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