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By Stig-Arne Kristoffersen, Kiev, Ukraine 2010
Stig-Arne Kristoffersen started his career in Exxon (Esso Norway) in 1985 (25 years in
the industry). Since then he has worked for several major national and international oil
and gas companies, as well within the consultancy business and mid cap companies
within oil and gas industry performing exploration evaluation and risk analysis.
He has held several project manager and supervisor roles in various companies, and
advised on exploration strategies and risk analysis.
Play-Based Exploration (PBE) has become a trendy term in the oil and gas industry,
championed by companies like ExxonMobil, Shell and BP.
PBE methods vary significantly; some firms create ‘traffic light’ maps of overall
relative profitability, others partitioning probability into play/shared and local
/prospect-specific probability with assigned values.
Play-based exploration reflect a shift in focus, as prospects are not the basic unit of
exploration, but plays are.
Individual prospect probabilities are balanced and calibrated with the play maps, and
prospect volumes are validated against the field size distribution (FSD) for the play.
Exploration evaluation experts use play-based exploration (PBE) to build a full
understanding of the geological basins that should be explored and to reassess
exploration strategies.
· Play specific datasets (e.g. key well analysis, volumes, success rates)
· Segmented play maps
· Prospect probabilities to be reconciled with play (segment) in which they reside
to ensure spatial balancing
· Reconcile predicted prospect volumes with discovery history and exploration
maturity
· Making decisions at the Play level rather than at the next Prospect level.
Let us explain what a play is………
A Play is;
• an area and thickness with expected favorable conditions for hydrocarbon
accumulation, independent of other plays. A play may contain more than one reservoir
and is largely defined by the master seal.- (Mobil)
• a group of new field prospects (and perhaps several producing fields as well) having
similar source, reservoir and trap controls on oil and gas occurrence.- (Baker, 1986)
• a geologically coherent group of prospects (and fields)...- (White, 1993)
• a group of fields and prospects having a chance for charge, reservoir and trap and
belonging to a geologically related stratigraphic unit- (Shell)
• a geographically and chronostratigraphically bounded unit of reservoir(s) and seal(s)
charged by the same source rock interval(s).- (Maersk)
Common for them all is that we deal with a physical entity and not a concept
petroleum systems, and they have a common history.
• prospect probabilities are balance with the play (segment) in which they belong, to
ensure spatial balancing
• predicted prospect volumes are calibrated towards the discovery history and
exploration maturity
• use more than “traffic lights‟ to understanding shared and prospect-specific probability.
This has a pronounced influence upon decision-making
-Bid strategy and appropriate risk tolerance
-Prospect sequencing
-Value of information – key data needs
-Preferable partners of choice/acquisition candidates
• strategic Play Analysis should be the core business process through a straightforward
process for calculating company-capture volumes/value, investment efficiency, and
chance of company economic success
MAKING DECISIONS ATTHE PLAY LEVEL RATHERTHANTHE NEXT PROSPECT LEVEL
Creates the basis for;
• country/basin/play/entry and investment levels
• manpower allocation and amount
• strategies for where to generate the prospects for the next 5 yrs
• prospect decisions in light of basin chance and potential
• efficient and consistent way to communicate probability in a spatial manner
• decisions based on consistent results in a consistent manner and better assessment of
priorities of prospects (and plays)
• quicker reaction to opportunities and optimal decision making
• standardized workflow within the organization that increase productivity and reduces
costs
• company-consistent formats for data capture and presentation
• improves consistency for prospect chance and volume assessments
• dynamic and updated database as more data are acquired
• assist identifying areas where more, or better, data are required
Pg
Trap
Pg
Seal
Pg
Source
Pg
Reservoir
Pg
COS
UTM X Y Prospect
0.7 0.7 1.0 0.7 0.34 23 156,500 1,450,679 A
0.9 0.5 0.9 0.8 0.32 23 157,250 1,480,321 B
1.0 0.8 0.7 0.6 0.34 23 166,130 1,571,234 C
0.8 0.7 0.8 0.8 0.36 23 155,300 1,485,702 D
0.6 0.9 0.6 0.7 0.23 23 158,450 1,781,630 E
0.8 0.7 1.0 0.8 0.45 23 147,356 1,491,906 F
Risk parameters
Geographic
coordinates
GIS database
Play
map(s)
Layered GIS maps enable the user to select what information he/she wants to display
Source: www.npd.no factmaps
Increasing Pg values
Towards the
North to North East
Anomalously high Pg value
0.50
0.24
0.20
0.48
0.21
0.19
0.19
0.18
Too low Pg value
Too high Pg
Justifiable high Pg value
High risk Moderate risk Low risk 0.21Prospect Estimated Pg
“Traffic Light maps” could be a starting point and adequate for the moment,
however there are some constraints with these maps that you need to be aware
of.
• colors convey a notional probability, but no quantitative ability associated with
them
• can not use them for yet-to-find volumes, actual Pg estimates, chance of successful
play entry analytics
• chance and uncertainty (as expressed by quality and density of data) are not
expressed and there are different grades of each color
• there can be a bias to areas of high/low data
• no real basis for consistency
• play- and prospect-specific chance not differentiated
0.21Prospect Estimated Pg
0.21
0.0 – 0.1
0.1 – 0.2
0.2 – 0.3
0.3 – 0.4
0.4 – 0.5
0.5 – 0.6
0.6 – 0.7
0.7 – 0.8
0.9 – 1.0
Pg range
0.8 – 0.9
0.61
0.81
0.21
0.33
0.18
0.31
0.72 0.21
0.21
0.21
0.83
0.54
0.16
0.08
0.61
0.51
To high Pg
To high Pg
To low Pg
To low Pg
To low Pg
To low Pg
To low Pg
0.
