Assessment of subsurface shallow gas expressions

Assessment of Subsurface Shallow Gas Expressions,
Netherlands Offshore F3 Block,
in the Dutch Central Graben of the North Sea.
To
Geophysics Department, Faculty of Science
Cairo University, June 27, 2015

ACKNOWLEDGEMENTS
We would like to express our thanks and gratitude to Prof. Dr. Mohamed G. El-Behiry,
Professor of Applied Geophysics, and Geophysical Consultant for his Supervision on this
project, support and providing constructive comments and instructions that improve
the work.
We would like to express our thanks to Prof. Dr. Mohammed Mustafa Ghobashy,
Head of the Geophysics department, faculty of Science, Cairo University for his support
and encouragement.
We would like to express our sincere thanks and deep appreciation to Mohamed Salah
Sedek, staff of the geophysics department, Cairo University for his keen interest and
comments to improve this work.
We would like to express our thanks and gratitude to Ahmed Said Ahmed El-Wardany,
Senior Geophysicist at Agiba Petroleum Company for helping us to solve some of the
problems that we faced in petrel.
We would like to thank dGB Earth Sciences for providing 3D seismic dataset of Dutch
Offshore F3 Block

Abstract
Expressions of shallow gas of Dutch sector of the North Sea can be found on 3D seismic sur e s. A d the e
may be considered as a good accumulation for Hydrocarbon (gas).
We trying to make an assessment for these expressions by using the published seismic data of F3 block in
Netherlands Dutch Sector and well-logging data. To determine the most significant accumulation of gas.
We have to perform a qualitative and quantitative interpretation as (seismic interpretation, well logging
analysis, colored seismic inversion, and seismic modelling (structural and property models)). And we found the
most significant accumulation located in the (southern east) of the survey
In the first discussion the geological history of southern north sea in general then we focus specifically on the
studied area (F3 Block). We discuss the surface geology, geological setting, structure setting, tectonic evolution,
stratigraphic framework, salt tectonics, and finally petroleum geology.
In the second discussion we using petrel Software to applied the following steps:
1. Creating synthetic seismogram for the wells that have time depth curves from check shot.
2. Fault and horizon interpretation.
3. Depth conversion by Generation velocity model.
4. Modeling of structure framework and structure gridding.
5. Pillar grid and Fault Modeling
6. Prepare a Petrophysical evaluation of the potential gas reservoir of the study area are.
This steps applied to provide 3D seismic data interpretation about the studied area and also detecting the areas
with structure and Stratigraphy feature that could contain commercial accumulation of hydrocarbon.
Finall , this stud e o e ds suita le a eas o the depth aps that a e e pe ted to e good ese oi ….!!

Content
1. Introduction …………………………………………………………………………………………… 8
2. Geological Background …………………………………………………………….…………….
2.1 Introduction of Geolog ……..…………. 13
2.2 Geological “etti g ……………….…..…….
. Te to i s “etti g …………………….……..
. “alt Te to i s ………………………….……..
. “t atig aph ………………………….………..
2.6 Petroleum Syste ………………………….
. H d o a o pla ……………………..……
2.8 Geological stud of A ea F Blo k …..
3. Building a 3D project …………………………………….…………………….………………..
3.1 Synthetic Seismogram ………….….
3.2 Seismic Well Tie …………………….…
3.3 Horizon Interpretation …………….. 30
3.4 Seismic Attributes ……………………..
3.5 Fault Interpretation …………………. 42
. Iso ho es …………………………………..46
. Do ai Co e sio …………………………………………………………………………… 47
. Make Velo it Model …………….
. Depth Co e sio ………………….
. A e age Velo it Cu e ….……….
. “t u tu e Modeli g …………………………………………………..………………………
5.1 Structure Framewo k ……..………..
5. “t u tu e G iddi g …………………….
6. Well Loggi g A al sis ………………………………………………………………….. 60
6. I fo atio …………………………………………… 60
6.2 Cal ulatio s ………………………………………….. 60
7. Cross plots (Gas Indicator) ………………………………………………………… 65
8. Colored Seismic I e sio …………………………………………………………. 68
9. Fault Modeli g …………………………………………..………………………..………….. 70
10. Pilla G iddi g ……………………………………..…………………………………………… 73
11. P ope t Modeli g ……………………………………………..…………………………… 77
11.1 QC pro ess of Buildi g the Geo et ………….78
11. “ ale up Log ………………………………………….……. 79

11. Pet oph si al Modeli g …………………………..….
11. Ups ali g ……………………………………………......... 83
12. Prospect and Conclusion …………………………………………………………..
. ‘efe e e …………………………………………………………………………………. 90
Table of Figures
Figure (1) Location of Study Area
Figure (2) Sketch of the Marine Survey
Figure (3) Schematic representation of a traditional seismic survey.
Figure (4) Show the coordinate and Length of lines and the separation distance between lines with the Wells
Figure (5) Map Show the location of study area
Figure (6) Paleogaeographic reconstruction of the North Sea area and surrounding plates during the Caledonian phase.
Figure (7) Paleogaeographic reconstruction of the North Sea area and surrounding plates during the Variscan phase.
Figure (8) Paleogaeographic reconstruction of the North Sea area and surrounding plates during the Kimmerian phase.
Figure (9) Paleogaeographic reconstruction of the North Sea area and surrounding plates during the Alpine phase.
Figure (10) Schematic diagrams of the evolution of salt diapers.
Figure (11) Lithostratigraphy and tectonic history of the Netherlands offshore sector.
Figure (12) .Hydrocarbon systems in the Dutch subsurface.
Figure (13) Trap Style of Quaternary plays
Figure (15) Sketch of the Neogene fluvio deltic system in the Block
Figure (16) Show the Structure element of North Sea
Figure (17) a) The Thickness Map of Chalk Group (Late Cretaceous) b) The Thickness Map of the Lower and Middle North
Sea Group.
Figure (18) Cross Section A-A" which pass the F3 block
Figure (19) Show AI, Rc, Synthetic trace and Original trace at each depth on seismic well Tie.
Figure (20) a) Original inline 447 and synthetic trace of well F3-04, b) The Shift process for tie equals 3 msec,
c) the Original inline 447 after shifting.
Figure (21) a) display formation Tops on inline 447, b) picking the Horizon (FS8) on inline 447.
Figure (22 ) a) Tie Points of FS8 were created by interpretation along inline and x line b) This figure display the Location at
Cube that we used on the previous 5 figures.
Figure (23) Ghost Match the Horizon
Figure (24) a) Show the Color Code (intersections lines have the same Time).
b) Convert Horizon grid to Surface Map of FS8.
Figure (25) show all Horizons and well F3-04 and at Inline 447
Figure (25b) Show the Termination of Horizon and the Horizon Ages
Figure (26) 3D View of Seismic inline & xline, Horizons and Wells
Figure (27) a) seismic cube after applying Structure Smoothing Attributes, b) Raw seismic data at inline 100,
c) inline 100 after applying Structure Smoothing Attributes

Figure (28) a) Seismic Cube after applying the Variance Attribute, b) Raw Seismic data at inline 100,
c) inline 100 after applying the Variance Attribute.
Figure (29 ) a) Seismic Cube after applying Ant Tracking Attribute, b) Raw Seismic data at inline 100,
c) inline 100 after applying the Ant Tracking Attribute, d) Inline 120 & time Slice to highlight fault pass.
Figure (30 ) a) Seismic Cube after applying Chaos Attribute, b) Raw Seismic data at inline 100, c) inline 100 after applying
the Chaos Attribute, d) inline 100 after applying the Chaos Attribute in addition to Structure Smoothing Attributes.
Figure (31) Shows Horizons with important Faults at seismic line 140 inline.
Figure (32) Show All Faults cut Horizons in seismic line 140 inline.
Figure (33) show the extensions of all Faults
Figure (34 ) a) show the trend of faults 01,02,03,011 is at N-S b) show trend of faults 05,06,07,08,09,10 is at NE-S
c) show trend of faults 04 is NW-SE, but F17 & F18 is NE-SW
finally F19 it's trend divided into two parts 1-is NE-SW 2- is N-S.
Figure (35 ) a) show the Trend of faults 1,3,4,5,6 Is NW-SE b) Show the trend of Fault 2 is NE-SW
c) Show the Trend of Fault (-12) is NE-SW.
Figure (36 ) a) Show the Cut off the Ooseterout Fm by Faults 1 & 6 b) Show the Cut off the Berda Fm by Faults 1, 6, 4, 5,
c) Show the Cut off the base Tertiary by Faults 01, 03, 05, 06, 08, 09, 10, 11, 12.
Figure (37) zone of shallow: it has the minimum thickness at the north-east, and its maximum thickness at the southwest
as becomes thicker in the north-east direction, Zone of FS8: it becomes thicker in the west direction and thinner
in the east direction.
Figure (39) a) show example of Vo Surface, b) show example of K factor Surface.
Figure (40 ) this figures are showing the output of velocity model in time domain and depth domain firstly Shallow layer ,
FS8, FS7, Truncation, Top Forest, MF4, FS4, Mid Miocene Unconformity, base Tertiary, Finally the Salt layer
Figure (41) a) Velocity Cube, b) inline of Velocity Cube, c) xline Velocity Cube, d) time Slice of Velocity Cube.
Figure (42) to the left, input data like fault interpretations and horizon interpretations. To the right, the structural
framework with faults and horizons.
Figure (43) examples of truncation of Faults at Structure framework.
Figure (44) the transform from Faults to Surfaces at output of Structure Framework.
Figure (45) show Faults from Top layer to Bottom Layer at the zone of our interest.
Figure (46) Show the Output of Structural Framework (Horizons and Faults)
Figure (47) Show the Output of Structural Framework (Horizons and Faults) in actual Dimensional.
Figure (48) Building Model by grids (324 I x 475 J) = 153900 grids which each grid will Contains Multi Value of PHI & K and
later Pressure with RE Department.
Figure (49) Intersections of Layer Gridding
Figure (50) Focus of the grids (324 I x 475 J) = 153900 grids which each grid will Contains Multi Value of PHI & K and later
Pressure with RE Department
Figure (60) Show the number of Regions forming the Model.
Figure (61) intersections of Region Gridding.
Image (1) Base map for F3 block survey
Image (2) Logs of sonic GR resistivity and density with depth
Image (3) Multi-well histogram: gamma ray
Image (4) Logs of GR and Vsh with depth
Image (5) Logs of density and total porosity with depth

