Petroleum geologists have alwaysbeen frustrated by their inability toexamine the rocks in the wellbore directly.Faults, bedding and fracture orientation can beeasily assessed in outcrop, but data gathereddownhole is sometimes contradictory or unreliable. Bythe 1960s, several companies were developing borehole

imaging techniques to overcome this problem.

Downhole imaging technology has come a long way fromthe basic images produced by the Borehole TeleViewer

tool. Modern tools use resistivity and sonic variationsto map the borehole wall. The detailed images

which can now be obtained are comparable tocore and, unlike the average core, have no

missing sections.

In this article, Jaap Focke, Chris Heine andRoy Nurmi discuss the latest developments

in Middle East sandstones. Including important contributions from: Mohammed Al Dalab, Chief

Geologist for Abu Dhabi Marine and Stefan Luthi, Chief

Geologist for Schlumberger EAF.

The outcropon your desktop

40 Middle East Well Evaluation Review

1015

20 25

20

10

1000m 0 0.5kmc.i.: 20ft

0

40

60

20 40

40 20 0

P-6

P-12

P-8

P-13

P-10

P-5P-3

P-1P-9

P-11

Fig. 3.2: Dipmeter

surveys from two river

channels. The first

survey (a), carried out

using a High-Resolution

Dipmeter Tool (HDT*),

shows a scatter of dip

directions which do not

coincide with the

channel orientation

inferred from sediment

thickness. The second

survey (b) indicates a

transport direction

towards the south east

(with minor, possibly

tidal, variations). This

agrees with inferred

orientation. However,

dip results from any

single well in either

survey would not

necessarily indicate

actual river flow.

Modified from: K.Saito,

R. Nurmi, T. Uchiyama,

Dipmeter and

Workstation Aid

Geologic Interpretation.

World Oil, July 1987.

Fig. 3.1: River channels (ancient and modern) can be straight, high-energy

braided streams or low-energy meandering channels. This distinction is

critical to reservoir geometry.

River (or fluvial)

systems are common

oil and gas reservoirs.

The high-porosity channel

sands which contain the oil

or gas are usually contrasted with

facies equivalent non-channel silts or

muds. The distribution of these rock

types and the nature of the boundaries

between them (sedimentary or struc-

tural) are critical to reservoir develop-

ment. Geologists generally classify

channels as either braided or meander-

ing (figure 3.1).

Whatever the overall geometry of the

river deposit, small-scale variations in flow

and bedding make rivers very difficult to

characterize from borehole data alone.

Dip values from a single well usually tell

us very little about the ultimate transport

direction in a fluvial system (figure 3.2).

A combination of techniques is usually

required to determine the depositional

system. Borehole imagery, combined

with core data, has improved reservoir

mapping within the Hawtah trend, central

Saudi Arabia (Heine, MEOS 1993).

Borehole imagery has provided a direc-

tional component to the core-based depo-

sitional model. Net sand isopach maps of

the Unayzah Formation, contoured using

this oriented geological model, are suit-

able for geological modelling and, ulti-

mately, for reservoir simulation.

Sand mapping and net sand isopachs

have always been a fundamental part of

reservoir simulation. Geological input

has usually been a chronostratigraphic

layered model needed to develop a 3D

reservoir architecture for simulation.

A standard, computer-generated

isopach map is correct only in that it

does not break any contouring rules. The

maps generated in this way are a series

of closed thickness areas that do not

relate to a field-wide or regional deposi-

tional trend (figure 3.3). Most distance-

weighted techniques tend to wrap the

isopach around the edges of the data,

suggesting that the sand exists only in the

field - it has no source and no other depo-

sitional area outside the dataset - as

though it had fallen from space rather

than forming part of a continuous deposi-

tional sequence.

By adding imagery-derived transport

directions (arrows showing azimuthal

direction) at each well with borehole

imagery data, the contouring can be

carried out (initially by hand or ulti-

mately by a modified computer program)

with the values being influenced by the

directional values (figure 3.4).

In this example, core samples indi-

cated that the layer was typical of a

braided stream environment. By adding

current transport directions from sands

within the field it was possible to model a

west-to-east transport direction for the

braided stream deposits.

(a) (b)

C. Heine and D.H. Cooper (1996) Integration of Geosta-

tistical Techniques and Intuitive Geology in the 3D Mod-

eling Process. Ann. AAPG meeting San Diego.

K.H. Al-Sulami, C. Heine and J.R. Wilkins (1996) The

use of Geologic Models in Building the Stratigraphic

Framework and Influencing Attribute Interpolation in

the Hawtah Trend. GEO/96 Bahrain.

41Number 17, 1996.

A B C D E F G H I J K

A B D E F G H I J KC

Fig. 3.7: This reconstruction

represents the flood stage, with high

volumes of sediment input and partial re-

working of existing aeolian sandbodies. This

situation makes interpretation difficult when data

is restricted to core samples and standard logs.

PUU

PUUQusaiba shale

Back filled paleotopography

Flood plain/playa

Flood plain/playaSiltstones

Aeolian

Aeolian

Trough cross-beddedstacked braidedstream channels

Trough cross-bedded sandstone

N

S

Fig. 3.5: DIPS

WITHOUT DOUBTS:

The geologist can use

high-quality borehole

images to ‘see’ the

rocks and make dip

measurements as if

dealing with an

outcrop.

Fig. 3.3: A computer-

generated (mean square

root interpolation) map

of isopach values gives

no indication of

transport direction.

There is no depositional

continuity away from

the data and the isopach

values seem almost

random / non-geological.

Fig. 3.4: Isopach

values can be re-

interpreted using

directional data from

borehole images. This

shows a west-to-east

transport direction,

and variation

between point

thicknesses can be

interpolated (and

tested).

Fig. 3.6: LOOKING

FOR DIRECTIONS:

Analysis of dip

direction can give a

clear indication of

environment. This plot

indicates a south

flowing river channel

with a minor flow

component to the east.

In most cases, the only way to

remove doubts about dip directions is to

see the rocks. This is easy for an

outcrop, but at depth the geoscientist

must rely on electrical images (figure

3.5) to unravel complex depositional

environments.

Once the dip information has been

collected and current directions

assessed (figure 3.6) we can predict a

reservoir’s internal geometry and

likely extent. This allows the operator

to plan the locations of development

wells in a logical way, following sedi-

mentary trends, rather than the expen-

sive and time-consuming approach

which relies on ‘trial and error’ reser-

voir delineation.

