Marine Imaging in Three Dimensions:
Viewing Complex Structures
Recent developments in multimeasurement marine seismic acquisition and full
waveform imaging enable geophysicists to compensate for distortions caused by
shallow geology and sharpen images of deep targets to reduce the uncertainty of
seismic information.
Anatoly Aseev
Moscow, Russia
Sandeep Kumar Chandola
Low Cheng Foo
PETRONAS Carigali Sdn Bhd
Kuala Lumpur, Malaysia
Chris Cunnell
Malcolm Francis
Shruti Gupta
Peter Watterson
Gatwick, England
Michelle Tham
Kuala Lumpur, Malaysia
Oilfield Review 28, no. 2 (May 2016).
Copyright © 2016 Schlumberger.
For help in preparation of this article, thanks to Thomas
Ajewole, M. Nabil El Kady, M. Faizal Idris, Satyabrata Nayak
and M. Iqbal Supardy, PETRONAS Carigali Sdn Bhd, Kuala
Lumpur, Malaysia; and Richard Coates, Houston, Texas, USA.
Dynel 2D, IsoMetrix and Q-Marine are marks of
Schlumberger.
1. Christie P, Nichols D, Özbek A, Curtis T, Larsen L,
Strudley A, Davis R and Svendsen M: “Raising the
Standards of Seismic Data Quality,” Oilfield Review 13,
no. 2 (Summer 2001): 16–31.
2. Robertsson JOA, Moore I, Vassallo M, Özdemir K,
van Manen D-J and Özbek A: “On the Use of
Multicomponent Streamer Recordings for Reconstruction
of Pressure Wavefields in the Crossline Direction,”
Geophysics 73, no. 5 (September–October 2008):
A45–A49.
3. For more on full-azimuth seismic surveying and imaging:
Brice T, Buia M, Cooke A, Hill D, Palmer E, Khaled N,
Tchikanha S, Zamboni E, Kotochigov E and Moldoveanu N:
“Developments in Full Azimuth Marine Seismic Imaging,”
Oilfield Review 25, no. 1 (Spring 2013): 42–55.
4. Inline is in the direction the seismic vessel travels and
acquires data; crossline is in the direction perpendicular
to vessel travel.
5. For more on the Q-Marine system: Christie et al, reference 1.
For more on the 3C seismic MEMS accelerometer unit:
Paulson H, Husom VA and Goujon N: “A MEMS
Accelerometer for Multicomponent Streamers,” paper
We P6 06, presented at the 77th European Association of
Geoscientists and Engineers Conference and Exhibition,
Madrid, Spain, June 1–4, 2015.
4
Hydrocarbon exploration requires that geoscientists understand the geology of prospective reservoirs often located beneath complex rock layers.
From the geophysicist’s perspective, the overburden acts as a defective lens, distorting seismic
images of deeper geologic structures. As a result,
targets appear indistinct, distorted, out of place or,
in extreme cases, completely obscured. The geophysicist’s challenge has been to devise methods
for peering through the overburden and bringing
the underlying geology into focus.
Make-or-break decisions on project viability
often hinge on how well prospective reservoirs can
be imaged, a key factor determining exploration
risk. Operators need accurate images of reservoirs
to help them place exploration wells where they
effectively test the prospect, conduct field planning
and place development wells. In addition to imaging
reservoirs, geophysicists must correctly image the
overburden—the layers above the reservoir—to
reduce drilling risks from operational challenges
such as maintaining a stable wellbore and
controlling formation pressure.
The value that seismic data adds to the
exploration process depends on the quality of
the image produced and the cost incurred in
acquiring such data. Cost-effective seismic
acquisition requires surveying large areas
quickly without compromising data quality and
while minimizing operational and environmental
exposure. Fast acquisition helps shorten the
time frame between the decision to evaluate a
play and the decision to drill.
High-quality data enable exploration teams to
attain a clear understanding of the geology from
the seafloor to the target prospect and then to
decide whether to test and appraise the prospect.
The acquired data must also be suitable for use in
advanced processing, imaging, inversion and
interpretation workflows. These workflows provide vital inputs for geomechanical, reservoir and
basin models.
IsoMetrix marine isometric seismic technology
and full waveform inversion processing are
enabling imaging of complex structures in frontier
areas. The IsoMetrix technology allows for fullbandwidth imaging of fine-scale structures in the
subsurface in all directions—inline, crossline and
vertical—for detailed imaging from seabed to
reservoir. Full waveform inversion results in a
model of seismic velocities, which is used with the
seismic data to form an image of the geology from
the surface to the targets of interest.
This article describes surveys acquired using
IsoMetrix technology in offshore Malaysia and
the North Sea. The survey results demonstrate
the benefits of IsoMetrix technology for overcoming a challenging acquisition environment
and increasing spatial bandwidth and of applying
full waveform inversion for determining overburden and reservoir properties, specifically seismic velocities.
Improving Data and Image Quality
Good seismic imaging requires a chain of factors:
a good acquisition system, optimal survey geometry and accurate processing algorithms and
workflows. More than 15 years ago, Schlumberger
geophysicists embarked on a program to move
from conventional seismic acquisition toward discrete sensor technology. The technology includes
improvements in receiver sensitivity and positioning accuracy, steerable streamers, increased
source control and point-receiver acquisition,
which records traces from individual receivers to
provide consistently repeatable high-quality data.1
These capabilities are evolving. New measurements of the crossline and vertical gradients—
Oilfield Review
m
10 m
Single Channel Interpolation
x
P
Crossline direction
y
Multichannel Reconstruction
z
Crossline direction
Figure 1. Streamer element. An element of the IsoMetrix streamer system
(left) combines a hydrophone (inset) that measures pressure (P ) with a
calibrated, triaxial microelectromechanical (MEMS) accelerometer that
measures the axial, or inline (x), radial, or crossline (y), and vertical (z)
accelerations. The IsoMetrix technology facilitates interpolation between
streamers. Using hydrophone streamers (top right), only the amplitude of
variations with distance—of the pressure wavefield enable the signals received from a marine
seismic shot to be processed as a full 3D wavefield rather than as a collection of 2D profiles.2 In
addition, a newly developed, calibrated, broadband marine seismic source provides improved
low-frequency signal content; no source notches,
or missing frequencies, below 150 Hz for all directions within a 20° cone from the vertical; and
cancellation of the source ghost—a delayed
reflection of the source from the sea surface.
These acquisition improvements have been
complemented by innovations in marine
surveying geometries—for example, multivessel
shooting and full-azimuth source-receiver
configurations. Together, these technologies
make it possible to illuminate targets of interest
previously obscured by folded or faulted
sediment, overlying salt layers or other complex
geologic bodies.3
Seismic acquisition and survey geometry are
only the starting points for seismic imaging.