Image (6) Logs of density, total porosity and effective porosity
Image (7) Logs of resistivity, total porosity and water saturation
Image (8) Logs of effective porosity, total porosity, water saturation and permeability
Image (9) Logs of p wave velocity and s-wave velocity from castagna, corrected s-wave velocity and velocity ratio with
depth.
Image (10) Logs of p impedance, s-impedance, Mu-rho and lambda-rho with depth
Image (11) Logs of Mu rho, lambda-rho, and Vsh
Image (12) Zone with low Mu-Rho and low lambda values indicate to gas san
Image (13) Logs of Vp, vs ratio, p-impedance, and Vsh with logs
Image (14) Isolated zone with low p impedance and low velocity ratio close to 1.5 is indication of gas sand.
Image (15) Isolated zo e with low p i peda e differe e etwee la ’s o sta ts is i di atio of gas sa d
Image (16) Logs of mu-rho lambda rho difference and p-impedance with depth
Image (17) finally, these panels show the time and frequency domain operator which has been calculated.
Image (18) Bright spots BS1 and BS2 in FS8 trapped at fault
Image (19) Bottom of BS1 high positive relative impedance top of BS2 and BS4 high negative relative impedance
Image (20) BS4 accumulation due to high structure (elevation) may due to salt doming
Image (21) Tilted BS (short extension)
Figure (62) a) Show the Pillar (Have one stick of Fault), b) Show the Varies types of Fault Geometry,
c) Show the Control of Pillar (Editing)
Figure (63 ) Show the Edit of Faults 5 to truncate bottom with the Major Fault 1 also apply to F6 with F1, F4 with F1, F3
with F1, F9 with F8, F14 with F8. b) Seismic Line 130 Show the Truncation of Faults.
Figure (64) edit the Fault curvature between the Upper Thrown and down Thrown to Avoid the Horizon Spikes in
Modeling Horizons
Figure (65) Creating the Boundary around the Faults Zone and include Well Distributions for Petrophysical Study, then get
the trend for each Fault to control the Geometry for avoiding the –ve Cells.
Figure (66) a) Show the Mid Skelton of Faults of Pillar Grid, b) Show how the Cells arrangement with the Trend of Faults,
c) Show the wrong case if doesn't give trend for Faults.
Figure (67) Show the Steps of Making Horizon and Zones & Layering.
Figure (68) compute the Inter Layering between Horizons from well Section.
Figure (69) Show the Output of Making Horizon and Zones & Layering
Figure (70 ) a) Cube of Cell angle (QC-1), b) the Cube after Filtering by Showing the Cells which have lower 15 deg over the
90 degree, c) Show Histogram of data is Good * through the Major part have Low angle over the 90 deg.
Figure (71) a) Cube of Cell inside Out (QC-2), b) Histogram Show the Major of Cube is lying in Safe Side (0 to 0.5).
Figure (72) a) Cube of Bulk Volume (QC-3), b) Histogram show the Major Data have a Constant Volume, except the cells
which associated with Faults.
Figure (73) the result of the Scale up well logs process is placed as a property model icon in the Properties folder for the
3D grid. It only holds values for the 3D grid cells which the wells have penetrated.
Figure (74) The Scale up well logs process assigns log values to the cells in the 3D grid that are penetrated by the wells.
Figure (75) a) Porosity Cube, b) Inline of Porosity Cube, c) xline of Porosity Cube.
Figure (76) a) Permeability Cube, b) Inline of Perm Cube, c) xline of Perm Cube

Figure (77) a) Gridding and Upscaling of Porosity cube, b) Gridding and Upscaling of Permeability cube, c) Gridding and
Upscaling of layering cube.
Figure (78) histogram a) show the Porosity calculating by Arithmetic method b) Show the arithmetic Porosity with its
average (by Volume – Weighted).
Figure (79) a) show the Permeability calculating by Arithmetic & Harmonic method, b) Show the (A & H) Permeability with
its average (by Directional Averaging).
Fig (80) Show the ability to get Multi value for each grid.
Figure (81) a) TWT map and Depth Map Show the Trap, b) PHI slice of FS8 Show the High Porosity, c) K slice of FS8 show
The High Permeability, d) Grid of Slice Show the Multi Value Property for each Grid
Figure (82) Show the Saturation Cube, Figure (83) Show the Volume of Gas at FS8.

Assessment of Subsurface Shallow Gas Expressions | Cairo University
Graduation project 2015
8
1.Introduction
The Study Area is Nethe la ds Offsho e F Blo k, lo ated o the top of the Dut h Ce t al G a e of the
No th “ea. (N ° . / E ° 47.07)
Overview of Marine Survey
I a i e su e s the ost idel used seis i sou es a e ai gu s a d the e ei e s a e piezoele t i
se so s desig ated h d opho es, hi h a e dist i uted i side a tu e filled ith ke ose e, alled a
st ea e . All the a uisitio e uip e t sou es a d e ei e s used i a i e su e s is to ed ehi d
the seis i essel “he iff a d Gelda t, .
Seismic Sources:
Ai gu s a e i pulsi e ethods that eate seis i e e g . A ai gu is a li d i al de i e hi h is
filled ith high p essu ed ai that is sudde l eleased i to the ate ge e ati g a p essu e pulse.
Usi g a a a of a ia le size ai gu s Figu e athe tha usi g a si gle ai gu is o ada s the
sta da d p o edu e i the oil a d gas e plo atio i dust ; this ethod allo s p odu i g a sig al that
at hes as lose as possi le the theo eti al desi ed ha a te isti s of the i put sou e.
The biggest challenge in airguns is producing a seismic pulse as close as possible to a spike, because after the
first bubble pulse, an undesired train of waves is normally created (McQuillin et al., 1984). This effect is called
u le effe t a d its o igi is elated to alte atel o e ts of e pa sio a d o t a tio of the ai u le
formed by the shoot.
Many of the acquisition seismic surveys use arrays of variable size airguns disposed in a special geometry and
fired at different intervals to minimize the bubble effect. Synchronizing the firing time to align the first pressure
peak will produce a cancelation of the oscillatory signal, producing a signal with frequency as close as possible
to a spike pulse. Special types of airguns, called GI-guns were especially designed to minimize this effect (Sheriff
and Geldart, 1995).

9
Seismic Receivers
The receivers used in marine surveys are hydrophones, Standard hydrophones are piezoelectric sensors towed
inside a streamer and transform the compressional p-waves into an electrical signal.
A streamer is a neoprene tube where hydrophones are placed by groups in regular intervals with a total length
from 6 to 8km (Alfaro et al., 2007; Telford et al., 1989). The streamer is filled with a liquid lighter- than-water
(e.g. kerosene) to turn it neutrally buoyant. Connection wires in between hydrophones and from the receiver to
the recording system are also included inside the streamer (Sheriff and Geldart, 1995).
H d opho es a e a a ged i se tio s alled li e se tio s a d i ea h se tio the e a e t e t o o e
hydrophones spaced approximately 1m.
In terms of seismic processing the signal received at each hydrophone inside a section is summed up and is
considered just one receiver group (or channel). This technique improves the signal-to-noise ratio but when
there is a great component of noise acquired with the signal, it can damage the quality of the data (Alfaro et al.,
. Dead se tio s se tio s ithout h d opho es, a e pla ed et ee li e se tio s to gi e the desi ed
length and configuration to the streamer.
Figure (2) Sketch of the Marine Survey

10
Seismic Marine Acquisition Surveys
A marine acquisition survey requires that the water column is deep enough (more than 10m deep) to allow
freedom of movements for seismic vessels with lengths between 30 to 70m. Marine seismic acquisition is faster
and consequently cheaper when compared to land surveys, since there are less non-productive time5 (Telford
et al., 1990; Sheriff and Geldart, 1995).
In conventional seismic acquisition surveys, the data is acquired by a single seismic vessel sailing in straight
parallel lines, with opposite directions providing a coverage of about every 12.5m, with multiple streamers, over
a target area (Figure 16). The seismic vessel is normally equipped with eight to ten streamers and a variable
number of airguns and source arrays, depending on the target depth (Alfaro et al., 2008).
This kind of survey has a high percentage of non-productive time represented by curved path between the end
of one line and the beginning of the next. In total, non-productive time can reach 50% of the total duration of
the survey, therefore increasing acquisition costs (Buia et al., 2008).
If well planned, this acquisition geometry is enough to obtain a reasonable imaging of the subsurface for
almost all geological environments. Moreover, since it is a standard oil industry acquisition scheme, seismic
processing flows are well known and easily applied with high effectiveness in noise reduction and
improvement of the data quality. However, there are imaging limitations related to some geological.
Contexts which cause ray bending (e.g. areas affected by intense salt tectonics) and when there are
infrastructures that obstruct the acquisition path creating coverage gaps (Alfaro et al., 2007).
Marine seismic acquisition surveys have narrow azimuth-offset coverage, just +/- 10º azimuths for far offsets
(Figure 19a), since the illumination is just in one direction and the direction of the reflected ray path will be
close to the vessel track. In order to attenuate the lack of azimuth-offset illumination of this acquisition
geometry, it should be carried out ensuring the maximum possible trace coverage per bin (Alfaro et al., 2007;
Buia et al., 2008).
This conventional acquisition geometry is the mostly used acquisition method to acquire 3D seismic data
worldwide. However, seismic data can easily have low quality, making the interpretation process very difficult,
leading to possible incorrect reservoir prediction and characterization. Alternative seismic acquisitions
geometries based on more than one sailing direction have been more recently developed to obtain more
consistent and reliable 3D seismic data (Alfaro et al., 2007).
Figure (3) Schematic representation of a traditional seismic survey. The vessel sails in parallel lines with
opposite directions, curved paths represent non-productive time because the acquisition system is switched
off. The target area is divided in bins for the purpose of processing the data (Buia et al., 2008).