5
0
0.
2
40.
2
0
0.
4
8
0.
2
1
0.
1
9
0.
1
90.
1
8
Too
high
Pg
Post prospect Pg
on CRS maps
Placing prospect
success case volumes in
Play Field Size
Distribution (total life
and recent play history)
Placing remaining
prospect’s in play
„creaming‟ curve
Check for consistencies within your datasets both historically and for the future
Make Strategic Play Analysis a core business process to create a straightforward process for
calculating company-capture of volumes/value, investment efficiency, and predictions of
company economic success
•make decisions at play level rather than next prospect
• country/basin/play/entry and investment levels
• manpower allocation and where to generate the prospects for the next strategic
period
• check for prospect probabilities consistency versus the play (segment) in which they reside
to ensure spatial balancing
• check the predicted prospect versus discovery history and exploration maturity curve
• consolidate shared and prospect-specific probability as it has a pronounced influence
upon;
• decision-making
• bid strategy
• setting proper risk tolerance levels
• prospect sequencing
• assess the value of information to decide what and where key data are needed
Play Segment Boundaries describes significant and abrupt changes in geology in the
overall play.
What does 40% chance of geological success mean in this context?
• 40% percent chance of a discovery, if you were to drill the entire area?
• 40% of the locations will encounter hydrocarbons?
• 40% of the locations will encounter hydrocarbons - given that at least one will
(average success rate)?
The answer depends upon whether the map you are using conveys play-scale or local
information
Prospect A Prospect B
Play Description Eocene Deep water sandstones in combined
stratigraphic and structural traps with Upper
Jurassic source. Migration and bio-degradation
is the critical factor for play
Upper Jurassic marginal to shallow marine and
deep water sandstones in stratigraphic and
structural traps, rotated fault blocks with Upper
Jurassic source. Presence of reservoir and seal
is the critical factor for play.
Play Pg 0.25 1.00
Prospect Pg 0.85 0.20
Total Pg 0.21 0.20
Risked mean volume 750 MBO 700 MBO
Unrisked mean volume for play 750 MBO/0.25 = 3BBO 700 MBO/1.0 = 700 MBO
This example will illustrate the importance of looking at both the play and prospect Pg to
understand the overall risk ranking of these prospects.
Future Undiscovered Potential for these plays, which have the same number of undrilled prospects
with identical future volume characteristics – and the resulting risked mean volumes for Play A is
750 MMBO and 700 MMBO for Play B.
The SUCCESS CASEVOLUMES for Play B remain 700 MBO, while for Play B, volumes are 3.0 BBO
Unless you understand and factor the two chance factors into your analysis, this could not be
assessed.
This example shows both Chance/Risk and Success CaseVolumes
Curved lines represent venture unrisked volume isopleth
Impact on chance of play entry which is geological success in this case.
Exploration management consider to enter into these two plays, A and B, and
they plan a 3 prospect evaluation program.
The chance that hydrocarbons are found in play A is about 25%, while suppose
you know the blend of chances for play B the chance is 60%.
Management has to make a decision as to whether its worth the incremental
risk of 60% versus 25%, to the reward of volumetric potential of 3 BBO versus
750 MBO undiscovered volumes.
Strategy choices based on this scenario could be;
• Drill the best remaining prospect in Play B
or
• Drill the area or get more data that will give the most information about
migration for Play A, which may or may not be the best prospect in Play A, but
the optimal stratigraphic test.
PBE - Play Based Exploration
Play type
Data Base
Play assessment
Play segment
inventory
Manpower
allocation
Capital
allocation
Results
• use of consistent methodology
• use of consistent terminology
• do regular plausibility and reality checks through;
• global peer assessment
• link of petroleum system to play to prospect/segment
• associate prospect to known discoveries
• check the spatial integrity of risk levels of play versus prospect
• use of consistent software tools
Every organization is different, and there is no simple one recipe solution on
how to implement Play Base Exploration into your organization. However
there are some important elements that needs to be in place to have any
chance of making successful implementation and execution of PBE.
•Appoint and acknowledge a technical champion / process owner for PBE
development
• Ensure a central coordination, but make sure it not becomes a control unit
• Acquire and maintain a global, map based datasets
• Establish a performance tracking and feedback process in your organization
• Do regular global calibration sessions
•Adopt a portfolio mind setting for plays and prioritize at the play level
So, given you some basic elements that should be present to succeed with PBE
implementation and execution.Then I will list some elements that will make it
fail.
• lack of clear process owner / sponsor
• management push-back
• sense of competition
• data silos
• moving minima
• improper (spectacular) analogs
• not calibrated analyses (prospect/segment to play)
• not calibrated analyses (play to play, part play to part play
The PBE workflow consists of some basic steps that has to be performed before
the tool is ready to be used in your organization.
These elements have to be in place before any analytics are tried out, otherwise
any analytics is deemed to give you false guidance in your exploration efforts.
