1. Data Analysis Lecture 12 Sand Fairway Burial History Trap Analysis A’
Slope
Non-
Marine
Near-
shore
Coastal
Plain
Sand Fairway
Basin
0 Ma
68 Ma
60 Ma
48 Ma
38 Ma
29 Ma
18 Ma
10 Ma
Burial History
Slide 1
Introductory slide for data analysis
The 4 images appear within the lecture
Trap Analysis
Synclinal Spill Point A’
Synclinal Spill Point
Controls HC Level
Low
Cross-Section View A
Map View
Low
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2. Objectives & Relevance
Introduce some types of analyses that are used to mature a lead into a prospect once the geologic framework is established
Slide 2
The objective of this lecture is to introduce some types of analyses that are used to mature a lead into a
prospect once the geologic framework is established
It will demonstrate some of the scientific methods we use to determine where to drill
Relevance:
Demonstrate some of the scientific methods we use to determine where to drill
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3. Overview of Data Analysis
Once the geologic framework is complete, we can:
Analyze present-day conditions
Where are potential traps?
How much might the trap hold (volume)?
What are the key uncertainties & risks?
Look for geophysical support
DHI and AVO analysis
Model basin fill
When/where have HCs been generated?
How have rock properties changed with time?
Slide 3
Once the geologic framework is complete, we can:
Analyze present-day conditions
Where are potential traps?
How much might the trap hold (volume)?
What are the key uncertainties & risks?
Look for geophysical support
DHI and AVO analysis
Model basin fill
When/where have HCs been generated?
How have rock properties changed with time?
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4. Time-to-Depth Conversion Identify Sand Fairways Identify Traps
Outline
Time-to-Depth Conversion
Identify Sand Fairways
Identify Traps
Geophysical Evidence
Direct HC Indicators (DHIs)
Amplitude versus Offset (AVO)
Basin Modeling
Back-strip stratigraphy (geohistory)
Forward model (simulation)
Slide 4
Outline of the topics that we will briefly discussed
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5. 1. Time-to-Depth Conversion
Horizons & Faults
in units of 2-way time
(milliseconds)
Velocity Data
derived from seismic processing
Well Data
calibration
Slide 5
Time to depth conversion
Our horizons and faults have been interpreted in units of two-way travel time
We need to get these to depth units – either feet or meters
We have course velocity information obtained during seismic data processing
We may also have well data that includes check shots or VSPs (Vertical Seismic Profiles)
these data are collected with shots at the surface and geophones down the well bore
thus they give us the link between depth in the borehole where the geophones are located and
two-way travel time that is measured when a shot goes off on the surface and is detected by a down-hole geophone
There are several methods to use velocity information to convert from time to depth
details are beyond the scope of this course
Bottom line – we can use velocities to convert our interpreted horizons and faults from time values to depth values (feet, meters)
Time-to-Depth
Conversion
Horizons & Faults
in units of depth
(meters or feet)
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6. Time-to-Depth Conversion Identify Sand Fairways Identify Traps
Outline
Time-to-Depth Conversion
Identify Sand Fairways
Identify Traps
Geophysical Evidence
Direct HC Indicators (DHIs)
Amplitude versus Offset (AVO)
Basin Modeling
Back-strip stratigraphy (geohistory)
Forward model (simulation)
Slide 6
We want to identify sand fairways – where we have the best chance to have reservoir-quality rocks
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7. 2. Identify Sand Fairways
For key seismic sequences, namely potential reservoir intervals
Reflection
Geometries
ABC codes
Interval
Attributes
Well Data
calibration
Seismic
Attribute Maps
Slide 7
In unit 10b we discussed the ABC method for capturing geometric observations and predicting EODs
