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42 Oilfield Review

New Dimensions in LandSeismic Technology

Malik Ait-MessaoudMohamed-Zerrouk BoulegrounAziza GribiRachid KasmiMahieddine TouamiSonatrach

Algiers, Algeria

Boff AndersonPeter Van BaarenWesternGeco

Dubai, UAE

Adel El-Emam

Ghassan RachedKuwait Oil CompanyKuwait

Andreas LaakeStephen PickeringWesternGeco

Gatwick, England

Nick MoldoveanuWesternGeco

Houston, Texas, USA

Ali zbek

Cambridge, England

For help in preparation of this article, thanks to Mark Daly,Jean-Michel Pascal Gehenn, Will Grace, Dominic Lowdenand Tony McGlue, Gatwick, England; Mark Egan andNorm Pedersen, Houston, Texas; Zied Ben Hamad, Lagos,Nigeria; Mahmoud Korba, Algiers, Algeria; and AndrewSmart, Kuwait.

DSI (Dipole Shear Sonic Imager), Q-Borehole andVSI (Versatile Seismic Imager) are marks of Schlumberger.Omega2, Q-Land, Q-Marine, VIVID and Well-Driven Seismicare marks of WesternGeco.

Advanced seismic acquisition and processing technology has come onshore.

A high-fidelity, high-resolution, integrated single-sensor system is now available

for use on land. This technology marks a significant step forward for exploration,

field development and production.

Seismic technology has achieved amazing featsin exploration and production activities in the

past few decades. The advance to three-

dimensional (3D) seismic acquisition and

imaging of the subsurface, introduced in the

1980s, was perhaps the most important step.1

Another was development of four-dimensional

(4D), or time-lapse, seismic data to monitor how

reservoir properties such as fluids, temperature

and pressure change during the productive life of

a field.2 Introduction of multicomponent seismic

data acquisition with the recording of shear wave

signals, in addition to compressional wave data,

provided a tool for rock characterization andidentification of pore-fluid types.3

With the worlds ever-growing demand for oil

and gas, the emphasis in the oil and gas industry

has shifted to exploring deeper, more complex

reservoirs and to enhancing production from

existing assets. Field life can be extended by

delineating bypassed oil and gas and by placing

production and injection wells optimally. The

proactive monitoring of reservoir fluid

behaviorsaturation and pressureover time,

allows remedial actions to be implemented

before production is affected.

For all these applications, the geophysicist,

geologist and reservoir engineer require reliable

and repeatable data of exceptional resolution

that can be fine-tuned to a specific reservoir

objective. Exceptional data resolution means

having data with increased frequency bandwidth

and low coherent and noncoherent noise, while

preserving signal fidelity.4

For decades, the battle between signal andnoise has driven the seismic industry to seek

ways to suppress noise and to enhance signal.

The signal is a true representation of the actual

reflection that corresponds to changes in rock

characteristics such as lithology, porosity and

subsurface structure. Both noise, which can be

coherent or noncoherent, and absorption of higher

frequencies by the Earth obscure the true nature

of the signal.

This article examines a new, integrated single-

sensor acquisition and processing system that

delivers measurements that were previously

unobtainable with conventional recording ofseismic data. Examples from producing assets in

Kuwait and Algeria illustrate the superior quality

of these data in terms of signal fidelity and

frequency bandwidth in comparison with data

acquired with conventional methods.

Challenges in Conventional Land Acquisition

Single-sensor seismic recording has been

available since the early days of seismic

exploration. The principle is simple. An impulse

source such as dynamite or a controlled-

frequency source such as a vibrating plate on a

truck sends acoustic energy into the Earth.5 This

energy propagates in many different directions.

Downward traveling energy reflects and refracts

when it encounters boundaries between two

materials with different acoustic properties.

Sensors or geophones placed on the surface

measure the reflected acoustic energy,

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Autumn 2005 43

converting it into an electrical signal that is

displayed as a seismic trace.6

A complication in land acquisition is that,unlike marine data, a seismic line is rarely shot

in a straight line because of the presence of

natural and man-made obstructions such as

lakes, buildings and roads. More importantly,

variation in ground elevation causes sound waves

to reach the recording geophones with different

traveltimes. The Earths near-surface layer may

also vary greatly in composition, from softalluvial sediments to hard rocks. This means that

the velocity of sound waves transmitted through

this surface layer may be highly variable. Static

correctionsa bulk time shift applied to a

seismic traceare typically used in seismic

processing to compensate for these differences

in the elevations of sources and receivers and

near-surface velocity variations.7

Another major problem in land acquisition i

that land sources typically generate energy tha

travels horizontally near the surface, also known

as airwaves and ground-roll noise. Conventiona

sensor arrays comprising strings of geophones

1. Beckett C, Brooks T, Parker G, Bjoroy R, Pajot D, Taylor P,Deitz D, Flaten T, Jaarvik LJ, Jack I, Nunn K, Strudley Aand Walker R: Reducing 3D Seismic Turnaround,Oilfield Review7, no. 1 (January 1995): 2337.

2. Aronsen HA, Osdal B, Dahl T, Eiken O, Goto R,Khazanehdari J, Pickering S and Smith P: Time Will Tell:New Insights from Time-Lapse Seismic Data, OilfieldReview 16, no. 2 (Summer 2004): 615.