•play definitions (vertical/stratigraphical)
• geographic definition of play boundaries
• play portioning (segments) distinguished by abrupt and significant changes
changes in geology and other factors
• assigning chance variables to the play segments
• assign segment counts, FSD’s to each part play (Yet to Find Calculation)
• use maps to help guide exploration strategy
(PBE pyramid modified after D. Roberts, 2005)
Iteration when new
geological data and
analysis are
available
Long term Global processes Basin tectonics
Cyclical sedimentation
(megasequences)
- Assembly/Disassembly
- Relative sea level
- Paleogeography
- Paleolatitude
- Paleoclimate
- Convergent/Divergent
- Temporal changes in basin
- Style and impact upon sedimentation
- Predictable stratigraphic architecture
(transgressive/regressive)
- TIMING OF BASIN FORMATION
- SOURCE PREDICTION
- LITHOFACIES
- PRESERVATION RISK GIANT
- FIELDS
- RICHNESS RISK
- RESERVOIR
- SOURCE
- SEAL
By using a predictive stratigraphic model on a basin scale
PORTFOLIO
MANAGEMENT
PLAY
DELINIATION
SPATIAL
RELATIONSHIPS
PETROLEUM
SYSTEMS
TEMPORAL
RELATIONSHIPS
SPATIAL
RELATIONSHIPS
PREDICTIVE
STRATIGRAPHIC MODEL
BASIN SCALE
PLAY/ CONCESION SCALE
PHYSICAL PLAY ENTITIES
Source Rocks and Depositional Sequences
90% of world's reserves provided by source rocks deposited during 33% of
Phanerozoic time (6 time periods)
(Klemme and Ulmishek, 1991)
Structural and Preservation Styles
80% of the world's giant fields are located in 3 types of poly-history basins - 'A'
foredeep, cratonic-rift, Atlantic-rift
(Brooks, 1990, using Carmalt and St. John, 1986)
Location (Tectonic Realms)
68% of world's reserves are located in 17% of its total area (Tethyan realm); 91%
of world’s reserves are inTethyan and Boreal realms
(Klemme and Ulmishek, 1991)
Recent Generation
70% of world's reserves generated 90 MY-present. 40% generated 35MY-present
(Klemme and Ulmishek, 1991)
Megasequences are regional scale basin-fill patterns associated with significant (plate-scale) basin-forming processes.
A relatively small number of megasequence types are recognized (e.g., sag, synrift, foreland) , and each is characterized by unique
depositional patterns.
Generic models are widely published.
Megasequences form the first level primary stratigraphic analysis building block for basin analysis. Boundaries are usually very
pronounced on regional seismic lines
IODP Canada
One key aspect of identifying megasequences is that
source rocks are found at predictable positions within
each sequence
• relationship between
major tectonic events
and stratigraphy
• lithological variations
across basin
• variations in preserved
section(s) across basin
• primary source/seal/
reservoir intervals
• characterize basin tectonic setting
• evaluate the tectono-stratigraphic setting, regional tectonic elements, and
their changes through time
• identify megasequences (regional reservoir / seal pairs)
• map regional changes in gross depositional environment
• assess petroleum systems
• define number of plays
Generation
Migration
Trapping
Preservation
A discrete system of hydrocarbon which encompasses: Migration , trapping, preservation.
All elements and processes, from generating kitchen to final resting place.
The basic plumbing in a oil and gas perspective.
(Dow, 1974)
(AAPG Memoir 60, Magoon and Dow)
Gain an understanding about, and convey:
• distribution of source rocks; areal differences in richness/thickness
• distribution of thermal maturity (oil/gas) - today and at key times in the past
• areas that have expelled oil/gas after trap formation
• areas from which charge can migrate to structures, migration pathways
• understand the distribution of known accumulations
We use Play (Attribute) Maps to understand the Spatial Relationships and
TimingWorksheets to reveal the Dynamics of a Petroleum System
(http://pubs.usgs.gov/)
In addition one can add confidence levels to each factor presented in this
chart, to assist in quantification of factor probabilities
The basic unit of prospect risk analysis is the prospect (more precisely the objective
within the prospect).
The basic unit in play analysis is the Play Segment (defined as the subdivision of an
overall play where the boundaries are marked by an abrupt change, usually in geology)
Each Play Segment must be assessed for, and assigned a set of probability values, trap
density (or predicted number of undrilled prospects), and predicted future field size
distribution (FSD).
Chance values and volume assessments should reconcile at the prospect and play level.
Never draw segment boundaries through the middle of identified prospects!
Plays are defined both in time (vertical/stratigraphic) and spatial (map)
Plays are defined stratigraphically by the coupling similar reservoir, seal, charge
To determine the appropriate number of plays, an understanding of the basin
petroleum system is required.
To define a play that is separate from other plays, there has to be some geological
element that makes it different (independent) from the prospective strata
above/below.This is often a regional master seal, occasionally the influence of a
different source rock.
Individual play boundaries are defined (in map-view) by regional extent of charge,
reservoir, seal, and traps.
• tectonic elements, structural domains
• lease status, topography, other cultural data
• well penetrations and results (including reason for failure, if known)
• prospects & leads
• discoveries in play, and estimated EUR by Play
• play element outlines
• reservoir fairway edge (e.g. subcrop or pinchout edge)
• effective seal outlines
• source rock presence/quality/maturity/migration outlines
• confidence/knowledge indicator (2D/3D seismic, data quality polygons etc.
• regional cross-section of play
• annotations - scribble on those maps!
Area of Interest (AOI)
Open acreage
Cultural data
Source map
Maturity Charge R0 Quality
Slicks Seeps Temperature
Inversion timing Fetch
Top/lateral Seal
Isopach Rheology Pressure analysis
Timing
Reservoir
Facies Isopach AVO Porosity
Permeability Amplitudes Net Net/Gross
Provenance
Structure of reservoir
Tectono-stratigraphic timing Fault analysis
Velocity sensitivity
Database
Key wells well analysis Risk statistics
Field analogs Creaming curves
Future Field Size Distribution (FSD)
Overlie maps to determine the “sweetspots” and boundaries with significant changes to define the play boundaries
1. determine amount of plays recognized stratigraphically
2. data mine and organize available data into a spatial database
3. archive and geo-reference maps in GIS format
4. analyze play test data (play specific)
5. gather field size information (play specific)
6. define the overall play outline
7. segment the play as appropriate; assign chance values, trap counts, Field Size
Distribution’s (FSD’s) for use inYetTo Find (YTF) analytics
8.Use maps to guide prospect Pg assessment, and overall strategy
Reservoir extent
Source extent
Seal extent
Prospects
Partition the play and assign probabilities to each play segment
Play outline
A play can be subdivided into play segments for several reasons.