11
Identification of Data
A Coordination system (x, y in UTM31, ED50 format)
The 3D seismic survey is covering an area of approximately 16×24 km2.
The data set of this study covers only the younger sequences and has become publicly available.
The research data consisted of:
1) 3D seismic data of F3 Dutch offshore block:
2) well log data (GR. sonic, Porosity and density) of four wells, i.e. F02-1, F03-2, F03-4, and F06 -1.
The data volume consists of 650 in-lines and 950 cross-lines.
The inline length is 23678.35m and the in-line interval is 25m.
The cross-line length is 16124.43m and the cross-line interval is 25.03m.
The sampling rate is 4ms and the number of samples per trace is 462
3D seismic data has European polarity with zero phase by mainly observing two geological features
(i.e. seabed and shallow gas sand).
The seismic data are post-stack time migrated, data and therefore a function of two-way travel time.
The original F3 dataset is rather noisy. To remove the noise, a dip-steered median filter with a radius of
two traces was applied to the data.
Figure (4) Show the coordinate and Length of lines and the separation distance between lines with the Wells

12
The Programs
The software for this research were a Petrel, Techlog and Hampson-Russell
We proposed all of them a part of solutions to help finding new hydrocarbon fields with lower
exploration risks at under-explored areas.
Petrel
Petrel is a Schlumberger owned E&P software platform that provides an integrated
solution from exploration to production. It allows the user to interpret seismic data,
perform well correlation, build reservoir models suitable for simulation, submit and
visualize simulation results, calculate volumes, produce maps and design development
strategies to maximize reservoir exploitation.
It addresses the need for a single application able to support the "seismic-to-simulation" workflow,
reducing the need for a multitude of highly specialized tools. By bringing the whole workflow into a
single application risk and uncertainty can be assessed throughout the life of the reservoir.
Techlog
Techlog is a Schlumberger owned Windows based software platform intended to
aggregate all the wellbore information. It allows the user to interpret any log and core
data. It addresses the need for a single platform able to support all the wellbore data
and interpretation integration workflows, reducing the need for a multitude of highly
specialized tools. By bringing the whole workflow into a single platform risk and
uncertainty can be assessed throughout the life of the wellbore.
Hampson-Russell
Hampson-Russell is owned by CGG (originally an acronym for Compagnie Générale de
Géophysique) that is a French-based geophysical services company founded in 1931.
Hampson-Russell software integrates all the data, tools and processes for reservoir characterization
into a simplified and intuitive package for easy navigation, quick learning curve and fast results.
The Hampson-Russell software suite of reservoir characterization tools encompasses all aspects of
seismic exploration and reservoir characterization, from AVO analysis and inversion to 4D and
multicomponent interpretation.

13
2. Geological Background
2.1 Introduction
The North Sea basin is located in NE Europe and lies between the United Kingdom, and Norway just
north of The Netherlands and can be divided into many sub-basins. The Southern North Sea basin is
the largest gas producing basin in the UK continental shelf, with production coming from the lower
Permian sandstones which are sealed by the upper Zechstein salt.
The evolution of the North Sea basin occurred through multiple stages throughout the geologic
timeline. First the creation of the Sub-Cambrian Peneplain, followed by the Caledonian Orogeny in the
late Silurian and early Devonian. Rift phases occurred in the late Paleozoic and early Mesozoic which
allowed the opening of the NE Atlantic. Differential uplift occurred in the late Paleogene and Neogene.
The geology of the Southern North Sea basin has a complex history of basinal subsidence that had
occurred in the Paleozoic, Mesozoic, and Cenozoic. Uplift events occurred which were then followed
by crustal extension which allowed rocks to become folded and faulted late in the Paleozoic.
Tectonic movements allowed for halokinesis to occur with more uplift in the Mesozoic followed by a
major phase of inversion occurred in the Cenozoic affecting many basins in NW Europe. The overall
saucer-shaped geometry of the southern North Sea Basin indicates that the major faults have not been
actively controlling sediment distribution.
2.2 Geological setting
The North Sea area was the site of a triple plate collision zone during the Caledonian orogeny .Four
major tectonic events influenced the area since the Cambrian :
(i) the Caledonian collision during Late Ordovician to Early Silurian,
(ii) subsequent rifting and basin formation mainly identified in the Carboniferous to Permian,
(iii) Mesozoic rifting and graben formation and
(iv) inversion during Late Cretaceous to Early Tertiary
The Caledonian collision involved two large continents, Baltica to the east and Laurentia to the west,
as well as the micro-continent Avalonia to the south which by middle Ordovician times separated from
Figure (5) Map Show the location
of study area

14
Gondwana. Baltica and Avalonia were prior to the collision separated by the narrow Tornquist Sea
while Laurentia was separated from the two opposing continents by the larger Iapetus Ocean.
2.3 Tectonic setting
The Mesozoic structures underneath the North Sea can be seen as a failed rift system. After initial
crustal extension and the formation of rift basins during the Triassic and Jurassic periods, the extension
concentrated on the other side of the British Isles, which would create the northern Atlantic Ocean.
The rift basins even saw some inversion during the late Cretaceous and Eocene epochs. From
the Oligocene onward, tensions in the European crust caused by the Alpine orogeny to the south
cause a new, more modest phase of extension. Some grabens in the area are still active.
2.3.1 Tectonic Phases
a) Caledonian Phase
Although most wells in the North Sea do not reach deep enough depths to provide data of the
basement of the North Sea Basin, onshore outcrops and some deep wells have allowed correlation of
this basement to the Caledonian tectonic phase. These are mainly metamorphic and igneous rocks
that have strongly been deformed by the Caledonian mountain building phase.
The Caledonian phase was active from about 510 Ma until approximately 390 Ma.
Plate Tectonic Setting:
The Caledonians were the result of the collision between Laurentia, Baltica and Avalonia during the Pre
Silesian. It was one of the first orogenies that would eventually be the result of the formation the
super continent Pangaea. In the Early Paleozoic almost all landmass was Concentrated and united to
form the supper continent Gondwana. Then, from 650 to 550 Ma the smaller continents of Baltica,
Laurentia and Avalonia rifted to the north and the Iapetus Ocean developed in between these
continents.
These continents were now positioned around 30º on the Southern hemisphere and around 505 Ma
the first proof of subsidence of the Iapetus Oceanic crust subsiding below Baltica was recorded in the
rock record of Scandinavia (Finnmarkian phase). The tectonic metamorphic evolution of the
Finnmarkian phase are coeval with the intrusion of Alkaline igneous bodies of the Seiland Igneous
Province (Sturt et al., 1978) This phase thus probably reflects the collision of island arcs against Baltica,
while the Iapetus ocean slowly closed. A second minor collision phase is reflected in the Jammtlandian
phase around 455 Ma. Similar collisional phases have been recorded on the Laurentia side of the
Iapetus where an island arc caused the tectonic orogeny between 480 and 435 Ma.

15
b) Variscan (Hercynian) Phase
The Variscan phase occurred during the late Paleozoic from late Devonian times to the End of the
Permian (380 to 250 Ma). A gigantic mountain range was produced by the suture of Gondwanaland
and Laurussia and this resulted in a new super continent, Pangaea.
It s a i po ta t te to i phase fo the No th “eas h d o a o potential, especially in the South.
This is because the Variscan phase marks the beginning of very important sedimentary infill into the
basins underlying the current North Sea.
At the end of the Devonian Gondwanaland started colliding with Laurussia in the North. The area of
the North Sea was now located just above the equator around 10º latitude.
The end of the Variscan phase would finally produce the supercontinent Pangea but this suture can be
subdivided into several phases. At the end of the Early Devonian Laurussia was assembled and the
cratons of Siberia and China had started merging with it in the East.
In the Late Devonian and the Beginning of the Carboniferous the small archipelago of Armorica
collided with the South of Laurussia. This marked the beginning of the Variscan phase and caused
mountains to form just east of the preexisting Caledonians. The Variscan orogony was the result of a
series of smaller collisions between Laurussia and smaller continental plates moving northwards.
Figure (6) Paleogaeographic reconstruction of the North Sea area and surrounding plates during the
Caledonian phase. Red arrows depict general plate movements and the red dot shows the location of the
North Sea.
Figure (7) Paleogaeographic reconstruction of the North Sea area and surrounding plates during the Variscan
phase. Red arrows depict general plate movements and the red dot shows the location of the North Sea.