Once we have EODs, we use depositional models to predict lithologies – including sand fairways
We can also use seismic attributes (amplitude, frequency, etc.) over an interval associated with the
sequence we are interested in
If we have well data, we can use it to calibrate the seismic response, i.e., we know the lithology at
the well location and can use the seismic response there to help predict away from the well(s)
To predict away from the wells (i.e., at an undrilled location) we will use ABC maps seismic attribute maps to
predict EODs, infer lithologies, and identify potential sand fairways
EODs
environments
of deposition
Sand Fairways
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8. Example: Nearshore Sands
Coastal Plain
Nearshore
Slope
Basin
Slide 8
Here is an example where the reflection geometries are fairly diagnostic
We have oblique progradation indicated by the seismic reflection geometries
This is very similar to the cartoon example covered in lecture 10b
We can predict where we would find coastal plain, shoreface and offshore deposits
We can then infer that there is a good possibility that we have a sand fairway in the region of nearshore deposits (yellow)
Basin
Slope
Non-
Marine
Near-
shore 10 20 40 50
Coastal
Plain 30
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9. Time-to-Depth Conversion Identify Sand Fairways Identify Traps
Outline
Time-to-Depth Conversion
Identify Sand Fairways
Identify Traps
Geophysical Evidence
Direct HC Indicators (DHIs)
Amplitude versus Offset (AVO)
Basin Modeling
Back-strip stratigraphy (geohistory)
Forward model (simulation)
Slide 9
Next we have to identify traps – structural, stratigraphic, or combination traps
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10. Combination traps (structure + stratigraphy)
3. Identify Traps
Use depth (or time) structure maps, with fault zones, to look for places where significant accumulations of HC might be trapped:
Structural traps
e.g., anticlines, high-side fault blocks, low-side roll-overs
Stratigraphic traps
e.g., sub-unconformity traps, sand pinch-outs
Combination traps (structure + stratigraphy)
e.g., deep-water channel crossing an anticline
Slide 10
We use depth (or time) structure maps, which include the fault zones, to look for places where significant accumulations of
HC might be trapped:
Structural traps would be things such as: anticlines, high-side fault blocks, or low-side roll-overs (slides 11 and 12)
Stratigraphic traps would be things such as: sub-unconformity traps, or sand pinch-outs (slides 13 and 14)
Combination traps (structure + stratigraphy) would be things such as: a deep-water channel that crosses an anticline (slide 15)
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11. Structural Traps – A Simple Anticline
Synclinal Spill Point
If HC charge is great A’
Low A
Synclinal Spill Point
Controls HC Level A’ A
Slide 11
Here is an example of a simple structural trap – an anticline
On the left is a map view; on the right is cross-section A-A’
If enough HC has migrated into the trap, it will be filled to a spill or leak point
For this example, the spill point is on the ENE side of the high (anticline)
If more HC is added to this trap, the extra HC will spill to the ENE, possibly filling another trap further along the migration pathway
Low
HCs migrate to anticline
Traps progressively fills down
When HCs reaching the trap is greater, the trap is filled to a leak point
Here there is a synclinal leak point on the east side of the trap
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12. Structural Traps – A Simple Anticline
Synclinal Spill Point
If HC charge is limited A’
Low A
HC Migrating to Trap
Controls HC Level A’
Only enough oil has reached the trap to fill it to this level A
Slide 12
If the amount of HC reaching the trap is small (less than the trap could hold), then the trap is said to be under-filled
In this example the trap is ‘HC charge-limited’ and is not filled to the spill point
The way the cross-section is drawn, both ‘bumps’ have been filled to about the same level