The boundaries of these segments should represent an abrupt and significant
change in one or more geological parameters.
The family of drilled and undrilled prospects in a segment are assumed to have a
fairly common geologic history.
When segments reflect changes in assessed probability (either at the play or
prospect level) a play segment is synonymous with the term Common Risk
Segment (CRS).
Play
Play Segment
Common Risk
Segment (CRS)
Be generous when drawing the overall play outline, it is a ZERO probability line!
Prepare overall play outline first and then subdivide, based (hierarchically) on:
1) Gross Depositional Environment (GDE)
2) Structural style of trap
3) Business/geopolitical boundaries (Venture Segments)
4) Others as needed
Do not make play segment sub-divisions too small.
Create the minimum number of play segments needed to answer your technical
and strategic issues.
Each segment must be assigned:
- Probabilities, discussed at length later
- - A characteristic discovery/field/prospect size distribution
- - A characteristic remaining lead density
It is the segment that forms the basic unit of assessment in PBE
Tie assessment to chance of minimum (or more)
• Chance of a geological success (flowable hydrocarbons)
• No thought to commerciality or economics as these are moving targets.
Use same chance factors for prospects and plays
Compare prediction to recent track record in play/segment (for proven portions of
play)
Document predictions, track results - Zero data does not mean zero chance
Zero data does not mean zero chance for play
The method, and mathematics must deal with :
The toleration of more than one well before play is abandoned (sometimes
you are interested inVenture Chance of Success).
The drilling of more than one prospect, given success.Often many prospects,
some of which will be successful, and some not (so we are dealing with an
average chance of success at the play/segment level).
The fact that for a family of prospects, there are elements of chance that
might condemn them all (often source-related) and elements that vary from
prospect to prospect
2
1
4
7
5
3
9
8
6
2 wells tested dry, 9 prospects remaining to drill. Shared chance (Play/Segment probability)
What is the chance of future discoveries on one or more of the remaining prospects?
2
1
4
7
5
3
9
8
6
1 well dry, another oil discovery, 9 prospects remaining to drill.
Local chance (Prospect success ratio)
If there is another discovery, what percentage of chance is there of these will be successful?
To convey, in a company-consistent way, regional probability of success (or failure)
Define the “sweet spots” of a play, to focus exploration activity and technology
spending
To define (via the split of play and prospect level risks) the direct linkage between a
prospect and its neighbors.
Understand areal extent of highest potential chance uplift through a well test to tell
what is the influence of the next well drilled.
Validate individual prospect Pg estimates (Total Chance)
Provide needed chance inputs for calculating undiscoveredYet to Find (YTF) volumes
2 types of maps needs to be created;
Play Chance of Success (COS) maps.
The CRS-Play (segment) maps will reflect specific chance elements. Reflect
elements affecting all prospects in a play (segment)Used to derive probability of a
play (segment) geologic success
For proven plays, all or most of the CRS maps may be set to 1.0 (for elements
proven over the entire play (segment))
Prospect Chance of Success (COS) maps.
Reflect elementd that make some prospects successful, and others fail
Where play is proven, average prospect/lead chance of success is the definite COS
Prospect Psource
Prospect Preservoir
Prospect Ptrap
Prospect Pg total
The total chance of success for prospects within the polygons of the final resulting
COS map if the petroleum system works.
Colors can have values or just be colors – depend on what further work needed. If you
want to getYTF and proper quantitative prospect ranking in PBE fashion, need
values.
Combined all P maps
Play multiply Prospect
Psource x
Psource
Ptiming/migrat
ion
x
Ptiming/migrat
ion
Preservoir x
Preservoir
Ptrap x
Ptrap
Pcontainment x
Pcontainment
P play total x Pprospect total
=
=
=
=
=
=
Play based prospect
Psource - total
Ptiming/migration - total
Preservoir - total
Ptrap - total
Pcontainment - total
P total
A well-organized database is the most important element of the play analysis, and a key
well dataset is a critical component.
The areal extent of the database should capture all possible extensions of all possible plays
within the basin).
Be aware of any confidentiality implications of sharing data with third parties
If original/internal data and interpretation are not available, third party material can be
used, even including scanned and geo-referenced figures. An analysis derived from such
sources will be of lower confidence than one based on in-house work.
All data must be broken out pr play.
Different elements of the play may require some of the same maps (e.g., maps related to
thermal history may be relevant to both source and migration and reservoir quality).
Some maps can be applicable for more than one play in the same basin (e.g., source and
migration maps, structural elements maps)
It is very important to annotate the confidence level in both data and interpretation.
Post drill analysis – results and reason for dry if so
Success/failure, and reasons for failure, are play-specific. For instance, a dry well
may penetrate multiple plays and fail in each play for a different reason.
Sometimes wells fail due to non-geological reasons (geomechanical, formation
damage).
There is no substitute for wading through the data and looking at each well in
your defined play.The drilling history of the basin must be understood to gain
insights into critical risk elements.
It can be a PAIN to do ␣ but the time investment is worth it!
Focus on wildcat wells. Discoveries help to delineate proven portions of the play.
In very large and/or mature plays, you may need to focus upon just key wells.
Some preliminary mapping is needed to make judgments as to why unsuccessful
wells failed.The more mature the regional synthesis, the better your judgments
will be. Failure mode is group consensus.
