This document provides an introduction to seismic interpretation. It begins with an overview of seismic acquisition methods both onshore and offshore. It then discusses key concepts in seismic data such as common depth points, floating datum, two-way time, and the relationship between time and depth. The document also covers seismic resolution, reflection coefficients, and examples of calculating tuning thickness. Finally, it discusses important steps for seismic interpretation including checking the line scale and orientation and interpreting major reflectors and geometries.
3D Facies Modelling project using Petrel software. Msc Geology and Geophysics
Abstract
The Montserrat and Sant Llorenç del Munt fan-delta complexes were developed during the Eocene in the Ebro basin. The depositional stratigraphic record of these fan deltas has been described as a made up by a several transgressive and regressive composite sequences each made up by several fundamental sequences. Each sequence set is in turn composed by five main facies belts: proximal alluvial fan, distal alluvial fan, delta front, carbonates platforms and prodelta.
Using outcrop data from three composite sequences (Sant Vicenç, Vilomara and Manresa), a 3D facies model was built. The key sequential traces of the studied area georeferenced and digitalized on to photorealistic terrain models, were the hard data used as input to reconstruct the main surfaces, which are separating transgressive and regressive stacking patterns. Regarding the facies modelling has been achieved using a geostatistical algorithm in order to define the stacking trend and the interfingerings of adjacent facies belts, and five paleogeographyc maps to reproduce the paleogeometry of the facies belts within each system tract.
The final model has been checked, using a real cross section, and analysed in order to obtain information about the Delta Front facies which are the ones susceptible to be analogous of a reservoir. Attending to the results including eight probability maps of occurrence, the transgressive sequence set of Vilomara is the greatest accumulation of these facies explained by its agradational component.
3D Facies Modelling project using Petrel software. Msc Geology and Geophysics
Abstract
The Montserrat and Sant Llorenç del Munt fan-delta complexes were developed during the Eocene in the Ebro basin. The depositional stratigraphic record of these fan deltas has been described as a made up by a several transgressive and regressive composite sequences each made up by several fundamental sequences. Each sequence set is in turn composed by five main facies belts: proximal alluvial fan, distal alluvial fan, delta front, carbonates platforms and prodelta.
Using outcrop data from three composite sequences (Sant Vicenç, Vilomara and Manresa), a 3D facies model was built. The key sequential traces of the studied area georeferenced and digitalized on to photorealistic terrain models, were the hard data used as input to reconstruct the main surfaces, which are separating transgressive and regressive stacking patterns. Regarding the facies modelling has been achieved using a geostatistical algorithm in order to define the stacking trend and the interfingerings of adjacent facies belts, and five paleogeographyc maps to reproduce the paleogeometry of the facies belts within each system tract.
The final model has been checked, using a real cross section, and analysed in order to obtain information about the Delta Front facies which are the ones susceptible to be analogous of a reservoir. Attending to the results including eight probability maps of occurrence, the transgressive sequence set of Vilomara is the greatest accumulation of these facies explained by its agradational component.
The analysis of all of the significant processes that formed a basin and deformed its sedimentary fill from basin-scale processes (e.g., plate tectonics)
to centimeter-scale processes (e.g., fracturing)
is one of the first steps in
searching for oil and gas resources that directly
affects the land and the landowners Seismic surveys are like sonar on steroids They are based on recording the time it takes for sound waves generated by controlled energy sources .The survey usually requires people and machinery
to be on private property and may result in
disturbances of the land such as the clearing of
trees
2 d and 3d land seismic data acquisition and seismic data processingAli Mahroug
The seismic method has three important/principal applications
a. Delineation of near-surface geology for engineering studies, and coal and mineral
exploration within a depth of up to 1km: the seismic method applied to the near –
surface studies is known as engineering seismology.
b. Hydrocarbon exploration and development within a depth of up to 10 km: seismic
method applied to the exploration and development of oil and gas fields is known
as exploration seismology.
c. Investigation of the earth’s crustal structure within a depth of up to 100 km: the
seismic method applies to the crustal and earthquake studies is known as
earthquake seismology.