3. Barkved O, Bartman B, Compani B, Gaiser J, Van Dok R,Johns T, Kristiansen P, Probert T and Thompson M:The Many Facets of Multicomponent Seismic Data,Oilfield Review16, no. 2 (Summer 2004): 4256.

4. Coherent noise is unwanted seismic energy that showsconsistent phase from one seismic trace to another. Thismay consist of waves that travel through the air at verylow velocities such as airwaves or air blast, and groundroll that travels through the top of the surface layer, alsoknown as the weathering layer. The energy trapped

HardDisk/Processing

Conventional Data Q-Land Data

FieldTape

DigitalGroupForming

a common-midpoint (CMP) gather. The number of tracessummed or stacked is called a fold. For instance, in24-fold data, every stacked trace represents the averageof 24 traces. In the case of dipping beds, there is nocommon depth point shared by multiple sources andreceivers, so dip-moveout (DMO) processing becomesnecessary to reduce smearing or inappropriate mixing of

data. For more on seismic recording: Farmer P, Gray S,Whitmore D, Hodgkiss G, Pieprzak A, Ratcliff D andWhitcombe D: Structural Imaging: Toward a SharperSubsurface View, Oilfield Review5, no. 1 (January1993): 2841.

Ashton CP, Bacon B, Mann A, Moldoveanu N,Dplant C, Ireson D, Sinclair T and Redekop G:3D Seismic Survey Design, Oilfield Review6, no. 2(April 1994): 1932.

7. Ongkiehong L and Askin HJ: Towards the UniversalSeismic Acquisition Technique, First Break6, no. 2(1988): 4663.

within a layer, also known as multiples, is another formof coherent energy. Noncoherent energy is typicallynonseismic-generated noise, such as noise from wind,moving vehicles, overhead power line or high-voltagepickup, gas flares and water injection plants.

5. A vibrator source sends a controlled-frequency sweepinto the Earth. The recorded data are then convolvedwith the original sweep to produce a usable signal.

6. Each trace consists of one recording corresponding to asingle source-receiver pair. In practice, traces from onesource are simultaneously recorded at several receivers.Then, sources and receivers are moved along the surveyline and another set of recordings is made. When aseismic wave travels from a source to a reflector andthen back to the receiver, the elapsed time is the two-way traveltime. The common depth point (CDP) is thehalfway point of the path; it is situated vertically belowthe common midpoint. Sorting of traces by collectingtraces that have the same subsurface midpoint is called

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are based on the assumption that the upward

traveling energy, or the reflected wave, arrives at

the array essentially vertically and simultaneously,

while the surface-wave noise arrives mainly

horizontally and sequentially. To cancel this

source-generated noise, spatially distributed

receiver groupsarraysare summed.8 Ideally,

this process results in an attenuation of the noise

and an improvement of the signal.

However, there are problems associated with

conventional arrays. In reality, the sensor array is

often not located on flat and homogeneous

ground, so local changes in elevation and surface

geology lead to fluctuations in the signal arrival

time (left). These fluctuations are called intra-

array perturbations. The hard-wired sensor array

instantaneously sums all traces, and in the case

of intra-array perturbations, this would lead to a

partial cancellation of signal. The resulting

output trace would then be at a lower frequency

than each of the input signals, and the amplitude

would be smaller than the sum of the individual

amplitudes, a phenomenon known as thearray effect.

Aliasing is a well-known problem that arises

when the sampling rate of a signal is inadequate

to capture the higher frequencies in the signal.9

Not only is the information contained in higher

frequencies lost, it is incorrectly represented

(below left). Aliasing is a consideration for

spatial sampling too, not just temporal sampling.

Ground roll typically contains many different

wavelengthsrelated to the distance between

successive peaks in a waveformthat are

shorter than the typical group interval or the

distance between receiver array centers ofgravity in a conventional survey. Due to

undersampling of ground-roll energy, this energy

is aliased and passed on to the signal bandwidth,

causing ambiguity between signal and noise.

44 Oilfield Review

> Conventional acquisition onshore. Seismic energy recorded at the receiversarrives at different times because of elevation differences and near-surfacevelocity variations (top). In conventional acquisition, strings of geophoneshard-wired together average the individual sensor measurements and deliverone output trace, whose location is denoted by the center of gravity of thearray, indicated by the red dot (bottom). The resulting output trace has agenerally lower frequency than each of the input signals, and the amplitude issmaller than the sum of the individual amplitudes, a phenomenon known asthe array effect.

Receiver array length: 45.76 m

7

m

2.08 m 4.16 m

Seismicsource Receiver array

Geophone

> Aliasing effect. Sampling at a frequency lower than the highest frequencypresent in the signal (red curve) results in insufficient samples to capture allthe peaks and troughs present in the data. Not only will inadequate samplingmiss the information on higher frequencies but the signal will be incorrectlydefined (blue curve).

t

samplingrate

Undersampled seismic signalProperly sampled seismic signal

8. Newman P and Mahoney JT: PatternsWith a Pinch ofSalt, Geophysical Prospecting21, no. 2 (1973): 197219.

9. Aliasing is the ambiguity that arises because ofinsufficient sampling. It occurs when the signal issampled less than twice the cycle. The highestfrequency defined by a sampling interval is termed theNyquist frequency and is equal to inverse of 2t, wheret is the sampling interval. Frequencies higher than theNyquist frequency will be folded back or wrappedback. This condition can be observed in video or motion

pictures: the spoke wheels on horse-drawn wagonssometimes appear to be turning backward instead offorward. Aliasing can be avoided by a finer spatialsampling that is at least twice the Nyquist frequency ofthe waveform.

