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TRANSCRIPT
The New Paradigms in Oil and Gas Exploration and
Production and Implications for The Niger Delta
NAPE Technical Lecture Series
January 2008
By
Kehinde o. LADIPO (FNAPE; FAS)
Senior Advisor
Lekoil
Churchgate Towers, Lagos
• Introduction
• Current Realities and Challenges
• Future Trends
• Concluding Remarks
The New Paradigms in Oil and Gas Exploration and
Production: Implications for Increased Potentials of
The Niger Delta
Exploration and Exploitation strategies of oil and gas are changing,
driven by need for
▪ Reduction in life cycle evaluation from discovery to first oil/gas
▪ Cost Reduction
▪ Lower oil price
▪ Increasing technological challenges to identify new and by-
passed oil and gas
Introduction : Strategic Imperatives
- Exponential increase in Data volume:
o higher fidelity of seismic data
o sophistication of log acquisition from drilling
o legacy data, interpretation and models
- Discipline Experts and Teams with ability to analyze data (workflow implementation) and generate models
o work in silos, and
o integration in often limited
- Increasing need for
o greater sophistication of subsurface models
o consistency of model hierarchies and management of uncertainties
o integrations of knowledge and skills sets,
o multi-dimensional analyses and
o interrogation of large, diversified data types
Introduction: Current Realities
…. hence the need to evolve new strategies
Introduction: The New Approach in E&P
Designing a New strategy for E&P Teams must be underpinned by:
1. Knowledge Management - “New and robust subsurface concepts and models”
2. Technology Applications and Integrated interpretation
- “New Platforms and integration of workflows”
- “Reduction of Interpretation Cycle Time”
1. Data Management - “Managing Big Data”
- “Ability to Sweat information from existing and New Data”
4. Workflow and Discipline Team knowledge integration
- “from Asset Based teams to Internal and Collaborative”
5. People - Attitudes
- Expertise Skills of the future
Source: Osahon, G; In Nigerian Association of Petroleum Explorationists
Special Commercial Bulletin Vol 1.11, 2016
Current Realities: Niger Delta Resource Base
• Over 65Bln Barrels produced and current reserves estimates of ca 35Bln
• Mainly from Conventional play onshore and shallow water
• YTF estimates of ca. 70-75Bboe from onshore deep play and upper slope systems (future reserves addition)
• Ability to realize potential of the undiscovered resources is key and requires new thinking
….. Concepts, technology, Integration and
People Skills
Deep Play
Onshore
Decoding the “DNA” of the Niger Delta
▪ Tectonics and Structural Framework
▪ Sedimentation and Sand(%) Distribution
• Sediment supply
• Depositional Processes
▪ Gross Depositional Environment
▪ Accommodation Space
▪ Sediment Supply
▪ Structure & Sedimentation
▪ Hydrocarbon Occurrence
➢ Subsidence rates and Delta Evolution
➢ Trapping Configurations
➢ Delta Evolution
➢ Depositional Setting and Controls
➢ Implications on HC distribution (e.g. sd%)
➢ Basin fill histories
➢ Onshore-Offshore linkage
➢ Depositional models and Stratigraphic Architecture
➢ Source rock maturity and Fluid Type
➢ HC expulsion and timing
➢ Overpressure
DNA – Structure and Tectonic Framework
• New tectonic model of
gravity sliding has resulted
in new play opportunities in
the deep, otherwise
interpreted as shale
diapiric structures
Niger Delta DNA – Tectonics Evolution and Sedimentation
Schematic Framework of megastructures and Trapping Styles
• Trapping styles in the conventional delta mainly structural and constitute ca.90% of the discovered potential
• Onshore-offshore linkage opens new depositional models and geometries of the deeper potential
• The New Deep play is combination traps (lowstand wedge) and stratigraphic traps (upper-mid-slope aprons, canyons and fans)
• Potential to add significant reserves
Gross Depositional Setting – Lowstand Wedge
Reconstructed Gross Depositional Environment Shelf Margin Growth and architecture of low stand
wedge due influence of syn-sedimentary faulting
• Lowstand Shelf Margin wedge as defined from regional framework studies
• New play models of the deep untested sequences
• Below current conventional delta Courtesy SPDC
GDE Characterization of Shelf Margin Deltas
• GDE Models occur at 3rd and 4th order scales
• 3rd and 4th order cycles interpreted from seismic stratigraphy and well log stacking patterns
• Stratigraphic geometry and isopach demonstrate thickening of wedge against bounding
fault – increased fault activity during lowstand
• Important for sand% estimation
thins seaward, clinoforms
TST: landward dipping onlaps
thins seaward dipping clinoformsTop Wedge 2
Base Wedge 2
Top Wedge 1
E2000
E3000
E3500
E4000
E5000
E6000
19.4 MFS
F1000
SSTVD 0.00 175.00GR_NORM 0.10 2000.00RES_DEEP
E2000
E3000
E3500
E4000
E5000
E6000
F1000
19.4 MFS
GBARAN-005 [SSTVD]
E2000
E3000
E3500
E4000
E5000
E6000
19.4 MFS
F1000
HST
E6000
E5000
E4000
E3500
E3000
TST
LST
19.4 MFS
Top Wedge 1
Base Wedge e 2 (20.4 SB?)