The oxford dictionary defines an attribute as, “a quality ascribed to any person or thing”. We have extended this definition to: “seismic attributes are all the information obtained from seismic data, either by direct measurements or by logical or experience based reasoning
In reflection seismology : aseismic attributes is a quality extracted or derived from seismic data that can be analyzed in order to enhance information that might be more subtle in a traditional seismic image , leading to a better geological or geophysical interpretation of the data
Over the past decades, we have witnessed attribute developments track breakthroughs in reflector acquisition and mapping, fault identification, bright spot identification, frequency loss, thin bed tuning, seismic stratigraphy.
The analysis of all of the significant processes that formed a basin and deformed its sedimentary fill from basin-scale processes (e.g., plate tectonics)
to centimeter-scale processes (e.g., fracturing)
is one of the first steps in
searching for oil and gas resources that directly
affects the land and the landowners Seismic surveys are like sonar on steroids They are based on recording the time it takes for sound waves generated by controlled energy sources .The survey usually requires people and machinery
to be on private property and may result in
disturbances of the land such as the clearing of
trees
2 d and 3d land seismic data acquisition and seismic data processingAli Mahroug
The seismic method has three important/principal applications
a. Delineation of near-surface geology for engineering studies, and coal and mineral
exploration within a depth of up to 1km: the seismic method applied to the near –
surface studies is known as engineering seismology.
b. Hydrocarbon exploration and development within a depth of up to 10 km: seismic
method applied to the exploration and development of oil and gas fields is known
as exploration seismology.
c. Investigation of the earth’s crustal structure within a depth of up to 100 km: the
seismic method applies to the crustal and earthquake studies is known as
earthquake seismology.
The oxford dictionary defines an attribute as, “a quality ascribed to any person or thing”. We have extended this definition to: “seismic attributes are all the information obtained from seismic data, either by direct measurements or by logical or experience based reasoning
In reflection seismology : aseismic attributes is a quality extracted or derived from seismic data that can be analyzed in order to enhance information that might be more subtle in a traditional seismic image , leading to a better geological or geophysical interpretation of the data
Over the past decades, we have witnessed attribute developments track breakthroughs in reflector acquisition and mapping, fault identification, bright spot identification, frequency loss, thin bed tuning, seismic stratigraphy.
У рамках програми «Підвищення кваліфікації фахівців нафтогазової галузі України для міжнародного співробітництва та роботи у західних компаніях», за підтримки компанії «Shell» 6 березня в аудиторії ВНЗ «Інститут Тутковського» відбулися курси підвищення кваліфікації на тему «Від побудови сейсмічних зображень до інверсії».
An example of 3D conductivity mapping using the TEMPEST airborne electromagne...Richard Lane
"An example of 3D conductivity mapping using the TEMPEST airborne electromagnetic system" by Richard Lane *, Andy Green +, Chris Golding *, Matt Owers *, Caleb Plunkett *, Phil Pik +, Daniel Sattel *, Bob Thorn + (* CRC AMET (Fugro Airborne Surveys), + CRC AMET (CSIRO)). This is a presentation given at the ASEG Conference, March 2000, Hobart, Tasmania, Australia. For further information, please see ; Lane, R., Green, A., Golding, C., Owers, M., Plunkett, C., Pik, P., Sattel, D., Thorn, B., 2000: An example of 3D conductivity mapping using the TEMPEST airborne electromagnetic system, Exploration Geophysics, 31, 162-172.
Slide 1: Title Slide
Extrachromosomal Inheritance
Slide 2: Introduction to Extrachromosomal Inheritance
Definition: Extrachromosomal inheritance refers to the transmission of genetic material that is not found within the nucleus.
Key Components: Involves genes located in mitochondria, chloroplasts, and plasmids.
Slide 3: Mitochondrial Inheritance
Mitochondria: Organelles responsible for energy production.
Mitochondrial DNA (mtDNA): Circular DNA molecule found in mitochondria.
Inheritance Pattern: Maternally inherited, meaning it is passed from mothers to all their offspring.
Diseases: Examples include Leber’s hereditary optic neuropathy (LHON) and mitochondrial myopathy.
Slide 4: Chloroplast Inheritance
Chloroplasts: Organelles responsible for photosynthesis in plants.
Chloroplast DNA (cpDNA): Circular DNA molecule found in chloroplasts.