10. El-Emam A, Moore I and Shabrawi A: Interbed MultiplePrediction and Attenuation: Case History from Kuwait,presented at the 2005 SEG International Exposition and75th Annual Meeting, Houston, (November 611, 2005).

11. Roden R and Latimer R: An IntroductionRockGeophysics/AVO,The Leading Edge22, no. 10(October 2003): 987.

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Autumn 2005 45

Tests of varying array lengths have shown the

degradation in signal quality caused by

increasing the array size (right). For longer

offset receiver arrays, the arrival time of the

signal can vary significantly at either end of the

array, smearing the higher frequencies when

summed within the group. Therefore, just as

adequate temporal sampling of the recorded

trace is needed to successfully record a given

frequency, a sufficiently small group interval is

required to record a particular spatial frequency.

A problem common to all seismic acquisition

is energy trapped between subsurface layers,

known as interbed multiples, caused by a strong

velocity contrast between layers. This occurs

when the energy from the source reflects more

than once in its travel path. Interbed multiples

are analogous to a bouncing ball trapped between

two layers, which continues to bounce until it

loses its energy. Borehole seismic data, which are

acquired when sources are placed on the surface

and receivers are anchored in a borehole, help

identify the interfaces that generate theseinterbed multiples. Recent developments in data-

driven methods and the use of vertical seismic

profile (VSP) data to guide surface-seismic

multiple attenuation, such as Interbed Multiple

Prediction (IMP), seem promising.10

The quality of the raw seismic dataset is

fundamental to achieving superior frequency

resolution and high signal-to-noise ratio.

Amplitude and phase preservation of the input

signals is critical in all facets of stratigraphic

interpretation, including prestack seismic

inversion, amplitude variation with offset (AVO)

and amplitude variation with angle (AVA)interpretation. An analysis of the variation in

reflection amplitudes with source-geophone

distance or offset gives some valuable insights

into reservoir properties such as lithology,

porosity and pore fluid.11

Because land data often exhibit poor signal-to

noise ratios arising from irregular geometries and

noise contamination, a fundamental change in

acquisition and processing methods was required.> Signal degradation with an increase in array size. A point-source, point-receiver test was carriedout with single sensors spaced 2 m [6.6 ft] apart and a single vibrator source. A 16-m [53-ft] arraywas formed by summing groups of nine consecutive geophones and assigning the summed signalto a channel placed in the center of gravity of the array (bottom). The group interval is the distance

between consecutive channels. Similarly, a 32-m [105-ft] array was formed by summing groups of17 consecutive geophones. By using 2-m sensor spacing, wave types were recorded without aliasing(top left). As the sensors were grouped into arrays of increasing length of 16 m ( top middle) and32 m (top right), first the airwave, then the ground roll and finally the first breaks became aliased,manifested as cross-banded signal areas in the shot domain. Aliasing also manifests as a wrap-aroundof the noise energy in the frequency-wavenumber domain, not shown here. (Data courtesy of Shell.)

0.0

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A Change in Acquisition Philosophy

In the early 1990s, WesternGeco began extensive

research on compressional wave (P-wave)

sensitivity that led to a fundamental change in

acquisition philosophy. Experiments conducted

on synthetic signals revealed the effects of

source and receiver statics, recording electronics

specifications, source phase distortion and

receiver sensitivity on P-waves (below).

Excluding coherent source-generated noise,

ambient noise and source frequency sweep, the

dominant effects on the signal-to-noise ratio are

due to perturbations that could not be corrected

for within an analog array. Factors such as source

and receiver statics, coupling of the geophone to

the ground, geophone position and tilt, source

positioning, and amplitude and phase distortion

in the sources were more important than

hardware changes in the geophone or the

recording system itself. A small error of 1 ms in

receiver statics results in the introduction of

-29 dB of noise relative to the signal. Such static

errors are commonly found within a conventionalanalog receiver group.

Knowledge gained from these experiments

was used to design and build the Q-Land single-

sensor land seismic system to reduce the effects

of these perturbations while addressing the issue

of coherent noise removal such as ground roll. A

receiver spacing that is half (or less) of the

ground-roll wavelength would be adequate to

sample ground-roll noise without aliasing. Just as

temporal aliasing arises from insufficient

sampling in time, a large receiver interval leads

to spatial aliasing.

The new Q-Land system digitizes each sensor

at the recording location (next page, top). To

achieve this fine spatial sampling, the recording

system requires a massive increase in the

number of live channels. A live channel means

that the receivers are connected to record

simultaneously. Compared with a typical high

channel-count conventional system, which may

have 4,000 to 5,000 channels that record live, the

new point-receiver acquisition system has 20,000

or more live channels. The Q-Land system is the

first to implement an integrated point-receiveracquisition and processing methodology.