Stratigraphic Architecture of a lowstand wedge calibrated with well logs 3rd , 4th Order Parasequence Sets Interpretation, Well-5
Top Wedge 2
Thickness (m)
>120
100-120
80-100
60-80
40-60
<40
Well-5 (partial penetration of Wedge)
1 km Courtesy SPDC
Gross Depositional Environments Along A Composite Regional Line
and 3D Fault Framework and , Eastern Delta
KEY TO DEPOSITIONAL MODELS:
SMD - Shel margin Delta
DBD – Deep Buried Delta
CRPO – Counter Regional
Pinch-Out
RSMA - Retrograde Slope
Margin Apron
S_Ap - Slope Apron
• Stratigraphic Trap, downdip of erosional
features on shelf edge and shelf deltas
• Fore setting of packages suggests isolated
lobes with limited lateral continuity
• Overlain by continuous high amplitude
reflectors, i.e. shale drapes
• Associated with Rotational Slump cars (RSM),
typical of upper slope margin
Seismic Facies and geometry - Retrograde Slope Margin (RSM)
GDE Characterization of Retrograde Slope Margin
Advances in Seismic Technologies For The Deep Play
Processing Technologies- Time migration
- Depth migration
- Merged regional seismic lines
Fault Imaging- Fault imaging (Flatter*)
- Fault Shadow effects
Velocity Modeling - Overpressure
- True amplitude processing and Phase decomposition (and non-amplitude supported
plays)
Attribute Analyses, Rock Physics and Inversion
(Flater is a Shell Proprietary processing software)
10Km
Merged Arbitrary Regional Seismic Profile Across Eastern Niger Delta
Geophysical Modeling of Stratigraphic Data
Nor th Nor th Nor th
C04s 1 1 km C04s1 1 k m C04s 1
1 km
C06 C06 C06
C07 C07 C07
C05 C05 C05C05s 1 C05s 1 C05s1
C 0 8 C 08 C 08C 02 2 11/29-2 C 0 2 2 11 / 29-2 C02 2 11/2 9-2
C 20s2 C13 C20s2 C13 C20s2 C13
C20 C 1 6 C20 C 1 6 C20 C1 6
C 01 C27 C12s1
C 01 C27 C12s1
C 01 C2
7 C12s 1
C21 C21 C 21
C 14s1 C 14s 1 C 14s1C 19 C25 C 1 9 C25
C 1 9 C25C40 C40 C40
C18s 1 C 18s1 C18s1C36 C36 C36
C38 C 38 C38
C 39 C 2 3s 1 C 39 C23 s1 C 3 9
C 23s 1
(1) Ra n noc h For mation-Bed set 3 (2) Ra nnoc h Formation-B ed set 5 (3) Ra n noch Forma ti o n-B ed set 7
P e rmea bil ity (mD)
10001 00
10
W es t10 .1
Et ive
(3) 1
(2) R anno ch
5 0 ft
(1)
Broom
0
5300 m
Nor th Nor th Nor th
C04s 1 1 km C04s1 1 k m C04s 1
1 km
C06 C06 C06
C07 C07 C07
C05 C05 C05C05s 1 C05s 1 C05s1
C 0 8 C 08 C 08C 02 2 11/29-2 C 0 2 2 11 / 29-2 C02 2 11/2 9-2
C 20s2 C13 C20s2 C13 C20s2 C13
C20 C 1 6 C20 C 1 6 C20 C1 6
C 01 C27 C12s1
C 01 C27 C12s1
C 01 C2
7 C12s 1
C21 C21 C 21
C 14s1 C 14s 1 C 14s1C 19 C25 C 1 9 C25
C 1 9 C25C40 C40 C40
C18s 1 C 18s1 C18s1C36 C36 C36
C38 C 38 C38
C 39 C 2 3s 1 C 39 C23 s1 C 3 9
C 23s 1
Rannoc h For mation-Bedset 3 Ra nnoc h Formation-Bedset 5 Rannoch Formation-Bedset 7
Permea bil ity (mD)
10001 00
10
W es t10 .1
Et ive
1
Rannoch
5 0 ft
Broom
0
5300 m
Permea bil ity (mD)
100
1
C02 2 11/29-2 C02 2 11 / 29-2 C02 2 11/2 9-2
C14s1 C14s 1 C14s1
C40 C40 C40
C38 C 38 C38
Nor th Nor th Nor th
C04s 1 1 km C04s1 1 k m C04s 1 1 km
C06 C06 C06
C07 C07 C07C05 C05 C05
C05s 1 C05s 1 C05s1
C 08 C08 C08
C 20s2 C13 C20s2 C13 C20s2 C13
C20 C 1 6 C20 C 1 6 C20 C1 6
C 01 C27 C12s1
C 01 C27 C12s1
C 01 C27 C12s 1
C21 C21 C 21
C 19 C25 C 1 9 C25 C 1 9 C25
C18s 1 C 18s1 C18s1C36 C36 C36
C 39 C 23s 1 C 39 C23 s1 C 3 9 C23s 1
(1) Rannoc h Formation-Bedset 3 (2) Ra nnoc h Formation-Bedset 5 (3) Rannoch Formation-Bedset 7