16
c) Kimmerian Phases
The Kimmerian phase marked the beginning of the breakup of Pangaea and the creation of the
continental configuration as we know it today. It is a phase of mayor rifting and produced small
confined oceanic basins ideal for hydrocarbon accumulation due to anoxic conditions.
Organic rich deposits, primarily the Kimmeridge clays, were widely deposited during this phase and it is
of mayor importance, especially in the Northern North Sea. The Kimmerian phase lasted most of the
Mesozoic and stretches from the Late Triassic to the Early Cretaceous (240 to 120 Ma). It is generally
subdivided in an Early, Mid and Late Kimmerian phase.
During the Jurassic rifting activity reached its peak and North America moved away from Eurasia. This
rift first developed in the North and slowly spread southwards.
At the beginning of the Jurassic the Panama straight was still closed causing the Tethys Ocean and
many of its branches to contain rather stagnant stratified seawater.
Only during the Cretaceous the Panama straight would open up causing an oceanic current to develop
from East to West It was also during the Cretaceous that the Southern part of the newly formed
Atlantic Ocean opened up between Africa and South America. At the end of the Mesozoic the North
Sea area had almost reached its current position.
Figure (8) Paleogaeographic reconstruction of the North Sea area and surrounding plates during the Kimmerian
phase. Red arrows depict general plate movements and the red dot shows the location of the North Sea.

17
d) Alpine Phase
In the late Cretaceous around 100 Ma the Alpine phase commenced. This last tectonic phase is still
active today and has formed Europe as we currently know it. Of most small plates in the
Mediterranean area. During this phase the North Sea acquired its current configuration.
Subsidence rates were still high and the Tertiary succession is about 2500m thick. Sediment deposited
during this time has little to no source rock potential and also mayor reservoirs are still to be
discovered. The structures formed during this time are of prime importance though. In most cases the
now compressional setting caused by tectonic activity in the South caused inversion tectonics of most
pre-Tertiary structures.
By the late Cretaceous the North Sea area had moved to about 60º N and rifting activity had almost
stopped in the area. At the same time North America was moving Westwards as the Atlantic Ocean
opened up. Also towards the South, South America was rifting away from Africa, while the later
rotated anti-clockwise and started moving North as shown in Fig.5
Figure (9) Paleogaeographic reconstruction of the North Sea area and surrounding plates during the Alpine phase.
Red arrows depict general plate movements and the red dot shows the location of the North Sea.

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2.4 Salt Tectonics
Salt tectonics is the movement of a significant amount of evaporites encompassing salt rock within a
stratigraphic sequence of rocks. Within the Southern North Sea basin this plays a huge role in the oil
and gas industry because the tectonic events throughout the geologic timescale allowed these
halokinesis structures to trap areas of natural resources.
The major salt basin were clearly deposited by gravity driven measurements with three basinal areas
the German, English and Norwegian basins .The Southern North Sea basin concerns the English and
German zechstein salt basins. The German basin can be categorized as a salt wall which is a linear
diapiric structure possibly related either to basement faulting or to the controlling effect of regional
dip, and the English basin is categorized as a salt pillow type of structure, developed in association with
thinning of overlying beds but without diapiric effects. The major types of salt structures in this basin
are salt pillows or swells which lie in the cores of buckle fold structures.
Figure (10) Schematic diagrams of the evolution of salt diapers. a) Jurassic (201–154 Ma); b) Rijnland–Early Chalk
Group (139–100 Ma); c) Upper Chalk Group (75–61.6 Ma); d) Base Lower North Sea Group (61.6 Ma); e) Middle North
Sea Group (61.6–12 Ma); f) present day geometry.

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2.5 Stratigraphy
- Paleozoic:
The oldest stones that you can find at the surface of the earth originate from the Carboniferous
period. This era started 355 million years ago and ended about 290 million years ago. In the north and
south of the Netherlands, this laye of sto e lies fou kilo ete s elo the ea th s su fa e. Due to
erosion however, this stratum of stones has since disappeared. The layer on top of the Carboniferous
layer is about 250 million years old (the Permian era). This layer consists of course to fine grained
clastic sediments (sandstone), is known for its natural gas reservoir. During the Permian, in the north
of the Netherlands large quantities of rock salt were produced (zechstine Group).
- Mesozoic:
The era Triassic followed the Permian. Some stones that were formed are: sandstone, evaporite
(sediments that were created through of evaporation of water), chalk, dolomite, shale and gypsum.
Shale disappeared almost everywhere because of erosion. By the end of Triassic (about 200 million
years ago), a sedimentation process started which would last for approximately 20 million years.
During the Jurassic period (200 – 160 million years ago) rocks that may contain petroleum were
formed. This is why the ground under the North Sea contains so much petroleum.
Later, in the Cretaceous period, the sea played an important role in the development of the Dutch
landscape. Another consequence of the impact was an increase in the average sea temperature by 10
degrees Celsius. In some parts of Europe, the average sea temperature was at that time a comfortable
25 degrees Celsius – much warmer than the North Sea is nowadays during the summer.
- Cenozoic
The sediments of the Mesozoic were later covered with younger sediments. Clay layers that originate
from the Oligocene (40 – 24 million years old) are mined in quarries and used to produce bricks. In the
following era, the Miocene (24 – 5 million years ago), quartz and brown coal were formed in the
south-eastern part of the Netherlands. The Pliocene was the transitional stage between the Miocene
and the Pleistocene, which started 1.8 million years ago. The clay and sand sediments that can be
found in the surroundings of the city of Breda were formed during the Pliocene. In the Pliocene, the
rocks that were transported by the rivers Rhine and Meuse dominated the scenery.

20
Figure (11) Lithostratigraphy and tectonic history of the Netherlands offshore sector. Adapted from Duin et al.
(2006); formation characteristics from Van Dalfsen et al. (2006). Purple tectonic phases are extensional. Green
tectonic phases are contractional.

21
2.6 Petroleum system
In the Dutch subsurface the gas plays are volumetrically and economically by far the most important.
With respect to the ages of source rocks, reservoirs and seals these plays belong predominantly to a
Paleozoic hydrocarbon system. Where the thick Permian Zechstein salt is present, it provides an
effective seal between this system and the oil plays which belong almost entirely to Mesozoic
hydrocarbon systems.
Around 85% of all gas production has been from pre-Zechstein Permian (Rotliegend Group)
aeolian dune sandstones, and 13% from Triassic fluvial sandstones. Much of the remaining
production has been from Carboniferous fluvial sandstones.
Gas: source rocks and generation:
The principal source rocks for gas are the Upper Carboniferous, Westphalian coals and carbonaceous
shales, which are present in much of the subsurface. Almost all the gas found has been generated
from these source rocks.
The cumulative thickness of the coals is several tens of meters. They occur mostly in the Maurits
Formation (Westphalian B), and are less common in other Westphalian units. Because of Early Permian
uplift and erosion the Westphalian source rock thickness is locally much reduced. Where the total
Westphalian of ca. 5.5 km thickness is preserved, the maturities vary significantly from top to bottom.
Secondary source rocks for gas occur in basal Namurian organic rich shales. In most places these
source rocks became overcooked during deep pre-Kimmerian burial. Nevertheless, the Namurian is
thought to have contributed significantly to the nitrogen charge, which is mainly expelled at much
higher temperatures than hydrocarbon gas.
In general, hydrocarbon generation from the Westphalian coals was widespread until the Middle
Jurassic. After the Middle Jurassic, a distinction must be made between the Kimmerian rift basins and
the platforms and highs. During the Late Jurassic to Early Cretaceous rifting, hydrocarbon generation
accelerated within the rift basins as a result of increased subsidence.
This generation halted during the Late Cretaceous due to inversion related uplift and declining heat
flow. At the margins of the basins, where inversion had been limited and was followed by strong
Tertiary subsidence, for example on the south-west margin of the West Netherlands Basin, charge
from the Westphalian resumed during the Tertiary and continues until the present day.
The platforms and highs, on the other hand, were uplifted during the Late Jurassic, interrupting
hydrocarbon generation. Where subsequent burial caused temperatures at the Westphalian source-
rock levels to exceed the maximum temperatures reached earlier, gas generation resumed.
Secondary source rocks for gas occur in Upper Jurassic and Lower Cretaceous coals of the Delfland
Subgroup in the West Netherlands and Broad Fourteens basins, and of the Central Graben Subgroup of
the Dutch Central Graben and Terschelling Basin.

22
Figure (12) .Hydrocarbon systems in the Dutch subsurface.Arrows show from which source rocks the main
reservoirs have been charged with gas and/or oil. The Upper Permian Zechstein salt, present in much of the
subsurface, provides a regional seal between a Paleozoic gas and a Mesozoic oil and gas system. Not shown is
that with time probably 98% of the generated hydrocarbons escaped into the biosphere.