By breaking complex fluvial environ-

ments into a series of smaller chrono-

stratigraphic units (figure 3.7), the

geoscientist can start to define reservoir

zones and estimate reservoir continuity.

x450.0

x451.0

x452.0

x453.0

x454.0

x455.0

N

S

W E

x449.0

Proto Omanmountains

Hasirah

Jawdah

Huqf h

igh ax

is

Cratonic Rub al Khali basin

Alluvial plain

42 Middle East Well Evaluation Review

Fig 3.8: Palaeogeography of the Gharif Formation, Oman. There was widespread deposition of coastal

and alluvial clastic sediments across Arabia during the Permian. Late Palaeozoic river channels in

southern Oman (a) are associated with a late Palaeozoic glaciation. The coastal channel deposits (b) are

small, widespread sand bodies. So, although the Gharif Formation contains a significant volume of oil, it

is distributed over a wide area in small fields and reservoirs. Glacial striations (c) are the clearest

indication of ice movement at this stratigraphic level.

The way things were

Palaeogeographical studies of the

Arabian Peninsula indicate that there

was widespread deposition of coastal

and alluvial clastic sediments during the

Permian (figure 3.8).

The Permian Gharif Formation in

Oman contains significant volumes of oil.

Unfortunately, these reserves are dis-

tributed over a very large area in numer-

ous small fields and reservoirs. The

Gharif Formation consists of fluvial and

coastal clastic sediments with one major

phase of marine influence (the Haushi

Limestone).

Exploration has yielded more than 50

discoveries, of which over 30 have been

developed into producing fields. Some

estimates suggest that the Gharif

Formation contains around 23% of

Oman’s remaining oil reserves. The

highly variable production performances

from field to field (and, in some cases,

from well to well) are a major difficulty

in prospect evaluation.

The reservoirs display a range of

accumulation conditions and oil proper-

ties, various styles of reservoir architec-

ture and variable heterogeneity. This

situation effectively rules out intensive

pre-development appraisal and acquisi-

tion of continuous core samples. The

efforts expended on a single well (char-

acterizing sediment grain size, sorting,

mineralogy and diagenesis) may yield no

results which can be applied to other

wells or reservoirs in the field. The alter-

native to detailed analysis is a policy of

rapid simple development where suc-

cessful wells (including exploration

wells) have been put into production as

soon as possible after discovery. This

approach has been facilitated by the

desert environment in which the fields

occur. The follow-up technique is low

risk outstep development wells, drilled

soon after the initial discovery while the

reservoir is still largely unknown. After

approximately one year of production,

more wells may be drilled if the perfor-

mance of the initial well(s) has proved

satisfactory.

At this stage, well-to-well correlations

provide the first real model of reservoir

architecture. The model is calibrated

with log and pressure data from the new

(a)

(b)

(c)

J. W. Focke and J. Van Popta (1989) Reservoir evalua-

tion of the Permian Gharif Formation, Sultanate of

Oman. SPE 17978.

Photo: J. W. Focke

43Number 17, 1996.

Eastern flankCentral Oman

Khuffcarbonates Marker limestone

Khuff

Multistoreyfluvial sheet sand(FU megasequence)

Channel sandswith associated fines

Playa claystone

Coastal plain(lake/bayhead deltas)

Thick lacustrine Rahab Shale

in salt dissolution area

Possible disconformity

Transgressive

deltaic complex

Offshore muds

Progradingcarbonateplatform

Culmination of

transgression

Unidiff. alluvial plaindeposits (FU megasequence)

Gharif

Middle

Upper

Lower

Al Khlata

Khuff

Basal

Overall?

Fig. 3.9: The top of the

Gharif Formation is

well defined in

northern and central

Oman by the base of

the Khuff carbonates.

However, in southern

Oman the situation is

less straightforward.

J.W. Focke and J. Van

Popta (1989). SPE

17978.

well(s) and production data from the

older well(s). As the database grows,

completion and development practices

(e.g. well spacing) are adapted.

This approach has underlined the

importance of surveys, such as those

carried out by the Repeat Formation

Tester (RFT*) tool, which allow opera-

tors to gain an insight into reservoir

architecture and connectivity. In one

field, where five Gharif wells had been

producing for about 12 months, RFT

pressures taken in new wells indicated

that the Lower and Middle Gharif sands

were all in pressure communication. At

the same time, differential depletion

between the various sand bodies pro-

vided information on the lateral extent of

shale breaks and the effect of these

shales on vertical communication. The

location of sand bodies on opposite

sides of a fault probably increases con-

nectivity between units in this field.

Using this type of data, completion inter-

vals can be combined, although in this

case separate development was contin-

ued with a view to applying thermal

recovery methods (steam soak) at a later

stage. An additional benefit from the RFT

survey was the first indication of aquifer

activity in the reservoirs.

The top of the Gharif Formation is well

defined in northern and central Oman by

the base of the Khuff carbonates.

However, in southern Oman the situation

is less straightforward with Khuff clay-

stones overlying Gharif claystones (figure

3.9). Seismic attribute mapping has been

attempted in several fields but small

acoustic impedance contrasts between

the sediments affected the overall quality

of the results. Thick Mesozoic and

Tertiary carbonates mask the weak

primary reflections from the Gharif,

making it almost impossible to discrimi-

nate between the Gharif Formation and

overlying red beds.

In central Oman, Upper Gharif

channel sands are often isolated from

each other by claystones, whereas the

Middle Gharif channel sands tend to be

laterally connected into more or less cor-

relatable packages (see also figure 3.11

which represents the Upper and Middle

Gharif).

The Lower Gharif coastal sands are

often straightforward sheet sands with

excellent correlation. Horizontal drilling

is difficult because of the depth (1500 m

to 3000 m) and the need to drill build-up

sections through very reactive clay-

stones. However, this technique is now

providing the key to unlocking the

reserves. Geosteering is particularly

useful in chasing the laterally stacked

channels of the Middle Gharif. Slimhole

FEWD (Formation Evaluation While

Drilling) tools and oriented tools will help

in the development of this play.

Other modelling techniques (e.g.

probabilistic modelling) may be applied

in large fields, but are considered uneco-

nomic for the smaller fields. A great deal

of information must be gathered in order

to determine the dimensions, fluvial set-

tings and transport directions of individ-

ual sand bodies.

44 Middle East Well Evaluation Review

Marker 1

Marker 2

Marker 3

Marker 4

Domain 2

Domain 1

0.01 - 0.1mm 1 - 10cm 1 - 10m 10 - 100m

1 2 3

CMR / thin section FMI / hand lens Imagery / core Testing / outcrop

Fig. 3.11: Meandering channels in river valleys and abandonment of delta channels produce

sediment sequences which are vertically and laterally variable, containing a large number of small

reservoir-quality sandstone compartments, at various scales from hundreds of metres down to

millimetres. (Modified from K. Weber (1986) in: Reservoir Characterisation, Lake and Carrol,

Academic Press)

Fig. 3.10: The depth of investigation for various downhole techniques determines how much of the

geology around the borehole can be ‘seen’ and the detail in which it will be recorded. Cores provide

very detailed information close to the borehole, logs provide a little less detail with greater degree of

penetration, and well tests can detect important reservoir features, such as faults, a long way into

the formation.