1000
10 W es t
0 .1
Et ive
(3) 1
(2) R anno ch 5 0 ft
(1)
Broom 0
5300 m
Stratigraphic Forward Modeling (Basin Scale)
Reservoir Modeling (Field Scale)
Volume Attributes: Unsupervised
Classification
3D Attribute Matrix Volume
AVO Inversion Attributes & Rock Physics Characterization of Seismic Facies
Calibration (1D):
• S-impedance• Mu-rho• Lambda-rho
Propagation
- Supervised vs.
Unsupervised (AI)
2D Depositional Facies From Seismic Inversion and Attribute
Analyses (Artificial Intelligence)
Reservoir Properties Seismic Inversion & Reservoir Property TrendsLithology Differentiation
(Source: Bernard Ebere et al., 2016, 2017
Reservoir Scale
GeoTeric© 18
Integrated Rock Physics, Structural Modeling and Stratigraphic Data
RokDoc Stochastic inversion Ji-Fi technology (Joint impedance and Facies inversion technology (Ji-Fi)
Allows uncertainty analyses in reservoir properties to be taken into account, producing multiple possible
geological realizations. (Source: ikonscience.com)
Rock Physics: Scenario Modeling and Uncertainty Analyses of Seismic Inversion
(Source: Paradigm. In: Secrets To Doing Business Successfully In Oil, Gas
September 13, 2017)
Rock Physics and Inversion:
Machine Learning-Based (AI) Rock-Type Classification .
Advanced Seismic Inversion
Controlled propagation of log
facies calibrated seismic
response to predict
- Seismic data and facies from
logs to predict facies volumes
and their probability of
occurrence to improve
reservoir characterization
Data Management
• More effective storage and access of data and
management strategies
Advanced Subsurface Interpretation Tools
• Robust Interpretation and Integration platforms (data,
concepts, workflow streams, legacy knowledge)
Collaborative Platform(s)
• integration of different data types and workflows
• Simultaneous and interactive interrogation of data types
and
• Scalable and consistent models
People & Knowledge
• provide QA of subsurface models
• Adaptation to the New World and acquisition of New Skills
The New Paradigm: Big Data is now ‘A Reality’
The Transformation in G&G
The Future is more of AI:
- Integrate workflows
- Eliminate errors in interpretation
- Generate more multiple realizations
of the subsurface
- Improve uncertainty management
and estimation of probabilities to
rank model outputs
- Drive Collaboration of experts and
teams
- Improve data and knowledge
management
- Save costs
• The evolution of new concepts is key to ensure reserves growth, even in ‘brown’ field basins
• The challenges of ‘big data’, ‘workflow and discipline integration’ required to evolve new
concepts, as well as ‘scalable and consistent models’ of the subsurface need new approaches
• Technological Advances of today driven increasingly by AI and fusion of knowledge and
skills sets, teams and workflows will be the future, to reduce life cycle evaluation time and
realize value quickly
• The Geoscientist of the near future therefore require multi-dimensional skills sets to evaluate
multi-component data sets simultaneously, including higher levels of IT capabilities
• A new approach of skills training and development is a must for the E&P professional
Concluding Thoughts
Acknowledgements
• SPDC
• Lekoil
• StratKol Consult Ltd. and Colleagues and Sources