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2.7 Hydrocarbon play
Tertiary and Quaternary plays
In the IJsselmonde structure in the West Netherlands Basin, small amounts of gas have been tested
from the Lower Tertiary Basal Dongen Sand, which lies some 30 m above the base of the Lower North
Sea Group, and has average porosities ranging from 34 to 39%.
In the east Netherlands, the gas trapped in the Basal Dongen Tuffite in the De Wijk field has not been
developed because of anticipated subsidence problems during production.
The main Tertiary-Quaternary gas accumulations occur in the A and B blocks of the northern offshore
at depths of 400 to 700 m. Strong amplitude anomalies and deeper pull-downs on seismic profiles
clearly indicate the presence of gas in subtle structures of only several tens of meters height.
Most of the shallow gas accumulations are associated with gas chimneys, indicating leakage. Although
the gas-bearing sandstones had been seen on seismic, and were encountered in wells with deeper
objectives, it took until 1988 before well A12-3 tested potentially economic production rates from the
shallow gas discovered by well A12-1 in silty sands in the topsets of Plio-Pleistocene prograding shelf
sequences. Further shallow gas accumulations were discovered in B10, B13 and B16-1. Sand
production
From these unconsolidated reservoirs poses a major development problem.
Figure (13) Trap Style of Quaternary plays

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2.8 F3 Block Study Area
Location of F3
F3 is a block in the Dutch sector of the North Sea. Its coordinates are (N ° . / E ° . ) as
shown in Fig
Geological setting
The data set applied in this research is from the F3 block in the Dutch sector of the North Sea. Chalky
sediments were deposited in the F3 block at the end of the early Paleocene, but a sudden increase in
the supply of silica-clastics occurred because of the Laramide tectonic phase, which meant the
deposition of chalky sediments was concluded During the Neogene, sedimentation rates significantly
surpassed the subsidence rate and the North Sea.
Basin was defined by a period of rapid deposition and shallowing of the basin. The most important
geological occurrence in that period was the expansion of deltaic systems.
The delta systems in the North Sea region can be classified into two groups according to sources of the
sediments. Until the early Pliocene, the main transport factor was the Baltic river system that
deposited coarse fluvial sediments. Afterwards, German rivers became the main agent in the North
Sea .The Cenozoic sequence could be subdivided into two main packets separated by the mid Miocene
unconformity (MMU)
Figure (15) Sketch of the Neogene fluvio deltic system in the Block

25
The region between the Lower Tertiary and the mid-Miocene unconformities are known as the Lower
Cenozoic sequence. The area from the mid-Miocene unconformity up to the sea bottom forms the
Upper Cenozoic sequence.
The reflections from the layers between the unconformity and the Plio-Pleistocene boundary in the
Upper Cenozoic sequence are most interesting for this work. This region is a deltaic sequence
subdivided into three subsequences (Units 1, 2 and 3).
Unit 1 belongs to the first phase of the delta s e olutio a o e the u o fo it . Field e aluatio s
show that their height varies between 4 and 10 ms two way travel time. Unit 2 belongs to the second
phase of delta evolution and consists of sigmoid progradational reflection configurations. This unit
shows a prograding clinoform pattern formed by superimposed sigmoid reflections. Unit 3 belongs to
the final phase of delta evolution.
Structural of F3Block
Figure (16) Show the Structure element of North Sea

26
Figure (18) Cross Section A-A" which pass the F3 block
Figure (17) a) The Thickness Map of Chalk Group (Late Cretaceous)
b) The Thickness Map of the Lower and Middle North Sea Group

27
Building a 3D Project
3.1 Synthetic Seismograms
Synthetic seismograms are the bridges between geological information (well data in depth) and geophysical
information (seismic in time). This essentially involves a two-step process:
1. Time converting the wells by means of check shot data and sonic logs, establishing time-depth
relationships for the wells.
2. Generating synthetic seismograms from density logs, sonic logs and a seismic wavelet by calculating
acoustic impedance and reflection coefficients, which are then convolved using a wavelet.
Any changes to the time-depth relationship can be made and seismic horizons can be correlated with
the stratigraphic boundaries identified in the well logs.
3.2 Seismic well tie process dialog
The Seismic well tie process, found under Geophysics in the Processes pane, is one out of two
approaches to generating synthetic seismograms in Petrel.
In the Seismic well tie process, interactive sonic calibration, wavelet extraction and building, as well as
interactive stretch and squeeze of time-depth curves can be performed.
1-Sonic calibration
The sonic calibration workflow used in the Seismic well tie process, includes the ability to edit a knee
curve based on time-depth information (typically checkshots data), interactively do sonic calibration
and view the resulting calibrated sonic log while editing. It is also possible to redefine the datum
(datuming) in the process and specify the output after calibration.

28
Wavelet extraction
The wavelet extraction workflow used in the Seismic well tie process, is a tool for performing
deterministic wavelet extraction by selecting the seismic volume and input logs of interest. The
position of the extraction location can be changed interactively based on predictability to optimize on
the wavelet to use. Changing the extraction location automatically updates the extracted wavelet with
its corresponding power and phase spectra, as well as the resulting synthetic trace.

29
Wavelet viewer
The Wavelet viewer workflow used in the Seismic well tie process, is a window designed to view any
premade, loaded or already generated wavelets with the corresponding power and phase spectra.
Seismic well tie
One of the first steps in interpreting a seismic dataset is to establish the relationship between seismic
reflections and stratigraphy. For structural mapping, it may be sufficient to establish approximate
relationships (e.g. reflection X is near Base cretaceous).
The best source of stratigraphic information, wherever it is available, is well control. Often wells will
haves sonic (i.e. formation velocity) and formation density logs, at least over the intervals of
commercial interest: from these it is possible to construct a synthetic seismogram showing the
expected seismic response for comparison with the real seismic data.
In addition, some wells will have
Vertical Seismic Profiling (VSP)
data, obtained by shooting a
surface seismic source into
a down-hole geophone, which
has the potential to give a more
precise tie between well and
seismic data.
Fig (19) Show AI, Rc, Synthetic trace
and Original trace at each depth
on seismic well tie

30
3.3 Horizons Interpretation
The next step after seismic to well tie and getting the formation tops, starting to interpret (picking)
Tops of formations in the whole seismic volume.
Guidelines for 3D horizon interpretation :-
- Horizon interpretation May be executed before/after initial fault interpretation
- The minimum set of horizons:
all unconformities and sequence boundaries
major lap surface and maximum flooding surfaces
- Other levels may also be needed: time to depth conversion, structural modelling & kitchen/maturity modelling
- Start with shallow horizons on obvious events and to interpret step-by-step from top to bottom, as structural
complexity increases and imaging breaks down.
- Correlate a particular horizon on a coarse grid of lines away from wells, and make sure you always
close a loop back to your starting point to verify that the horizon of interest is consistently picked.
- Ensure that there is no misties of horizons and faults.
- It is then safer not to interpret closer to a fault plane than 1-3 traces.
Figure (20) a) Original inline 447 and synthetic trace of well F3-04
b) The Shift process for tie equals 3 msec
c) the Original inline 447 after shifting

31Figure (21 ) a) display formation Tops on inline 447, b) picking the Horizon ( FS8) on inline 447

32
Figure (22 ) a) Tie Points of FS8 were created by interpretation along inline and x line
b) This figure display the Location at Cube that we used on the previous 5 figures
Ghost tool
The Ghost curve is used to create a small bitmap of reflector events on a seismic line from the same seismic
display or from a different seismic volume showing different attributes. The area can be moved to other parts of
the same seismic line (or other seismic lines) to compare signal patterns and identify the same horizons across a
fault. For example, when a ghost is created it will be
located in the seismic interpretation window folder
in the Windows pane.
Figure (23) Ghost Match the Horizon

33
Figure (24) a) Show the Color Code (intersections lines have the same Time).
b) Convert Horizon grid to Surface Map of FS8

34
Figure (25) show all Horizons and well F3-04 and at Inline 447
The seismic data includes 11 horizons :
1- Salt 2- Base Tertiary
3- Mid Miocene 4- FS4
5- MFS4 6- FS6
7- Top Forests 8- truncation
9- FS7 10- FS8
11- Shallow
Figure ( 25b) Show the Termination of Horizon and the Horizon Ages

35
Figure (26) 3D View of Seismic inline & xline, Horizons and Wells
3.4 Attribute Generation
Attribute generation in Petrel is split into two separate processes, the Volume attributes and Surface
attributes processes. They are similar in the sence that they both contain a library of different seismic
attribute classes for display and use with the seismic interpretation workflow in Petrel. Seismic
attributes help to enhance information that might be subtle in conventional seismic, leading to a
better understanding and interpretation of the data.
Volume attribute based on various properties of the analytical signal, it makes virtual or realized
(physical) volumes of the input seismic.
1-Structural Smoothing
Smoothing of the input signal guided by the local structure to increase the continuity of the seismic
reflectors. Principal component dip and azimuth computation are used to determine the local
structure. Gaussian smoothing is then applied parallel to the orientation of this structure.
The Structural smoothing attribute can also be used to illuminate "flat spots" within the seismic
volume. By running the smoothing operation without Dip guiding, horizontal features such as fluid
contacts can be emphasized.

36
Figure (27) a) seismic cube after applying Structure Smoothing Attributes
b) Raw seismic data at inline 100
c) inline 100 after applying Structure Smoothing Attributes

37
2- Variance (Edge method)
The Variance attribute that can be used to isolate edges from the input data set. By edge, this means
discontinuities in the horizontal continuity of amplitude.
Variance is applicable as a stratigraphic attribute. If run with a short window, it can bring out
depositional features, including reefs, channels, splays, etc.
Dip guided variance is useful for accentuating structural features like faults. For stratigraphic features
(i.e. channels), variance without dip-guidance is a better choice.
Figure (28) a) Seismic Cube after applying the Variance Attribute
b) Raw Seismic data at inline 100
c) inline 100 after applying the Variance Attribute

38
4-Ant Tracking:
Ant tracking is used to extract faults from a pre-processed seismic volume. The pre-processing could
be variance or chaos combined with structural smoothing. Currently, only realized volumes can be
calculated.
This unique algorithm is part of an innovative workflow that introduces a new paradigm in fault
interpretation. The procedure consists of four steps. The first step is to condition the seismic data by
reducing noise in the signal. The second step enhances the spatial discontinuities in the seismic data
(fault attribute generation, edge detection). The third step, which generates the Ant track volume,
significantly improves the fault attributes by suppressing noise and remains of non-faulting events.
This is achieved by emulating the behavior of ant colonies in nature and how they use foramens to
mark their paths in order to optimize the search for food. Similarly, "artificial ants" are put as seeds on
a seismic discontinuity volume to look for fault zones. Virtual pheromones deployed by the ants
capture information related to the fault zones in the volume. The result is an attribute volume that
shows fault zones very sharp and detailed.

