) measured by wireline pressure tests.

Because equations 2 and 3 describe incompres-

sible, steady flow, the radial distance to undisturbed

formation pressure is infinite and the natural log is

therefore not definable. Real reservoirs and fluids are

compressible, and the approximation represented by

the Dupuit assumption can be solved with a radius

equal to the distance with undisturbed pressure (radius

of influence). For the small volumes of filtrate leaking

from a borehole that has good mud properties, the

radius of influence is probably in the order of 3 m

(10 ft) or so, unless the well has serious fluid-loss prob-

lems or a highly compressible fluid. Doubling this

radius will increase the calculated supercharge by about

30%. An uncertain radius of influence and a poorly con-

strained filter-cake permeability limit the supercharge

approximation to order-of-magnitude estimates. Pre-

diction quality is insufficient to correct supercharged

tests, but it is sufficient to predict settings where super-

charge may be significant.

If average drilling conditions are assumed, super-

charge can be estimated as a function of formation and

filter-cake permeability (Figure 11). For example, a su-

percharge of about 3 kPa per 1000 kPa mud overbal-

ance (3 psi/1000 psi overbalance) can be expected in a

reservoir having a permeability of 1 md under typicaldrilling conditions (30 cm borehole diameter, filter

cake 1.2 cm thick having permeability of 0.1 Ad).

If supercharging is relatively small compared to over-

balance, the first term in the denominator of equation 3

Brown 303

Figure 11. Supercharge modeled as a function of rock per-meability and overbalance using equation 3. Vertical axis issupercharge normalized to overbalance (supercharge in kPa/1000 kPa is equal to psi/1000 psi). Assumed borehole con-ditions are indicated on the figure. The range of the modeledfilter-cake permeability is that expected in water-based mudwith modern mud systems.

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can be dropped. Supercharge becomes linearly propor-

tional to the inverse of formation permeability where

overbalance, filter-cake properties, and radius of in-fluence are similar. This leads to the familiar linear rela-

tionship between supercharge and inverse of formation

mobility (e.g., Pelissier-Combescure et al., 1979). The

correlation is extended to low supercharge by plotting

both axes on logarithmic scales (Figure 12). If the data

form a trend with a logarithmic slope near 1, then the

pressures are consistent with supercharge. Buildup mea-

sures low-formation mobility better than drawdown;

thus, the inverse of the Horner or spherical slope against

pressure can be used instead of drawdown mobility,

but the correlation slope should lie near 1. The highest

supercharged tests are those with the lowest forma-tion mobility; thus, tests with the most severe super-

chargeare likelyto have incomplete buildup.Tests should

be extrapolated to static pressures before analyzing for

supercharging.

BETWEEN-WELL PRESSURE DIFFERENCES

Absolute-gauge and depth accuracy limits the inter-

pretation of data from multiple wells, even where the

tool type and service company are the same. Absolute-

gauge accuracy is about 14 kPa (2 psi) for typical

operating depths and pressures (Joseph et al., 1992).

Most examples of between-well error are less than

this, near 10 kPa (1.5 psi; Figure 13). I have also seen

cases where static excess pressures differ by as much

as 35 kPa (5 psi) between nearby wells where the

only reasonable cause for pressure difference is gauge-

calibration error. Error this high has not been observed


10000

1000

Horner slope (MPa)/log(normalized time)

Supercharge

(kPa)

0.01 0.1 1 10 100

1

10

100

1000

Supercharge

(psi)

1

10

100

1000

Figure 12.Plot of logarithm of supercharge (static formationpressure minus pressure expected at test depth) vs. logarithmof the inverse of buildup permeability, as indicated by the Hor-ner slope. Horner slope is the regression of pressure againstthe log of Horner-normalized time. A trend having a loga-rithmic slope near 1 indicates that data are consistent withsupercharge origin. The slope flattens at high Horner slopesbecause the maximum supercharge is the overbalance. Dataare from Temane area, Mozambique.