Inheritance Pattern: Often maternally inherited in most plants, but can vary in some species.
Examples: Variegation in plants, where leaf color patterns are determined by chloroplast DNA.
Slide 5: Plasmid Inheritance
Plasmids: Small, circular DNA molecules found in bacteria and some eukaryotes.
Features: Can carry antibiotic resistance genes and can be transferred between cells through processes like conjugation.
Significance: Important in biotechnology for gene cloning and genetic engineering.
Slide 6: Mechanisms of Extrachromosomal Inheritance
Non-Mendelian Patterns: Do not follow Mendel’s laws of inheritance.
Cytoplasmic Segregation: During cell division, organelles like mitochondria and chloroplasts are randomly distributed to daughter cells.
Heteroplasmy: Presence of more than one type of organellar genome within a cell, leading to variation in expression.
Slide 7: Examples of Extrachromosomal Inheritance
Four O’clock Plant (Mirabilis jalapa): Shows variegated leaves due to different cpDNA in leaf cells.
Petite Mutants in Yeast: Result from mutations in mitochondrial DNA affecting respiration.
Slide 8: Importance of Extrachromosomal Inheritance
Evolution: Provides insight into the evolution of eukaryotic cells.
Medicine: Understanding mitochondrial inheritance helps in diagnosing and treating mitochondrial diseases.
Agriculture: Chloroplast inheritance can be used in plant breeding and genetic modification.
Slide 9: Recent Research and Advances
Gene Editing: Techniques like CRISPR-Cas9 are being used to edit mitochondrial and chloroplast DNA.
Therapies: Development of mitochondrial replacement therapy (MRT) for preventing mitochondrial diseases.
Slide 10: Conclusion
Summary: Extrachromosomal inheritance involves the transmission of genetic material outside the nucleus and plays a crucial role in genetics, medicine, and biotechnology.
Future Directions: Continued research and technological advancements hold promise for new treatments and applications.
Slide 11: Questions and Discussion
Invite Audience: Open the floor for any questions or further discussion on the topic.
Earliest Galaxies in the JADES Origins Field: Luminosity Function and Cosmic ...Sérgio Sacani
We characterize the earliest galaxy population in the JADES Origins Field (JOF), the deepest
imaging field observed with JWST. We make use of the ancillary Hubble optical images (5 filters
spanning 0.4−0.9µm) and novel JWST images with 14 filters spanning 0.8−5µm, including 7 mediumband filters, and reaching total exposure times of up to 46 hours per filter. We combine all our data
at > 2.3µm to construct an ultradeep image, reaching as deep as ≈ 31.4 AB mag in the stack and
30.3-31.0 AB mag (5σ, r = 0.1” circular aperture) in individual filters. We measure photometric
redshifts and use robust selection criteria to identify a sample of eight galaxy candidates at redshifts
z = 11.5 − 15. These objects show compact half-light radii of R1/2 ∼ 50 − 200pc, stellar masses of
M⋆ ∼ 107−108M⊙, and star-formation rates of SFR ∼ 0.1−1 M⊙ yr−1
. Our search finds no candidates
at 15 < z < 20, placing upper limits at these redshifts. We develop a forward modeling approach to
infer the properties of the evolving luminosity function without binning in redshift or luminosity that
marginalizes over the photometric redshift uncertainty of our candidate galaxies and incorporates the
impact of non-detections. We find a z = 12 luminosity function in good agreement with prior results,
and that the luminosity function normalization and UV luminosity density decline by a factor of ∼ 2.5
from z = 12 to z = 14. We discuss the possible implications of our results in the context of theoretical
models for evolution of the dark matter halo mass function.
THE IMPORTANCE OF MARTIAN ATMOSPHERE SAMPLE RETURN.Sérgio Sacani
The return of a sample of near-surface atmosphere from Mars would facilitate answers to several first-order science questions surrounding the formation and evolution of the planet. One of the important aspects of terrestrial planet formation in general is the role that primary atmospheres played in influencing the chemistry and structure of the planets and their antecedents. Studies of the martian atmosphere can be used to investigate the role of a primary atmosphere in its history. Atmosphere samples would also inform our understanding of the near-surface chemistry of the planet, and ultimately the prospects for life. High-precision isotopic analyses of constituent gases are needed to address these questions, requiring that the analyses are made on returned samples rather than in situ.