The same concept is applicable to the seismic

sources. The source array can be replaced by

point sources. In addition, to prevent aliasing in

the common midpoint domain, the source

interval should be small, ideally equal to the

receiver interval. The new point-source, point-

receiver recording technique replaces the

conventional method of using sensor and source

arrays to attenuate noise and to improve signal-

to-noise ratio.12 Recording seismic data through

point receivers rather than analog receiver

arrays has several potential advantages,

including better static solutions, velocity

estimation, amplitude preservation, bandwidth

retention and noise attenuation.

This point-source, point-receiver methodology

increases data volume by more than an order of

magnitude. Advances in data transmission and

computing power have enabled the development

and deployment of this cost-effective, high

channel-count recording system.

A New Integrated Acquisitionand Processing System

The new Q-Land system is a 20,000 live-channel

seismic acquisition and processing technology.

The typical sampling rate for the system is 2 ms.

However, the Q-Land system can record with

30,000 live channels when the sample rate is

changed to 4 ms. Digital recording of the

incoming wavefield at densely spaced receiver

positions ensures that the recorded signal

and noise are properly sampled and are

therefore unaliased.

In Q-Land acquisition geometry, one source

line and one receiver line that are orthogonal toeach other form a cross-spread. These are then

repeated spatially within the acquisition area.

Each source-receiver pair generates a trace that

corresponds to a subsurface midpoint. If the

midpoints corresponding to all source-receiver

pairs are binned, with a bin size equal to half the

receiver by half the source interval, every bin will

be one midpoint corresponding to single-fold

coverage. Thus, the cross-spreads provide single-

fold subsets of the continuous wavefield, sampled

finely enough to prevent aliasing of the coherent

noise, through which a cross-spread volume is

generated (next page, bottom).

46 Oilfield Review

> P-wave sensitivity chart for land acquisition. Experiments were conducted on synthetic signals tounderstand the effect of perturbations such as source and receiver statics, recording electronics,source phase distortion, and receiver sensitivity. The chart shows that hardware changes in thereceiver or the recording system have low signal error, as compared with other factors that cause asignificantly higher signal error. The ability to correct for these higher order perturbations allows forthe preservation of signal fidelity and bandwidth within the seismic data.

Distortion

Gain tolerance

Synchronization

0 -10 -20 -30 -40 -50

Signal error in dB

Signal error, %, 95% confidence interval

Perturbation

-60 -70 -80 -90

100 31.6 10 3.16 1 0.32 0.1 0.03 0.01 0.003

-100

Harmonic distortion

Amplitude

Phase

Source position

Receiver statics

Source statics

Harmonic distortion

Geophone sensitivity

Natural frequency

Temperature

Coupling

Tilt

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System

Receiver

Source

Statics

12. Ongkiehong and Askin, reference 7.

13. Christie P, Nichols D, zbek A, Curtis T, Larsen L,Strudley A, Davis R and Svendsen M: Raising theStandards of Seismic Data Quality, Oilfield Review13,no. 2 (Summer 2001): 1631.

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Sophisticated algorithms are then applied in

a processing technique called digital group

forming (DGF). DGF comprises three main steps.

The first is correction to each geophone for intra-

array perturbations such as amplitude, elevation

differences and near-surface velocity variations.

After the geophone outputs are grouped, the

result is a signal with a frequency bandwidth

similar to that of the individual traces and an

amplitude almost equal to the sum of the

individual amplitudes. This step is similar to the

one applied in the Q-Marine single-sensor

marine seismic system.13

> A three-dimensional (3D) display of the cross-spread volume. A cross-spread configuration is achieved by deploying receivers along a line in onedirection and placing sources along an orthogonal line (right). Each source-receiver pair generates information from a subsurface point that, for a flatsurface, is located at the midpoint between source and receiver (gray area). In this example of cross-spread configuration, with receiver sampling at 5 m[16 ft] and source sampling at 20 m [66 ft], the subsurface coverage is single fold. A 3D view of the cross-spread volume shows that the ground-roll noiseis confined within a conical shape volume, making its removal or attenuation by 3D filters in the frequency-wavenumber domain more effective (left).

ReceiverlineSourcelin

e

Time

Sourceline

Receiver line

Area ofcommonmidpointcoverage

> The Q-Land acquisition and processing system. A line ofreceivers is laid out perpendicular to a line of sources andevery source point is recorded by every receiver point. Theexample shows 10 receiver lines that are 200 m [656 ft] apart,with 1,824 point receivers per receiver line that result in18,240 live receivers (top). In digital group forming using theOmega2 software processing system, the seismic traces fromindividual geophones have perturbation corrections made toeach geophone (bottom). Data-adaptive filters are thenapplied over a number of traces to suppress coherent noise.An output trace from a number of sensors can then be pro-duced at the desired spatial sampling.

Sou

rceline

Receiver line

Rec

eiverlines200ma

part

Sources

1,824 receivers per line

Sensors

Fieldacquisition

system

Digitalgroup forming

Digital signalsfrom individual

sensors

Hard disk/processing

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The second step applies data-adaptive filters

for noise suppression. Noise attenuation can

include, but is not limited to, coherent and

ambient-noise attenuation, high-voltage power

line pickup cancellation, and airwave and flare-

noise attenuation. There are different ways to

attenuate noise using digital filtering techniques.