Combines data as to whether wildcat was a valid test with estimated cause of failure.
Valid successes would be colored all green. Symbols could easily be adapted within a
map-based GIS system.These results should be posted on all play maps to aid in
interpretation of chance of success or probabilities.
Well result pr risk element Color code pr risk element Test validity
Reservoir
Source
Trap/Closure
Migration/timing
Seal/Preservation
Present
Uncertain
Absent
Valid
Invalid
(Modified fromTranter, 2009)
PBE - Play Based Exploration

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PBE - Play Based Exploration

  • 1. By Stig-Arne Kristoffersen, Kiev, Ukraine 2010
  • 2. Stig-Arne Kristoffersen started his career in Exxon (Esso Norway) in 1985 (25 years in the industry). Since then he has worked for several major national and international oil and gas companies, as well within the consultancy business and mid cap companies within oil and gas industry performing exploration evaluation and risk analysis. He has held several project manager and supervisor roles in various companies, and advised on exploration strategies and risk analysis.
  • 3. Play-Based Exploration (PBE) has become a trendy term in the oil and gas industry, championed by companies like ExxonMobil, Shell and BP. PBE methods vary significantly; some firms create ‘traffic light’ maps of overall relative profitability, others partitioning probability into play/shared and local /prospect-specific probability with assigned values. Play-based exploration reflect a shift in focus, as prospects are not the basic unit of exploration, but plays are. Individual prospect probabilities are balanced and calibrated with the play maps, and prospect volumes are validated against the field size distribution (FSD) for the play. Exploration evaluation experts use play-based exploration (PBE) to build a full understanding of the geological basins that should be explored and to reassess exploration strategies.
  • 4. · Play specific datasets (e.g. key well analysis, volumes, success rates) · Segmented play maps · Prospect probabilities to be reconciled with play (segment) in which they reside to ensure spatial balancing · Reconcile predicted prospect volumes with discovery history and exploration maturity · Making decisions at the Play level rather than at the next Prospect level. Let us explain what a play is………
  • 5. A Play is; • an area and thickness with expected favorable conditions for hydrocarbon accumulation, independent of other plays. A play may contain more than one reservoir and is largely defined by the master seal.- (Mobil) • a group of new field prospects (and perhaps several producing fields as well) having similar source, reservoir and trap controls on oil and gas occurrence.- (Baker, 1986) • a geologically coherent group of prospects (and fields)...- (White, 1993) • a group of fields and prospects having a chance for charge, reservoir and trap and belonging to a geologically related stratigraphic unit- (Shell) • a geographically and chronostratigraphically bounded unit of reservoir(s) and seal(s) charged by the same source rock interval(s).- (Maersk) Common for them all is that we deal with a physical entity and not a concept petroleum systems, and they have a common history.
  • 6. • prospect probabilities are balance with the play (segment) in which they belong, to ensure spatial balancing • predicted prospect volumes are calibrated towards the discovery history and exploration maturity • use more than “traffic lights‟ to understanding shared and prospect-specific probability. This has a pronounced influence upon decision-making -Bid strategy and appropriate risk tolerance -Prospect sequencing -Value of information – key data needs -Preferable partners of choice/acquisition candidates • strategic Play Analysis should be the core business process through a straightforward process for calculating company-capture volumes/value, investment efficiency, and chance of company economic success
  • 7. MAKING DECISIONS ATTHE PLAY LEVEL RATHERTHANTHE NEXT PROSPECT LEVEL Creates the basis for; • country/basin/play/entry and investment levels • manpower allocation and amount • strategies for where to generate the prospects for the next 5 yrs • prospect decisions in light of basin chance and potential
  • 8. • efficient and consistent way to communicate probability in a spatial manner • decisions based on consistent results in a consistent manner and better assessment of priorities of prospects (and plays) • quicker reaction to opportunities and optimal decision making • standardized workflow within the organization that increase productivity and reduces costs • company-consistent formats for data capture and presentation • improves consistency for prospect chance and volume assessments • dynamic and updated database as more data are acquired • assist identifying areas where more, or better, data are required
  • 9. Pg Trap Pg Seal Pg Source Pg Reservoir Pg COS UTM X Y Prospect 0.7 0.7 1.0 0.7 0.34 23 156,500 1,450,679 A 0.9 0.5 0.9 0.8 0.32 23 157,250 1,480,321 B 1.0 0.8 0.7 0.6 0.34 23 166,130 1,571,234 C 0.8 0.7 0.8 0.8 0.36 23 155,300 1,485,702 D 0.6 0.9 0.6 0.7 0.23 23 158,450 1,781,630 E 0.8 0.7 1.0 0.8 0.45 23 147,356 1,491,906 F Risk parameters Geographic coordinates GIS database Play map(s)
  • 10. Layered GIS maps enable the user to select what information he/she wants to display Source: www.npd.no factmaps Increasing Pg values Towards the North to North East Anomalously high Pg value
  • 11. 0.50 0.24 0.20 0.48 0.21 0.19 0.19 0.18 Too low Pg value Too high Pg Justifiable high Pg value High risk Moderate risk Low risk 0.21Prospect Estimated Pg