Richard's entangled aventures in wonderlandRichard Gill
Since the loophole-free Bell experiments of 2020 and the Nobel prizes in physics of 2022, critics of Bell's work have retreated to the fortress of super-determinism. Now, super-determinism is a derogatory word - it just means "determinism". Palmer, Hance and Hossenfelder argue that quantum mechanics and determinism are not incompatible, using a sophisticated mathematical construction based on a subtle thinning of allowed states and measurements in quantum mechanics, such that what is left appears to make Bell's argument fail, without altering the empirical predictions of quantum mechanics. I think however that it is a smoke screen, and the slogan "lost in math" comes to my mind. I will discuss some other recent disproofs of Bell's theorem using the language of causality based on causal graphs. Causal thinking is also central to law and justice. I will mention surprising connections to my work on serial killer nurse cases, in particular the Dutch case of Lucia de Berk and the current UK case of Lucy Letby.
Observation of Io’s Resurfacing via Plume Deposition Using Ground-based Adapt...Sérgio Sacani
Since volcanic activity was first discovered on Io from Voyager images in 1979, changes
on Io’s surface have been monitored from both spacecraft and ground-based telescopes.
Here, we present the highest spatial resolution images of Io ever obtained from a groundbased telescope. These images, acquired by the SHARK-VIS instrument on the Large
Binocular Telescope, show evidence of a major resurfacing event on Io’s trailing hemisphere. When compared to the most recent spacecraft images, the SHARK-VIS images
show that a plume deposit from a powerful eruption at Pillan Patera has covered part
of the long-lived Pele plume deposit. Although this type of resurfacing event may be common on Io, few have been detected due to the rarity of spacecraft visits and the previously low spatial resolution available from Earth-based telescopes. The SHARK-VIS instrument ushers in a new era of high resolution imaging of Io’s surface using adaptive
optics at visible wavelengths.
Introduction:
RNA interference (RNAi) or Post-Transcriptional Gene Silencing (PTGS) is an important biological process for modulating eukaryotic gene expression.
It is highly conserved process of posttranscriptional gene silencing by which double stranded RNA (dsRNA) causes sequence-specific degradation of mRNA sequences.
dsRNA-induced gene silencing (RNAi) is reported in a wide range of eukaryotes ranging from worms, insects, mammals and plants.
This process mediates resistance to both endogenous parasitic and exogenous pathogenic nucleic acids, and regulates the expression of protein-coding genes.
What are small ncRNAs?
micro RNA (miRNA)
short interfering RNA (siRNA)
Properties of small non-coding RNA:
Involved in silencing mRNA transcripts.
Called “small” because they are usually only about 21-24 nucleotides long.
Synthesized by first cutting up longer precursor sequences (like the 61nt one that Lee discovered).
Silence an mRNA by base pairing with some sequence on the mRNA.
Discovery of siRNA?
The first small RNA:
In 1993 Rosalind Lee (Victor Ambros lab) was studying a non- coding gene in C. elegans, lin-4, that was involved in silencing of another gene, lin-14, at the appropriate time in the
development of the worm C. elegans.
Two small transcripts of lin-4 (22nt and 61nt) were found to be complementary to a sequence in the 3' UTR of lin-14.
Because lin-4 encoded no protein, she deduced that it must be these transcripts that are causing the silencing by RNA-RNA interactions.
Types of RNAi ( non coding RNA)
MiRNA
Length (23-25 nt)
Trans acting
Binds with target MRNA in mismatch
Translation inhibition
Si RNA
Length 21 nt.
Cis acting
Bind with target Mrna in perfect complementary sequence
Piwi-RNA
Length ; 25 to 36 nt.
Expressed in Germ Cells
Regulates trnasposomes activity
MECHANISM OF RNAI:
First the double-stranded RNA teams up with a protein complex named Dicer, which cuts the long RNA into short pieces.
Then another protein complex called RISC (RNA-induced silencing complex) discards one of the two RNA strands.
The RISC-docked, single-stranded RNA then pairs with the homologous mRNA and destroys it.