Production

Cores

Shale

Logs

RFT

MDT

0.1 1 10 100 1000 10000

Well testing

Shale

Distance from borehole, ft.

First class compartments

The detection of thin beds and shale

baffles is simplified using high-resolution

borehole imaging techniques. However,

these features must be tested using other

tools such as the RFT or MDT tools.

Pressure data (figure 3.10) should be

used to test for fault compartments that

have been created by faults which are

defined in the imagery. This helps to

reduce the risk of leaving large volumes

of by-passed oil in the reservoir.

Imagery can help geoscientists to select

the best location for seismic investigations

such as VSP or walkaway surveys.

Channel compartments

When close to source, rivers are high-

energy depositional systems moving

large volumes of relatively coarse sedi-

ment. As the river approaches the sea its

energy decreases as does its capacity to

carry sediment. The river channel

usually starts to meander across the

valley floor and, if conditions at the coast

are suitable, forms a delta. Deltas build

up sediment volumes through time and

the river channel moves across the delta

as it develops. This produces discrete

sandstone compartments within the

delta. Consequently, individual reservoir

compartments within a delta sandstone

are normally quite small and variable

through the sequence, with little lateral

or vertical connectivity (figure 3.11).

Dipmeter doubts

In environments where sedimentary

dips are highly variable, a dipmeter can

not be expected to present a clear

picture of the interval. Even cores are

not completely reliable - incomplete sec-

tions are an obvious problem, but even

when samples have been recovered

they may be unrepresentative and

remain open to mis-interpretation.

The analyst, who must worry about

unselected dips and missing core sec-

tions, has very little completely reliable

evidence on which to base an environ-

mental reconstruction. If a detailed reser-

voir model is important, and in most

reservoirs it will be essential for optimiza-

tion of oil and gas production, a sedimen-

tological framework based on detailed

imaging techniques must be developed.

The major difficulty with sand chan-

nels in, for example, a delta environment

is finding the channels. Over relatively

short geological time-scales, rivers

change their position and deltas change

their shape. The lateral

movement of rivers (avul-

sion), combined with

subsidence and sedi-

mentation, means that

channel deposits do

not form a continuous

layer. In delta reser-

voirs, the channels are

oil-rich targets set in a

mass of unproductive

silts and shales.

Number 17, 1996.

Composition and size

Shape and orientation

Packing

Resistivityincreasing

Cementednon-poroussandstone

Highresistivity

Low resistivityif conductive fluidin pore space

Poroussandstone

Electricalbeddingplane

Sandstone

Shale

Grain supported

Matrix supported

Angular grains

Rounded grains

Fig. 3.12: THE END OF THE BED: Sandstone beds can be defined from a wide variety of

mineralogical, textural and grain size variations. The identification of bed boundaries is crucial

to formation evaluation - if the alternations of shale, silts and sands in a thin bed reservoir can

not be identified, no reliable assessment of reservoir quality can be made.

Before dips can be measured we

have to identify the bedding planes. In

outcrops bedding is usually obvious

and, with the aid of high-quality images,

it can normally be identified very easily

in the borehole. However, for those who

rely on dipmeter data alone, bed bound-

aries are not so easy to identify.

How thick is thick?

In any sequence, the thickness of sedi-

mentary layers is highly variable.

Alternations of thin shale laminae with

thickly-bedded sandstones are uncom-

mon, but they do occur, and many sedi-

ments have definite grading patterns

(increasing or decreasing grain size) up

or down the sequence.

There are many kinds of bed bound-

ary (figure 3.12). The features which sep-

arate one bed from the next can depend

on surprisingly subtle changes in grain

size, packing or orientation. These subtle

changes may have a major influence on

formation and reservoir properties - for

example by altering porosity or perme-

ability in a few key layers.

Borehole images allow the geoscien-

tist to identify and characterize bed

boundaries and to see sharp and grada-

tional contacts. More and more dips are

being measured using borehole tech-

niques, but they are still presented in the

format which those who have always

worked with dipmeters will recognize - a

profile of tadpoles or arrows.

The main difference is that the values

can be confirmed by direct observation

of the features being measured.

The orientation of reservoir bodies

which are too small to be resolved by

even 3D seismic methods are often

determined by geological interpretation

of their internal characteristics, including

cross-bedding. Their geometry is gener-

ally interpreted by determining the

direction of the palaeocurrent which

deposited the sediment, although the

sedimentary drape above a reservoir

body, or the compaction of sediments

below it, can also be used. Sandstone

reservoirs are generally channels or

bars that can be readily subjected to this

sort of geometrical analysis.

Channel compartments

Channel sands, in contrast to the silts

and muds which comprise the other

parts of fluvial environments, are gener-

ally good reservoir rocks. This is

because they are relatively porous and

clean (i.e. have a low shale content).

A drilling and production programme

that will intersect and drain as many of

these pay zones as possible must be

devised. This plan will rely on the geo-

scientist’s model - an assessment of

channel size, location and connectivity.

In complicated sedimentary settings this

model is usually based

on information from

cores and bore-

hole imagery.

45

46 Middle East Well Evaluation Review

Well No. 6Well No. 3Well No. 5Well No. 4

Khu

ffLo

wer

Per

mia

n

0

50 ft

100 ft

Legend

Medium/coarse sandstone

Fine sandstone

Siltstone/shale

Dolomite

GR GR GR GR

Iran16

000'

2000

0'

2000

0'16

000'

Qatar

SaudiArabia

Dubai

Abu Dhabi

Oman

4

53

6

Fig. 3.14: OFF THE KHUFF: Correlation of Lower Permian rocks, offshore Abu Dhabi, showing

pre-Khuff clastics. Modified from T.H. Hassan, M.A. Al Dabal and M.E. El-Said, ADMA-OPCO,

MEOS, (1995). SPE 29801.

Fig. 3.15: Structural contour map of the pre-

Khuff in Abu Dhabi showing location of

sequences shown in 3.14. Modified from

A.R. Ali and S.J. Silwadi, ADNOC, MEOS,

(1989). SPE 18009.

Probing the pre-Khuff

The Khuff Formation straddles the

Permian-Triassic boundary, which means

that it was laid down about 250M years

ago. This unit marks the widespread

development of marine carbonate

deposits during the Mesozoic. In

Palaeozoic sequences continental clastic

rocks predominate.

In Central Saudi Arabia, the Khuff

Formation lies unconformably on top of

the Unayzah Formation. The Unayzah

was deposited as coalescing alluvial fans,

dominated by braided streams (figure

3.13) which graded into playa lakes

under semi-arid conditions. The well-

defined pre-Khuff unconformity is often

marked by a caliche (a ‘palaeo-soil’) and

soil horizons.