This would be true if HC migration came from the NW or SE
If HC migration came from the west, it would first fill the western ‘bump’ to the saddle point and then HC would
start to fill the eastern ‘bump’
If HC migration came from the east, how would the two ‘bumps’ fill? Fill east first; then spill to west
Low
HCs migrate to anticline
Traps progressively fills down
When HCs reaching the trap is small, the trap is under-filled – it could hold more
Here the trap is ‘charge-limited’ and is not filled to the synclinal leak point
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13. Structural Traps – A Roll-Over Anticline
Faulted Anticline – Fault Leaks
Faulted Anticline – Fault Seals A A’ A A’
Leak at Fault
Controls HC Level
Synclinal Leak Point
Controls HC Level
Slide 13
Here is another type of structural trap with two degrees of fill
On the left, a cross-section is on top and a map view is below
where the reservoir on the down side touches the fault is the leak point
more HC fill would leak across and up the fault plane and move through the high-side sands
On the right, a cross-section is on top and a map view is below
here the fault ‘seals’ – does not allow HC to move through it
the reservoir fill level is controlled by a synclinal leak point to the west
This illustrates the importance of predicting whether a fault leaks or seals HCs
It could be that the left case does not hold enough HC to be an economic success, but the right case does hold
enough HC to be an economic success
There are methods to predict the sealing potential of faults, but that topic is beyond the scope of this course A A’
Leak Point
Leak Point
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14. Stratigraphic Traps – Sub-Unconformity & Reef
Upper Sand
Lower Sand
Slide 14
Here are two stratigraphic traps
On the left, a cross-section is on top and a map view is below
This represents a sub-unconformity style of trap
sands below the unconformity have a component of dip and form the reservoir
above the unconformity is a marine shale that provides the seal
here the big unknown is how far downdip the sands contain HCs
On the right, a cross-section is on top and a map view is below
This represents an isolated carbonate reef
porous and permeable carbonate facies form the reservoir – often in the edges of the reef rather than in the
central lagoon facies
Again there has to be an adequate seal facies capping the reef and along the edges A
Upper Sand A’ B B’
Lower Sand
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15. Combo Traps – Channel over an Anticline
Structure
Stratigraphy A A
Low
Shale
Channel Margin
High
Channel Axis
Channel Margin
Shale
Low
Slide 15
This slide illustrates a combination trap
Top left = structure map with an anticline in the center
Top right = depositional facies – a deep water channel system. The axial facies (light yellow) has the best reservoir properties
Bottom right = cross-section showing structure, depositional facies, and green is where the oil is trapped
Bottom left = map view with structure contours, facies belts and oil within reservoir quality rocks
The anticline causes oil to migrate towards the high point (crest)
The facies belts limit the producible reservoir to the channel axis facies
The trap has both a structural & a stratigraphic component A’ A’ A A’
Structure + Stratigraphy
OIL
Water
Cross Section
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16. Time-to-Depth Conversion Identify Sand Fairways Identify Traps
Outline
Time-to-Depth Conversion
Identify Sand Fairways
Identify Traps
Geophysical Evidence
Direct HC Indicators (DHIs)
Amplitude versus Offset (AVO)
Basin Modeling
Back-strip stratigraphy (geohistory)
Forward model (simulation)
Slide 16
Next we will highlight some geophysical evidence for the presence of HCs
There are two types of evidence:
DHIs – Direct Hydrcarbon Indicators
AVO – Amplitude Versus Offset
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17. DHI = Direct Hydrocarbon Indicator
What Are DHIs?