39
Figure (29 ) a) Seismic Cube after applying Ant Tracking Attribute
c) inline 100 after applying the Ant Tracking Attribute
d) Inline 120 & time Slice to highlight fault pass

40
4- Chaos
The chaotic signal pattern contained within seismic data is a measure of the "lack of organization" in
the dip and azimuth estimation method. Chaos in the signal can be affected by gas migration paths,
salt body intrusions, and for seismic classification of chaotic texture. The chaos attribute is scaled from
0-1.
Chaos in the signal can be used to illuminate faults and discontinuities and for seismic classification of
chaotic texture. Chaos can be related to local geologic features as it will be affected by gas migration
paths, salt body intrusions, reef textures, channel infill, etc.
Enhancing fault appearance on edge detection volumes
Several attributes are available which are capable of highlighting fault features. Variance is an excellent
starting point to capture fault expression in the data. The visualization of faults is best seen in time
slice orientation.

41
Figure (30 ) a) Seismic Cube after applying Chaos Attribute
c) inline 100 after applying the Chaos Attribute
d) inline 100 after applying the Chaos Attribute in addition to Structure Smoothing Attributes

42
3.5 Fault Interpretation
In this step, we generate different faults for each horizon (between up throw & down throw).
Known as fault stick, after that we take each generated fault in different view to see what is the extent
of each fault in the area. Group of fault sticks together comprise the fault plan.
Guidelines for the Interpretation of Faults:-
-Interpret all visible faults - in order to maximize the understanding of deformational history and the controls on
trapping and flow
- The definition of appropriate selection criteria for faults to be interpreted as 3D planes is essential to be used.
- Along the entire Subsurface Interpretation workflow (structural and reservoir model building, upscaling,
reservoir simulation).
- Sequencing faults for interpretation should consider structural setting and kinematics.
- As a minimum, all faults that directly affect volumetric must be fully interpreted, i.e. those faults that are
(potentially) sealing and occur in (potential) trap geometries. Generally these faults are also the ones that
are to be included in the static reservoir model.

43
Fig (31) Shows Horizons with important Faults at seismic line 140 inline
Fig (32) Show All Faults cut Horizons in seismic line 140 inline
Figure (33) show the extensions of all Faults

44
Trend of Faults
Fig (35 ) a) show the Trend of faults 1,3,4,5,6 Is NW-SE
b) Show the trend of Fault 2 is NE-SW
c) Show the Trend of Fault (-12) is NE-SW
Fig (34 ) a) show the trend of faults 01,02,03,011 is at N-S
b) show trend of faults 05,06,07,08,09,10 is at NE-S
c) show trend of faults 04 is NW-SE, but F17 & F18 is NE-SW
finally F19 it's trend divided into two parts 1-is NE-SW 2- is N-S

45
Fault Polygons
Show the Cut off the Horizons by Faults
Figure (36 ) a) Show the Cut off the Ooseterout Fm by Faults 1 & 6
b) Show the Cut off the Berda Fm by Faults 1, 6, 4, 5
c) Show the Cut off the base Tertairy by Faults 01, 03, 05, 06, 08, 09, 10, 11, 12

46
3.6 Isochores
Calculates the thickness between the given surface and another using the dip and azimuth of the
surfaces. (true stratigraphic thickness) or TVT (true vertical thickness).
Figure(37)zoneofshallow:ithastheminimumthicknessatthenorth-east,anditsmaximumthicknessatthesouth-
westasitbecomesthickerinthenorth-eastdirection
ZoneofFS8:itbecomesmorethickerinthewestdirectionandthinnerintheeastdirection.

47
4.Domain Conversion
Domain conversion allows you to take data from one domain, typically seismic data in time, and
convert it to another, typically depth, to correlate it with well data and perform volume calculations.
This action can be performed at any time in the workflow (before or during model building) and
exactly when it is done will depend on the particular issues in the project.
The uncertainties connected to interpolating velocities far from well control makes domain conversion
a critical step in the modeling process that should be investigated thoroughly.
The workflow of converting data between domains within Petrel is split into two processes:
 Make velocity model: Defines how the velocity varies in space.
 Depth conversion: Uses the velocity model to move data between domains.
Domain conversion can be used to move data from time to depth or reverse, but also to move data
between two versions of the same domain.
4.1 make velocity model
Within this process, define the zones in space where the velocity can be described in a common
manner, and then describe the velocity model to use in each zone.
Each zone in the velocity model must have a definition of the velocities within that zone. Velocity
models available in Petrel include:
 V=Vint: At each XY location the velocity is constant through the zone.
 V=Vo+kZ: At each XY location, the velocity changes in the vertical direction by a factor of k. Vo
represents the velocity at datum, and Z the distance (in length units, not time) of the point
from datum. NB Vo is the velocity at Z=0, not the top of the zone and will therefore be much
lower than the velocities seen in the layer, possibly even negative in extreme cases. As time
and depth decrease downwards, a negative value of k results in velocities which increase with
depth. Typical values for k are between 0 and -0.2. This velocity model is also referred to as
Linvel.
 V=Vo+ k (Z-Zo): As above, however, here the values are measured relative to the top of the
zone. For example, Vo represents the velocity at the top of the zone and (Z-Zo) represents the
distance between the point and the top of the zone. Again, a negative value of k will result in
velocities which increase downwards. Typical values for k are between 0 and -0.2. This velocity
model is also referred to as Adlinvel.
 V=Vo+kT: This is the same as V=V0+K*Z except that it is for conversion to the time domain.

48
4.2 Depth conversion
Once a velocity model has been created, it can be used to depth convert objects. Objects which can be
depth converted include:
 Surfaces
 Horizon Interpretation
 Fault Interpretation
 Points
 Seismic data (attribute of the original which can be realized)
 3D grids (copy of the original or overwrite the original)
Surfaces, interpretations and points are depth converted by adding an additional attribute to the
object. This means they can be automatically switched between time and depth using the window's
domain. When displaying depth converted objects, Petrel will ensure that only objects that are
converted by using the same.
Figure (39) a) show example of Vo Surface, b) show example of K factor Surface

49

50

51

52
4.3 Average velocity cube:
Create an average velocity cube from a velocity model.
Figure (40 ) this figures are showing the output of velocity model in time domain and depth domain
firstly Shallow layer , FS8, FS7, Truncation, Top Forest, MF4, FS4,
Mid Miocene Unconformity, base Tertiary, Finally the Salt layer

53
Figure (41) a) Velocity Cube, b) inline of Velocity Cube, c) xline Velocity Cube
d) time Slice of Velocity Cube

54
5. Structural Modeling
5.1 Structural Framework
The Petrel structural framework allows interpretation data to be combined together to construct a
structural model. The structural framework functionality solves many of the problems posed by complex
fault relationships. The model then feeds construction of geocellular models, including stair-step faults
to handle complex geometries. Consequently, these tools improve both the time to model and the
quality of geocellular grids.
The creation of the models can be tightly linked to seismic interpretation, allowing models to be built
on the fly in a "Modeling While Interpreting" workflow. The objective here is to facilitate the creation of
structurally correct interpretation.
The principal steps in creating a structural model are contained in three new processes:
 Geometry definition sets up the area of interest.
 Fault framework modeling, grids up the faults and creates relationships between connected
faults.
 Horizon modeling, grids up the horizon data then applies geological rules.
Figure (42) to the left, input data like fault interpretations and horizon interpretations. To the
right, the structural framework with faults and horizons.
Figure (43) examples of truncation of Faults at Structure framework.

55
Figure (44) the transform from Faults to Surfaces at output of Structure Framework.
Figure (45) show Faults from Top layer to Bottom Layer at the zone of our interest

56
Figure (46) Show the Output of Structural Framework (Horizons and Faults)
Figure (47) Show the Output of Structural Framework (Horizons and Faults) in actual Dimensional

57
5.2 Structural Gridding
Structural gridding process which enables users to directly construct corner point grids from the Petrel
structural framework, without needing to use pillar gridding workflows.
The structural gridding process allows users to omit particular horizons from the new grid. Removing
horizons will alter the zone hierarchy as zones are defined as the interval between horizons.
The new structural gridding process currently allows the construction of stair-stepped corner point
grids. The process automatically adopts the active Structural framework as the input to the corner
point grid and applies the geometry and the defined zones. However, these may be altered to suit the
purpose of the grid.
Stair-stepped grid creation requires that the zone model has been generated when modeling the
horizons of the structural framework
The structural gridding process can be used to construct a reservoir interval from a much larger
structural framework by defining the horizons in the vertical layering panel.
Figure (48) Building Model by grids (324 I x 475 J) = 153900 grids
which each grid will Contains Multi Value of PHI & K and later Pressure with RE Department

58
Figure (49) Intersections of Layer Gridding
Figure (50) Focus of the grids (324 I x 475 J) = 153900 grids
which each grid will Contains Multi Value of PHI & K and later Pressure with RE Department

59
Figure (60) Show the number of Regions forming the Model.
Figure (61) intersections of Region Gridding

60
6. Well logging analysis
6.1 Well information
Well name Surface X (m) Surface Y (m) Start depth (m) End depth (m)
F02-01 606549 6080124 35.90000 3128.0
F03-02 619091 6089516 30.9 2150.0
F03-04 623256 6082586 34.100 2663.0
F06-01 607902 6077213 28.60000 3534.50000
Well name Logs content
F02-01 Gamma ray Sonic Density
F03-02 Gamma ray Sonic Density Resistivity
F03-04 Gamma ray Sonic Density Resistivity
F06-01 Gamma ray Sonic Density
Inputs log layout in tech-log software
6.2 The calculations
• . Volu e of shale f o Ga a ay
• . Total Po osity f o De sity
• . Effe ti e Po osity f o De sity
• . The fo atio ate satu atio usi g the A hie e uatio
• . The pe ea ility f o the "Coates" e uatio
• . Cal ulatio of elo ities.
• . al ulatio of i peda e
• . al ulatio of La ’s o sta ts Mu a d la da
Base map for F3 block survey
Logs of sonic GR resistivity and density with depth