Accompanied by onboard processing capabilities,
data reliability has vastly improved. In addition,
the application of robust seismic inversion and
imaging techniques, such as full waveform inversion and reverse time migration, allow geophysicists to deliver sharper images and estimate rock
properties for explorationists and reservoir
May 2016
the wavefield (blue) can be measured at each streamer location (black
dots). Therefore, the reconstructed wavefield (red) between streamers
is aliased and incorrect. Using multisensor streamers (bottom right), the
wavefield amplitude and gradient (cyan) can be measured at each streamer
location. Consequently, using both attributes of the wavefield, geophysicists
can reconstruct the wavefield accurately between streamers.
engineers who develop static and dynamic
models of the reservoir. These models are based
on the seismic results—images, velocities and
horizons—that are integrated with well data.
Before drilling, explorationists use the models to
predict the petroleum systems present within the
seismically imaged volume, define plays and
locate prospects for drilling. Reservoir engineers
use refinements of these models to plan field
development and, later, manage hydrocarbon
recovery operations.
Imaging Between Streamers
The purpose of IsoMetrix technology is to provide a densely sampled representation of the
wavefield in all directions. An idealized seismic
acquisition system would be able to record the
seismic signals from everywhere below the surface. This capability would maximize the opportunities for separating the signal from unwanted
noise and imaging the reflectors in the subsurface. However, conventional seismic data are
recorded along only a small number of long
streamers towed behind a vessel. Thus, although
conventional seismic data are well sampled in
recording time and along the streamer (inline),
they are not recorded between the streamers
(crossline), which may be separated by large distances of 50, 75 or 100 m [164, 246 and 328 ft].4
As a result, any waves propagating in the
crossline direction may be aliased, or inadequately sampled.
Often, the focus of marine seismic imaging is to
thoroughly sample the wavefield in the reservoir.
However, good sampling of the wavefield in the
overburden is also important because these depths
must be imaged correctly to enable the geophysicist to see clearly into the reservoir. Sampling the
seabed or other interfaces that generate multiple
reflections is important because such reflections
interfere with primary reflections. Shallow depths
are important because of possible seabed and
shallow subsurface hazards to drilling.
Typical marine seismic receivers are hydrophones that record the pressure wavefield only.
Reconstruction of the pressure field between
streamers requires interpolation between
known pressures at each streamer location and
results in crossline pressure fields becoming
aliased and incorrect.
The IsoMetrix technology is based on the
Q-Marine point-receiver marine seismic system
and combines hydrophones for measuring the seismic wavefield pressure with a three-component
(3C) microelectromechanical systems (MEMS)
unit.5 The 3C MEMS unit contains three orthogonal accelerometers for measuring the full 3D vectorial motion—magnitude and direction—of the
recorded wavefield (Figure 1).
5
Survey vessel
Streamers
line
Inli
Cross
ne
Seismic dataset
Figure 2. Marine seismic acquisition via conventional versus IsoMetrix technology. Conventional
surveys (left) are acquired using streamers of closely spaced hydrophones. The resultant seismic
dataset consists of a set of parallel vertical sections. Surveys acquired with IsoMetrix technology (right)
use streamers of closely spaced multisensor receiver units. The multiple components enable
interpolation between streamers, and the resultant dataset is a true 3D grid.
By adding 3C accelerometers, the marine
receivers record the variation of acceleration,
which is proportional to the pressure gradient, or
the spatial derivative of pressure with direction.
In an acoustic material such as water, hydrophones measure the pressure (P) fluctuations
caused by the seismic wave. Three-component
accelerometers measure the accelerations in
three orthogonal directions (ax, ay and az).
Newton’s Second Law specifies the force that
results from a difference in pressure; the force is
directed from high to low pressure. The relationship between the difference in pressure with
direction—the spatial derivative of P—and the
acceleration, for example in the x direction, is
ρ × ax = −∂P/∂ x, where ρ is the material density,
and the direction of force is opposite, or negative
to, that of the pressure gradient. This type of relationship holds for each spatial direction (x, y and z)
and allows the calculation of the spatial derivative
of pressure directly from the acceleration measurement. Consequently, knowing the pressure
gradients, geophysicists can reconstruct the unaliased pressure field in all directions. Therefore,
geophysicists can estimate the 3D wavefield
around the streamers using the same spacing in all
directions—inline, crossline and vertical.
Reconstructing the Wavefield
The ability to measure the crossline wavefield
gradient enables geophysicists to acquire marine
6
seismic data using streamers spaced farther
apart than those in conventional surveys and to
reconstruct the 3D wavefield on a dense grid at
points between streamers (Figure 2). For example, if the actual recordings were accomplished
using eight streamers spaced 75 m apart, providing a streamer spread that is 525 m [1,720 ft]
wide, the wavefield may be reconstructed as if it
were recorded using virtual streamers spaced a
tenth of the distance—7.5 m [24.6 ft] apart.
When wide streamer spacing is used, areas of
exploration can be surveyed faster and more efficiently using fewer sail lines, thereby reducing
survey duration, acquisition cost, operational
complexity and exposure to adverse environmental conditions.
Recording the vertical wavefield component
improves the geophysicist’s ability to remove
noise, particularly ghost reflections, which are
always present in marine seismic survey recordings. Ghosts are generated when the upward traveling primary signal is reflected downward by the
sea-air interface. This downward traveling ghost is
detected by the seismic receivers and, if uncorrected, causes a frequency dependent blurring of
the final image. Using the vertical acceleration
measurements, the geophysicist can separate the
upgoing and downgoing components of the wavefield, thereby facilitating removal of ghost reflections. The ability to remove the ghosts also allows
IsoMetrix streamers to be towed deeper than
hydrophone-only streamers; towing deep often
reduces other sources of noise such as those
caused by ocean waves and by the motion of the
streamer through the water.
Generalized matching pursuit (GMP) is a processing method that can take advantage of the
multimeasurement data delivered by the
IsoMetrix technology.6 The GMP process operates
on components of the seismic wavefield that are
not confined to traveling straight from the source
to the receiver but instead have a significant
degree of propagation across the streamer
spread. These components may include seismic
reflections, diffractions, multiples or other noise
modes, and, if not treated correctly, can generate
spurious effects in the final images. For example,
any energy arriving from the crossline direction,
which had been spatially aliased previously in
conventional datasets, can now be sampled
appropriately using GMP spatially and temporally by taking advantage of the crossline and
vertical gradient measurements.
The GMP process is data driven and has
proved that it can interpolate the pressure
wavefield accurately in the crossline direction,
even in adverse situations in which the results
from conventional processing would be highly
aliased. The output from the GMP process is a
grid of data channels spaced 6.25 m [20.5 ft]
apart in the inline direction along virtual
streamers, which are nominally separated by
6.25 m in the crossline direction.
The ability to image in 3D enables geophysicists to consider seismic survey acquisition
designs that depart from common practice, as
one operator learned when faced with data
acquisition challenges.
Challenging Acquisition Conditions
To clearly define prospects in the South China
Sea, geophysicists at PETRONAS Carigali Sdn
Bhd acquired a broadband 3D seismic survey offshore Malaysia. The survey area is an elongated
rectangle oriented NW–SE. A major N–S striking
fault crosses the survey area, and structural dips
6. For more on generalized matching pursuit: Özbek A,
Vassallo M, Özdemir K, van Manen D-J and
Eggenberger K: “Crossline Wavefield Reconstruction
from Multicomponent Streamer Data: Part 2—Joint
Interpolation and 3D Up/Down Separation by Generalized
Matching Pursuit,” Geophysics 75, no. 6 (November–
December 2010): WB69–WB85.