In Oman, the Khuff Formation lies on

the Gharif Formation. The Gharif con-

tains oil and gas. Correlation in the

Gharif (figures 3.14 and 3.15) has been

hampered by poor gamma ray distinc-

tion of rock types - a result of high

feldspar content in the sandstone and

low radioactivity in the shales. In addi-

tion, intense calcite cementation occurs

in many fields - adversely affecting

density and sonic wireline responses.

The Formation MicroScanner* (FMS)

can help the geologist to pick out

bedding and palaeocurrent indications

that would otherwise be masked by

cementation effects.

Levee splays Channel bar Channel Flood plain

Widespread sand sheet

Fig. 3.13: Braided river depositional system from the Lower Carboniferous of Abu Dhabi. Modified

from T.H. Hassan, M.A. Dabal and M.E. El-Said, ADMA-OPCO, MEOS, 1995. SPE 29801.

47Number 17, 1996.

Das Island

Abu Dhabi

N

W

>6

5-6

1-4

YibalRub al Khalibasin

?

10m

10m20m

30m

40m

10m

0 30 60km

N

300 000

400 000+

500 000+

2500 000

2400 000

2300 000

Ooidal facies (potential reservoir)

Shallow shelffacies

Backbar facies Thickness of porous(>5%φ ) limestone

Progradation directionof ooidal crossbeds

Approx. Northernlimit of basal upperkhuff red beds

(a)

(b)

Fig. 3.17: Prevailing

wind directions, in the

Permian help to

explain the distribution

of Permian sediments

around the islands

offshore Abu Dhabi

(a). A detailed model

(b) shows how

individual reservoirs

formed, while (c)

reveals how the rocks

appear in outcrop.

From: C.G.L. Mercadier

and S.E. Livera (1993)

Applications of the

Formation

MicroScanner to

Modelling of

Palaeozoic Reservoirs

in Oman. IAS Special

Publication.

(c)

Cores and currents

The heterogeneity of carbonate rocks is

well known within the oil industry, in

fact it was this property which led to the

introduction of ‘whole-core analysis’

which uses an entire core section -

rather than a one inch plug of the sort

routinely taken from sandstone core.

A review of numerous enhanced oil

recovery projects has indicated that car-

bonate reservoirs are always more

complex than initial estimates would

have us believe.

3D seismic surveys have confirmed

the large scale reservoir heterogeneities

and FMI/FMS analysis has revealed high-

permeability beds and unknown com-

partments which can ruin waterflood

programs. Some of the best carbonate

reservoirs consist of grainstone facies

that were deposited as shoaling upwards

sequences. However, thin zones of high-

permeability grainstone may cross lower

permeability wackestone reservoir

sequences. These grainstones probably

represent storm deposits or may be asso-

ciated with short-term falls in sea level.

Palaeocurrent studies in the Middle

East have shown that the best reservoir

facies may develop around structural

highs. Palaeocurrents in the Permo-

Triassic Khuff were found to be domi-

nantly south and southwest (figure 3.16),

causing shoaling buildups along the

southern and southeastern flanks of

fields in Abu Dhabi (figure 3.17a). Similar

facies have been mapped in Oman

where palaeocurrents were also directed

towards the south and east, with a pro-

nounced development and thickening of

the oolite shoal facies in that direction.

Modern current systems -a tale of tails

In southeastern parts of the Gulf the

accumulation of sediment around some

islands and reefs has been controlled by

the direction of the prevailing winds.

The distribution of sediments around

bathymetric highs off the coast of Abu

Dhabi (figure 3.17b) is concentrated on

the leeward side of these highs, i.e. the

side away from the prevailing wind. The

sediments often stretch out into long,

linear accumulations behind the islands

and reefs. The sediments are usually

cross-bedded carbonate grainstones

(figure 3.17c).

The development of these sediment

‘tails’ can give us a clearer insight into the

processes which have shaped sediment

distribution in the past. This, in turn,

allows a more informed interpretation of

the palaeocurrent directions in reservoirs.

Fig. 3.16: During the Permian, the

continents were grouped

together to form Pangea, a

‘super-continent’. Detailed

research into conditions

at that time indicate

that the prevailing

wind direction in the

Middle East was from

the northwest.Pangea

48 Middle East Well Evaluation Review

Sandstone search inSaudi Arabia

The Permian Unayzah Formation within

the Hawtah trend in Central Saudi Arabia

has been re-evaluated several times as

additional data from cores, conventional

logs (figure 3.18) and borehole imagery

(figure 3.19) have accumulated. The for-

mation consists of red conglomerate,

sandstone, siltstone, mudstone, caliche

and occasional nodular anhydrite. Facies

changes reflect the numerous sub-envi-

ronments and possible faulting and basin

growth during deposition.

Initial interpretations, based on just a

few wells, suggested a marginal marine

environment. This interpretation rested

primarily on the fact that sand packages

could be correlated over long distances.

However, the presence of very well-

rounded (near-spherical) quartz grains

and a high degree of compositional matu-

rity throughout the rock (figure 3.20) did

not seem to support this finding. Mature

sediments typically contain no angular

grains and there is little grain size varia-

tion. This degree of maturity, unusually

high for a marine deposit, was attributed

to sediment re-working with the well-

rounded grains being derived from the

erosion of well-rounded and mature sedi-

ment source. The contrast between

aeolian and glacial sand grains (figure

3.21) is very clear.

As the field was developed, new core

studies and borehole images helped geo-

scientists to revise their model: suggesting

a continental clastic depositional setting

dominated by alluvial fan and braided

stream deposits which graded into playa

lakes under arid and semi-arid conditions.

The ‘frosted’ appearance of these

quartz grains (figure 3.22), bi-modal grain-

size distribution and adhesion ripples

within a sabkha facies indicated an

aeolian influence in this depositional

system. Apparent dip angles measured in

sandstone cores often approached 30°,

but the mechanical coring process

changed sample orientation in the core

barrel - obscuring or destroying bedding

relationships. To make matters worse,

these apparent aeolian facies frequently

appeared not as solid cores but as piles

of sand in a core tray.

Fig. 3.18: This log and the dips shown on the

accompanying ‘tadpole’ plot indicate that the

sequence has intervals of consistent and well-

defined bedding (e.g. between x300ft and x325ft).

From: C. Heine (1993).

Fig. 3.19: A closer examination of the sequence and the

addition of borehole imagery (a) reveals that the dips in the

interval immediately below x300ft are typical of aeolian

beds. The beds are arranged in 15 to 20 ft units with dip

angles of around 30°. The dips provide a clear indication of

local wind transport direction (b). From: C. Heine (1993).

(a)

X305

X200

X300

X400

X310

X315

X320

C. Heine (1993) Integrating Borehole Imagery and Con-

ventional Core Data, Unayzah Formation, Hawtah

Field, Central Saudi Arabia, MEOS, Bahrain 1993. SPE

Paper 25638.

(b)

49Number 17, 1996.