THE RISC COMPLEX:
RISC is large(>500kD) RNA multi- protein Binding complex which triggers MRNA degradation in response to MRNA
Unwinding of double stranded Si RNA by ATP independent Helicase
Active component of RISC is Ago proteins( ENDONUCLEASE) which cleave target MRNA.
DICER: endonuclease (RNase Family III)
Argonaute: Central Component of the RNA-Induced Silencing Complex (RISC)
One strand of the dsRNA produced by Dicer is retained in the RISC complex in association with Argonaute
ARGONAUTE PROTEIN :
1.PAZ(PIWI/Argonaute/ Zwille)- Recognition of target MRNA
2.PIWI (p-element induced wimpy Testis)- breaks Phosphodiester bond of mRNA.)RNAse H activity.
MiRNA:
The Double-stranded RNAs are naturally produced in eukaryotic cells during development, and they have a key role in regulating gene expression .
Professional air quality monitoring systems provide immediate, on-site data for analysis, compliance, and decision-making.
Monitor common gases, weather parameters, particulates.
7. Seismic method
Use acoustic waves (sound) to image the
subsurface
• Measure
• time for sound to get from surface to subsurface
reflectors and back - Two-way travel time (twt)
• Amplitude of reflection
• Wanted:
• Depth - Need to know subsurface velocities
• Rock properties (porosity, saturation, etc.)
10. Seismic acquisition
• Some energy will be reflected, some will be transmitted where there is a change in AI
• Amount reflected (amplitude of reflection) will depend on the relative difference in physical
properties across the interface
V11
V11
V22
V - V
V + V
2 2
2 2 11
11
– Define reflection coefficient (RC)
RC = AI2 – AI1
AI2 + AI1
– If AI2 > AI1 – positive RC
– If AI2 < AI1 – negative RC
14. Seismic resolution
• Convolutional theorem just described has
interesting implications for vertical resolution
– Each interface produces a distinct reflection.
– If reflections are widely enough spaced, each will
be recognizable.
– Once reflections start to get closer, they start to
interfere with each other.
– At some point adjacent reflections could be so
close that they completely cancel each other out.
20. Seismic acquisition
• Example 1:
V = 7,000 m/s
F = 50 Hz
l= V/F
= 7,000/50
[(m/s)/(cycles/s)]
= …….m
• Example 2:
V = 3,000 m/s
F = 50 Hz
l= V/F
= 3,000/50 [(m/s)/(cycles/s)]
= ……….m
22. Seismic acquisition
From the following Tuning Curve:
The following seismic section / Tuning curve showing
zone between TWT (0 to 200 ms) with dominant
frequency = 45 HZ. If the velocity of this interval is
5000m/sec.
-Compute the tuning thickness.
- Can you see/pick this interval in the seismic
section if its thickness is 15 meter? Why?
23. Understanding the Data
• Common Depth Points (CDPs)
• Floating datum
• Two way time (TWT)
• Time versus depth
24. Common Depth Points (CDPs)
CDPs are defined as ‘the common
reflecting point at depth on a
reflector or the halfway point when
a wave travels from a source to a
reflector to a receiver’.
25. Floating datum
The floating datum line represents travel time between the recording surface and the zero line
(generally sea level). This travel time depends on rock type, how weathered the rock is, and
other factors.
The topographic elevation is the height above sea level of the surface along which the
seismic data were acquired.
27. Time versus depth
• Two way time (TWT) does not
equate directly to depth.
• Depth of a specific reflector
can be determined using
boreholes.
• For example, 926 m depth =
0.58 sec. TWT
33. Random Noise
• energy which does not exhibit correlation from trace to trace
• not generally source generated (the noise would be present whether we were shooting or not)
Examples:
Swell Noise
Instrument Noise
Shark bites
Powerline Noise
Traffic (vehicles, people, animals)
Wind
Falling Debris
Earthquakes
34. Coherent Noise
• predictable from trace to trace across a group of traces i.e. have a phase relationship between
adjacent traces
• often source generated ( if we weren’t shooting the noise would not occur)
Examples:
Multiples
Direct arrivals
Ground roll
Refractions
Airwave
Cable Jerk
Autofire
Ship’s propeller noise
44. FK filter
• FK filter: Is a dip or velocity filter. Where filtering is performed on data after it has undergone a
2D fourier transform into the FK domain.