  • 12. “Traffic Light maps” could be a starting point and adequate for the moment, however there are some constraints with these maps that you need to be aware of. • colors convey a notional probability, but no quantitative ability associated with them • can not use them for yet-to-find volumes, actual Pg estimates, chance of successful play entry analytics • chance and uncertainty (as expressed by quality and density of data) are not expressed and there are different grades of each color • there can be a bias to areas of high/low data • no real basis for consistency • play- and prospect-specific chance not differentiated
  • 13. 0.21Prospect Estimated Pg 0.21 0.0 – 0.1 0.1 – 0.2 0.2 – 0.3 0.3 – 0.4 0.4 – 0.5 0.5 – 0.6 0.6 – 0.7 0.7 – 0.8 0.9 – 1.0 Pg range 0.8 – 0.9 0.61 0.81 0.21 0.33 0.18 0.31 0.72 0.21 0.21 0.21 0.83 0.54 0.16 0.08 0.61 0.51 To high Pg To high Pg To low Pg To low Pg To low Pg To low Pg To low Pg
  • 14. 0. 5 0 0. 2 40. 2 0 0. 4 8 0. 2 1 0. 1 9 0. 1 90. 1 8 Too high Pg Post prospect Pg on CRS maps Placing prospect success case volumes in Play Field Size Distribution (total life and recent play history) Placing remaining prospect’s in play „creaming‟ curve Check for consistencies within your datasets both historically and for the future
  • 15. Make Strategic Play Analysis a core business process to create a straightforward process for calculating company-capture of volumes/value, investment efficiency, and predictions of company economic success •make decisions at play level rather than next prospect • country/basin/play/entry and investment levels • manpower allocation and where to generate the prospects for the next strategic period • check for prospect probabilities consistency versus the play (segment) in which they reside to ensure spatial balancing • check the predicted prospect versus discovery history and exploration maturity curve • consolidate shared and prospect-specific probability as it has a pronounced influence upon; • decision-making • bid strategy • setting proper risk tolerance levels • prospect sequencing • assess the value of information to decide what and where key data are needed
  • 16. Play Segment Boundaries describes significant and abrupt changes in geology in the overall play. What does 40% chance of geological success mean in this context? • 40% percent chance of a discovery, if you were to drill the entire area? • 40% of the locations will encounter hydrocarbons? • 40% of the locations will encounter hydrocarbons - given that at least one will (average success rate)? The answer depends upon whether the map you are using conveys play-scale or local information
  • 17. Prospect A Prospect B Play Description Eocene Deep water sandstones in combined stratigraphic and structural traps with Upper Jurassic source. Migration and bio-degradation is the critical factor for play Upper Jurassic marginal to shallow marine and deep water sandstones in stratigraphic and structural traps, rotated fault blocks with Upper Jurassic source. Presence of reservoir and seal is the critical factor for play. Play Pg 0.25 1.00 Prospect Pg 0.85 0.20 Total Pg 0.21 0.20 Risked mean volume 750 MBO 700 MBO Unrisked mean volume for play 750 MBO/0.25 = 3BBO 700 MBO/1.0 = 700 MBO This example will illustrate the importance of looking at both the play and prospect Pg to understand the overall risk ranking of these prospects. Future Undiscovered Potential for these plays, which have the same number of undrilled prospects with identical future volume characteristics – and the resulting risked mean volumes for Play A is 750 MMBO and 700 MMBO for Play B. The SUCCESS CASEVOLUMES for Play B remain 700 MBO, while for Play B, volumes are 3.0 BBO Unless you understand and factor the two chance factors into your analysis, this could not be assessed.
  • 18. This example shows both Chance/Risk and Success CaseVolumes Curved lines represent venture unrisked volume isopleth
  • 19. Impact on chance of play entry which is geological success in this case. Exploration management consider to enter into these two plays, A and B, and they plan a 3 prospect evaluation program. The chance that hydrocarbons are found in play A is about 25%, while suppose you know the blend of chances for play B the chance is 60%. Management has to make a decision as to whether its worth the incremental risk of 60% versus 25%, to the reward of volumetric potential of 3 BBO versus 750 MBO undiscovered volumes. Strategy choices based on this scenario could be; • Drill the best remaining prospect in Play B or • Drill the area or get more data that will give the most information about migration for Play A, which may or may not be the best prospect in Play A, but the optimal stratigraphic test.
  • 21. Play type Data Base Play assessment Play segment inventory Manpower allocation Capital allocation Results
  • 22. • use of consistent methodology • use of consistent terminology • do regular plausibility and reality checks through; • global peer assessment • link of petroleum system to play to prospect/segment • associate prospect to known discoveries • check the spatial integrity of risk levels of play versus prospect • use of consistent software tools
  • 23. Every organization is different, and there is no simple one recipe solution on how to implement Play Base Exploration into your organization. However there are some important elements that needs to be in place to have any chance of making successful implementation and execution of PBE. •Appoint and acknowledge a technical champion / process owner for PBE development • Ensure a central coordination, but make sure it not becomes a control unit • Acquire and maintain a global, map based datasets • Establish a performance tracking and feedback process in your organization • Do regular global calibration sessions •Adopt a portfolio mind setting for plays and prioritize at the play level
  • 24. So, given you some basic elements that should be present to succeed with PBE implementation and execution.Then I will list some elements that will make it fail. • lack of clear process owner / sponsor • management push-back • sense of competition • data silos • moving minima • improper (spectacular) analogs • not calibrated analyses (prospect/segment to play) • not calibrated analyses (play to play, part play to part play