7. Chandola SK, Foo LC, El Kaldy MN, Ajewole TO, Nayak S,
Idris MF, Supardy MI, Tham M, Bayly M, Hydal S,
Seymour N and Chowdhury B: “Dip or Strike?—
Complementing Geophysical Sampling Requirements and
Acquisition Efficiency,” Expanded Abstracts, 85th SEG
Annual International Meeting and Exhibition,
New Orleans (October 18–23, 2015): 110–114.
Oilfield Review
N
Fault
Average dip
~40˚ to 50˚
acc
60˚
ess
area
30˚
Average dip
~25˚
0˚
Structural dip, E–W direction
Major faults, N–S direction
Geologic dip of surface of interest
Figure 3. Geologic structure. In the time structure map of the horizon of interest (left), the contour
interval is 100 ms two-way traveltime. The black area is a major fault surface that dips to the east.
The white quadrilateral is the survey area, and a no-access area is west of it. The fault is 5 to 8 km
[3 to 5 mi] wide, has a N–S strike and a throw of about 2.5 s two-way traveltime. The horizon map on
the right—the surface area at the prospective reservoir level—shows structural dips that have been
estimated from legacy seismic data. The dips are aligned along a W–E trend.
Scenario 1
Scenario 2
Main Survey Area
E–W shooting
10 streamers, 8,000 m long,
towed 100 m apart
Patch Survey Area
N–S shooting
10 streamers, 8,000 m long,
towed 50 m apart
Entire Survey Area
N–S shooting
10 streamers, 8,000 m long,
towed 100 m apart
During seismic processing, the
streamer data are processed
and output to a 6.25-m × 6.25-m
grid that is 8,000 m long and
950 m wide.
6 km
˜1
m
˜5
km
e
Strik
km
e
Strik
˜5
6k
˜1
Dip
Dip
vey
Are
a
0 km
˜5
Enti
ur
re S
Ma
i
rve
n Su
y Ar
ea
ea
r
ss a
ea
rea
y Ar
ss a
urve
acce
ch S
No-
Pat
0 km
˜5
e
Zon
ault
in F
a
M
acce
No-
May 2016
Average dip
~7˚
N o-
as high as 50° occur in the area along a W–E
trend (Figure 3). The area is bounded on the west
by a no-access zone that survey vessels are not
permitted to enter.7
Typically, optimal seismic acquisition geometry
for conventional 3D surveys requires shooting
parallel to the predominant structural dip
direction. This inline direction facilitates closespaced sampling of the seismic wavefield in the dip
direction, in this case W–E, in which the geology
has the most variation. In addition, the typical
conventional seismic bin, or survey subdivision,
into which geophysicists sort seismic traces, is
asymmetric and elongated in the structural strike
direction, which is the crossline direction.
The no-access zone prohibited the vessel from
obtaining full subsurface coverage at the western
edge of the survey and presented an acquisition
challenge to geophysicists, who considered two
options (Figure 4). In the first scenario, they
could acquire most of the survey by shooting
short lines, spaced 100 m apart, parallel to dip to
avoid the no-access area. Then, complete the survey using long lines, spaced 50 m apart, sailing
parallel to strike adjacent to the no-access zone
boundary; the close line spacing of these strikeparallel lines ensured adequate sampling of the
structural dip. Alternatively, they could acquire
the entire survey using exclusively strike-parallel
sail lines.
The first option was inefficient because of the
two acquisition directions, which required nonproductive time during the many turns and while the
streamers were repositioned for close spacing. The
second option was more efficient for acquiring
data but risked degrading the seismic information
if acquired using conventional technology.
According to conventional wisdom, the strike-parallel survey direction, which had typical line spacing and sampling of the seismic wavefield in the
dip direction, was not ideal for imaging the subsurface and meeting the objectives of company geologists and geophysicists.
The company used IsoMetrix technology,
which enabled symmetric, isometric, or equidistant, sampling of the wavefield in the inline and
crossline directions, to acquire the survey parallel to the structural strike. In addition, the company acquired a smaller swath of data in the
direction of the dominant structural dip, which
would allow comparison and validation of the
integrity of survey shooting in strike.
The data were acquired using ten 8-km [5-mi]
long streamers spaced 100 m apart. The streamers were towed at a water depth of 18 m [59 ft] to
minimize noise from variable currents and
inclement weather during the survey campaign.
Estimated Survey Duration:
Scenario 1 = 2 × Scenario 2.
Figure 4. Acquisition options. The survey was restricted by a no-access area on its western
boundary. The company geophysicists considered two options for acquiring the seismic data. In the
first option (left ), the acquisition vessel would sail the main survey area in the dip direction and then
reconfigure the streamers and sail the patch survey area, adjacent to the no-access boundary, in
the strike direction. In the second option (right ), the entire survey area would be acquired by sailing
in the direction of geologic strike and would parallel the no-access boundary. The company chose
the second option and elected to use IsoMetrix technology, which allows for reconstruction of the
wavefield sampled equally in both inline and crossline directions, to acquire the data.
7
Bathymetry from Multibeam Echo Sounder
Bathymetry from IsoMetrix Technology
5 km
5 km
10 × 100 m spread
6.25 × 6.25 m binning
5 × 5 m sampling
Figure 5. Seafloor features. Bathymetry data (left) were acquired using a multibeam echo sounder; the black arrows indicate features such as sand dunes,
waveforms, mounds and pockmarks on the seafloor. A map of the seafloor surface (right) from the seismic data, which were acquired using IsoMetrix
technology, showed similar features.
After acquisition, the data were preprocessed
and then the full 3D wavefield was calculated
using simultaneous interpolation and deghosting
by means of the GMP method. Next, the upgoing
pressure wavefield (P-wave) was output on a
6.25‑m by 6.25‑m grid for each shot record for
further processing and imaging.
The data proved to be of high quality. For
example, a map of the seafloor surface showed
sand banks similar to those observed in bathymetry data obtained using a high-resolution multibeam echo sounder (Figure 5).
Upon comparing the dataset acquired in the
strike direction with that acquired in the dip
Control Swath
Production Volume
1s
1s
5s
5s
Dip shooting direction, inline stack
18 km
Strike shooting direction, crossline stack
18 km
Figure 6. Comparing acquisition directions. Both seismic sections (left and right) are from identical
locations but resulted from perpendicular acquisition directions. The section on the left was from
the control swath acquired in the dip, or crossline, direction and stacked in the strike, or inline,
direction. The section on the right was from the production volume and acquired in the strike direction
but stacked in the dip direction. Except for subtle differences, the sections show similar results
and indicate that the IsoMetrix technology yields similar quality data regardless of the acquisition
direction. The magenta ovals indicate structures, or features, that appear different from one another
as a result of acquisition in the strike direction rather than in the dip direction.