100m

Truever

tica

ldep

th

10 kPa

Excess pressure

1

23

4

5

67

Well

1 psi

Figure 13.Example between-well absolute pressure accuracy

indicated by excess pressure vs. depth. Perfect accuracy andreservoir communication would plot as a single vertical trend.The data show both within-well and between-well differences,having a total variation in the order of 12 kPa (1.8 psi). Varia-tion includes effects of both depth uncertainty and pressure-gauge absolute accuracy. Higher data scatter in some wellsindicates poorer logging conditions and tool stability. Data werecollected from a large anticlinal gas accumulation having a highpermeability, sheet-sandstone reservoir, and excellent lateralcommunication. Wells were located up to tens of kilometersapart. Pressures were collected using different SchlumbergerMDT tools.

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using the latest generation of tools. Occasionally, there

is an excess-pressure difference close to 100 kPa (14.5

psi) between runs using different tools in the same well

or nearby wells with good pressure communication.

This pressure difference is probably caused by absolute

pressure mistakenly reported as gauge pressure. In my

experience, most examples of different runs using the

same tool in the same well have between-test repro-

ducibility similar to that within each run. This is not

true where the pressure tool has been fished or roughly

handled.

Pressure differences caused by errors in absolute-

depth accuracy between wells may cause apparent pres-

sure differences between wells. In some wells, especially

deviated wells, absolute-depth error may contribute more

to theexcess-pressure error than thegaugeerror. Typical

absolute-depth error in vertical wells is in the order of

0.03% where cable stretch has been corrected for tension,

temperature, and pressure (Sollie and Rodgers, 1994).

Excess-pressure uncertainty caused by depth uncer-

tainty at 3 km depth in vertical wells is at best near

10 kPa (1.5 psi), similar to the 14-kPa (2 psi) absolute-

gauge error for temperature-compensated quartz gauges

reported by Veneruso et al. (1991). Highly deviated wells

will have a greater depth error (Wolff and deWardt,

1981; Brooks and Wilson, 1996).

Between-well excess-pressure differences can be

corrected by adjusting absolute pressure, absolute depth,

or both. The effect of correcting a depth error is dif-

ferent from that of correcting a gauge error. This is

best illustrated with an example (Figure 14). A gas

accumulation over water is penetrated and tested bytwo wells, and well 2 has either a depth or pressure

error. If the depth of well 2 is shifted to align the water

trends, the free-water level of well 2 becomes lower

than well 1. If the pressure of well 2 is shifted to align

the water trends, the free-water level in well 2 is

higher than well 1. If the free-water level elevation

is assumed to be the same, then both the depth and

pressure are adjusted (Rodgers, 1998). If the same free-

water level is assumed, then the data cannot test com-

munication or tilting; thus, the between-well pressure

comparison does not provide any new information. New

depth surveys may resolve ambiguity if they reducedepth uncertainty. In addition, if either the depth or

pressure correction necessary to align the data exceeds

reported accuracy, then that correction is probably not

reasonable.

EXAMPLES

Villano Field, Oriente Basin, Ecuador

Villano field is a heavy oil accumulation in the south-western Oriente basin, Ecuador. The Albian Lower Hol-

lin Sandstone reservoir has a few shale beds high in

the section, but most of the unit is high-permeability,

moderate-porosity, fluvial sandstone. The trap is a fault-

bend fold anticline with no major faulting within the

main part of the reservoir. The oil and water densities

are similar; thus, the free-water level is barely evident

on the pressure-depth plot (Figure 1). The slope inflec-

tion on the excess-pressure diagram constructed using

water density (0.966 g/cm3) readily identifies the free-

Brown 305

Pressure

Wel

l1

Wel

l2

Dep

th

correc

tion

Pressurecorrection

Well 2 FWL after

pressure shift

Well 2 FWL after

depth shift

Wel

l2af

ter

pressuresh

ift

Well2after

depthshift

D

epth

Well 1 FWL

Well 2 FWL

Figure 14. Ambiguity of correcting between-well pressure-trend differences. Wells show different pressure trends causedby between-well pressure gauge or depth error (solid lines). Ifwater is hydrostatic, the two water-leg pressure trends shouldbe the same. There are three ways to align the water trends:pressures can be adjusted, depth can be adjusted, or bothdepth and pressure can be adjusted to align the free-waterlevels (FWL). If well 2 pressure is shifted, the FWL of well 2 liesabove that of well 1 (dashed line). If well 2 depth is shifted, theFWL of well 2 lies below that of well 1 (long-short dash). With-out independent evidence for the cause of the pressure-trenddifference, any correction is ambiguous.