However, the design of optimal 3D digital filters

is important to realize the potential of point-

receiver recording.

An ideal filter would pass all the desired

frequencies in the pass band with no distortion,

and completely reject all frequencies outside the

range of interest, called the stop band. The ideal

spatial anti-alias filter response would also be

azimuthally isotropic, that is the array response

would be the same for energy arriving from all

angles. There are two problems associated with

anti-alias filter performance for conventional

data acquisition: imperfect rejection of

azimuthally varying levels of noise in the stop

band and an imperfect flat response in the pass

band (below). The Q-Land technique of forming

an orthogonal acquisition geometry into cross-

spreads is well suited to the application of three-

dimensional anti-alias filters. A filtering

technique based on the APOCS method

alternating projections onto convex setsis an

effective approach that works optimally on cross-

spread geometry.14

48 Oilfield Review

14. A well-known mathematical technique, APOCS is aniterative technique that derives filter parameters toremove coherent noise. The algorithm, working in 3Dspace, switches constantly between sample domainwith time on one axis and x and y on the other twoaxesand frequency transform domainwithfrequency on one axis and wavenumber in x and y

directions, kx and ky, on the other two. Wavenumber isthe inverse of wavelength and represents the frequencyof the wave in space. For more on APOCS: zbek A,Hoteit L and Dumitru G: 3-D Filter Design on aHexagonal Grid for Point-Receiver Land Acquisition,EAGE Research Workshop, Advances in SeismicAcquisition Technology, Rhodes, Greece,September 2023, 2004.

Quigley J: An Integrated 3D Acquisition and ProcessingTechnique Using Point Sources and Point Receivers,Expanded Abstracts, 2004 SEG International Expositionand 74th Annual Meeting, Denver, (October 1015, 2004):1720.

17. A zero-offset VSP is acquired when a seismic sourceis placed on the surface close to the wellhead andreceivers are positioned at different depths in aborehole. In a walkaway VSP, an array of receiverscollects data for multiple source positions located alonga line that extends from the wellhead. For more on VSPand walkaway VSPs: Arroyo JL, Breton P, Dijkerman H,

Dingwall S, Guerra R, Hope R, Hornby B, Williams M,Jimenez RR, Lastennet T, Tulett J, Leaney S, Lim T,Menkiti H, Puech J-C, Tcherkashnev S, Burg TT andVerliac M: Superior Seismic Data from the Borehole,Oilfield Review15, no. 1 (Spring 2003): 223.

15. Shabrawi A, Smart A, Anderson B, Rached G andEl-Emam A: How Single-Sensor Seismic ImprovedImage of Kuwaits Minagish Field, First Break23, no. 2(February 2005): 6369.

16. The Q-Borehole system optimizes all aspects of boreholeseismic services, from job planning through dataacquisition, processing and interpretation. Well logs,VSP and surface-seismic data are combined to build aproperty model of vertical velocities, frequencyattenuation factors, anisotropy related to verticalvariations in interval velocities and the multipleswavefield. The model is then used for enhancedsurface-seismic processing and calibration in theWell-Driven Seismic process.

> Three-dimensional spatial anti-alias filter response. The problem of unwanted noise contaminating the signal bandwidth area is illustrated. The spatialanti-alias filter response displays amplitude on the vertical axis, and wavenumbers along the two horizontal axes, kx and ky, in x and y directions. The color

represents the magnitude in dB. An efficient filter would pass the signal that is at around k=0, and stop or reject any noise for all other directions for k 0.For a conventional 16-m receiver array, noise leaks into the signal from almost all azimuths ( left). In contrast, for point-receiver data, the anti-alias filterusing the APOCS filter design technique shows the effectiveness of the filter in rejecting noise ( right).

0

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The last step is spatial resampling of the

output data according to the desired group

interval. Analog arrays, once laid out in the field,

have almost no flexibility to adjust the output-

sampling interval, whereas with digital group

forming, any output sampling is possible down to

the granularity of the individual sensors.

While data from conventional arrays may

provide reasonable results for structural

interpretation, detailed reservoir analysis using

seismic inversion or AVO techniques is limited to

a narrow frequency band because of aliased

noise wrapping back in the frequency range of

interest (below right). With such reduced

bandwidth, AVO and inversion are unlikely to

produce meaningful results. The densely spaced

point receivers employed by Q-Land methodology

provide alias-free data, and hence, a more

complete bandwidth for AVO interpretation.

In complex geological settings where conven-

tional array data are unable to deliver the

required results, single-sensor data provide

significant improvement in signal fidelity andfrequency bandwidth. This improvement enables

interpretation of subtle stratigraphic features

and increased vertical and lateral resolution of

the seismic response as demonstrated in the

following two examples from Kuwait and Algeria.

Pioneering New Technologies in Kuwait

The Minagish field in southwestern Kuwait was

selected for a Q-Land pilot study in 2004, to

address several development and exploration

objectives. One goal was to provide a detailed

image of multiple reservoir intervals within the

Cretaceous for fluid-front monitoring.Discovered in 1959, the Minagish field is one

of the countrys main producers, with production

primarily from carbonate rocks, including the

Minagish oolites. A waterflood program resulted

in water influx overriding oil in layers with

high permeabilities.