8
direction, geophysicists judged the datasets to be
similar (Figure 6). The fine spatial sampling of
the wavefield in the inline and crossline directions obtained with IsoMetrix technology enabled
the company to accomplish its geologic and geophysical objectives and achieve acquisition operational efficiency.
In addition to freeing up constraints on seismic
survey acquisition design, uniform inline and
crossline data wavefield estimation facilitates the
increase in spatial resolution and bandwidth
required to compensate for distortions caused by
shallow overburden layers and to sharpen images
of deeper targets. These improvements in resolution and bandwidth helped reduce the uncertainty
of seismic information across the operator’s drilling prospects.
Broadband in 3D
Oil discoveries at three locations in the southwest Barents Sea have generated significant
interest in exploration of the region. The discoveries offshore northern Norway at the Gohta
prospect in 2013 and at the Alta prospect in 2014
were both by Lundin Norway AS; those at the
Wisting Central prospect in 2013 were by OMV
(Norge) AS. The Gohta and Alta discoveries were
west of the Loppa High, a roughly 150 km [90 mi]
long and 100 km [60 mi] wide tilted fault block
that has been affected by a series of events in the
North Atlantic Ocean that include:
•Paleozoic rifting
•Mesozoic opening of the North Atlantic Ocean
and of the Greenland and Norwegian seas
•Quaternary glaciation.
Oilfield Review
E
W
0.5 s
Bjørnøyrenna
fault complex
Hoop
fault complex
Bjørnøyrenna
fault complex
A
A
Hoop
fault complex
Loppa High
5.0 s
N
0.5 s
S
Asterias
fault complex
Asterias
fault complex
B
B
Variance
Low
5.0 s
High
Reflection amplitude
–
0
Figure 7. Fault system. This seismic time slice (left) at 1,100 ms is through
the Loppa High; the seismic attribute is displayed to emphasize the variance
in seismic reflectivity—areas of high variance values are colored from
black to red and yellow. Three major fault systems, which show up as areas
of high variance, affected the Loppa High. The W–E striking Asterias fault
complex crosses the Loppa structure in the south; the southern portion of
the SW–NE striking Hoop fault complex cuts across and forms the narrow
The WesternGeco seismic vessel Western
Trident acquired the East Loppa Ridge survey in
2014. The survey covered 4,777 km2 [1,844 mi2]
and is part of the Schlumberger Multiclient
Barents Sea program. The program used
IsoMetrix technology to record wide spatial
bandwidth data—the recorded wavefield contains the fine-scale detail necessary to represent
subsurface geology accurately.
In conventional 3D seismic surveys, a common objective is to acquire broadband surveys of
high temporal—traveltime—bandwidth and
resolution. The ideal broadband survey has a
wide band, or range, of frequencies and is
acquired at a high sample rate. The objective for
maximizing temporal bandwidth is primarily to
maximize resolution in depth—to image thin
beds and small faults.
Geology is best understood by observations in
three dimensions, which requires maximizing
May 2016
+
Loppa High graben and the Bjørnøyrenna fault complex separates the
Loppa High from the Bjørnøya basin (not shown) on the west. Sections A
and B (right top and bottom) display grabens associated with the fault
systems. The northern portion of the Loppa structure is in the center of
Section A. Section B shows graben structures in the north associated with
the Hoop fault complex and in the south associated with the Asterias fault
complex, which separates the Loppa High from the Hammerfest basin.
spatial bandwidth in all directions. In the spatial
domain, the wavenumber (k) is the spatial
frequency, or the number of wavelengths—wavecycle lengths—λ per unit distance. The
wavenumber is analogous to the temporal
frequency (f) or the number of wave periods—
wave-cycle times—T per unit time. Wavenumber
in the space domain and frequency in the time
domain are related through the phase velocity
(vp), which is equivalent to wavelength divided
by period (vp = λ / T ), frequency divided by
wavenumber (vp = f/k) or wavelength times frequency (vp = λ × f ).8 Consequently, for 3D seismic imaging of geology, the notion of broadband
must be expanded to include 3D spatial bandwidth and resolution.
The East Loppa Ridge survey was acquired
using 12 streamers that were 7 km [4.3 mi] long,
spaced 75 m apart and towed at a constant depth
of 25 m [82 ft]. After acquisition, the datasets
were preprocessed and then simultaneously spatially dealiased and receiver-deghosted in 3D by
means of the GMP method.
The tectonic, stratigraphic and petroleum
systems geology of the southwest Barents Sea
region is complex.9 The structural setting resulted
from several tectonic events that established a
dense mosaic of fault systems (Figure 7). The
8. In this context, phase refers to a wave of a single
frequency in a wave train. The phase could be of a
compressional (P) wave, shear (S) wave, other waves or
their associated reflections and refractions; the wave’s
velocity is the phase velocity.
9. Henriksen E, Ryseth AE, Larssen GB, Heide T, Rønning K,
Sollid K and Stoupakova AV: “Tectonostratigraphy of the
Greater Barents Sea: Implications for Petroleum
Systems,” in Spencer AM, Embry AF, Gautier DL,
Stoupakova AV and Sørensen K (eds): Arctic Petroleum
Geology. London: The Geological Society, Memoir 35
(August 9, 2011): 163–195.
Gernigon L, Brönner M, Roberts D, Olesen O, Nasuti A
and Yamasaki T: “Crustal and Basin Evolution of the
Southwestern Barents Sea: From Caledonian Orogeny to
Continental Breakup,” Tectonics 33, no. 4 (April 2014):
347–373.
9
W
0.5 s
E
5 km
5.0 s
Reflection amplitude
–
0
+
BCU
Seafloor
Tertiary
Upper Triassic-Jurassic
Lower-Middle Triassic
Late Carboniferous to
Permian carbonates
Carboniferous postrift
Evaporites
Carboniferous synrift
Pre-Carboniferous
basement
Figure 8. East Loppa regional seismic section. The seismic section (top) runs from the Loppa Ridge
in the west toward the Ottar basin in the east. The interpretation (bottom) is a balanced section,
which was modeled using the Dynel 2D restoration and forward modeling tool. This section shows
extensional rifting and synrift and postrift sediment deposition during the Carboniferous period.
During the Late Carboniferous to Permian, a carbonate platform developed and evaporate was
deposited. During the lower to middle Triassic uplifting and tilting of the Loppa High, karstification
of the carbonates and sedimentation of shales occurred. The upper Triassic and Jurassic periods
were characterized by high clastic sedimentation rates and floodplain development from rivers and
deltas. Rifting occurred again during the upper Jurassic to lower Cretaceous; the base Cretaceous
unconformity (BCU) defines the transition from synrift to postrift sedimentation. Finally, Tertiary
sediments occur above the BCU to the seafloor.
10.Gabrielsen RH, Færseth RB, Jensen LN, Kalheim JE and
Riis F: “Structural Elements of the Norwegian
Continental Shelf. Part I: The Barents Sea Region,”
Stavanger, Norway: Norwegian Petroleum Directorate,
NPD Bulletin no. 6, May 1990.