•Produce a diagram that shows how each of the following events in the XT domain are
represented on an FK spectrum: shallow dip, steep dip, flat event.
•Define each of the following terms : pass zone, reject zone, taper zone.
The Fourier Transform
Time domain Frequency Domain
46. Know Your Events
Frequency ( Hz )
Wavenumber, K = ---------------------------- X Dip ( ms / tr )
Trace Interval ( m )
We can now separate events on the basis of their dips and/or frequencies
53. Statistical Deconvolution
We can now use Statistical deconvolution techniques to remove the system
wavelet, by compressing it to a spike, and hence derive the reflectivity.
70. Positioning Problems
Energy
Source
The seismic ray hits an inclined
surface at 90º and reflects back
0.4 s -
The reflection is
displayed beneath the
source-receiver midpoint
Bounce
Point
Migration
71. Time for an Exercise
1
2 3 4 65
Where would the reflection lie?
90º
Migration
72. Time for an Exercise
1
2 3 4 65
Where would the reflection lie?
Compass
Migration
73. Time for an Exercise
1
2 3 4 65
Where would the reflection lie?
Migration
74. Exercise Answer
1
2 3 4 65
The reflection is downdip and its
dip is less than the interface
Migration
85. Pre Stack migration (2D marine)
Field data in
Mute
NMO correction
Migration
Stack
Amplitude scaling
Filtering
Final products
Energy spreading corrections Amplitude recovery
Low-cut / velocity filtering Noise rejection
Wavelet compression / demultiple Deconvolution
Velocity Analysis
Near/far offset noise removal
Summing traces within a cmp.
Lowcut / highcut / signal enhance
Time variant amplitude balancing
Cosmetic plotting test:bias/gain
Final velocity field
Initial velocity field
Migration
Data re-ordering
Possible additional velocity Analysis
CMP gather
Remove source wavelet from data Signature decon.
Define positions and relationships Geometry
DemultipleRemoving multiples
Final velocity field
SHOT SORTED
CMP SORTED
OFFSET SORTED
STACK SORTED
86. Processing Sequence (3D marine)
Field data QC & edit
Signature Decon.
Amplitude recovery
Noise rejection
Deconvolution
NMO correction
Apply automatic field edits
QC navigation data and select
binning strategy
2:1 data reduction
Temporal resample
Initial velocity field
DMO on velocity lines
Final velocity field
Nav./seismic merge
Mute
3D DMO & Stack
Migration
Migration vel. field
Demultiple
Time variant filtering
Time variant scaling
final products
field data
QC shot data
As early as possible!
QC stack displaysPre Stack Migration
87. Processing Sequence (2D land)
Basic Processes
Field data in
Geometry
Amplitude recovery
Noise rejection
Deconvolution
CMP gather
Mute
NMO correction
2D DMO & Stack
Migration
Amplitude scaling
Filtering
Final products
Residual statics
Field statics
loop
Initial velocity field
2D DMO
Final velocity field
88. Virtually all processing projects will require the following:
• Accurate locating of shots and receivers and their relationship
• Time-correction to a known datum
• Amplitude recovery
• Noise attenuation
• Signal enhancement
• Cmp gathering
• Demultiple
• Normal move-out correction (including muting any noise introduced)
• Residual time-corrections (land data)
• Correction for smearing within a cmp - dip-moveout correction
• Data reduction - stacking
• Repositioning / imaging - Migration
89. Seismic interpretation
• Check line scale and orientation.
• Work from the top of the section,
where clarity is usually best,
towards the bottom.
• Distinguish the major reflectors
and geometries of seismic
sequences.
91. Understanding the data (1)
CDPs are typically marked at intervals along the top of seismic lines and they are
regularly spaced to form a horizontal scale. Here, 80 CDPs represent about 1
kilometre (km).
92. Understanding the data (2)
Signals from farther away
will provide information for
deeper horizons
Gaps in land seismic data are
due to omissions where data
could not be acquired
For example, it is not always
possible to transmit the
signal above pipes, in
sensitive areas and above
buildings
93. Understanding the data (3)
• Two way time (TWT) is recorded on
the vertical axis of the seismic line in
fractions of a second. Sometimes it is
more convenient to express time as
milliseconds.