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water level (Figure 3). Water-leg excess-pressure trends

are offset by about 1 kPa (0.2 psi) across a minor shale

layer. This shale acts as a barrier separating water zones

with slightly different pressures. This barrier is below

the oil-water contact, but it may affect water coning

during field production.

Oilexcess-pressuredata (calculated with 0.91 g/cm3)

seem to have considerable scatter, but this is caused

by the extreme magnification of the excess-pressure

scale (Figure 5). Oil excess pressure ranges from about

6709 to 6714 kPa (972.3 to 973 psi), a range of 5 kPa

(0.7 psi). No pressure barriers can be identified in the

oil column. The free-water level is the intersection of

the vertical oil pressure trend and the water trend. Its

elevation is 3068.6 m subsea, as determined by

algebraic intersection of the excess-pressure trends of

Figures 3 and 5. Some tests above the free-water levelfall on the water excess-pressure trend. No physical

barrier separating the oil tests from the water tests

is present; thus, this distribution is interpreted as a

capillary-threshold effect. Oil pressures are not

measured deeper in the borehole because oil is im-

mobile below this depth and the gauge measures only

mobile fluid pressure. The oil-water contact lies be-

tween the deepest pressure test falling on the oil trend

and the shallowest pressure test falling on the water

trend. The oil-water contact depth derived from the

wireline pressure data corresponds to an abrupt upward

increase in oil saturation determined by wireline loganalysis.

The oil-water pressure difference measured at the

oil-water contact corresponds to the native oil-brine

capillary displacement pressure at reservoir conditions,

using the concept of Desbrandes and Gualdron (1987).

If so, the capillary entry pressure of Hollin sandstone

at this depth is about 5 kPa (0.7 psi). Typical mercury

capillary displacement pressures of Hollin sandstones

are on the order of 56 kPa; thus, calculated product of

oil surface tension and wettability is about 0.032 N/m

(32 dyn/cm). This is a fairly high product, indicating

that conditions in the field are strongly water wet.

Temane Area, Mozambique

The Temane gas discoveries in Mozambique occur as

separate gas pools in thin, coarsening-upward, Creta-

ceous sandstones. The traps are simple dip-closures at

relatively shallow depth. The low gas density causes gas

pressures to plot as an almost vertical trend with depth;

thus, there is little advantage to using excess pressure.

This example illustrates the detection of supercharging.

Despite excellent borehole environmental condi-

tions, some pressures are quite anomalous (Figure 15).

Upper parts of the sandstone reservoir have a gradient

indicating gas density near 0.1 g/cm3, a value expected

at these depths and pressures. Deeper in the sand-

stone, the pressure increases rapidly with depth as if

the fluid was becoming denser. This appears at first

glance to be a fluid contact; however, the density of the

deeper fluid would have to be approximately 5 g/cm3

to account for the slope of the deeper interval. The

pressure data were analyzed to determine the cause of

this effect and the true gas-water contact elevation.

Upon inspection of the buildup curves, it became

apparent that most of the pressure tests in the lower

part of the sandstone were incompletely built up. The

first step was extrapolation to static pressure. This causes

the pressure trend to steepen even more (Figure 15).Because the pressures appeared too high, the possibility

of supercharging was investigated. Buildup mobilities


1 50

Gradient due to

density (g/cm )

Pressure (MPa)

1304

1305

1306

1307

1308

Depth(m)

13.513.4 13.6 13.7 13.8 13.913.3

Uncorrected

Extrapolated

shale

shale

3

Figure 15. Pressure-depth plot showing an apparent in-creasing density in the lower part of the pressure survey from awell in the Tamane area in Mozambique. Uncorrected data(crosses) indicate density changing from a gas gradient (0.1g/cm3) down section to a gradient exceeding 5 g/cm3. Most ofthe lower tests were incompletely built up; thus, static pressureswere extrapolated (diamonds). Extrapolation-corrected data in-dicate even greater density change. The reservoir is coarsening-upward sandstone. Shading indicates bounding shales. No shalebarriers are present in this reservoir.

