Fast, interactive hydrocarbon systems modelling

1
Fast, interactive hydrocarbon systems modelling
2
Why? The point of a geometric approach

• Focuses on first order effects
• Fast to run
• Easy to change
• Easy to communicate

The ability to easily, and above all rapidly,
integrate structural and sedimentological
effects, regional and local effects into a first
order model allows the many more scenarios to be
assessed.
This means greater confidence in the scenario you
choose.
3
What can geometric modelling reveal?

• viability of sediment access
• location of depocenters
• potential to locate occurrence of fault seal
  issues
• potential accumulation number, size and location
• correlation with known data
• prospect sensitivity to multiple factors, e.g.
  timing of events, isostatic effects, facies
  distribution

4
Workflow
change model, e.g. geometry, attributes
5
Workflow model building

• horizons and faults in a tidy model
• cultural data included, e.g. existing fields
• seismic attributes integrated
• facies maps integrated

The model can be refined during restoration

• erosion rebuilt
• palaeobathymetric data included

6
Workflow populating with attributes

• can be derived from many sources
• can be added from spreadsheets
• can be edited by hand or painted onto surface
• can vary laterally and between layers

7
Workflow Backstripping
Initial model
Top layer removed, model isostatically adjusted
8
Workflow Backstrip
Further backstripping and isostatic adjustement
to deposition time
9
Workflow Analyse for deposition
Sediment depocenters mapped and filled to
desired level. Sand body shape and location
integrated into model
10
Workflow Analyse for charge
Hydrocarbon migration paths shown in white for
reservoir facies. Sand bodies mapped as facies
attributes on surface, (warm colours
sand-prone).
11
Workflow Sensitivity testing

• impact of isostatic adjustment

Without isostatic adjustment
With isostatic adjustment
Accumulations are large and simple in shape
Accumulations are much smaller!
12
Example 1 Salt
13
Example 1 Salt
Sediment spill thickness 500ft
Isolated sediment packages
14
Example 1 Salt
Sediment spill thickness 1000ft Note increased
size of individual catchment areas
Partially merged sediment packages
15
Example 1 Salt
Sediment spill thickness 1500ft Note increased
size of individual catchment areas
Fully merged sediment packages
16
Example 1 Salt
Up-dip hydro-carbon migration routes (T2) related
to sediment spill planes(T5)
Prospects
Pull-up artefact below isolated salt
17
Example 1 Salt
Sediment accumulations
oil migration routes
18
Example 1 Salt

• Benefits focussed technical effort
• Location of potential reservoir bodies can be
  mapped and high risk areas discarded
• Coincidence of high potential for reservoir
  presence can be matched with high charge potential

This can be done before any detailed facies
analysis, thermal history analysis etc needs to
be done.
19
Example 2 Reservoir presence
Depositional surface
present day
depositional time
20
Example 2 Reservoir presence

• Prospect area showing
• known sand pinchout
• modeled sand pinchout
• seismic attribute limits

21
Example 2 Reservoir presence
With modelled compacted sediment fill
22
Example 2 Charge risk
Northern producing fields Prospect has no
charge potential as kitchen is too far to
west Prospect is super drainage cell for the
region at gt120m fill
23
Example 2 Charge risk
Northern producing fields Prospect with charge
and culminations Prospect is super drainage cell
for the region
24
Example 2 Charge risk

• Model
• Both the Base Lower Cretaceous and Balder
  horizons.
• Base Lower Cretaceous conditioned to Jurassic
  sub crop line
• Balder conditioned to sand pinch out

25
Example 2 Charge risk
Northern producing fields receive
charge Prospect super drainage cell for the
region relying on spill from northern producing
fields Charge from the south bypasses upper
reservoir
26
Example 2 Reservoir presence/Charge risk

• Benefits prospect viability
• Sediment model assessed for viability
• Multiple charge scenarios assessed for their
  impact on the charge potential

This allows a variety of charge paths and times
to be considered before assessing the likely
charge risk on the prospect. It also allows
better definition of more detailed
reservoir/thermal models in the event of
successfully locating an accumulation.
27
Example 3 Evolution of deposition

• Model has been decompacted and backstripped
• Sediment was sourced from north

Depth map of depositional surface, blue deep
28
Example 3 Evolution of deposition
Red earliest stage deposition Blue latest
stage deposition
Seismic amplitude map
29
Example 3 Evolution of deposition

• Main depocenter occupies south west corner of
  model
• Correlates with red amplitude values
• Unconnected depocenter to the north
• Correlates with red amplitude values.

450m depositional fill
30
Example 3 Evolution of deposition

• Main depocenter has extended to the north and
  slightly to the east.
• Partially matched by grey amplitude values

460m depositional fill
31
Example 3 Evolution of deposition

• Depocenters merge across the southern area,
  extending to the east.
• Correlates with the grey amplitude values

470m depositional fill
32
Example 3 Evolution of deposition

• Final geometry of depocenters shows a poorer
  correlation with the amplitude pick.

480m depositional fill
33
Example 3 Evolution of deposition

• Eastwards migration of the depositional system
• Supporting the interpretation made for the
  amplitude map.
• Northern depocenter has remained unchanged

Composite map of deposystem edge
34
Example 3 Evolution of deposition

• Benefits - early stage prospect assessment and
  risk factor identification
• Rapid test of evolution of depositional fill
  provided confirmatory evidence for initial
  premise
• Sequential fill in 10m increments of uncompacted
  fill demonstrates the extreme sensitivity of
  prospect shape to depositional thickness.

This allows early stage support for prospect
validity plus highlighting the potential risk
areas for further study
35
Conclusions - Benefits of geometric
dispersal/migration testing

• Fast, easy
• Concept validity testing
• Early prospect evaluation support
• Multiple scenario testing
• Identification of relevant sensitivity factors
• Larger database for detailed model building

36
Acknowledgements
The author would like to thank colleagues at
Midland Valley for discussions and
recommendations. Midland Valley would like to
thank bp for the permission to use some of the
models which appear in this presentation. The
functionality presented here was developed in
association with bp.