• TWT is the time required for the
seismic wave to travel from the
source to some point below the
surface and back up to the receiver.
95. Objectives of Well-Seismic Ties
• Well-seismic ties allow well data, measured in units of depth, to be
compared to seismic data, measured in units of time.
• This allows us to relate horizon tops identified in a well with specific
reflections on the seismic section.
• We use sonic and density well logs to generate a synthetic seismic
trace.
• The synthetic trace is compared to the real seismic data collected
near the well location.
97. Check Shot Data
• Check shots: measure the vertical one-way
time from surface to various depths
(geophone positions) within the well.
– Used to determine start time of top of well-
log curves
– Used to calibrate the relationship between
well depths and times calculated from a
sonic log
98. Pulses Types
• Two options for defining the pulse:
A. Use software that estimates the pulse
based on a ‘window’ of the real seismic
data at the well (recommended)
B. Use a standard pulse shape specifying
polarity, peak frequency and phase:
• Minimum phase
• Zero phase
• Quadrature
99. We ‘block’ the velocity (sonic) and density logs and compute an impedance ‘log’
Velocity Density Impedance
=x
Shale
Sand
Shale
Sand
Shale
Lithology
Reflection
Coefficients
• We calculate the reflection coefficients at the step-changes in impedance
*
Wavelet
• We convolve our pulse with the RC series to get individual wavelets
• Each RC generates a wavelet whose amplitude is proportional to the RC
Synthetic
• We sum the individual wavelets to get the synthetic seismic trace
The Modeling Process
122. Top down approach - Picking intersted Horizon
• Start at the top of the section, where definition is usually best
• Work down the section toward the zone where the signal to
noise ratio is reduced and the reflector definition is less clear
129. velocity from check-shot survey
• The velocity required for the map is Average velocity
• In case of determining velocity from check-shot survey, the result velocity will multiplying by 2 (to convert
it to one way time).
130. Depth contour map
• We extract the depth map values from the velocity & one way time map.
131. Depth Conversion-Simple Average Velocity
• Convert depth to depth below seismic reference datum, and convert TWT to a one-way
time.
133. Types of Petroleum Traps
❖ Several geologic structures may act as petroleum traps,
but all have two basic conditions in common:
1) Porous, permeable reservoir rock that will contain
quantities of oil and gas that make it worth drilling.
2) Impermeable cap rock that traps oil and gas preventing
it from escaping to the surface.
❖ Types of Petroleum traps include:
1) Anticline Trap 3) Fault Trap
2) Salt Dome Trap 4) Stratigraphic Trap
134. Types of Petroleum Traps
1) Anticline Trap:
• If a permeable rock like sandstone or limestone is located between
impermeable rock layers like shale and the rocks are folded into an
anticline, oil and gas can move upward in the permeable reservoir rocks,
and accumulate in the upper region of the anticline.
135. How to find oil: Source rock, reservoir rock, traps
137. Types of Petroleum Traps
2) Fault Trap :
➢ If faulting can shift permeable and impermeable rocks so
that the permeable rocks always have impermeable
rocks above them, then an oil trap can form.
➢ Note that both normal faults and reverse faults can form
this type of oil trap.
139. Types of Petroleum Traps
3) Salt Dome Trap :
➢ Here we see salt that has moved up through the Earth,
punching through and bending rock along the way.
➢ Oil can come to rest right up against the impermeable
salt, which makes salt an effective trap rock.
142. Types of Petroleum Traps
4) Limestone Reef Trap :
➢ Limestone reef trap is a type of stratigraphic trap.
➢ When coral reefs become buried by other
impermeable sediments they can form excellent oil
sources and reservoirs.
143. Example 1
Which petroleum trap would be formed by a simple fold?
(A) anticline (B) fault
(C) salt dome (D) stratigraphic
The limestone reef trap belongs to which type of petroleum
trap?
(A) anticline (B) fault
(C) salt dome (D) stratigraphic
144. Example 2
Based on the diagram below, which is the correct match
between the force and petroleum trap produced?