DHI = Direct Hydrocarbon Indicator
Seismic DHI’s are anomalous seismic responses related to the presence of hydrocarbons
Acoustic impedance of a porous rock decreases as hydrocarbon replaces brine in pore spaces of the rock, causing a seismic anomaly (DHI)
There are a number of DHI signatures; we will look at a few common ones:
Amplitude anomaly
Fluid contact reflection
Fit to structural contours
Slide 17
A DHI is a direct hydrocarbon indicator
This means that there is something anomalous in the seismic response caused by the presence of HCs
When the porous rock has HC in the pore spaces of the rock, the combination of velocity and density results in
a diagnostic seismic anomaly (a DHI)
There are a number of DHI signatures that we look for, such as:
an Amplitude anomaly
a Fluid contact reflection
the anomaly exhibits a good Fit to structural contours
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18. Typical Impedance Depth Trends
In general:
Oil sands are lower impedance than water sands and shales
Gas sands are lower impedance than oil sands
The difference in the impedance tends to decrease with depth
The larger the impedance difference between the HC sand and it’s encasing shale, the greater the anomaly
IMPEDANCE x 103 5 10 15 20 25 3 4
SHALE
OIL
SAND 5
Looking for
shallow gas 6
Slide 18
This graph is based in data from the Gulf of Mexico – impedance versus depth for shales and for sands with 3 types
of fluids in the pores: water, oil, gas
Look around 4,000 ft
shale and water sand have about the same impedance so reflection amplitudes would be weak (low)
oil sand has an impedance that is about 15% lower
if a thick oil sand is encased above and below by shales and water sands, it would be associated
with a moderate to high reflection amplitude from its top and base (with opposite polarities)
gas sand has an impedance that is about 40% lower
if a thick gas sand is encased above and below by shales and water sands, it would be associated
with an extremely high reflection amplitude from its top and base (with opposite polarities)
at a depth of 4,000 ft, we should be able to differentiate water sands from oil sands from gas sands by the amplitude response
At 7,500 feet, an oil sand would have about 8% lower impedance; gas about 25% lower
there would still be significant impedance contrasts, but the amplitudes would not be as strong
The deeper the potential reservoir, the less diagnostic is the amplitude response
Gas sand would be diagnostic; oil sands might be harder to detect
Using reflection amplitudes to detect the presence of HCs is commonly referred to as “Bight Spot” technology
It works in many basins, not just the Gulf of Mexico
GAS
SAND
DEPTH x 103 FEET 7
WATER SAND 8
Looking for
deep oil 9 10
Data for Gulf Of Mexico Clastics
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19. DHIs: Amplitude Anomalies
Anomalous amplitudes
Change in amplitude
along the reflector
Low
High Amplitude
Slide 19
These images are from some modeled seismic data with random noise included
The left image shows two regions with anomalous amplitudes – dark blacks and big excursions in the troughs (whites)
In the upper region, the basal strong reflection also appears rather flat – another clue
In the right image, a much thicker reservoir is modeled
There are several clues to note:
the reflection at the top (yellow line) changes from low to high amplitude as it goes from a water sand (left) to a HC sand (right)
the strong basal reflection on the right indicates the bottom of the HC-filled sand
towards the center, the strong black becomes nearly flat
this flat to dipping geometry at the base of the HC-bearing zone is commonly called a “hockey stick”
the central (flat) portion is a reflection off the fluid contact – HC-filled sand above with water-filled sand below
although the sand properties are the same, having different fluids results in different velocities and densities
for the formation and thus different seismic responses
So on the right we have two lines of evidence
an amplitude anomaly at the top and base of the HC-bearing rock, and
a fluid contact reflection
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20. DHIs: Fluid Contacts
Hydrocarbons are lighter than water and tend to form flat events at the gas/oil contact and the oil/water contact.
Thicker Reservoir
Fluid contact
event
Slide 20
Here are two more seismic models (with added noise) to illustrate a fluid contact reflection
Note the “hockey stick” in the upper image
For the lower image, the reservoir is thinner – note no internal ‘peak’
IMPORTANT – a fluid contact will be flat (horizontal) in depth, unless there is a hydrodynamic gradient causing it to tilt
Since we are looking at data in the time domain, there can be some distortions if the velocities above the reservoir
vary laterally and cause a flat event in time to be tilted on a time section
Thinner Reservoir
Fluid contact
event
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21. DHIs: Fit to Structure
Since hydrocarbons are lighter than water, the fluid contacts and associated anomalous seismic events are generally flat in depth and therefore conform to structure, i.e., mimic a contour line
Slide 21
If we have a prospect with a fluid reflection, that fluid reflection should be flat in depth
We can plot where the fluid reflection is and post it on a map
We can then measure how well it conforms to a constant depth contour around a structure (anticline)
If we are working in units of two-way time, it usually show a good to fair fit to structure
If the fit to structure is not good, we would convert the interpreted top of reservoir horizon from two-way time to
depth (ft or meters) and check again
It is rare that the fluid contact actually dips in depth due to a hydrodynamic gradient
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22. What is AVO?