The Pre-Khuff unconformity is a

major break, separating the Unayzah

from the overlying Khuff Formation. The

sediments at the base of the Khuff

Formation are marine and marginal

marine shales/marls. These grade up

into dark grey shale, dolomite, limestone

and anhydrite deposits.

By August 1993, more than 40 of the

wells drilled along the Hawtah trend had

been cored, and over 50 had been

imaged using either Fullbore Formation

MicroImager (FMI*) or Formation

MicroScanner (FMS). In the early stages

of development drilling, poor hole condi-

tions (including large washouts) limited

the effectiveness of borehole images.

Modified drilling practices have

improved borehole conditions in the

loosely-consolidated layers, greatly

improving the quality of results from all

pad contact logging tools. Borehole

images taken from previously washed-

out sections have revealed planar

tabular sandstone beds which may be

more than 25 ft thick, characterized by

dips which increase upwards to values

in the range 30° to 33°.

When all of the evidence is brought

together it becomes clear that there are

preserved aeolian sandbodies and a sig-

nificant volume of re-worked aeolian

sands within the adjacent fluvial facies

which comprise the Permian Unayzah

Formation. The presence of a significant

aeolian component is being integrated

into the existing 3D geological model and

seems certain to bring some fundamental

changes to the reservoir simulation.

Fig. 3.22: Electron

microscopy reveals

the ‘frosted’ or

‘pock-marked’

surface of this sand

grain, which

indicates a high-

energy aeolian

environment. The

surface textures of

modern sand grains

are a clear

indicator of

environment, but

ancient grains,

which make up

sandstone

reservoirs, must be

interpreted with

greater caution

since diagenetic

(chemical and

pressure) effects

can alter their

appearance.

Fig. 3.21: The conchoidal (curved and ridged)

fracture shown here is typical of glacial

deposits. Detailed mineralogical and textural

examination of sandstones can reveal the

environment of deposition. This helps the

geoscientist to assess the probability of finding

reservoir-grade sands and the likely geometry

of any that are encountered.

Fig. 3.20: Grain

rounding increases

as a sediment is

transported or ‘re-

worked’ from one

deposit to another.

The spherical sand

grains in this rock

have been subjected

to a high degree of

transport or re-

working. Grains

from river, beach or

glacial environments

are generally more

angular.

50 Middle East Well Evaluation Review

Fig. 3.23: MASS MIGRATION

Transverse dune migration produces

a distinctive facies of large aeolian

crossbeds.

Fig. 3.24: The inter-dune beds are characterized by lower porosity than

the dune sandstones. These thin layers, which will act as barriers to

vertical flow, can not be clearly identified using a dipmeter. Only

borehole imaging can provide details of distribution and thickness for

these problem beds.

030 0 10 20 30

Cross section

Wel

l bor

e10

0ft

200f

t

PorosityDipmeter

(dip magnitude)

Wind path

Wind path

Dune migration

Any way the wind blows

Aeolian sediments are very different

from those deposited by fluvial systems.

In arid and semi-arid climates, sedimen-

tary grains are weathered from existing

rock masses and transferred in seasonal

streams along wadis. Once these

ephemeral streams have dried, the

sands, silts and muds are influenced by

local or regional winds; the grains being

size-sorted and rounded as the wind

transports and deposits them.

These aeolian sediments often form

very extensive sheets of dunes (figure

3.23) and so produce an overall reser-

voir geometry which is easier to predict

than those encountered in fluvial

systems. The large cross-beds of a

typical aeolian deposit can be easily

detected by dipmeter surveys (figure

3.24). However, aeolian sands are

complex, having significant small scale

permeability and porosity variations

which subdivide them into numerous

reservoir compartments. The thin inter-

dune sabkha (coastal salt flat) facies

which separate the dune sandstones

contain evaporites and muds which are

important barriers to fluid flow.

Traditional dip measurement tech-

niques, such as those made using the

HDT dipmeter, can identify the major set

boundaries in a sandstone but will not

resolve the individual laminae within a

set (figure 3.25). Electrical imaging

imposes no constraint on the size of

crossbeds which can be detected.

A. setthickness

20˚10˚

xs

SS - massive

Shale

SS - crossbed set

Lamina

Wellborediameter

Fig. 3.25: The HDT dipmeter will only identify major ‘sets’ of crossbeds.

Borehole imagery imposes no constraint on the size of crossbed which

can be detected. Thin laminations within a set can be recorded.

R. Nurmi (1985) Eolian Sandstone Reservoirs: Bedding

Facies and Production. SPE Paper 14172.

10 acre well spacing

2640ft

(b)

51Number 17, 1996.

Fig. 3.26: In aeolian

sandstones lateral

permeability variations

(a) effectively divide the

reservoir into a series of

discrete compartments.

Attempts to maximize

production will rely on

intersecting and draining

as many of these

compartments as

possible. There are

several models for

estimating compartment

geometry in sandstone

reservoirs. In this

example (b), average

crossbed thickness is 20 ft

and the estimated length

is 200 x 20 ft, while width

is 100 x 20 ft.

0

Top view

Cross section

150 20 0g.r. porosityMax.

permeability Min.permeability

Fig. 3.27: Cambro-Ordovician Haima Group in

the Eastern Flank oilfields of Oman.

HUQF

MahwisFormation('00s m)

AminFormation

('0s - '00s m)

HaradhFormation

('00s - '000s m)

KarimFormation

(0 - 600 m+)

Low

er H

aim

a G

roup

Upp

er H

aim

a G

roup

GhudunFormation(0 - '0s m)

Qibit Fn.

Options in Oman

The dominantly aeolian Amin Formation

(part of the Haima Group) in Oman pro-

vides excellent examples of high-angle,

wind-ripple cross-stratification in clay-

free, high permeability sandstones. These

excellent reservoir properties may lead

some geoscientists to dismiss the need

for detailed characterization in this type

of reservoir. However, permeability

anisotropy plays a major role in oil and

gas production from similar Middle East

reservoirs.

Horizontal permeability anisotropy

(figure 3.26) is due to grain size varia-

tions within foresets where the minimum

values are aligned parallel to the palaeo-

wind direction.

Vertical permeability variations are

due to the different types of stratification

found at various levels in an aeolian

sequence. These variations include the

presence of inter-dune deposits and thin

fluvial layers. Detailed modelling of these

variations has not been carried out, but

would be essential before any attempt

was made to enhance oil recovery from

Haima reservoirs such as the Nimr Field.

Differences in foreset laminae thickness

and the variable geometry of inter-dune

sediments in the Amin Formation can be

classified using the FMS tool. In Nimr

Field, the Amin Formation has become

an important target for horizontal drilling

and the need to quantify vertical perme-

ability variation is crucial for the assess-

ment of well productivity.