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were estimated from buildup slopes for each test. Filter-

cake properties were estimated from mud tests reported

on daily well reports. From these data, supercharge wascalculated using equation 3. In general, there is a good

comparison between predicted supercharge and ob-

served supercharge (Figure 16). This strongly supports

the hypothesis that supercharging is responsible for

the high measured pressures. The sandstone has a dis-

tinct coarsening-upward texture that is reflected by

upward-increasing permeability in the sandstone. Su-

percharge increases systematically down the section

as reservoir permeability decreases. Once the cause of

anomalous pressures was identified, the intersection

of the pressure trend of the good gas tests and water

tests in nearby wells indicated the actual free-waterlevel.

Gulf of Mexico

An offshore Louisiana shelf, Gulf of Mexico well pen-

etrated several petroleum- and water-bearing zones. The

presence of petroleum was known from conventional

wireline logs; thus, the pressure survey was run to de-

termine petroleum fluid type and predict fluid contacts

if possible. Wireline pressures were measured, but in-

terpretations of the raw data were ambiguous due to

bad tests, multiple thin-reservoir zones, and multiple

fluids. Bad data are caused by seal leakage or a tight,

supercharged reservoir (Figure 17A). The permeabil-

ity threshold for supercharging was estimated from

well data, and tests with permeability below the thresh-

old were edited out. Tests with leaky probe seals were

identified from buildup characteristics. If leaks devel-

oped late in the test, earlier test data were extrapolated

to static pressure; otherwise, leaky tests were omitted.

Average correction of acceptable data is about 4 kPa

(0.6 psi; Figure 17B). The edited data showed much less

scatter (Figure 17A). The uppermost tested zone had too

few reliable tests to estimate fluid density. Petroleum

zones in the edited data were identified by clockwise

rotationof excess-pressure trends from vertical(zones 1and 3, Figure 17C).

Brown 307

10000

0.1

1

10

100

1000

0.0001 0.001 0.01 0.1 1 10 100 1000

Formation permeability (md)

Supercharge(kPa)

model

Figure 16. Comparison of modeled supercharge against for-mation permeability (line) having observed supercharge (points),assuming the section is entirely gas saturated. Close fit of themodel to data indicates that the high static pressures in the lowerpart of the survey are supercharged (same data as Figure 15).

1

2

3

50 psi

1.07 g/cm

Unedited data

Edited data

500 psi

Pressure (MPa)

900

850

800

750

700

65060 65 70 75

Sub

seadepth(m)

3 0 5 10Pressure correction (kPa)

27.8 28.3 28.8Excess pressure (MPa)

(A) (B) (C)

3

Figure 17. Gulf of Mexico example. Shaded zones indicateshale. (A) Pressure-depth plot having both unedited (open dia-monds) and edited (filled diamonds) wireline pressure data.Petroleum-bearing zones are hard to identify because of thethin, multiple reservoirs and spurious data. (B) Magnitude ofpressure corrections for acceptable data. Supercharged tests,

tight tests, and tests with significant probe-seal leaks wereremoved from the data set. (C) Excess-pressure-vs.-depth plotof edited data from the lower two-thirds of the run. Excesspressure is calculated using water density calculated in zone 2(1.07 g/cm3). Petroleum-bearing zones can now be clearly dis-tinguished from water zones by difference slopes. The waterzone in the middle of the section has greater pressure thanthe water legs of overlying and underlying petroleum-bearingintervals; thus, these data cannot be used to estimate the free-water level for the penetrated accumulations. Data from upper-most zone are not plotted because they are off the scale.Numbers refer to the zones analyzed in Figure 18.

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Zone 1 with a fluid density of 0.46 g/cm3 is con-

sistent with a liquid condensate (Figure 18A). No excess-

pressure offset or density change across the upper shale

in this reservoir is present; thus, the shale is not a geo-

logical pressure barrier. The single test below the lower

shale has slightly higher excess pressure, but the differ-

ence lies within expected data scatter, and thus, the lower

shale is not interpreted as a barrier.

Zone 2 is entirely water bearing with a density of

1.07 g/cm3, consistent with the high salinity of the pore

water. Excess pressures in the thicker, medial sandstone

are constant, indicating vertical pressure communication

over geological time (Figure 18B). The excess pressures

decrease up section, indicating upward cross-formational

water flow.