11.For more on the Gipsdalen Group: Larssen GB,
Elvebakk G, Henriksen LB, Kristensen S-E, Nilsson I,
Samuelsberg TJ, Svånå TA, Stemmerik L and Worsley D:
Upper Paleozoic Lithostratigraphy of the Southern
Norwegian Barents Sea. Stavanger, Norway: Norwegian
Petroleum Directorate (2002).
“Barents Sea—Carboniferous to Permian Plays,”
Norwegian Petroleum Directorate, http://www.npd.no/
en/Topics/Geology/Geological-plays/Barents-Sea/
Carboniferous-to-Permian/ (accessed August 29, 2015).
10
12.For more on petroleum systems: Al-Hajeri MM,
Al Saeed M, Derks J, Fuchs T, Hantschel T, Kauerauf A,
Neumaier M, Schenk O, Swientek O, Tessen N, Welte D,
Wygrala B, Kornpihl D and Peters K: “Basin and
Petroleum System Modeling,” Oilfield Review 21, no. 2
(Summer 2009): 14–29.
13.For more on the Snadd Formation: Klausen TG,
Ryseth AE, Helland-Hansen W, Gawthorpe R and
Laursen I: “Regional Development and Sequence
Stratigraphy of the Middle to Late Triassic Snadd
Formation, Norwegian Barents Sea,” Marine and
Petroleum Geology 62 (April 2015): 102–122.
14.Houbiers M, Wiarda E, Mispel J, Nikolenko D, Vigh D,
Knudsen B-E, Thompson M and Hill D: “3D FullWaveform Inversion at Mariner—A Shallow North Sea
Reservoir,” Expanded Abstracts, 82nd SEG Annual
Loppa High area contains three major fault complexes.10 The Asterias fault complex forms the
southern boundary, which separates the Loppa
High from the Hammerfest basin to its south. The
southern portion of the Hoop fault complex
strikes SW–NE and cuts across the Loppa structure as a narrow graben. The Bjørnøyrenna fault
complex separates the Loppa High from the
Bjørnøya basin on the west. Broadband seismic
images make it possible to delineate the fault
patterns and establish the regional structural
framework within the East Loppa Ridge survey
area. The structural framework influences local
petroleum systems.
The Gohta and Alta oil discoveries were in
reservoirs located in carbonates of the Gipsdalen
Group, which were deposited in warm, shallow
marine environments during the Late
Carboniferous to Permian periods and, since
then, have been altered by dolomitization and
karstification (Figure 8).11 Additional petroleum
systems elements in the Loppa High area include
reservoir prospects in Triassic sandstones, source
rocks in Carboniferous synrift and postrift sediments and in Permian and Triassic sediments
and seals formed by Triassic and Cretaceous
shales.12 The broadband East Loppa Ridge seismic dataset offers an opportunity for detailed
interpretation of the complex geology in the
Loppa High area.
The upper Paleozoic carbonates have been
the most promising stratigraphic level for Loppa
High exploration (Figure 9). Broadband seismic
data facilitate detailed mapping, analysis and
interpretation of the carbonate morphology,
which has polygonal ridges characteristic of modern carbonate platforms.
Oil has been discovered in the upper Triassic
Snadd Formation but at locations with low reservoir quality. Within the Snadd Formation, the
broadband seismic data reveal the fluvial system and aid automated mapping, which should
reduce the uncertainty of locating higher quality reservoir sands. The data show complex
International Meeting and Exhibition, Las Vegas,
Nevada, USA (November 4–9, 2012).
Houbiers M, Mispel J, Knudsen BE and Amundsen L:
“FWI with OBC Data from the Mariner Field, UK—The
Impact on Mapping Sands at Reservoir Level,” paper
We 11 05, presented at the 75th European Association of
Geoscientists and Engineers Conference and Exhibition,
London, June 10–13, 2013.
Østmo S, McFadzean P, Silcock S, Spjuth C, Sundvor E,
Letki LP and Clark D: “Improved Reservoir
Characterisation by Multisensor Towed Streamer
Seismic Data at the Mariner Field,” paper We P03 12,
presented at the 76th European Association of
Geoscientists and Engineers Conference and Exhibition,
Amsterdam, June 16–19, 2014.
Oilfield Review
Figure 9. Carbonate reservoir. The seismic time horizon of the top surface of
the Late Carboniferous– to Permian-age Gipsdalen Group is shown in map
(left ) and perspective (right ) views. These views show a seismic attribute
that emphasizes edges on the surface. The surface in both views displays
polygonal ridges that are reminiscent of polygonal oceanic reef systems
observed in modern carbonate platform environments (inset).
fluvial and floodplain geology and reveal that
the channel system is associated with floodplain development (Figure 10).13 The data
reveal a variety of fluvial features, including
point-bar systems, clustered channel fill complexes and ribbon-channel sandstone bodies;
the ribbon channels were at depths greater
than 1,000 m [3,280 ft] and estimated to be less
than 100 m wide.
The East Loppa Ridge survey demonstrates
the imaging power of acquiring true 3D, broadband seismic data. High spatial resolution in all
directions facilitates and improves imaging of
complicated 3D geology such as fault networks,
anastomosing fluvial channel complexes and carbonate platform deposition and karstification.
The increased detail offered by broadband images
promotes improved understanding of petroleum
system geology and better discrimination of lithologies and their rock properties.
Full Waveform Inversion
Geophysicists use full waveform inversion (FWI)
for calculating horizontal and vertical seismic
wave velocities of geology from the surface to targets of interest. The result is a velocity image in
depth that reveals the sought-after structural
and depositional information.
Traditional migration produces an image of the
subsurface by attempting to reposition, or migrate,
seismic data reflection points to their correct locations in 3D space. A velocity model is almost
always an input to migration; and a refined velocity model may be a byproduct of migration.
Unlike conventional migration, FWI is a
method for building a velocity model by attempting
to match the complete recorded wavefield that
May 2016
results as seismic waves travel through the Earth
and encounter changing properties in the
subsurface geology. The starting point for FWI is
an approximate model of velocities. Geophysicists
use this velocity model to simulate the recorded
wavefield. They then subtract the simulated
wavefield from the observed wavefield to obtain
the residual wavefield. The residual wavefield
is then backward propagated—extrapolated
downward in space or backward in time—through
the velocity model to obtain a dataset of velocity
gradients. These gradients inform where to
increase or decrease velocities but not by how
much. To calculate a velocity model update, the
gradients are multiplied by a step length, which
scales the gradients. The velocity updates are
added to the current velocity model to create a
new velocity model, and the process is repeated.
The iterations continue until the residual
wavefield is acceptably small, meaning that the
modeled wavefield closely approximates the
observed wavefield. The final model of seismic
velocities can be used as an input to migration to
produce an image that better represents subsurface rock characteristics or may be used directly to
interpret rock and fluid properties.