In the Haradh Formation (figure 3.27)

sediment accumulations are generally

very thick. The Amal Eastern High Field,

for example, has an oil column more

than 250 m thick. Given these large inter-

vals, it is simply not economic to core

complete stratigraphic sections in each

well. The decimetre-scale trough cross-

stratified sandstones which make up the

Haradh Formation, are interpreted as

braided stream deposits. The sediments

of this formation are generally very sand-

rich (94% reservoir sand in the Amal

Eastern High Field) but minor shale

intervals have a disproportionate influ-

ence on fluid flow. The sandstones are

interrupted by mudflake conglomerate,

patches of calcite cement and continu-

ous thin shale layers. These features

control effective vertical permeability - a

vital parameter when Enhanced Oil

Recovery (EOR) is being contemplated.

The carbonate cemented horizons and

shale layers are impermeable and will

control, for example, the rise of steam in a

reservoir undergoing thermal EOR

schemes. Unfortunately, most of these

features are too small to be investigated

using conventional logging techniques.

The FMS, however, can provide some

vital information. Conventional logs offer

essentially ‘one dimensional’ measure-

ments with a resolution of about 25 cm.

The FMS, in contrast, provides 3D infor-

mation on continuous and dis-continuous

mudstones, pervasive and non-pervasive

carbonate sediments at a significantly

higher vertical resolution. ‘Static normal-

ization’ processing can help to highlight

resistivity contrasts (i.e. those due to

grain size, shaliness and oil saturation)

and so indicate reservoir quality.

(a)

52 Middle East Well Evaluation Review

Fig. 3.28: Sandstone bodies are usually extremely variable and complex systems. They are not

simple, homogeneous collections of quartz grains and any reservoir model which treats them as

though they were is bound to run into trouble.

Fig. 3.29: Sediments

can slump or be

deformed by tectonic

effects. If these were

reservoir rocks, a

dipmeter survey in a

borehole passing

through the slumped

block would give dip

values completely

unrelated to original

bedding dip in the

formation.

Variable sandstones

Some people think of sandstones as a

homogeneous collection of quartz grains

more or less bound together by an

evenly developed and distributed

cement. In the rush to generate numbers

for porosity, permeability and overall

unit thickness, detailed sedimentary

structure and fabrics can be ignored.

Unfortunately, even the best reservoir

sandstones do not behave as neat,

homogeneous packages - cross-bedding,

fractures and small scale facies varia-

tions are ever present complications

(figure 3.28).

In both complex and apparently

simple sedimentary environments,

logging techniques must be used with

great care and results reviewed in the

light of all possible sedimentological

interpretations. For example, average

dips taken from a meandering, cross-

bedded channel sand are of little value if

taken in isolation from overall sandbody

geometry and palaeocurrent directions.

In the past, sedimentary models were

based on dipmeter readings from bore-

holes supplemented by readings from

outcrops where these were available.

The main problem with dipmeter results

is the tool’s lack of ‘selectivity’. The dip-

meter (unlike the geologist working at an

outcrop) does not discard dubious dips

from slumped or rotated blocks (figure

3.29). In an aeolian environment, where

a geologist would make sure that large

and small scale crossbeds were

recorded, the dipmeter only records the

largest crossbeds.

Dipmeters have been used to define

structural features in wells for more than

60 years. They developed from simple

origins to become the relatively

advanced dip assessment tools that are

used throughout the oil and gas industry.

However, dipmeter studies are a ‘black

box’ technique - the operator has virtu-

ally no control over the actual measure-

ment process. In dipmeter surveys the

dips are generally derived from com-

puter correlation of a small number of

resistivity curves. The presence and

structure of faults are assessed from the

geometry of dip profiles but can not be

confirmed by visual inspection. Results

from even the most sophisticated dipme-

ter tools must be interpreted carefully.

In complicated structures, particularly

those with very high dips, dipmeters

provide only a fraction of the high-

quality information which is available

from imaging techniques.

Modern borehole imaging tools such

as the FMS or FMI tool have greatly

improved our understanding of borehole

geology, and allow the geologist to select

borehole dips from a computer screen as

though selecting them from an outcrop.

This has made imaging techniques

invaluable when drilling in structurally

complex regions.

However, this is only part of the

story. Once the dips have been selected

a whole range of modelling processes

are set in motion. Sedimentary dips are

the raw material of depositional analysis.

Dip values must be combined with data

on sediment thickness and character to

provide a realistic reservoir model

which can be used for other purposes,

such as simulation studies.

Original bedding orientation

Slumped and rotated block

53Number 17, 1996.

Borehole images from a Palaeozoic to

Lower Jurassic fluvial sequence in

Egypt’s Western Desert (figure 3.30)

allowed the measurement of 77 cross-

beds over a vertical interval of 120 ft. The

crossbed distribution shows a range of

azimuths in excess of 180°. This wide

scatter led to the conclusion that there

was more than one ‘family’ of crossbeds.

The scattered values were interpreted as

being the result of changing bedform

alignment along a shifting channel axis.

Attempts were made to model this

data. The model contained three key

parameters;

• channel sinuosity;

• channel migration angle, and

• bedform curvature.

The migration angle of the bedforms

was taken as zero (since it would be

both clockwise and anti-clockwise

depending on its location in the

channel). The bedform migration factor

is implicit in the channel sinuosity

(which represents the flow lines at the

base of the channel). Systematic com-

90˚

0˚

B

A 2b

d

b1

270˚

180˚

γE=d/b1

Elliptical model

B

B

A

A

WD

α

γ

λ

Plane view

Section

S=α/λ

D1 D3...I1 I2D2

Sinusoidal model

00

0.1

60 120 180 240 300 360

Observed

Modelled

Azimuth

Fre

quen

cy

BEDDING BY NUMBERS

Fig. 3.31: Two bedform crestline models -

elliptical (above) and sinusoidal (below)

have been developed in an attempt to

improve the geoscientist’s understanding of

crossbed directions and distributions and to

provide a simple mathematical description of

the sediments.

Fig. 3.30: Electrical imagery showing

crossbeds in a Palaeozoic to Lower Jurassic

fluvial sandstone from Egypt’s Western

Desert. Bedform models require a large

number of accurate bedding measurements -

borehole imagery can provide this

information quickly and efficiently.

Fig. 3.32: crossbed data from a fluvial sandstone in Egypt’s Western Desert. The graph shows 77

observations (grey bars) and best fit obtained for a model having elliptical bedform crestline with

E=1.0, channel sinuosity S = 0.5 and channel migration γ = 5° (red line).

putational fits were carried out for 350

combined models. The best result was

obtained using semi-circular bedforms in

river channels with a sinuosity of 0.5 and

a slight, oblique migration of 5° to

account for the asymmetry. Mean

channel flow was towards the north-west

(from the African Craton towards the

modern Mediterranean Sea). The mod-

elling results suggest that these bedforms

were deposited in a wide, braided river

system with fairly sinuous channels in

which crescentic (or possibly lunate)

megaripples were formed.

crossbed data distributions for unidi-

rectional bedforms are usually obtained

by direct measurement from outcrops or

wellbores. However, these distributions

can be simulated using simple geometric

models. Numerical and analytical

approaches have been used to predict

azimuth distributions as a function of the

shape of the bedform crest line and

angle of migration (figure 3.31).