Zone 3 is petroleum- and water-saturated sand-

stone. Petroleum fluid density is 0.68 g/cm

3

, consis-tent with a high-volatile oil or black oil with a high

gas-oil ratio (GOR; Figure 18C). Water has a density

similar to that of zone 2, but the excess pressure is

much lower (75 kPa [11 psi] less than the deepest zone

2 test; Figure 17). This indicates that fluids in zone 3

communicate with permeable zones shallower than

zone 2; otherwise, water pressure could not drop below

that of zone 2. Zone 3 probably intersects a fault along

which fluid leaks, whereas the sandstones in zone 2 do

not intersect a transmissive fault. If this interpretation

is correct, the spillpoint for zone 3 may occur at the fault

intersection with the reservoir. This also explains why

zone 2 sandstones are not charged with petroleum.

No oil tests occur below the shale in zone 3 (Figure

18C). This may be caused by either capillary effects

or by shale sealing the base of the oil accumulation.

Drawdown mobilities of these tests are about 49 md/

cp, or about 25 md with assumed filtrate viscosity. Well-

sorted, fine-grained sandstones with a permeability of

25 md have a displacement pressure of 1426 kPa

(24 psi) under reservoir conditions (Smith, 1966). Cap-

illary pressure in the uppermost water test is 10 kPa(1.5 psi). This is less than the capillary-displacement

pressure expected for the lower sandstone; thus, mobile

oil saturation would not be expected in this zone,

even if the shale did not seal.

DISCUSSION

Suitable Data and Settings for Excess-Pressure Analysis

High-resolution analysis of wireline pressure data re-quires good-quality data. Test buildup curves should

always be evaluated for data-quality control. The end

user rarely examines the paper logs that contain build-

up data; they are usually filed and forgotten. Digital

files are rarely even archived. Sometimes, test depth or

final buildup pressure is incorrectly transcribed to the

summary tables given to the end user. I recommend

that the end user at least qualitatively examine build-

up curves for all tests prior to data analysis.

Strain-gauge pressure data do not have the repro-

ducibility necessary for meaningful results, given the

small excess-pressure variations in most petroleum ac-cumulations. Uncompensated quartz gauges measure

pressure reliably if the gauge is allowed to stabilize to

reservoir temperatures before beginning the pretest. Most

temperature-compensated quartz-gauge data have suffi-

cient resolution and reproducibility to apply the excess-

pressure approach.

Even temperature-compensated quartz pressure

gauges will give poor results under bad logging condi-

tions. Some settings always give poor results because

supercharging and probe-seal leakage are common. Most



760

1.07 g/cm

Zone 2(B)

1 psi

620 650 680

820

800

780

Subseadepth(m)


0.68 g/cm

858

854

850

Subseadepth(m)

Zone 3(C)

1 psi

410 420 430

728

724

720

716

Subseadepth(m)

0.46 g/cm


Zone 1(A)

0.5 psi

175 185

3 3 3

Figure 18. Detailed analysis of three zones in the Gulf of

Mexico example. Shaded zones indicate shale. (A) Zone 1excess-pressure-vs.-depth plot (fluid density of 0.46 g/cm3,consistent with condensate). Shales do not act as geologicalbarriers, because data form a single excess-pressure trend. (B)Zone 2 excess-pressure-vs.-depth plot (fluid density of 1.07g/cm3, salt water). Shales act as pressure barriers. Offsets ofexcess-pressure trend indicate upward flow of water. (C) Zone 3excess-pressure-vs.-depth plot is calculated with a fluid densityof 0.68 g/cm3 (high-GOR oil). The shale might act as a seal,but the lack of petroleum in the lower zone is more likelycaused by insufficient capillary pressure. Zone numbers areshown on Figure 17.

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pressure tests in highly fractured reservoirs show probe-

seal leakage during buildup. If all of the leaking tests

are omitted from the data set, few data are left to ana-

lyze. Pressure buildup data can be used to rank tests by

quality, and the best-quality tests can be used for in-

terpretations. Many tests in low-permeability reservoirs

will be supercharged. The reservoir zones with high per-

meability will be closest to actual reservoir pressure.