This technique was used in Mariner field, discovered in 1981 and located about 150 km [93 mi]
east of the Shetland Islands on the UK Continental
Shelf in the North Sea. The field is under development by operator Statoil UK Limited with partners
JX Nippon Exploration and Production (UK)
Limited and Dyas UK Limited. The field consists of
two reservoirs. The shallow reservoir contains
heavy oil of 12.1 API gravity and is about 1,200 m
[3,940 ft] below sea level in sands of the Heimdal
member of the Middle to Late Paleocene Lista
Variance
Low
High
Figure 10. Floodplain channels. This seismic
time slice at 1,100 ms is at the depth of the upper
Triassic Snadd Formation. The time slice shows
the variance in reflectivity. The dark linear and
curvilinear features are faults. The lighter gray,
sinuous and interweaving features are networks of
fluvial channels crisscrossing a floodplain.
Formation, composed predominantly of shale. The
deeper reservoir in the Maureen sandstone
member contains heavy oil of 14.2 API gravity and
is at the base of the Early Paleocene Våle
Formation at depths of 1,400 to 1,500 m [4,590 to
4,920 ft] below sea level.
The Mariner field presents various challenges
for seismic imaging.14 The shallow overburden
above the reservoirs contains channel sands that
have higher seismic velocities than those of surrounding geologic units. These sands can be
mapped easily, but their presence causes distortions in the images of the reservoir zones beneath
them. For example, shallow, high-velocity channel sands cause pull-ups of, or apparent structural high spots in, underlying reflectors. The
Heimdal reservoir sands consist of complex channel sands as well as sand injectites, or sand intrusions; these sands are difficult to image because
of their low impedance contrast with the shales
that host them. The Maureen sandstone contains
small-scale faults and calcite layers that are
important for developing production from the
11
sandstone but are below the detection
capabilities of traditional seismic techniques.
The imaging challenges presented by the
reservoirs may be mitigated by full waveform
processing techniques that enable removal of the
distortions caused by the high-velocity channel
sands in the shallow overburden.
In 2012, the operator acquired a broadband
seismic survey at the Mariner field using the
WesternGeco IsoMetrix technology. The survey
data were acquired using eight streamers, each
3 km [1.9 mi] long, spaced 75 m apart and towed
at a constant depth of 18 m. After acquisition, the
data were preconditioned and then simultaneously interpolated and deghosted using the GMP
method. The upgoing pressure wavefield was
then output on a 6.25‑m by 6.25­m grid for subsequent processing and imaging.15
Initial inspection of the dataset showed it to
be richer in high frequencies than in two conventional 3D seismic datasets and richer in low frequencies than in an earlier ocean bottom cable
(OBC) survey. Both qualities are important for
resolving subsurface geology and velocities
through inversion of seismic data. High frequencies enable resolution of relative velocities
between small stratigraphic and structural
details. Low frequencies facilitate determination
of absolute velocities, which are calibrated
against borehole data.
The data underwent fast-track processing,
using prestack time migration, which demonstrated the Heimdal member sands could be
imaged more reliably using the broadband data
than the earlier data.16 The operator’s geoscientists were able to establish the relationship
between seismic reflectors and geologic horizons
with improved confidence.17 Encouraged by these
results, WesternGeco geophysicists applied FWI to
the broadband dataset.18
The starting point for FWI is a velocity model
(Figure 11). The geophysicists began with a simple
model, using seismic velocities interpreted from
sonic logs from wells in the area of the Mariner
field, which were then interpolated laterally
between the wells along layers bounded by known
geologic horizons. Based on previous processing
studies, the overburden formations were assumed
to be anisotropic; the P-wave anisotropy parameters epsilon (ε) and delta (δ) were initially defined
as linearly increasing from the seafloor to the base
Cretaceous unconformity but were subsequently
updated using a multiparameter inversion step in
the FWI workflow.19
The geophysicists wanted to know whether the
results of FWI would isolate the velocities in
shallow channel sands within the overburden. As a
test, one of the known channels delineated from
legacy 3D seismic data was inserted into the initial
velocity model and given a higher velocity than its
host units. If successful, the FWI method would
sharpen the velocities within this control channel
but also pick out other channels in the area.
To compensate for velocity imprecisions
introduced by interpolation, the geophysicists
applied one iteration of common image point
(CIP) tomography to the interpolated velocity
model. Common image point tomography is an
iterative method of inverting for seismic velocities using seismic reflections. During an iteration, the amount of residual moveout—depth
variation—along reflections in prestack depthmigrated (PSDM) CIP gathers is used to determine adjustments in the velocity model to bring
the subsequent version of the PSDM image into
better focus.20 After one iteration of CIP tomography, the velocity model was smoothed and ready
for input to the FWI process.
Next, the geophysicists started the FWI process, which, beginning with the initial earth
model of velocities, iteratively models the
observed seismic wavefield and adjusts the velocities in the earth model until there is an acceptable match between the modeled wavefield and
the recorded wavefield.21 The observed wavefield
was the upgoing P-wave wavefield that had been
isolated at an early stage of processing from the
broadband dataset. The criterion for convergence to an acceptable match between synthetic
and observed wavefields is to minimize a misfit
function that quantifies the difference between
the modeled and measured data. To ensure that
the FWI process converges on the global, or true,
minimum rather than a localized minimum, the
geophysicists conduct FWI in stages. First, they
find an acceptable fit of the low-frequency
wavefield. They then add and fit to successively
15.Özbek et al, reference 5.
16.Migration is a seismic processing step in which
reflections in seismic data are moved to their correct
locations. Time migration locates reflections in two-way
traveltime—from the surface to the reflector and back
as measured along the image ray. Depth migration
locates reflectors in depth. Mathematically, migration is
performed by various solutions to the wave equation
that describe the passage of seismic waves through
rock. Kirchhoff migration is a ray-based approximation
founded on the integral solution to the wave equation
derived by 19th-century German physicist
Gustav Kirchhoff.
For more on migration and imaging: Albertin U, Kapoor J,
Randall R, Smith M, Brown G, Soufleris C, Whitfield P,
Dewey F, Farnsworth J, Grubitz G and Kemme M:
“The Time for Depth Imaging,” Oilfield Review 14, no. 1
(Spring 2002): 2–15.
17.Østmo et al, reference 14.
18.Gupta S, Cunnell C, Cooke A and Zarkhidze A:
“High-Resolution Model Building and Imaging Workflow
Using Multimeasurement Towed Streamer Data: North
Sea Case Study,” Expanded Abstracts, 85th SEG Annual
International Meeting and Exhibition, New Orleans
(October 18–23, 2015): 1049–1053.
19.The base Cretaceous uniformity is the term applied to a
strong seismic reflection surface that is mappable over
much of the continental shelf in the North Sea. The
reflector is an unconformity that is located close to the
bottom of Cretaceous-age rocks and separates
sediments deposited before rifting of the North Sea from
sediments deposited after rifting.
Anisotropy is the variation of a physical property,
such as P- or S-wave velocity, with the direction
of its measurement. For more on elastic anisotropy:
Armstrong P, Ireson D, Chmela B, Dodds K, Esmeroy C,
Miller D, Hornby B, Sayers C, Schoenberg M, Leaney S
and Lynn H: “The Promise of Elastic Anisotropy,”
Oilfield Review 6, no. 4 (October 1994): 36–47.