61
1. The calculatio s Volu e of shale fro ga a ray
2. This method calculates the volume of shale with a GR curve only as input3.
4.
Volu e of shale output
2. The calculation (Total Porosity from Density)
Name Unit Description
Inputs Gamma ray (GR) gAPI Gamma ray log reading
parameters Gamma ray matrix (GRmatrix) gAPI Gamma ray log reading in 100% matrix rock
Gamma ray shale (GRshale) gAPI Gamma ray log reading in 100% shale
Method of calculations Larionov Tertiary rocks method
Output Volume of shale (Vsh) v/v
Well name Min. value Max. value
F02-01 6.63725 144.935
F03-02 2.19819 138.735
F03-04 6.74552 124.521
F06-01 21.912 148.593
GRmatrix GRshale
The average 9.3719 139.192
Name Unit Description
inputs Bulk density (� ) g/cm3 Density log reading
parameters
Bulk density matrix (�� ) g/cm3
Density log reading in 100% matrix rock (2.65)
(default)
Bulk density fluid (��) g/cm3 Density log reading in 100% water(1.0) (default)
outputs Total density Porosity (∅ ) v/v Total Porosity
GR index=
� − � �
� ℎ − � �
Multi-well histogram: gamma ray
Logs of GR and Vsh with depth
Note: Zones with high
gamma ray have more shale
Total Porosity from
Density
∅ =
�� − �
�� − ��
Larionov Tertiary rocks method: � = 0.08 ∗ .7 ∗ � �
-1)

62
Total Porosity fro De sity output
3. The calculation (Effective Porosity from Density)
Effective porosity = total porosity – (total shale porosity * volume of shale)
Effe ti e Porosity fro De sity output
Name Units Description
Inputs Bulk density (� ) g/cm3 Density log reading
Volume of shale (Vsh) v/v
parameters Bulk density matrix (�� ) g/cm3 Density log reading in 100% matrix rock (2.65) (default)
Bulk density fluid (��) g/cm3 Density log reading in 100% water (1.0) (default)
Bulk density shale (� h) g/cm3 Density log reading in 100% shale (2.4) (default)
Outputs Effective Porosity (∅e) v/v Effective Porosity
Note:
the zones with higher density is lower in
total porosity Density inversely
proportional with porosity
Logs of density and total porosity with depth
∅e = ∅ – (∅Tsh-Vsh);
Where: ∅ =
� −�
� −�
,
And ∅ ℎ =
� −� ℎ
� −�
Note: at zones with high volume of shale
∅e < ∅
Logs of density, total porosity and effective porosity

63
4. The calculation(saturation from Archie)
The formation water saturation using the Archie equation
=
�∗
∗∅
1
Hydrocarbon saturation (SH) = 1 – Water saturation (SW)
“aturatio fro Ar hie output
5. The calculations (permeability from coates):
The permeability from the "Coates" equation �� = � ∗ ∅e ∗
−
Name Units description
inputs Effective Porosity (∅e) v/v Calculated Effective porosity
Water saturation (Sw) v/v Calculated water saturation
Parameters
Coates permeability (kc) mD
permeability derived using the Timur-Coates model, (650)
default
Outputs Permeability (PERM) mD Calculated permeability
Name Symbol Unit value
Inputs Formation Resistivity Rt ohm.m
Calculated total porosity ∅ v/v
parameters Tortuosity factor a unitless 1 (default)
Cementation exponent m unitless 2 (default)
Saturation exponent n unitless 2 (default)
Formation Water Resistivity Rw ohm.m 0.03 (default)
Outputs Water Saturation SW_AR v/v
We calculated the saturation from
F03-02 and F03-04 wells that have
resistivity logs
Logs of resistivity, total porosity and water saturation
Note:
Zones with higher porosity and higher
resistivity have lower water saturation

64
Per ea ility fro oates outputs
6. The Calculation of velocities:
• P a e elo ity fro so i ft/s =
6
∆
he e: ∆ o p essio al slo ess us/ft
• “ a e elo ity fro astag a’s e uatio fo et sa d/ shale
Vs = . * Vp + - .
The two coefficients can be changed to match your reservoir trend (empirically) .but it does not apply to gas sands.
 Use Biot-Gass a e uatio s to al ulate the o e t Vs alues i gas sa d
ith i puts of p , Vs f o astag a’s e . a d fluid satu atio “
 Velo ity ratio = Vp/Vs
Velo ities output
Logs of effective porosity, total porosity, water saturation and permeability
Note:
Zones with high effective porosity and low
water saturation have higher permeability
Logs of p wave velocity and s-wave velocity from castagna,
corrected s-wave velocity and velocity ratio with depth
Vs castagna Vs corrected
Shear wave velocity changed
according to saturated fluid

65
7. Calculation of impedance
• P-i peda e o o p essio al i peda e = P- a e elo ity Vp * de sity �
• “-i peda e o shea i peda e = “- a e elo ity Vs * de sity �
8. Cal ulatio of La ’s o sta ts Mu a d la da :
Mu-Rho GPA*g/ = “-i peda e where Rho is density
La da-Rho GPA*g/ = P-i peda e - * “-i peda e where c = 2
Cal ulatio of i peda e a d la ’s o sta ts output
7. Cross plots (gas indicators)
• 1. Mu-Rho Vs Lambda-Rho
• 2. Velocity ratio Vs p-impedance
• 3. Lambda-Rho(-) Mu-Rho difference Vs p-impedance
La ’s o sta ts ill e used i oss
plots (for gas indication)
Logs of p impedance, s-impedance,
Mu-rho and lambda-rho with depth

66
1. Mu-Rho Vs Lambda-Rho
2. Velocity ratio vs p-impedance
Zone with low Mu-Rho and low lambda
values indicate to gas sand
Logs of Mu rho, lambda-rho, and Vsh
Gas sand according to cross plot locate at FS8
Isolated zone with low p impedance and low
velocity ratio close to 1.5 is indication of gas sand
Logs of vpvs ratio, p-impedance, and Vsh with logs

67
3. Lambda-Rho(-) Mu-Rho difference Vs p impedance
Gas sand according to cross plot locate
at FS8
but F03-02 have more gas than F03-04
Isolated zone with low p
impedance difference between
la ’s o sta ts
is indication of gas sand
Gas sand according to cross plot locate at FS8
but F03-02 have much more gas than F03-04
Logs of mu-rho lambda rho difference and p-impedance with depth

68
8. Colored Seismic inversion
In this process, there is a single operator, O, which is applied to the seismic trace S to transform
it directly into the inversion (impedance) result Z: Z = O* S
The operator of colored seismic inversion
Colored inversion output
 The first panel shows a plot of the
amplitude spectrum of impedance
from a series of wells vs Frequency.
This is shown on a log/log scale.
 The red line is a regression curve,
which represents the Desired output
of the Colored Inversion.
 Intercept = 7.49103
 gradient = -120288
 The second panel shows two curves.
One is the amplitude spectrum of the input seismic
data.
The second is the desi ed output from the previous
panel.
(Note that this is now curved, because we are showing a linear
Scale in Frequency.)
 The horizontal red line is the Spectrum
Threshold.
This sets a frequency range over which the inversion
operator will be calculated.
Only those frequencies for which the seismic
spectrum
(Blue) is above the threshold will be used in the
calculation. The threshold prevents division by zero or
small noise values.
Finally, these panels show the time and frequency
domain operator which has been calculated.
inline100
Bright spots BS1 and BS2 in FS8 trapped at fault

69
Slice 560 ms
Bottom of BS1 high
positive relative
impedance
top of BS2 and BS4
high negative relative
impedance
Inline 686
BS4 accumulation due
to high structure
(elevation) may due
to salt doming
Inline 432
Slice 790 ms
Tilted BS
(short extension)

70
9.1 Fault Modeling
defining the faults in the geological model which will form the basis for generating the 3D grid. These
faults will define breaks in the grid, lines along which the horizons inserted later may be offset. The
offset which occurs is entirely dependent upon the input data, so modeling reverse faults is just as
easy as modeling normal faults.
Linear, vertical, listric, S-shaped, reverse, vertically truncated, branched and connected faults can be
created in Petrel. The program allows you to create structurally and geometrically correct fault
representations.
Faults are built using Key Pillars. A Key Pillar is a vertical, linear, listric or curved line described by two,
three or five so called Shape Points; two for vertical and linear, three for listric and five for curved.
Several Key Pillars joined together by these Shape Points define the fault plane.
When building a structural model in Petrel, fault modeling is the first step. The user must create Key
Pillars along all the faults to incorporate them into the reservoir model.
Keep in mind when building the model, that the Fault Modeling process, in conjunction with the Pillar
Gridding process, is very much an iterative procedure. Going back to the Fault Modeling process may (in
some cases) be the solution to some Pillar Gridding problem.
Figure (62) a) Show the Pillar (Have one stick of Fault)
b) Show the Varies types of Fault Geometry
Fig(62)ShowtheControlofPillar(Editing)

71
Trunction
Truncate Top Pillars: will truncate the Top Shape Point towards the selected Key Pillar.
Truncate Bottom Pillars: will truncate the Base Shape Point towards the selected Key Pillar.
Remove truncation: Use this when you revise the interpretation of how two faults are truncated toward each
other.
Figure(63)ShowtheEditofFaults5totruncate
bottomwiththeMajorFault1
alsoapplytoF6withF1,
F4withF1,
F3withF1,
F9withF8,
F14withF8.
b)SeismicLine130ShowtheTruncationofFaults

72
Curvature
Figure (64) edit the Fault curvature between the Upper Thrown and down Thrown
to Avoid the Horizon Spikes in Modeling Horizons