A previous 3D seismic survey in 1996, with

source and receiver arrays of 50-m [165-ft]

spacing, provided poor imaging of deeper

prospects and limited the vertical and lateral

resolution at principal reservoir zones.

Characterizing fracture density and orientation,

necessary to optimally place horizontal wells and

maximize production, was also a problem. Noise

arising from gas flares and water injection plants,

coupled with seismic-generated noise such as air

blast, ground roll and multiples, caused extreme

distortions in the seismic data.

In addition, the Minagish field posed an

unusual operational hazard. The area was strewn

with unexploded cluster bombs and mines from

earlier military activity.

A detailed understanding of the internal

reservoir structure was essential for a planned

water injection scheme to work. Forward seismic

modeling using rock properties from core

samples and logs has shown that a 5 to 95%

change in water saturation could result in a 5%

difference in acoustic impedancea product of

velocity and density of the rock. However, a

previous 4D study in 1998 shows the inability to

detect these small changes due to the

background noise level in conventional seismic

data. Some of the limiting factors were frequency

resolution, inferior noise attenuation and a low

signal-to-noise ratio. To allow monitoring of

minute changes in reservoir behavior, it was

obvious that a step change in acquisition

methodology was necessary to reduce noncoherent

signal and coherent noise.

Four tightly grouped vibrators in a rectangle

of 12.5 m [41 ft] by 5 m [16.4 ft] vibrated in

synchrony at 60% of their peak force capability o

80,000 lbf [356 kN]. Driving at less than peak

force provided a low distortion in the seismic

source. The vibrators were set as close a

possible to resemble a point source while

maximizing energy input into the Earth. The

Q-Land system recorded 14,904 channels at a

2-ms sampling rate.15 Perturbation correction

were made to each receiver and each source

prior to summation in the DGF process.

In addition, a Q-Borehole integrated borehole

seismic study was planned at the inception of the

Q-Land pilot program.16 A zero-offset VSP and

two walkaway VSPs recorded the data around the

center of the survey area.17 The integration o

surface seismic and borehole geophysical data

was vital to ensure that all steps in the

processing sequence, from digital group forming

through to the final migrated stack, were

optimally calibrated utilizing some of the latest

> Impact of aliasing on frequency bandwidth. A test conducted with a 16-m receiver array displaysaliasing of ground roll and airwave because of the wrap-around effect seen in the frequency-wavenumber (fk) domain (left). The airwave (solid black line) is completely aliased. However, the

ground-roll noise (dashed black line) is folded back into the signal frequency band above thefrequency where the dashed lines intersect. The signal, which is expected to dominate the centralarea of the fk plot as k approaches zero, becomes contaminated. This means that data-adaptivespatial filtering can no longer remove the coherent noise without damage to the signal. The usablefrequency bandwidth for AVO processing, for example, is substantially reduced for conventional arraydata because aliasing distorts the higher frequencies in both amplitude and phase. In contrast to thispoint-receiver data clearly show an unaliased response that permits processing of the entire usefulfrequency range without coherent noise contamination (right). (Data courtesy of Shell.)

U s a b l e b a n d w i d t h

-200 -100 0

Wavenumber, 1/km

Point Sensors at 2 m

100 200

Usable

bandwidth

60

50

40

30

20

10

0

-30 -20 -10 10 200

Wavenumber, 1/km

30

Frequency,

Hz

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50

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30

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Aliasednoise

16-m Array

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developments in the Well-Driven Seismic

process.18 Restoration of true amplitude

and phase, effective multiple suppression

and compensation for frequency absorption

with depth provided superior imaging and

resolution (above).

The zero-offset VSPs at two control wells, an

injector and a producer, resolved seven intra-

reservoir zones. Conventional seismic data, with

a frequency bandwidth of 10 to 45 Hz, showed

only three of these events, which led to a flawed

interpretation that there were no obstructionsbetween the two wells and injected fluids could

flow freely between two wells. The Q-Land

volume imaged the same seven intrareservoir

zones seen on the VSPs. The enhanced resolution

from Q-Land data, with a frequency bandwidth of

6 to 70 Hz, enabled the seismic interpreters to

map stratigraphic features. Also identified were

tar mats at the injector well that act as baffles

and inhibit fluid movement. In addition, minor

faults and deeper gas targets obscured by

interbed multiples energy were now imaged.19

Encouraged by the results of this Q-Land pilot

study, the operator is in the process of planning a

full-field survey using the Q-Land system. Plans

to reevaluate pore pressure and fracture

characterization incorporating the new Q-Land

data are also under consideration.

The Seismic Challenge in Algeria

An oil field in Algeria, known to be one of the

most seismically challenging fields in the world,

was selected for a Q-land study. Since the

discovery of this field in the 1950s, many wellshave been drilled. Oil and gas production is

mainly from Cambro-Ordovician fluviomarine,

clastic reservoirs. Despite the large number of

wells drilled, abrupt changes in lithology and

fault compartmentalization have made full-field

reservoir characterization from well data alone

difficult. Few seismic surveys have been

attempted in the past because of a poor seismic

response and failure to image the reservoir

zones. As a result, reservoir zones were identified

from petrophysical and pressure data. In

addition, a weak correlation between well

log and core permeability indicated that

the permeability could be strongly influenced

by fractures.