AVO = Amplitude vs. Offset
We can take seismic data and process it to include all offsets (full stack) or select offsets (partial stacks)
For HC analysis, we often get a near-angle stack and a far-angle stack
The difference in amplitude for a target interval on near vs. far stacks can indicate the type of fluid within the pore space of the rock
AVO analysis examines such amplitude differences
Slide 22
AVO is an analysis of how reflection amplitude varies as a function of incident angle
I lied before when I said the reflection coefficient was a function of velocities and densities – please forgive me
There is another factor that can be important, the angle of incident of the seismic energy hitting the interface
If a shot and receiver are close, then the incident angle is close to 90°
However, if the shot-to-receiver distance is several kilometers, the incident angle could be greater than 30°
The impact of the incident angle is different for shales, water-sands, oil-sands and gas-sands
AVO analysis capitalizes on these differences
We can ask our data processors to stack the data (combine shot-receiver pairs) in different ways
A full stack uses all shot-receiver pairs at all incident angles
A near stack might use only the receivers in the first (nearest to the boat) half of the streamers
A far stack might use only the receivers in the second (farthest from the boat) half of the streamers
We can then compare the reflection amplitude from a reflection off the top of a potential reservoir from the near stack
relative to amplitude on the far stack
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23. Some Additional Geophysics
Energy
Source
Receiver 
Seismic reflections are generated at acoustic boundaries θ θ
Layer N
Layer N +1
Slide 23
This shows one source-receiver pair and illustrates the incidence angle Θ
Note: the physics dictates that we really want Θ, the angle of incidence
It is easier for us to stack the seismic data by distance along the streamer/cable
AVO is amplitude versus offset – or distance along the streamer
AVA is amplitude versus angle – a better way to do things but a bit more expensive to obtain
Many companies do AVA in the data processing, but get sloppy in their terminology and call it AVO analysis
The amplitude of a seismic reflection
is a function of:
velocities above & below an interface
densities above & below an interface
θ - the angle of incidence of the seismic energy }
Change in Impedance
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24. Why Do We Care?
Reflection amplitude varies with θ as a function of the physical properties above and below the interface
Rock / lithologic properties
Properties of the fluids in the pores
Examining variations in amplitude with angle (or offset) may help us unravel lithology and fluid effects, especially at the top of a reservoir
Slide 24
This slides explains (again) why we care about AVA or AVO
Note in the diagram, the top of the reservoir is in a trough
The excursion to the left (amplitude) for the near offset stack is noticeably less than the
excursion to the left (amplitude) for the far offset stack
The same can be said for the base of the reservoir and its associated peak (black)
Why the polarity change (top = trough, base = peak)?
The yellow HC sand has a lower impedance than the other layers
So there is a decrease in impedance at the top of the reservoir (higher to lower impedance) and
an increase in impedance at the base of the reservoir (lower to higher impedance)
Top of Reservoir
Base of Reservoir
Impedance
Lo Hi
Zero
Offset
Near
Offset
Full
Offset
Far
Offset
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25. AVO: Quantified with 2 Parameters
We quantify the AVO response in terms of two parameters:
Intercept (A) - where the curve intersects 0º
Slope (B) - a linear fit to the AVO data
CDP Gather: HC Leg
Time
Angle/Offset
AVO Curve
AVO Crossplot
Negative Intercept
Negative Slope
Slide 25
We need a way to easily analyze amplitude changes with angle or offset
Geophysicists defined two parameters for us: A and B
The diagram on the left is a flattened CDP gather – the common traces for a location with the ‘hyperbolas’ removed
by correcting the gather with an appropriate velocity
the trace on the left is close to 90° incidence; the one on the right is close to 35°
The red line is the position of the top of a reservoir
The second diagram shows the amplitude of the trough with angle (or offset)
the trough amplitudes (negative numbers) become more negative with angle (or offset)
We can approximate this amplitude variation with a straight line fit
this straight line can be characterized by a slope (gradient) and an intercept (value when x = 0; 90° incidence)
The parameter A is the intercept value; B is the slope (or gradient)
We can express the amplitude vs offset as a point on the right chart, which plots A (intercept) against B (gradient or slope)
Typically we build seismic models and fill a sand layer with the three types of fluid – water, oil, gas
Each fluid type will lie in a different portion of the A B crossplot (right chart)
The more separate the three points, the easier it is to differentiate water-sands from oil-sands from gas-sands
Amplitude
Angle/Offset
AVO Gradient (B)
Oil
Water
For some reservoirs, the AVO response differs when gas, oil and water fill the pore space
Gas
AVO Intercept (A)
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26. Seismic Example Alpha Fluid Contact? Gas over Oil? Fluid Contact?