73
10. Pillar Griding
The process of Pillar Gridding will generate a corner point 3D grid from the fault model. Pillar Gridding
is the p o ess of aki g the “keleto F a e o k . The skeleto is a g id o sisti g of a Top, a id a d
a Base skeleton grid, each attached to the Top, the mid and the Base points of the Key.
In addition to the three skeleton grids, there are pillars connecting every corner point of every grid cell
to their corresponding corners on the adjacent skeleton grid(s).
When creating your skeleton grid you will work with the Mid Skeleton grid. The Mid Skeleton grid is
the grid attached to the mid-lines that connect the Key Pillars. The purpose is to create a grid that
looks OK at the midpoint level, with respect to the grid cell size, orientation and appearance of the
cells.
The next step is to extrapolate this Mid Skeleton grid upwards and downward in order to create the
Top and Base skeletons. The result of the Pillar gridding has to be checked for crossing pillars, and the
intersections (shown in the figure b below) are the most efficient tool for QC. Once the skeleton is, the
input surfaces can be inserted into it, honoring the faults that have been created
Fault Modeling - defining the faults in the geological model which will form the basis for generating the
3D grid. These faults will define breaks in the grid, lines along which the horizons inserted later may be
offset. The offset which occurs is entirely dependent upon the input data, so modeling reverse faults is
just as easy as modeling normal faults.
Figure (65) Creating the Boundary around the Faults Zone and include Well Distributions for Petrophysical
Study, then get the trend for each Fault to control the Geometry for avoiding the –ve Cells

AssessmentofSubsurfaceShallowGasExpressions|CairoUniversity
Graduationproject2015
74
Figure (66) a) Show the Mid Skelton of Faults of Pillar Grid
b) Show how the Cells arrangement with the Trend of Faults
c) Show the wrong case if doesn't give trend for Faults

75
Horizons and Zones
The generation of structural models is done in a process called Pillar Gridding. Pillar Gridding is a
unique concept in Petrel where the faults in the fault model are used as a basis for generating the 3D
grid. Several options are available to customize the 3D grid for either geo-modeling or flow-simulation
purposes.
The result from Pillar Gridding is a set of pillars, both along the faults but also in between faults. The
grid has no layers, only a set of pillars with user given X and Y increments between them (like a
pincushion). The layering is introduced when making horizons and zones.
Horizons Zones and Layering
After
Make Horizons
After
Make Zones
After
Make Layering
Main Reservoir
Layer
Zonation's
Isochores
Vertical
resolutions by
cell thickness
Figure (67) Show the Steps of Making Horizon and Zones & Layering

76
Figure (68) compute the Inter Layering between Horizons from
well Section
Figure (69) Show the Output of Making Horizon and Zones & Layering

77
11. Property Modeling
Property modeling is the process of filling the cells of the grid with discrete (facies) or continuous
(petrophysics) properties. Petrel assumes that the layer geometry given to the grid follows the
geological layering in the model area. Thus, are these processes dependant on the geometry of the
existing grid. When interpolating between data points, Petrel will propagate property values along the
grid layers.
11.1 The Data analysis will help to QC and interpret the data, to identify key geological features, and to
prepare the input for Petrophysical modeling.
1-Cell Angle (QC)
this calculates the deviation (from 90 degrees) of the angles in each cell (absolute values).
Figure (70 ) a) Cube of Cell angle (QC-1)
b) the Cube after Filtering by Showing the Cells which have lower 15 deg over the 90 degree
c) Show Histogram of data is Good * through the Major part have Low angle over the 90 deg

78
2- Cell Inside Out (QC)
to measure the quality of the simulation grid block geometry
Figure (71) a) Cube of Cell inside Out (QC-2).
b) Histogram Show the Major of Cube is lying in Safe Side (0 to 0.5).

79
3-Bulk Volume (QC)
this calculates the bulk volume of each cell in the 3D grid.
11.2 Scale up well logs
When modeling different properties, the modeled area is divided up by generating a 3D grid. Each grid
cell has a single value for each property. As the grid cells often are much larger than the sample
density for well logs, well log data must be scaled up before it can be entered into the grid. This
process is also called blocking of well logs.
Principles of Scale up well logs
When upscaling well logs, Petrel will first find the 3D grid cells which the wells penetrate (see Figure 1).
For each grid cell, all of the log values that fall within the cell will be averaged according to the
selected algorithm to produce one log value for that cell.
For discrete well logs (for example, facies or zone logs), the average method Most of is recommended.
The upscaled value will then correspond to the value that is most represented in the log for that
particular cell.
Figure (72) a) Cube of Bulk Volume (QC-3)
b) Histogram show the Major Data have a Constant Volume, except the cells which associated
with Faults

80
The layout and the resolution of the 3D grid will control how many and
which cells each well penetrates. A dipping layering scheme, compared to a
horizontal scheme, can dramatically alter the results from the Scale up of
well logs process and the subsequent property modeling.
Fig (73) the result of the Scale up well logs process is placed as a property
model icon in the Properties folder for the 3D grid. It only holds values for
the 3D grid cells which the wells have penetrated (Figure 0).
Fig (74) The Scale up well logs process assigns log values to the cells in the
3D grid that are penetrated by the wells.
11.3 Petrophysical Modeling
Petrophysical modeling is the interpolation or simulation of continuous
data (e.g. porosity, permeability, etc.) throughout the model grid. In Petrel
Deterministic (estimation or interpolation) and Stochastic methods are
available for modeling the distribution of continuous properties in a
reservoir model.
Petrophysical Modeling Methods
The Petrophysical modeling algorithm that we used is Moving average
(interpolation)
Moving average: Finds an average of input data and weights according to
distance from wells. The algorithm is fast and will create values for all cells. It can also create "bulls
eyes" if the range of the input data is large. The algorithm will not generate values larger or smaller
than the min/max values of the input data.

81
Figure (75) a) Porosity Cube, b) Inline of Porosity Cube, c) xline of Porosity Cube

82
Figure (76) a) Permeability Cube, b) Inline of Perm Cube, c) xline of Perm Cube

83
11.4 Upscaling
Many reservoir flow simulators cannot directly and effectively handle the size of grids used in
geological models. Such models can easily contain as many as 10 million cells, whereas single CPU
simulations will only run in reasonable time with models of the order of 100,000 cells. Furthermore,
grids used in geological models are often unsuitable for simulation due to geometric problems such as
inside-out cells.
Upscaling is the process of creating a coarser (lower resolution) grid based on the geological grid
which is more appropriate for simulation. While this necessitates the omission of much of the
geological models fine detail, the result is intended to preserve representative simulation behavior.
In Petrel, upscaling is split into two steps
 Scale up Structure
Define the new layering scheme (numbers and shapes of layers) of the simulation grid.
 Scale up Properties
Populate grid properties, such as porosity and permeability, based on those in the fine grid.
Scale up Properties
Properties from one grid can be transferred to another grid of a different resolution or orientation
using the Scale up properties process. This is usually done in the context of building a simulation model
from a geological model, where the simulation model has been coarsened and reoriented for flow
simulation. However, the Scale up properties process places no restrictions on the grids that are used
as input and output, and the process can also be used to transfer properties between identical grids
and to downscale.
For most properties (e.g. porosity, net-to-gross), it is appropriate to upscale to a coarse grid using
weighted averaging of values from a fine grid. The fine grid cells in the vicinity of each coarse grid cell
are found, and their property values are weighted (by intersection volume and/or by other property
values such as net-to-gross) and aggregated using a specified averaging method (such as arithmetic or
geometric averaging). Discrete properties can be handled in the same way using aggregation methods
such as "most-of" (also known as "mode").
Permeability can be upscaled in the same way, but more sophisticated upscaling techniques are also
available. Flow-based upscaling methods perform a flow simulation on coinciding fine grid cells to
arrive at a representative permeability for each coarse grid cell. For these methods, upscaled
permeabilities are created for each grid direction by imposing appropriate pressure gradients on the
boundaries of the fine cell set, and solving for the internal pressure gradients to establish an overall
flow response.
Directional averaging methods are also available for permeability upscaling, wherein the permeability
values of the group of coinciding fine cells are averaged using a combination of arithmetic and
harmonic (or power) techniques. Again, multiple permeability properties are created for each of the I,
J and K directions
While the priority in upscaling properties such as porosity and net-to-gross is to maintain overall pore
volumes, the focus in permeability upscaling is to preserve flow behavior. As such, different algorithms
and techniques are applicable.

84
Fig (77) a) Gridding and Upscaling of Porosity cube
b)) Gridding and Upscaling of Permeability cube
c) Gridding and Upscaling of Layering cube

85
Figure (78) histogram a) show the Porosity calculating by Arithmetic method
b) Show the arithmetic Porosity with its average (by Volume – Weighted)

86
Fig (79) a) show the Permeability calculating by Arithmetic & Harmonic method
b) Show the (A & H) Permeability with its average (by Directional Averaging)
Fig (80) Show the ability to get Multi value for each grid

87
12. Characterization of Prospect
The Closure in time & depth domain
Filter the property

88

89
Figure (82) Show the Saturation Cube
13. Volumetric
General properties
Porosity: PHI
Net gross: 0.7
Properties in gas interval
Sat. water: Sw
Sat. gas: 1-Sw-So
Sat. oil: 0
Bg (formation vol. factor): 1 [rm3/sm3]
Recovery factor gas: 1
Figure (81 ) a) TWT map and Depth Map Show The Trap
b) PHI slice of FS8 Show the High Porosity
c) K slice of FS8 show The High Permeability
d) Grid of Slice Show the Multi Value Property for each Grid

90
Figure (83) Show the Volume of Gas at FS8
Reference
Website of Data: www. opendtect.org/
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