There are several geophysical and geological

challenges. The main producing reservoir, a

braided-channel fluvial system, has a highly

heterogeneous distribution of sand and shale.

The oil field has also been affected by multiple

episodes of fault deformation and reactivation,

resulting in complex fault and fracture patterns

that are difficult to image. Added to these

problems, a small velocity and density contrast at

the top of the reservoir and within the reservoir

units makes detection of reservoir units difficult.

In addition, the influence of strong interbedmultiples obscures the signal, and the presence

of a thick evaporite layer above the reservoir

causes severe attenuation of higher frequencies,

resulting in a poor signal-to-noise ratio. All these

problems lead to a poor tie to wells, making it

extremely difficult to map the interwell region.

Typically, the maximum usable frequency

obtained from the target reservoir has been

around 35 to 40 Hz. This translates into a

maximum vertical resolution of 40 m [131 ft].

However, mapping the reservoir units with any

degree of confidence requires a vertical

resolution of less than 20 m and much lower

noise levels.

50 Oilfield Review

18. The Well-Driven Seismic process uses borehole seismicdata for true amplitude and phase recovery, velocityanalysis, multiple attenuation, anisotropic migration andangle-based muting. For more on the Well-DrivenSeismic technique: Morice SP, Anderson J,Boulegroun M and Decombes O: Integrated Boreholeand Surface Seismic: New Technologies for Acquisition,Processing and Reservoir Characterization; HassiMessaoud Field, presented at the 13th SPE Middle EastOil and Gas Show and Conference (MEOS), Bahrain,June 912, 2003.

19. El-Emam et al, reference 10.

> Comparison of conventional 3D seismic data and Q-Land data in the Minagish field, Kuwait. The Q-Land data ( right) show a much higher lateral andvertical resolution as compared with conventional seismic data (left). The Minagish target reservoir appears at about 1,500 ms.

1,400

1,500

1,600

Two-waytraveltime,

ms

Conventional 3D Data Q-Land Data

1,700

1,800

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Autumn 2005 51

A pilot survey with the Q-Land system was

initiated to address these geophysical and

geological challenges. Integration of borehole-

seismic data and surface-seismic data was

planned at the onset of the project, and the

acquisition parameters were optimized through

presurvey planning and testing.

Q-Land seismic data were acquired over an

area covering 44 km2 [17 mi2], with a dense grid

of sensors, equating to a density of 20,000 sensors

per km2. Borehole geophysical data included

measurements of zero-offset VSP, a two-

dimensional (2D) walkaway VSP using the VSI

Versatile Seismic Imager with 154 geophone

positions in the borehole, and sonic measure-

ments using the DSI Dipole Shear Sonic Imager.

The Q-Borehole seismic system aided in

Well-Driven Seismic processing.

The surface-seismic processing results were

compared with well data at key stages in the

processing sequence, so that the processing

parameters were optimized to tie the fina

seismic data to the wells. The bandwidth

obtained ranged from 6 Hz to 80 Hz, nearly

double the previously recorded high-resolution

2D seismic results. For the first time, the

frequency resolution obtained from surface

seismic data matched that obtained from a VSP

providing an excellent well tie (below).

> A Q-Land example from Algeria. Exceptional resolution (frequencies above 80 Hz) was obtained with the Q-Land survey (top right), in which the frequencybandwidth has nearly doubled in comparison to a high-resolution 2D survey (top left). In addition, the excellent match between the vertical seismic profile(VSP) data (shown within the red box, bottom) and Q-Land data will permit advanced reservoir characterization studies. (Data courtesy of Sonatrach.)

High-Resolution 2D Data Q-Land Data

Two-waytraveltime,

ms

X,500

X,600

X,700

X,800

X,900

Y,000

Y,100

Distance Distance

VSP

Distance

Two-waytraveltime,

s

X.4

X.5

X.6

X.7

X.8

-25

-20

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0

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Power,dB

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-35-30

Signal

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Seismic amplitude was inverted to compute

absolute acoustic impedance (AI) volume (above).

Low AI correlates reasonably well with high-

porosity sands. At 80-Hz frequency, for an interval

velocity of about 4,500 m/s [14,765 ft/s], this low AI

zone equates to a thickness resolution of about

14 m [46 ft]. This degree of resolution has never

been achieved in this geological environment.

To assess the relationship between perme-ability and fault proximity, which is generally

associated with higher fracture density, several

seismic attributes were computed.

Extraction of fractures and faults from the

seismic data involved several steps. Seismic

attribute cubes that enhance discontinuities

in the data, also known as edge-enhancing

attributes, were computed. The edge-detection

seismic volumes include variance, dip and

deviation. The ant-tracking algorithm was then

applied to the edge-detection cube to highlight

the discontinuities in the seismic data, and to

map faults and fractures.20 Distance to fault

(DTF) attributes were then generated from

filtered sets of faults from the ant-track cube and

mapped into the 3D geocellular grid (next page).

The DTF attribute helps identify zones that

are highly fractured. A crossplot between

permeability and DTF confirms the trend: higher

well log permeability when close to faults. Astrong inverse relationship between core

permeability and DTF was observed on about 70%

of wells.

