Improving Exploration Performance: Our Learning Curve - Risk Manager Workshop New Orleans April 15, 2010
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Improving Exploration Performance: Our Learning Curve Jan Konstanty Exploration Portfolio Management & Prospect Appraisal Risk Manager Workshop New Orleans April 15, 2010
Who is Wintershall ?
Wintershall
Current Upstream Assets and Activities
Norway Germany The Netherlands
Expansion following Tight Gas Developments Field Developments
corporate acquisition Steam Flooding Projects
Qatar
Core regions
Block 4N and
Block 3 Exploration
OpCo / Office
Production and /
or exploration
Argentina Libya Russia
Aries/Carina As Sarah Field Achimgaz
Aguada Pichana On- & Offshore Yuzhno Russkoye
Onshore Exploration Exploration
Exploration Force Field
Paradigm Shift and Raising Challenge
Extend Plays
People Acreage
Short-Term Mid-Term
Exploration
NFE Greenfield
Performance
Value Volumes
Technology Portfolio
Portfolio RenewalHistorical Exploration Setup
Historical Exploration Setup
2006 Benchmark
Very good technical success rate
Variable approaches to chance & uncertainty definition
Finding
No central portfolio management
OIL&GAS
Volume delivery deviated from pre-drill assumptions
Not unique to Wintershall. Ignoring those symptoms
is a threat to exploration value creation.Improvement Measures
Improvement Measures
Play-Based Exploration
The PLAY is the commercial unit – NOT the prospect.
Play Evaluation Portfolio Upgrade Drilling Decision
Well Location
A Prospect 123456E 1234567N Prospect Summary Sheet
1 st Objectiv e A h o rizon
Common Risk Segment Map N Horizon Map
TD
Area /He ig ht
Critical Risks
xxxx m tvd b d f
t.b.a .
reserv o ir q u ality , i .e. co mmeri ca l flo w rates
Country Map
A MSV [bcm] x xb cm (P9 0 =x; P5 0 =x ; P1 5=x ) A prospect
‘Reservoir Effectiveness’* EOG/P
J. Konstanty Proposed Well
Dist. to Fa cilit ies
Ev a luated by
PAT da te
REP run
~xk m
Own er: In Terpreter; Dat e:
*(resides in ArcGIS with input: play map (c f. regional study), facies distribution, CF = reservoir POS; MSV; EV: 18% ;MSV = xbcm;EV= xbcm
presence*reservoir eff., co mpetitor data, cultural data) P10/P90 = x (“step-out ofproven play”)
A’ Confidence Index: Medium
Play Paleozoic Aeolian Gp.
Our block Trap Type strat., xkm East ofWell B
Chance Factor = 0.8 Seismic Coverage 3D
SeismicQuality good (3D), poor2D
New Play Components strat. trapping (test new play segment)
Evaluation Maturity medium
C-field Calibration Wells Well B, C, D
Prospect B Scal e
A Remarks progress 3D a.s.a.p. and new REP volumetrics
WellB Well proposed Play Chance “New PlayA Segment”
? Approx. Loc.
TW
T A Seismic Section A’
?
Prospect A
50%
C Horiz on ProposedWell Play CF
A Horiz on
Chance Factor = 0.5 Top Z 30% A Prospect
GWC = xxxxmss Play CF
Chance Factor = 0.2 10%
Play CF
Key Questions:
1. Why is the A ho rizon at Well D thickeni ng but as tight as on high?
2. Can we a pply seismic s tratig raphy ?
30%
3. Success case: w hat woul d be t he follow -up vol ume o f the new play s egme nt? ~x km Play CF
Existing producing wells Existing dry wells inconclusive wells
Confid entia l Drawin g No .: x x x x xx
Performance Check: Portfolio Iteration: Post-drill Result
Adjust Resources? Still fitting?
8Improvement Measures
Corporate Portfolio Management
€200mln? €400mln?
Evaluation consistency
+
Customised corporate ranking€650mln?
=
Optimised drilling sequence at any budget
… activity levels controlled by
budget availability or strategic aspiration.
Using a single corporate ranking for
budget allocation was key to performance.Performance Tracking
Performance Tracking
Predictive Capacity (Probability of Success)
100 2009 E&A
% expected successful
80
Actual Success Rate (%)
60
40
20
0
0-10 11-20 21-30 31-40 41-50 51-60 61-70 71-80 81-90 91-100
EPOS Categories (%)
11Performance Tracking
Predictive Capacity (Prospect Level)
2007
80%
60%
40%
No
No Bias
Bias =
= Uniform
Uniform Distribution
Distribution
20%
0%
P100-80 P80-60 P60-40 P40-20 P20-0
12Performance Tracking
Predictive Capacity (Prospect Level)
2008
80%
60%
40%
No Bias = Uniform Distribution
20%
0%
P100-80 P80-60 P60-40 P40-20 P20-0
13Performance Tracking
Predictive Capacity (Prospect Level)
2009
80%
60%
40%
No Bias = Uniform Distribution
20%
0%
P100-80 P80-60 P60-40 P40-20 P20-0
14Performance Tracking
High Ranks Did Deliver Best
Resource Additions per Quartile Rank Unit Finding Cost per Quartile Rank
Q1 Q2 Q3 Q4
7
8% 7,00
6
7% 6,00
5,00
4,00
US$/boe
2022% 3,00
64% 2,00
59 1,00
0,00
Q1 Q2 Q3 Q4
15Conclusion
Measurable Improvement
Portfolio additions & budget relocation paid back
Unit Finding Cost significantly decreased
Increased discovery rate
87% volume delivery
95% of resource additions from 25% ≤ GPOS ≤ 75%
Primary & secondary pre-drill risks confirmed in 75% of dry wells
16Conclusion
Key Success Factors & Collateral Benefits
Mandatory standards for prospect evaluation
Corporate prospect ranking drives budget allocation
Global upgrading requirements for local opportunities
Performance tracking
Common goals beyond local operating companies
Buy-in at all levels of the company
Exploration gained momentum
17Most Critical Success Factor
Finding New Plays and Portfolio Options
Fault Seal
Top Seal
Top Seal
Waste Zone
ReservoirTop Explorers Never Stop Learning.
Thank You.
Questions?
jan.konstanty@wintershall.comYou can also read