Slide 26
Here is a seismic line with good DHI evidence for HCs
The top of reservoir reflection changes amplitude with depth indicating a possible change in fluid type
There is a good fluid reflection at the oil-water contact; a more subtle one at the gas-oil contact
When we perform an AVO analysis, on an A versus B cross-plot, we get a three clouds of amplitude points that indicate we have gas high on the structure, oil at intermediate depths, and water-filled sands below the lower fluid event
Fluid Contact?
Oil over Water?
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27. Analyzing Present-Day Conditions
From present-day configurations, we can:
Predict where Sand Fairways & Source Intervals
Predict EODs and infer lithologies
Evaluate the Trap Configuration
Identify and Size Potential Traps
Consider spill / leak points
Consider if a Sealing Unit Exists
Can shales provide top & lateral seal?
Identify where a distinct HC response occurs
DHI and AVO analysis
Model a simple HC Migration Case
Use present-day dips on stratal units
Assume buoyancy-driven migration
Slide 27
Our interpretation shows us the present-day structure and stratigraphy
From this we can:
Predict where sand fairways & source intervals occur by predict EODs and inferring lithologies
Evaluate trap configurations by identifying and sizing potential traps and
considering spill / leak points
Consider if sealing units exist by determining if shales or other low permeability lithologies provide top & lateral seal
Identify where a distinct HC response occurs through DHI and/or AVO analysis
Model a simple HC migration case by using present-day dips on stratal units and
assuming buoyancy-driven migration
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28. We Would Like to Know More
We need to incorporate the element of time:
When did the traps form?
When did the source rocks generate HCs?
What was the attitude (dip) of the strata when the HCs were migrating?
What is the quality of the reservoir (Φ , k)
How adequate is the seal?
How have temperature and pressure conditions changed through time?
Slide 28
We would like to know more by including the element of geologic time
When did the traps form?
When did the source rocks generate HCs?
What was the attitude (dip) of the strata when the HCs were migrating?
What is the quality of the reservoir (porosity and permeability)
How adequate is the seal?
How have temperature and pressure conditions changed through time?