Epsilon (ε) and delta (δ) are P-wave parameters that
describe vertical transverse isotropy. Epsilon is the
P-wave anisotropy parameter and equal to half the ratio
of the difference between the horizontal and vertical
P-wave velocities squared divided by the vertical
P-wave velocity squared. Delta is describes nearvertical P-wave velocity anisotropy and the difference
between the vertical and small-offset moveout velocity
of P-waves. For more on seismic anisotropy parameters:
Thomsen L: “Weak Elastic Anisotropy,” Geophysics 51,
no. 10 (October 1986): 1954–1966.
20.For more on CIP tomography: Woodward M, Nichols D,
Zdraveva O, Whitfield P and Johns T: “A Decade of
Tomography,” Geophysics 73, no. 5 (September–
October 2008): VE5–VE11.
21.Vigh D, Starr EW and Kapoor J: “Developing Earth
Models with Full Waveform Inversion,” The Leading
Edge 28, no. 4 (April 2009): 432–435.
22.For more on multiscale inversion: Bunks C, Saleck FM,
Zaleski S and Chavent G: “Multiscale Seismic
Waveform Inversion,” Geophysics 60, no. 5 (September–
October 1995): 1457–1473.
23.Reference 16.
Build initial velocity model
Control test for FWI: Insert known channel
into velocity model
One iteration of common image point (CIP)
tomography to smooth velocity model
Low-frequency FWI iterations using
frequency band, 1.5 to 7 Hz
peak frequency, 2.5 Hz
Intermediate-frequency FWI iterations using
frequency band, 1.5 to 13 Hz
peak frequency, 5 Hz
One iteration of CIP tomography to refine
velocities in deepest intervals of the model
Multiparameter FWI to refine
anisotropic parameters
Final high-frequency FWI iterations to enhance
the resolution of velocities
Figure 11. Workflow for full waveform inversion.
12
Oilfield Review
higher frequency bands until there is an
acceptable fit of the full-frequency wavefield.
This sequential FWI procedure stabilizes the
inversion algorithm and ensures that the process
converges to a global minimum.22
Application of FWI to the broadband dataset
collected at Mariner field showed that a seismic
dataset acquired using IsoMetrix technology can be
inverted for a geologically relevant seismic velocity
model that is capable of sharpening the focus of
seismic images. After FWI processing, the velocity
model was input into two prestack depth migration
algorithms: a Kirchhoff depth migration (KDM) to
compare directly against legacy data volumes and a
high-frequency reverse time migration (RTM) performed directly in the natural shot domain after
GMP.23 The velocity model from FWI sharpened the
image of the control channel embedded into the
overburden of the initial velocity model and
highlighted additional channels (Figure 12).
Before FWI Processing
2,250 m/s
Depth slice, 158 m
1,700 m/s
2,025 m/s
Depth slice, 278 m
1,625 m/s
2,225 m/s
Depth slice, 844 m
2,500 m/s
1,500 m/s
2,025 m/s
After FWI Processing
2,250 m/s
Depth slice, 158 m
1,700 m/s
2,025 m/s
Depth slice, 278 m
1,625 m/s
2,225 m/s
Depth slice, 844 m
2,500 m/s
1,500 m/s
Figure 12. Comparing models before and after full waveform inversion (FWI).
Both seismic sections (left top and bottom) show the same geology to a
depth of 1,200 m [3,940 ft] below sea level. The depth sections are the result
of Kirchhoff depth migration (KDM); the sections are overlain by the velocity
model (colors) that was used as input to KDM. The top section resulted
from KDM using the initial velocity model. The control channel is in the top
center and was given a higher velocity than its surroundings. The bottom
May 2016
2,025 m/s
section resulted after using the velocities output after completion of FWI.
The control channel is in better focus, and the velocities of other channels
are evident. The velocities of the overburden units have become more
defined. The images on the right are depth slices at 158, 278 and 844 m
[518, 912 and 2,770 ft] below sea level. Compared with the before FWI
processing results, geologic features (yellow arrows) have become better
defined after FWI processing.
13
Legacy KDM Model
1,700
1,500
Onla
Two-way traveltime, ms
1,600
Isolated depositional sandstones
in the Frigg Formation mudstones
Onlap
p
1,800
1,900
2,000
2,100
1,600
1,700
1,800
1,900
2,000
2,100
Heimdal sandstone
1 km
Concept 1: isolated depositional sandstones
Heimdal sandstone
Sandstone intrusions crosscut the
Balder and Frigg Formation mudstones
Crestal intrusion fringe
n
trusio
-like in
Wing
Two-way traveltime, ms
1,500
Heimdal sandstone
1 km
Concept 2: sandstone intrusions crosscut mudstones
Top of the Frigg sandstone
Top of the Balder sandstone
Top of the Sele Formation
Top of the Heimdal sandstone
KDM using FWI Model
Reflection amplitude
–
0
+
Heimdal sandstone
RTM using FWI Model
Heimdal sandstone
Figure 13. Modeling results. A clear progression of improvement occurs from the legacy velocity
model and Kirchhoff depth migration (KDM, top) to the revised KDM using FWI model (middle) to the
high-resolution reverse time migration (RTM) also using the FWI model (bottom). The progression
demonstrates improved imaging of the steep dips and signal-to-noise characteristics in the reservoir
section, discriminating the Heimdal injectite, or intrusion, features (circled) from the background Lista
shales. The inset shows conceptual sketches of how the sandstone bodies or intrusions might have
become incorporated into the Lista shales above the Heimdal formation. (Inset adapted from Huuse
et al, reference 24.)
14
The velocities in the shallow layers became
more clearly defined. Below them, the reservoir
zones of interest were less distorted. Cross sections
through the KDM image volume showed that the
velocities from FWI made a demonstrable difference in the focusing and positioning of overburden
formations, while the RTM image volume gave the
best resolution and signal-to-noise discrimination of
Heimdal injectites against the background Lista
shales (Figure 13).24
The IsoMetrix marine isometric seismic technology and full waveform imaging are enabling and
complementary technologies for increasing the
qualitative and quantitative accuracy of seismic
information. The IsoMetrix technology allows
deghosting and interpolation of the recorded
wavefield to produce unaliased seismic records. In
turn, FWI provides geologically relevant velocities
at scales that can be used to bring the overburden
into focus. Together, these techniques enable geophysicists to image reservoir targets more clearly
(Figure 14).
Advances in the sequence of steps from seismic data acquisition to final imaging are helping
operators characterize the subsurface more
distinctly. Measurements of the pressure
wavefield and its gradients using IsoMetrix
technology represent a significant development
24.For more on injectites: Braccini E, de Boer W, Hurst A,
Huuse M, Vigorito M and Templeton G: “Sand Injectites,”
Oilfield Review 20, no. 2 (Summer 2008): 34–49.