  • 25. The PBE workflow consists of some basic steps that has to be performed before the tool is ready to be used in your organization. These elements have to be in place before any analytics are tried out, otherwise any analytics is deemed to give you false guidance in your exploration efforts. •play definitions (vertical/stratigraphical) • geographic definition of play boundaries • play portioning (segments) distinguished by abrupt and significant changes changes in geology and other factors • assigning chance variables to the play segments • assign segment counts, FSD’s to each part play (Yet to Find Calculation) • use maps to help guide exploration strategy
  • 26. (PBE pyramid modified after D. Roberts, 2005) Iteration when new geological data and analysis are available
  • 27. Long term Global processes Basin tectonics Cyclical sedimentation (megasequences) - Assembly/Disassembly - Relative sea level - Paleogeography - Paleolatitude - Paleoclimate - Convergent/Divergent - Temporal changes in basin - Style and impact upon sedimentation - Predictable stratigraphic architecture (transgressive/regressive) - TIMING OF BASIN FORMATION - SOURCE PREDICTION - LITHOFACIES - PRESERVATION RISK GIANT - FIELDS - RICHNESS RISK - RESERVOIR - SOURCE - SEAL By using a predictive stratigraphic model on a basin scale
  • 29. Source Rocks and Depositional Sequences 90% of world's reserves provided by source rocks deposited during 33% of Phanerozoic time (6 time periods) (Klemme and Ulmishek, 1991) Structural and Preservation Styles 80% of the world's giant fields are located in 3 types of poly-history basins - 'A' foredeep, cratonic-rift, Atlantic-rift (Brooks, 1990, using Carmalt and St. John, 1986) Location (Tectonic Realms) 68% of world's reserves are located in 17% of its total area (Tethyan realm); 91% of world’s reserves are inTethyan and Boreal realms (Klemme and Ulmishek, 1991) Recent Generation 70% of world's reserves generated 90 MY-present. 40% generated 35MY-present (Klemme and Ulmishek, 1991)
  • 30. Megasequences are regional scale basin-fill patterns associated with significant (plate-scale) basin-forming processes. A relatively small number of megasequence types are recognized (e.g., sag, synrift, foreland) , and each is characterized by unique depositional patterns. Generic models are widely published. Megasequences form the first level primary stratigraphic analysis building block for basin analysis. Boundaries are usually very pronounced on regional seismic lines IODP Canada One key aspect of identifying megasequences is that source rocks are found at predictable positions within each sequence
  • 31. • relationship between major tectonic events and stratigraphy • lithological variations across basin • variations in preserved section(s) across basin • primary source/seal/ reservoir intervals
  • 32. • characterize basin tectonic setting • evaluate the tectono-stratigraphic setting, regional tectonic elements, and their changes through time • identify megasequences (regional reservoir / seal pairs) • map regional changes in gross depositional environment • assess petroleum systems • define number of plays
  • 33. Generation Migration Trapping Preservation A discrete system of hydrocarbon which encompasses: Migration , trapping, preservation. All elements and processes, from generating kitchen to final resting place. The basic plumbing in a oil and gas perspective. (Dow, 1974)
  • 34. (AAPG Memoir 60, Magoon and Dow)
  • 35. Gain an understanding about, and convey: • distribution of source rocks; areal differences in richness/thickness • distribution of thermal maturity (oil/gas) - today and at key times in the past • areas that have expelled oil/gas after trap formation • areas from which charge can migrate to structures, migration pathways • understand the distribution of known accumulations We use Play (Attribute) Maps to understand the Spatial Relationships and TimingWorksheets to reveal the Dynamics of a Petroleum System
  • 36. (http://pubs.usgs.gov/) In addition one can add confidence levels to each factor presented in this chart, to assist in quantification of factor probabilities
  • 37. The basic unit of prospect risk analysis is the prospect (more precisely the objective within the prospect). The basic unit in play analysis is the Play Segment (defined as the subdivision of an overall play where the boundaries are marked by an abrupt change, usually in geology) Each Play Segment must be assessed for, and assigned a set of probability values, trap density (or predicted number of undrilled prospects), and predicted future field size distribution (FSD). Chance values and volume assessments should reconcile at the prospect and play level. Never draw segment boundaries through the middle of identified prospects!
  • 38. Plays are defined both in time (vertical/stratigraphic) and spatial (map) Plays are defined stratigraphically by the coupling similar reservoir, seal, charge To determine the appropriate number of plays, an understanding of the basin petroleum system is required. To define a play that is separate from other plays, there has to be some geological element that makes it different (independent) from the prospective strata above/below.This is often a regional master seal, occasionally the influence of a different source rock. Individual play boundaries are defined (in map-view) by regional extent of charge, reservoir, seal, and traps.
  • 39. • tectonic elements, structural domains • lease status, topography, other cultural data • well penetrations and results (including reason for failure, if known) • prospects & leads • discoveries in play, and estimated EUR by Play • play element outlines • reservoir fairway edge (e.g. subcrop or pinchout edge) • effective seal outlines • source rock presence/quality/maturity/migration outlines • confidence/knowledge indicator (2D/3D seismic, data quality polygons etc. • regional cross-section of play • annotations - scribble on those maps!