Minimizing mud overbalance during testing will also

minimize supercharging. Neither fractured nor low-

permeability reservoirs can be analyzed to the level

shown in the examples, but the process of quality con-

trol can usually change totally meaningless data into

data showing approximate fluid contacts and major

pressure barriers.

Pressures measured in wells having nearby pro-

duction are probably affected by production. Measuredexcess-pressure variation may be caused by differential

flow instead of static pressure variations. Pressure varia-

tions in wells affected by production have to be evalu-

ated for lateral connectivity to producing wells as well

as pressure variations caused by cross-formation flow.

Shallow gas has a density so low that the gas pres-

sure is almost uniform in the reservoir. Where gas den-

sity is low, there is no advantage to the excess-pressure

approach. Standard pressure-depthplots can be used to

evaluate fluid contacts and barriers.

Limits to Barrier and Fluid Contact Identification

The excess-pressure scale can be expanded sufficiently

to display small, random excess-pressure variation. Ran-

dom pressure variations will cause excess-pressure con-

figurations similar to barriers or fluid contacts if few

tests are available over the reservoir interval. The data

can be misinterpreted, unless statistical guidelines are

used to guide interpretation.

Like any statistical problem, the confidence in the

slope of a data trend or change of the mean between

two populations is controlled on the number of datapoints, the data variance, and (for confidence of slope

estimate) the depth range over which the slope is mea-

sured. Increasing the number of valid tests and test quality

control increases interpretation confidence. The thick-

ness of the petroleum-bearing reservoir (depth range)

is fixed. Using a given data variance, fluid-density reso-

lution can be increased only by taking more valid tests.

The confidence interval for the mean excess pressure

decreases with increasing sample size as predicted by

thetdistribution. Even when using a large number of

tests, slope changes in thin reservoirs may be difficult to

differentiate from excess-pressure offset across a barrier.

Possible barriers should always be verified by in-

tegrating pressure analysis with other data. A pressure

barrier must be associated with some lithological fea-

ture laterally extensive enough to isolate parts of the

reservoir. In most reservoirs, this is an evaporite bed,

mudrock bed, or clay-rich fault zone in the depth range

of the expected seal. If a small pressure offset is asso-

ciated with the same stratigraphic horizon in nearby

wells, then the barrier is probably valid.

Comparing results from nearby wells can also vali-

date small fluid-density changes. Within-well density

estimates are not affected by absolute pressure errors

between wells. Fluid density in the same compart-

ments or zone should be similar in nearby wells, and

the fluid contact should occur at approximately thesame elevation.

Using High-Quality Pressure Data

Fluid-density estimates from good-quality surveys are

accurate enough to estimate gas gravity and oil type,

not just general fluid type (water, oil, and gas). High-

resolution fluid-density estimates can be used to address

other exploration and development problems besides

the identification of general fluid type, fluid contact, and

barrier identification. The following are some exampleapplications of fluid-density estimates that I have used.

1. High-CO2 methane gas can be distinguished from

low CO2 methane gas by their subsurface density.

This technique works best where gas is dry because

ethane and other higher hydrocarbons also increase gas

density. CO2concentrations can be quantified where

gas density is modeled from well-constrained pres-

sure and temperature data.

2. Reservoir compartmentalization can be identified

by small petroleum density differences across poten-

tial barriers. Some flow barriers are permeable enoughfor pressures to equilibrate over geological time,

but insufficiently permeable to allow free mixing

of oils. Without mixing, small density differences are

preserved for geological lengths of time. This ap-

plication is similar to geochemical reservoir com-

partmentalization detection. Density-stratified oils

(oil density decreasing upward) are gravitationally

stable. Mixing is geologically slow, even where bar-

riers are absent. Oil density must be different at the

same elevation in different wells or oil density must

Brown 309

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decrease downward across a barrier in the same well

to indicate compartmentalization.

3. Zones with heavy oil can be distinguished from zones

having light oil in accumulations where oil quality

varies. Heavy oils have subsurface density heavier

than the density of associated light oils. Once high

density identifies zones with heavy oil, completion

strategies can be designed to maximize the econom-

ic mix of produced petroleum.