If a fluvial channel is described by a

sinusoid and dunes by semi-elliptical

crescents, the resulting crossbed

azimuth distribution g(α’) - over a suffi-

ciently large area - is the convolution of

the channel azimuth distribution f (α)

with the bedform azimuth distribution

h (α) in the form:

This is highly dependent on the

choice of convolution operator, f (ω)

which represents channel sinuosity.

crossbed azimuth distributions from

the field are generally assigned to inter-

vals which are too wide and may be too

noisy to allow stable Fourier transforms

over a wide range. Instead of this decon-

volution procedure, therefore, some

experts have used an ‘iterative forward

modelling’ process to model combinations

of bedform and channel azimuth scatters.

In the data set from the Egyptian

fluvial sandstone it was possible to

combine bedform curvature with

channel sinuosity to model the

observed crossbed scatter, thereby pro-

viding a simple simulation of hierarchi-

cal bedforms (figure 3.32).

g(α’) = f (α) h (α— α’)dα0

2π

S. Luthi, J.R. Banavar and U. Bayer (1989) Models to

interpret bedform geometries from crossbed data. Jour-

nal of Geology, (98) pp. 171-187.

54 Middle East Well Evaluation Review

FMSimages

Cor

e pi

ctur

e

Bed

bou

ndar

ies

Lith

olog

y

Grain size and bed boundary

Cla

y an

d si

lt Sand

Fin

e

Med

ium

Coa

rse

Gra

vel

8000

1600

0

4000

2000

1000500

250

12562

5 4 3 2 1 0 -1 -2 -3 -4

3140cm

Fig. 3.34: The detail

possible with the

FMS tool allows the

geoscientist to

establish bed

thickness and assess

lithology from core-

quality images.

From: J-C. Trouiller,

J-P. Delhomme, S.

Carlin and H.

Anxionnaz (1989)

Thin-bed reservoir

analysis from

borehole electrical

images. SPE Paper

19578.

Fig. 3.33: Sandstone bedding varies

through a wide range of thicknesses from very

fine laminae - which may be just a few millimetres

thick - to layers which are more than a metre thick. No

single tool can provide a complete characterization for this

range of thicknesses, that is why it is important to select the right

technique and the right tools for the job.

Standard Induction

Laterlog/Phasor Induction

compensated Neutron

logging tool

Gamma Ray/ERL Neutron

Line Density/Array Sonic

MSFL/EPT Tools

ERL LDT

Stratigraphic High Resolution

Dipmeter Tool

Formation MicroScanner

Thin section of pores, CMR

Very thick

Thick

Medium

ThinVery thin

Lam

inae

Bed

s

Roc

k la

yerin

g

0.10.3

1.0

3.0

10

30

100

Thi

ckne

ss c

m (

log

scal

e)

Thin and thinner

Sandstone layering can be on any scale

from many metres to a few millimetres

(figure 3.33). Complete characterization

must take all of these scales into

account. In turbidite sequences, layers a

few millimetres thick can be identified

from borehole imagery with core data

being used as a ‘quality control’ in some

intervals to ensure that thicknesses are

being recorded accurately.

Displaying core photographs and FMS

images side-by-side usually indicates that

the bedding characteristics are similar in

both images (figure 3.34). Thin bed

sequences, however, present a special

challenge to the electrical imager.

The problem with layers around 1 cm

thick is that they are below the resolu-

tion of standard logging tools. The

Stratigraphic High Resolution Dipmeter

Tool (SHDT) can identify beds down to

5 cm thick and simply classify them as

sands or shales. However, the SHDT

could not evaluate bedding continuity -

thin lenses could easily be mis-inter-

preted as continuous beds.

By taking more readings, the new gen-

eration of electrical imaging tools can

identify layers which are just 1 cm thick,

and the geometry of bed boundaries can

be determined much more accurately.

Lenses and pinch-out beds can often be

recognized in images when no other tool

could indicate their presence.

Cores versus image

Plotting thicknesses obtained from core

with those from FMS images show very

similar results (figure 3.35). However,

some data points plot outside the general

trend and these anomalies can be

explained as either; over-estimation of

FMS sand thickness or under-estimation

of core sand thickness.

Most of the discrepancies in beds more

than 5 cm thick are due to incomplete

core recovery (figure 3.36). By depth

matching core photographs with FMS

results it is apparent that pieces of core

have been lost, so the thickness measure-

ments from the cores were wrong.

One data point (number 3) calls for a

different explanation. The section shows

an irregular shale bed surrounded by a

faulted sand unit. Depending on the mea-

surement point chosen on the core,

thickness can vary by up to 5 cm and

this explains the differences.

In beds thicker than 5 cm most of the

discrepancies can be identified as core

recovery or core description problems.

55Number 17, 1996.

0 32 64 96 128 160

032

6496

128

160

Core thickness (cm)

FM

S th

ickn

ess

(cm

)

0 1 2 3 4 5 6 7 8 9 10

01

23

45

67

89

10

Core thickness (cm)

FM

S th

ickn

ess

(cm

)

5

1

2

34

4

3

21

Fig. 3.35: The discrepancies

between sandstone layer

thicknesses measured from the

Formation MicroScanner and

those measured direct from core

are normally the result of poor

core description or mis-

interpretation. Incomplete core

recovery is a significant problem

in estimating reservoir thickness.

Combining FMS and core data

allows the log analyst to arrive at

a true reservoir thickness even in

extremely friable rocks. From: J-C.

Trouiller, J-P. Delhomme, S. Carlin

and H. Anxionnaz (1989) Thin-

bed reservoir analysis from

borehole electrical images. SPE

Paper 19578.

Beds which are less than 5 cm thick

show a greater discrepancy between

core and electrical thickness estimates.

Some points indicate over-estimation of

sand thicknesses from the electrical

image data. These discrepancies are due

to uncertainties in core measurement

and in image measurement.

• Point 1 - error in core description, small

intervals of sand were neglected and the

whole interval treated as a shale bed.

• Point 2 - (FMS indicated 7 cm, core

data estimated 5 cm); this is a 7cm thick

sand bed, with the lower 5 cm partially

cemented. In the core description only

the cemented part has been counted as

sand, the other 2 cm of fine sand has

been lumped with the bounding shale.

• Points 3 and 4 - these examples indi-

cate where the electrical technique has

failed to identify thin shale layers

(around 1cm thick) that occur in the

thicker sands.