To answer these questions, we have to model the basin’s history from the time of deposition to the present
To answer these questions, we have to model the basin’s history from the time of deposition to the present
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29. Time-to-Depth Conversion Identify Sand Fairways Identify Traps
Outline
Time-to-Depth Conversion
Identify Sand Fairways
Identify Traps
Geophysical Evidence
Direct HC Indicators (DHIs)
Amplitude versus Offset (AVO)
Basin Modeling
Back-strip stratigraphy (geohistory)
Forward model (simulation)
Slide 29
That brings us to topic #5 Basin modeling
There are two approaches:
to go back in time from the present-day configurations – geohistory
to model the basin’s development forward through geology time - simulation
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30. Limited to Mapped Horizons Regular Intervals as Defined by the User
Basin Modeling
Back-strip the
Present-day
Strata to
Unravel
the Basin’s
History
Time Steps are
Limited to Mapped Horizons
Model Rock
& Fluid Properties
Forward through Time
Time Steps are
Regular Intervals as Defined by the User
0 Ma
18 Ma
Slide 30
Here is a simple cross-section with 4 major depositional units
brown, orange, yellow and green
We can back-strip each unit and estimate the basin’s shape – unit by unit
We do need to predict paleo-water depths
We are limited to the ages of the interpreted horizons – here 18 Ma, 29 Ma, 36 Ma and before deposition began at 42 Ma
After we do the back-stripping, we can estimate the parameters that controlled the basin’s development,
such as subsidence rates through time,
sediment supply through time,
paleobathymetry, and
some estimate of sea level change through time
We can then use basin simulation software to model the basin forward through time
We can use a much smaller time step, e.g., ½ million year
We can also model temperatures, pressures, HC generation, porosity changes, etc
29 Ma
36 Ma
42 Ma
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31. Basin Modeling We start with the present-day stratigraphy
Then we back-strip the interpreted sequences to get information of basin formation and fill
For some basins, we can deduce a heat flow history from the subsidence history (exercise)
Next we model basin fill forward through time at a uniform time step (typically ½ or 1 Ma)
If we have well data, we check our model
Temperature data
Organic maturity (vitrinite reflectance)
Porosity
Given a calibrated basin model, we predict
HC generation from source intervals
Reservoir porosity
Slide 31
Recap of how we might model a basin’s history
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32. Simple Model of HC Migration
Generate oil and gas at lower left
HCs ‘percolate’ into porous interval (white)
Trap A fills with oil and gas – gas displaces oil
Trap B fills with spilled oil and gas
Seal at B will only hold a certain thickness of gas
At trap B – gas leaks while oil spills
Trap C
Slide 32
This animation shows output from some HC migration software
Buoyancy is the driving mechanism and rock properties have to be defined
In this example:
Trap A has a very good seal – it has early oil fill which is displaced by late gas
Trap B has a good seal for oil but allows gas to leak once the gas thickness exceeds a critical value
Trap B maintains an oil leg – the gas can not displace all the oil since it leaks through the top seal
Excess oil in Trap B (with some dissolved gas) spills into Trap C
This is a 2-D model to help show conceptually the types of HC migration, leak and spill that could occur
Rock properties can be varied (e.g., stronger to weaker seals, different source rock properties)
We can build 3-D migration models as well, but often we do not have adequate data to constrain the results
We model different scenarios, but usually can not say which is correct before we drill
Trap B
Migration Path
Of Spilled Oil
Spillage of
Excess Gas
“Gas separator”
Trap A
Traps with unlimited charge
Source
Generating HCs
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33. Intro to Exercise
Goal: To map the extent of the A1 gas-filled reservoir W
Figure 1
Inline 840
A1 Gas
Sand E
Slide 33
This introduces the exercise
You will be mapping part of the A1 sand – the part where gas is in the pore space
Note the strong (high negative amplitude) trough
Also note there are faults
On this line a fault forms the western boundary of the gas field
Courtesy of ExxonMobil
L12 – Data Analysis

34. Changes in Amplitude Indicate Fluid
Gas Sand
Water Sand
Inline 840
Slide 34
You will be looking at the magnitude of the trough – its largest negative amplitude
The blow-up on the left shows extremely negative numbers
where the trough is vertical, the values are so negative that they have been clipped for display purposes
Compare this response to the blow-up on the right
On the right, where water is the pore fluid, the response is weaker (less negative numbers)
Traces are
‘clipped’
Figure 1
Courtesy of ExxonMobil
L12 – Data Analysis

35. Fluids within the A1 Sand
Inline 840
Figure 1
Slide 34
You can use the trough amplitudes to predict the fluid within the sand, as shown for inline 840
Extent of Gas
Courtesy of ExxonMobil
L12 – Data Analysis