4. Accurate prediction of phase behavior depends on

good samples, but collection of samples represent-

ative of the subsurface petroleum is not always suc-

cessful. In addition to collecting excellent-quality

samples in difficult settings (e.g., Reignier and Jo-

seph, 1992), wireline pressure tools can collect pre-

test data to test the quality of the samples. Reservoir

fluid density predicted by numerical or experimentalPVT models can be compared to the in-situ density

determined from pressure data. A large density dif-

ference between predicted and observed density at

reservoir conditions may indicate that GOR was in-

correctly estimated for the fluid modeling.

5. Pore-water salinity can be estimated where temper-

ature is known, and in areas with known low salinity,

the static reservoir temperature can be estimated

from the water density. Quantitative water salinity

or temperature prediction requires good models for

water density as a function of composition, tempera-

ture, and pressure. Water density models developedby Batzle and Wang (1992) have proven accurate

over the range of normal reservoir pressures and

temperatures.

The significance of pressure barriers on field produc-

tion behavior has sometimes been questioned because

many barriers affecting production are not pressure

barriers. The persistence of small excess-pressure off-

sets across barriers in a petroleum column indicates that

petroleum pressure has not equilibrated over geological

time. Other barriers have permeability high enough to

allow pressure equilibration, but too low for geochemicalequilibration. Geochemical means (Kaufman et al., 1990)

or small petroleum-density differences can detect these

barriers. At the high rates of flow during production,

all of these barriers affect production. In many fields,

insufficient uncontaminated oil samples are available

for geochemical analysis on the scale of the pressure

sampling. Pressure detection of barriers should be used

with geochemical detection methodologies wherever

possible, because both methods have their strengths,

and integrated interpretations are superior.

CONCLUSIONS

Conventional pressure-depth plots cannot fully dis-

play the resolution of modern wireline pressure data.

Excess-pressure plots show many subtle features in

the pressure data that can be easily overlooked on

pressure-depth plots. Excess pressure is the pressure

left after subtracting the weight of the fluid from the

total pressure. The excess pressure of static, homoge-

neous fluid in good pressure communication will not

change with depth; thus, excess-pressure variations

with depth indicate barriers and fluid contacts. The

excess-pressure scale can be expanded as much as nec-

essary to evaluate minor pressure barriers and density

changes. Using good data, within-well systematic excess-

pressure differences of less than 5 kPa (0.7 psi) can be

interpreted in terms of pressure barriers and fluid-density changes. Examples demonstrate the utility of

these techniques.

Data-quality evaluation is essential. Small anoma-

lies in the buildup-pressure curve indicate pressure

errors on the psi scale caused by leaking probe seals,

probe plugging, and gauge problems. Suspected super-

charged samples can be identified from equation 3 or

by plotting the logarithm of supercharge against the

logarithm of test mobility. Most bad tests have to be dis-

carded, but a few can be corrected if problems are minor.

Small excess-pressure differences between wells can-

not be detected as easily as within-well excess-pressuredifferences, because absolute-depth and pressure calibra-

tion between wells is poorer than within-well pressure

resolution. Between-well pressure corrections involving

simple pressure or depth shifts are ambiguous.

Fluid-density resolution is sufficiently high to use

for new applications. These include petroleum quality

evaluation, barrier detection by small density differences,

and validation of PVT models where sample quality is

questionable.

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Brown, A., and R. G. Loucks, 2000, Evaluation of anhydrite seals inthe Arab Formation, Al Rayyan field, Qatar (abs.): GeoArabia,v. 5, p. 6263.


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Desbrandes, R., and J. Gualdron, 1987, In situ rock wettabilitydetermination with formation pressure data: Society of Pro-fessional Well Log Analysts 28th Annual Logging SymposiumTransactions June July 1987, v. 1, p. Z1 Z20.

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Gray, G. R., and H. Darley, 1980, Composition and properties ofoil well drilling fluids, (4th ed.): Houston, Texas, GulfPublishing, 630 p.

Hubbert, M. K., 1956, Darcys law and the field equations of theflow of underground fluids: Petroleum Transactions of theAmerican Institute of Mining Engineers, v. 207, p. 222239.

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