Fig. 3.36: One major problem with core analysis

is missing sections. These sections can be

evaluated by borehole imagery. Imaging

techniques can also overcome orientation

problems due to core rotation during recovery.

This comparison shows that there are

cases where sand and shale thicknesses

can be mis-identified and mis-interpreted

by both techniques.

Two possible explanations for the

FMS response have been examined

using numerical modelling methods:

• broken mudcake and

• low contrast invasion.

In extremely thin beds no method can

guarantee perfect bedding description.

However, if operators are aware of

potential problems and interpret impor-

tant intervals carefully, with a combina-

tion of core and imaging, high-quality

results should be possible every time.

Egypt's thin beds

In Egypt’s Western Desert, the Bahariya

Formation has an unenviable reputation

for complexity. Generally described as a

complex, thin-bedded sequence, the

Bahariya has been interpreted in two fun-

damentally different ways - as a continen-

tal braided stream deposit and as a deep

marine sequence. The well-laminated

sands which comprise the formation are

difficult to interpret using conventional

well logs, a fact which contributes to the

uncertainty surrounding possible reser-

voir models.

Recent work suggests that the

Bahariya Formation developed in a tidal

flat environment with cross-cutting

channel sands. The key to this new inter-

pretation was borehole imagery. The

high-resolution which is possible using

tools such as the FMI tool has proved

essential in the development of Bahariya

reservoir models. The lack of well

defined cross-bedding features in some

intervals is now seen to be the result of

extensive bioturbation (burrowing) of

the type commonly found in low energy

tidal environments. Where good cross-

beds are developed the FMI images

allow rapid and accurate calculation of

bedding dip without the problems of

partial core recovery or core rotation.

The large scale channels, character-

ized by high-energy deposits, are well

developed in the southern wells where

sedimentation was dominated by fluvial

processes. In the north, tidal affects are

more important. The channels can be

modelled using isopach maps for the

sand units and linked thanks to the direc-

tional data derived from the FMI images.

56 Middle East Well Evaluation Review

Borehole imagery began during the late

1960s with the introduction of the Bore-

hole Televiewer (BHTV) tool (figure

3.38). Assessment by the oil and gas

industry suggested that the tool was inad-

equate for day-to-day application, but it

sparked an interest in borehole imagery.

Research groups in a number of oil com-

panies built their own prototypes.

Resistivity imagery developed

because even the most advanced dipme-

ter tools could not provide many of the

geological, petrophysical and reservoir

features necessary for reservoir evalua-

tion. This proved the need for a tool that

could ‘see’ the whole borehole. A tool

using an array of resistivity buttons - not

the horizontal scanning concept used by

the BHTV tool - was developed.

During field tests where fractures

were expected, BHTV image surveys

were run to assess the strengths and limi-

tations of resistivity as a tool for borehole

imagery. The tests confirmed the superi-

ority of the resistivity technique.

Since then, resistivity tools (such as

the Azimuthal Resistivity Imager or ARI*

tool) have been developed and have

proved very useful in horizontal wells.

Acoustic imaging methods were investi-

gated and the new UltraSonic Imager

(USI*) tool developed for use in cased-

holes, for damage and corrosion assess-

ment. When oil-base muds became more

common, the tool was modified to

produce the Ultrasonic Borehole Imager

(UBI*) tool.

WHO WANTS TO SEE ROCKS ON TV?

Fig. 3.38: Comparison of standard BHTV and electrical imagery. Electrical

techniques allow the operator to obtain good structural dip profiles even

in wells drilled with oil-base muds.

Making images work

For more than a decade experts have

tried to make the data in borehole images

more accessible. Various computer work-

stations have been developed to aid inter-

pretation. In 1984, the Dipmeter Advisor

was introduced. The ultimate aim was to

provide geologists with an expert system

for interpretation of dipmeter and open

hole log data. These tools could pick dips

and other features automatically from the

borehole images. The interpreter could

then examine the selected data to remove

inappropriate picks or to add anything

the system may have missed. This

approach helped to reduce the data selec-

tion burden on interpreters, leaving them

more time to analyse results.

In addition, the images can be manipu-

lated, using a process referred to as

‘interactive thresholding’ to reveal more

information about a sequence. For

example, images can be processed to

reveal only fractures (figure 3.37), or

vuggy pores in carbonate sequences or

to compute sand and shale content.

The appearance of new logging tools,

prompted a continuous upgrading of the

original system and led to the develop-

ment of the Formation Image Examiner

Workstation. This sophisticated geologi-

cal interpretation tool handles dipmeter,

FMS, BHTV and open hole log data.

Fig. 3.37: Computer manipulation of borehole

images allows the operator to enhance images -

identifying the areas and features of particular

interest. In this case, an FMS is modified to

show only the fractures in the sequence.

57Number 17, 1996.

Fig. 3.39: SEEING THE LIGHT?: Geoscientists want to ‘see’ sedimentary features and structures in the borehole. Resistivity-based borehole imaging tools

such as the FMI and FMS developed out of the BHTV tool that was introduced in the 1960s. Acoustic techniques have also proved invaluable - the USI

tool can be used in wells drilled using oil-based mud - a situation where the resistivity tools are ‘blind’. From: A. Hayman, P. Parent, P. Cheung and

P. Verges, Improved borehole imaging by ultrasonics. SPE Paper 28440, 1994.

Borehole images are essentially maps of

resistivity or acoustic variations within a

sequence. Resistivity varies with rock

geochemistry and formation fluids.

Saline formation waters and rock types

like shale are low resistivity layers while

sandstones - particularly those filled with

oil and gas - produce higher values.

The ability to differentiate clean sands

from shaly sands or shales gives a

clearer indication of pay thickness

(which can be particularly difficult in

thin-bedded reservoirs) and allows the

operator to compute a sand/shale ratio.

Other sedimentary features - graded

bedding, channel orientation and

palaeocurrent direction can also be iden-

tified from these resistivity variations.

Carbonate rocks can also be charac-

terized using tools like the FMS. Vuggy,

intergranular and mouldic porosity can

be imaged and the basic rock type

(grainstone, boundstone or carbonate

mudstone) determined quickly and

accurately.

Mastering magnetic methods

The Combinable Magnetic Resonance

(CMR*) tool has numerous oilfield appli-

cations. By manipulating hydrogen

protons in fluids, the tool gathers infor-

mation to assess parameters such as

porosity, permeability and free-fluid

index.

Nuclear magnetic resonance logging

has finally arrived. The wealth of petro-

physical data locked up in the NMR

relaxation times help to provide the

most important fact about a well - what

fluid it will flow, even in thinly-bedded or

shaly sand formations.

The future

Modern electrical imagery has revealed

the details of geology in the borehole

much more clearly than any dipmeter

technique (figure 3.39), and much more

cost-effectively than core. In future,

every new well in a field can be logged

to optimize the reservoir model, improve

the accuracy of simulations and so

increase total oil and gas recovery.