Huuse M, Cartwright J, Hurst A and Steinsland N:
“Seismic Characterization of Large-Scale Sandstone
Intrusions,” in Hurst A and Cartwright J (eds): Sand
Injectites: Implications for Hydrocarbon Exploration and
Production, AAPG Memoir 87. Tulsa: AAPG (2007): 21–35.
Oilfield Review
Ocean Bottom Cable Survey
IsoMetrix Survey
1.7 km
in marine seismic data acquisition. The
development of circle shooting, simultaneous
firing of sources and full-azimuth source-receiver
configurations embody advances in marine
seismic survey geometry and design. Full
waveform inversion, along with reverse time
migration, is advancing geophysicists’ capability
to develop data-driven velocity models. The
converging improvements on all three fronts—
acquisition, survey design and processing—
provide the means for imaging complex geologic
structures, forecasting drilling hazards and
illuminating reservoir targets. —RCNH
Figure 14. Comparing images from ocean bottom cable (OBC) and IsoMetrix technologies. Both images
are seismic depth sections to a depth of 1,700 m [5,600 ft] below sea level. They show the same
geology extracted from datasets that have been processed using similar workflows through FWI
and prestack depth migration; in each case, the color overlay is the P-wave velocity model that
results after processing. For the 2008 OBC survey (left), the FWI processing was completed to a peak
frequency of 10 Hz before migration using KDM. For the 2012 survey using IsoMetrix technology (right),
the FWI processing was completed to a peak frequency of 5 Hz, followed by migration using highresolution RTM. Despite some differences in the two workflows, both used a 2.5‑Hz peak frequency for
the first FWI updates. After processing, the velocity model result from IsoMetrix technology has the
same, or better, resolution in the shallow overburden as the model result from the OBC survey.
Contributors
Anatoly Aseev, based in Moscow, was a Seismic
Interpreter for Schlumberger Multiclient seismic
projects from 2014 to 2016, with focus on the
Norwegian Continental Shelf area. He began his career
in 2006 as a geologist with Rosneft in Krasnodar,
Russia, and worked on exploration projects in
the Ciscaucasia basin. He joined Schlumberger
PetroTechnical Services (PTS) in 2011 and served
as a geologist and then senior geologist working on
exploration projects in the Timan-Pechora, West
Siberia, Barents Sea and West Black Sea basins.
Anatoly holds an MSc degree in petroleum geology
from the North-Caucasus Federal University, Stavropol,
Russia. He is pursuing a PhD degree in regional
geology from Lomonosov Moscow State University.
Sandeep Kumar Chandola is a Custodian of
Geophysics with PETRONAS Carigali Sdn Bhd in
Kuala Lumpur. He served with Oil and Natural Gas
Corporation, the Indian national oil company, for
more than 20 years before joining Petronas Carigali
in 2005. His work has supported the design of 3D
acquisition geometries and the introduction of new
geophysical technologies to the company. He has a
master’s degree in physics from Hemvati Nandan
Bahuguna Garhwal University, Sringar, Uttarakhand,
India, and a specialized diploma in petroleum
geophysics from the Indian Institute of Technology
(IIT) Roorkee, Uttarakhand. He is a member of the
SEG, the European Association of Geoscientists and
Engineers and the Society of Petroleum Geophysicists
(India), an SEG Honorary Lecturer and an adjunct
lecturer at Universiti Teknologi PETRONAS, Malaysia.
Sandeep has authored more than 50 publications and
is a recipient of the National Petroleum Management
Programme Award for Excellence from the government
of India.
Chris Cunnell leads Technical Sales and Marketing
of IsoMetrix* for WesternGeco in Gatwick, England.
Chris, who has more than 20 years of geophysics
experience, joined Schlumberger in 1997 and has
May 2016
worked in technical, service and marketing managerial
positions in the UK, US and Egypt. Before joining
the team for IsoMetrix technology, Chris was based
in Cairo and managed advanced imaging services,
including full waveform inversion and Seismic
Guided Drilling* service, across the Middle East
and North Africa. He received an MBA degree from
the Rotterdam School of Management at Erasmus
University, the Netherlands.
Low Cheng Foo is Custodian of Geophysical Acquisition
for PETRONAS Carigali Sdn Bhd in Kuala Lumpur,
where he is involved with new technology projects
such as broadband, multicomponent, multiazimuth
and full azimuth seismic data acquisition. He has 35
years of experience with the company. Previously, he
was head of acquisition after serving as an acquisition
and processing geophysicist. He has been involved in
land, marine and transition-zone seismic acquisition
programs in various countries in Southeast Asia, the
Middle East, Suriname and Cuba. Low earned a BSc
(Hons) degree in physics, majoring in geophysics, from
the University of Science Malaysia in Penang.
Malcolm Francis is a Schlumberger Advisor and the
Eastern Hemisphere Exploration Services Manager
for WesternGeco in Gatwick. Before his current role,
he held technical and management positions as the
Eastern Hemisphere multiclient chief geophysicist,
global manager of geology and interpretation
and senior manager E&P solutions. Earlier in his
career, Malcolm managed the special processing
and interpretation departments. He began in the
industry in 1980 with Western Geophysical, where he
undertook collaborative research with Saudi Aramco.
He obtained a bachelor’s degree in geology from the
University of Manchester, England, and MSc and PhD
degrees in geophysics from Imperial College London.
Malcolm is a member of the European Association
of Geoscientists and Engineers, the SPE, SEG and
Petroleum Exploration Society of Great Britain and is
a Fellow of the Geological Society of London.
Shruti Gupta is an Area Geophysicist for Schlumberger
in Gatwick, England, where she provides technical
support for time and depth processing of marine and
ocean bottom cable (OBC) seismic data. Shruti, who
has more than seven years of experience in the oil and
gas industry, started her career with Schlumberger
as a field geophysicist on a land and transition zone
seismic acquisition crew in Egypt. She then worked
with the depth imaging group in Houston. She has an
MSc degree in applied geology from the IIT Kharagpur,
West Bengal.
Michelle Tham is the Technical Support Manager
for WesternGeco in the Asia Pacific region as well
as the Petrotechnical Expertise Discipline Career
Manager for the Schlumberger Asia region; she is
based in Kuala Lumpur. She began her career with
Schlumberger in Calgary and has worked in the US,
Myanmar, Indonesia, Australia, Nigeria, UAE and
Malaysia. Before her current position, she served as a
seismic data processing geophysicist, data processing
supervisor, staff geophysicist, area geophysicist,
seismic survey design and modeling manager and
geophysics global discipline career manager. Michelle
holds a BS degree in geophysics from the University
of Calgary.
Peter Watterson is the Manager of the Marine
Geosolutions Technology Commercialization group
for WesternGeco in Gatwick. His focus is on research,
engineering and marketing of various marine seismic
acquisition and processing technologies. Pete
began his career in the geophysics industry with
Western Geophysical in 1991 in London. He has held
positions in seismic data processing and technology
management in the UK, Venezuela, US, Trinidad and
Brazil and worked for several years as the regional
geophysicist for WesternGeco for South America. He
received a BSc degree in physics from the University
of Leeds, England.
An asterisk (*) denotes a mark of Schlumberger.
15