  • 40. Area of Interest (AOI) Open acreage Cultural data Source map Maturity Charge R0 Quality Slicks Seeps Temperature Inversion timing Fetch Top/lateral Seal Isopach Rheology Pressure analysis Timing Reservoir Facies Isopach AVO Porosity Permeability Amplitudes Net Net/Gross Provenance Structure of reservoir Tectono-stratigraphic timing Fault analysis Velocity sensitivity Database Key wells well analysis Risk statistics Field analogs Creaming curves Future Field Size Distribution (FSD) Overlie maps to determine the “sweetspots” and boundaries with significant changes to define the play boundaries
  • 41. 1. determine amount of plays recognized stratigraphically 2. data mine and organize available data into a spatial database 3. archive and geo-reference maps in GIS format 4. analyze play test data (play specific) 5. gather field size information (play specific) 6. define the overall play outline 7. segment the play as appropriate; assign chance values, trap counts, Field Size Distribution’s (FSD’s) for use inYetTo Find (YTF) analytics 8.Use maps to guide prospect Pg assessment, and overall strategy
  • 42. Reservoir extent Source extent Seal extent Prospects Partition the play and assign probabilities to each play segment Play outline
  • 43. A play can be subdivided into play segments for several reasons. The boundaries of these segments should represent an abrupt and significant change in one or more geological parameters. The family of drilled and undrilled prospects in a segment are assumed to have a fairly common geologic history. When segments reflect changes in assessed probability (either at the play or prospect level) a play segment is synonymous with the term Common Risk Segment (CRS). Play Play Segment Common Risk Segment (CRS)
  • 44. Be generous when drawing the overall play outline, it is a ZERO probability line! Prepare overall play outline first and then subdivide, based (hierarchically) on: 1) Gross Depositional Environment (GDE) 2) Structural style of trap 3) Business/geopolitical boundaries (Venture Segments) 4) Others as needed Do not make play segment sub-divisions too small. Create the minimum number of play segments needed to answer your technical and strategic issues. Each segment must be assigned: - Probabilities, discussed at length later - - A characteristic discovery/field/prospect size distribution - - A characteristic remaining lead density It is the segment that forms the basic unit of assessment in PBE
  • 45. Tie assessment to chance of minimum (or more) • Chance of a geological success (flowable hydrocarbons) • No thought to commerciality or economics as these are moving targets. Use same chance factors for prospects and plays Compare prediction to recent track record in play/segment (for proven portions of play) Document predictions, track results - Zero data does not mean zero chance Zero data does not mean zero chance for play
  • 46. The method, and mathematics must deal with : The toleration of more than one well before play is abandoned (sometimes you are interested inVenture Chance of Success). The drilling of more than one prospect, given success.Often many prospects, some of which will be successful, and some not (so we are dealing with an average chance of success at the play/segment level). The fact that for a family of prospects, there are elements of chance that might condemn them all (often source-related) and elements that vary from prospect to prospect
  • 47. 2 1 4 7 5 3 9 8 6 2 wells tested dry, 9 prospects remaining to drill. Shared chance (Play/Segment probability) What is the chance of future discoveries on one or more of the remaining prospects?
  • 48. 2 1 4 7 5 3 9 8 6 1 well dry, another oil discovery, 9 prospects remaining to drill. Local chance (Prospect success ratio) If there is another discovery, what percentage of chance is there of these will be successful?
  • 49. To convey, in a company-consistent way, regional probability of success (or failure) Define the “sweet spots” of a play, to focus exploration activity and technology spending To define (via the split of play and prospect level risks) the direct linkage between a prospect and its neighbors. Understand areal extent of highest potential chance uplift through a well test to tell what is the influence of the next well drilled. Validate individual prospect Pg estimates (Total Chance) Provide needed chance inputs for calculating undiscoveredYet to Find (YTF) volumes
  • 50. 2 types of maps needs to be created; Play Chance of Success (COS) maps. The CRS-Play (segment) maps will reflect specific chance elements. Reflect elements affecting all prospects in a play (segment)Used to derive probability of a play (segment) geologic success For proven plays, all or most of the CRS maps may be set to 1.0 (for elements proven over the entire play (segment)) Prospect Chance of Success (COS) maps. Reflect elementd that make some prospects successful, and others fail Where play is proven, average prospect/lead chance of success is the definite COS
  • 51. Prospect Psource Prospect Preservoir Prospect Ptrap Prospect Pg total The total chance of success for prospects within the polygons of the final resulting COS map if the petroleum system works. Colors can have values or just be colors – depend on what further work needed. If you want to getYTF and proper quantitative prospect ranking in PBE fashion, need values. Combined all P maps
  • 52. Play multiply Prospect Psource x Psource Ptiming/migrat ion x Ptiming/migrat ion Preservoir x Preservoir Ptrap x Ptrap Pcontainment x Pcontainment P play total x Pprospect total = = = = = = Play based prospect Psource - total Ptiming/migration - total Preservoir - total Ptrap - total Pcontainment - total P total
  • 53. A well-organized database is the most important element of the play analysis, and a key well dataset is a critical component. The areal extent of the database should capture all possible extensions of all possible plays within the basin). Be aware of any confidentiality implications of sharing data with third parties If original/internal data and interpretation are not available, third party material can be used, even including scanned and geo-referenced figures. An analysis derived from such sources will be of lower confidence than one based on in-house work. All data must be broken out pr play. Different elements of the play may require some of the same maps (e.g., maps related to thermal history may be relevant to both source and migration and reservoir quality). Some maps can be applicable for more than one play in the same basin (e.g., source and migration maps, structural elements maps) It is very important to annotate the confidence level in both data and interpretation.
  • 54. Post drill analysis – results and reason for dry if so Success/failure, and reasons for failure, are play-specific. For instance, a dry well may penetrate multiple plays and fail in each play for a different reason. Sometimes wells fail due to non-geological reasons (geomechanical, formation damage). There is no substitute for wading through the data and looking at each well in your defined play.The drilling history of the basin must be understood to gain insights into critical risk elements. It can be a PAIN to do ␣ but the time investment is worth it! Focus on wildcat wells. Discoveries help to delineate proven portions of the play. In very large and/or mature plays, you may need to focus upon just key wells. Some preliminary mapping is needed to make judgments as to why unsuccessful wells failed.The more mature the regional synthesis, the better your judgments will be. Failure mode is group consensus.
  • 55. Combines data as to whether wildcat was a valid test with estimated cause of failure. Valid successes would be colored all green. Symbols could easily be adapted within a map-based GIS system.These results should be posted on all play maps to aid in interpretation of chance of success or probabilities. Well result pr risk element Color code pr risk element Test validity Reservoir Source Trap/Closure Migration/timing Seal/Preservation Present Uncertain Absent Valid Invalid (Modified fromTranter, 2009)