However, to answer questions about whether

those fractures and small-scale faults enhance or

degrade permeability, grid cells were extracted

in the vicinity of seismic faults with greater

length, that is, those that intercept both

basement and the overlying Hercynian

unconformity. Seismic acoustic impedance was

then mapped into these cells to discriminate

between sealing and draining faults. A high cell-

average acoustic impedance in the vicinity of a

fault suggests that the fractures act as flow

barriers, because the fractures were cemented

with pyrite or shale. Conversely, a low acoustic

impedance in the vicinity of a fault suggests a

higher proportion of open, fluid-filled fractures,

which have lower density than rock. This may

suggest that tectonically induced fractures

enhance draining of hydrocarbon.

Wells are continually being drilled in this

area, and additional drilling is planned in 2006

guided by the interpretation results of the

Q-Land data.

Toward Fit-For-Purpose Seismic Data

The fundamentally improved measurements

delivered by Q-Land technology radically expand

the potential of seismic data. With the lower noise

associated with single-sensor acquisition and

processing, and the ability to correct for

perturbations within a group, array design and

fold are no longer the dominant factors inimproving signal-to-noise ratio. Rather, sensor

spacing and a requirement to adequately sample

coherent noise become the main drivers in

designing the acquisition geometry. Since it is

now possible to recover a signal more faithfully,

the vibrator source can also be reevaluated,

making it possible to record shorter, single

sweeps of frequency with a better sampling of

the wavefield.

These design considerations now offer the

possibility of acquiring point-source and point-

receiver exploration surveys with a lower field

effort, compared with equivalent surveys usingconventional source and receiver arrays. The

Q-Land surveys acquired to date suggest that the

use of smaller groups of vibrators can provide

data that are equal to or better than larger arrays

of vibrators and geophones. Smaller groups of

vibrators allow for more efficient operation.

The Q-Land VIVID imaging services enhance

the value of seismic data recorded throughout

the life of a field. In the exploration phase, the

low-noise Q-Land data make it possible to

acquire high-quality seismic surveys with wider

line spacing and lower fold than a survey

acquired with conventional technology and still

meet or exceed the imaging expectations. In

subsequent surveys for appraisal or development,

it is possible to acquire the data by interleaving

lines between the previous surveys to build up

the fold. The data from the original surveys and

the current survey are processed together using

52 Oilfield Review

> Acoustic Impedance (AI) cross section. The Hercynian unconformity forms the top of the reservoirzone (dashed line). The vertical thickness of the low AI interval within the reservoir section indicatesa thickness in the range of 10 to 15 m [33 to 49 ft]. (Data courtesy of Sonatrach.)

Well AcousticImpedance

Distance

Two-waytra

veltime,s

Normalizedacousticimpedance

Low

High

Depth

,ft

X.9

XY,000

XX,000

Y.0

Y.1

33 to 49 ft

Reservoirsection

20. The ant-tracking algorithm delineates discontinuities in aseismic cube and maps faults and fractures. Thealgorithm tracks discontinuities built upon previousknowledge, mimicking the behavior of ants when theyfind the shortest path between their nest and their foodsource. The ants communicate using pheromones, achemical substance that attracts other ants. Therefore,the shortest path to the food source will be marked withmore pheromones than the longest path, so the next antis more likely to choose the shortest route, and so on.The idea is to distribute a large number of theseelectronic ants in a seismic volume. Ants deployed

along a fault should be able to trace the fault surface forsome distance before being terminated. The algorithmthen automatically extracts the result as a set of fault-patches, a highly detailed mapping of discontinuities.Fault discrimination is based on the size of the fault, itsorientation, and on the amplitude of verticaldisplacement. For more on ant tracking: Pedersen SI,Randen T, Snneland L and Steen : Automatic FaultExtraction Using Artificial Ants, Expanded Abstracts,2002 SEG International Exposition and 72nd AnnualMeeting, Salt Lake City, Utah, USA (October 611, 2002):512515.

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A t 2005 53

the required group interval to image the target

correctly. This is the concept of uncommitted

seismic data for the life of a field.

Exploration leads can be pursued during the

same survey. This results in a lower cumulative

environmental footprint of the overall seismic

program, in addition to reduced development

time. As the data have a high signal-to-noise ratio

and fidelity, they can be reused at each stage of a

fields development, ensuring that the explora-

tion investment is not lost.

With unsurpassed seismic data quality and a

versatile approach to acquisition geometry and

innovations in processing, the Q-Land acquisi

tion and processing system will have a major

impact on the life of the field, in exploration

development and reservoir monitoring. RG

> Relationship between seismic acoustic impedance and permeability. Seismic acoustic impedance (AI) and distance to fault (DTF)attributes are combined and mapped onto a geocellular volume ( top). A dual filter based on proximity to fault and seismic AI thresholdvalue is applied to the volume. The filtering assumes that fractures that are open and fluid-saturated have lower velocity and density,and therefore lower AI (bottom right). These are discriminated against faults that are cemented, with higher AI caused by silicificationor pyrite filling (bottom left). (Data courtesy of Sonatrach.)

High Acoustic Impedance Along Faults

Combined Acoustic Impedance and Distance to Fault Attributes

Low Acoustic Impedance Along Faults

Flow barriers

Fractures enhancing permeability