i

INTEGRATED WELL TO SEISMIC

HYDROCARBON EVALUATION OF D-RESERVOIRS OF COASTAL SWAMP, NIGER

DELTA, NIGERIA

By, Eze, Judith Ijeoma

(PG/MSC/08/49649) Department of Geology,

University of Nigeria, Nsukka

Supervisor: Dr L.I Mamah

ii

INTEGRATED WELL TO SEISMIC HYDROCARBON

EVALUATION OF ‘D’-RESERVOIR SANDS OF THE COASTAL

SWAMP DEPO-BELT, NIGER-DELTA, NIGERIA

A THESIS SUBMITTED TO THE DEPARTMENT OF

GEOLOGY, UNIVERSITY OF NIGERIA, NSUKKA

IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR

THE AWARD OF MASTER OF SCIENCE (M.Sc) DEGREE IN

APPLIED GEOPHYSICS

BY

EZE, JUDITH IJEOMA

(PG/M.SC/2008/49649)

SUPERVISOR: DR. L. I. MAMAH

OCTOBER, 2012

APPROVAL PAGE

iii

Integrated Well to Seismic Hydrocarbon Evaluation of ‘D’-Reservoir Sands of the

Coastal Swamp Depo-belt, Niger-Delta, Nigeria.

BY

Eze, Judith Ijeoma

(PG/M.Sc/08/49649)

Submitted in Partial Fulfillment of the Requirement for the Award of Master of

Science (M.Sc) Degree in Applied Geophysics

Dr. L. I. Mamah Prof. (Mrs) O.P. Umeji Supervisor Head of Department

External Examiner

iv

DEDICATION

…… Dedicated to Almighty God, The giver of all things, and source of my strength.

.

v

ACKNOWLEDGEMENT

I would like to express my heart-felt gratitude to Petroleum Trust Development Fund

(PTDF) for the scholarship granted to me all through my master’s programme.

My sincere thanks to the Data and Consulting Services (DCS) of Schlumberger

Nigeria, and the Exploration Department of Shell Petroleum Development

Company, Port Harcourt (SPDC) under the aegis of Mr. Tola Adeogba and Femi

Ogunsiende for the privilege to use their facility and gain experience through an

Internship programme.

I warmly appreciate my supervisor Dr.L.I Mamah for his contribution. Also, my special

thanks go to my helpful industry mentors Dr Chris Wojcik, Pius Nweke and Dr Adelola

Adesida for their support, assistance and supervision which truly helped me a lot

towards this work. Their co-operation and assistance is highly appreciated.

I also wish to acknowledge the cordial friendship and technical supports from the

SPDC and DCS staff members, especially Segun Obilaja, Mrs. Favour Jaja, Mr. Otuka,

Mr. Ugwu Celestine, Bukky, Mr. Atitebi Babatope, Dr. Ozumba Bertram, Mr. Onu

Chukwuemeka, Mrs Tosin Odewoye, Martha Agi Monye, Dr John Afilaka, Dr Uche

Okorocha, Mr Udeme Udofia, Olalekan Elebute, Mr Marcus Nwagbara and Mrs.

Ojugba Fakuroa .

My special thanks to Professor Mosto Onuoha whose support and contributions to

this work cannot be overemphasized. Sir, I am very grateful.

Special regards also goes to my specials friends and colleague in the person of

Samuel Aralu, Stela, Chisom, Benson and others whose company made things easier

during this research.

I fondly remember and salute the families of Engr. L. Okwemmadu, and Mr. Pius

Chukwuka for their hospitality, care and support.

I also thank other staffs of Geology Department in the person of Professor Okogbue,

Dr Mode Ayonma, Dr Charles Ugwor, Dr Ekwe, Dr Amobi and others for their

encouragements.

vi

Finally, special thanks to my dear parents and siblings for their supports, love and

prayers.

May God Bless you all!

vii

TABLE OF CONTENTS

DEDICATION ii

ACKNOWLEDGEMENT iii

TABLE OF CONTENTS iv

LIST OF FIGURES vi

LIST OF TABLES xii

ABSTRACT xiii

CHAPTER ONE: INTRODUCTION

1.1 STATEMENT OF THE PROBLEM ………………………………………………………. …..1

1.2 TECHNICAL OBJECTIVES …………………………………………………………………………….2

1.3 METHODOLOGY..........................................................................................2

1.4 DATA SET……………………………………………………………………………………………….3

1.5 WORKFLOW……………………………………………………………………………………………….4

1.6. STUDY LOCATION……………………………………………………………………………………….5

CHAPTER TWO: LITERATURE REVIEW

2.1 NIGER-DELTA MORPHOLOGY (REGIONAL GEOLOGY)…………………………………..7

2.2 LOCATION AND REGIONAL SETTING…………………………………………………………….8

2.3 STRUCTURAL EVOLUTION AND TECTONICS………………………………………………….10

2.3.1 GROWTH FAULTS………………………………………………………………………………………….12

2.3.2 SHALE RIDGES AND SALT DIAPIRS………………………………………………………………..13

2.4 NIGER DELTA DEPO-BELTS……………………………………………………………………………14

viii

2.5 SEDIMENTATION AND STRATIGRAPHY OF THE NIGER-DELTA……………………….17

2.5.1 SEDIMENTATION……………………………………………………………………………………………17

2.5.2 STRATIGRAPHY……………………………………………………………………………………………..19

2.5.2.1 AKATA FORMATIOM……………………………………………………………………..…………….21

2.5.2.2 AGBADA FORMATION…………………………………………………………………………………22

2.5.2.3 BENIN FORMATION…………………………………………….………………………………………25

2.6 NIGER-DELTA PETROLEUM GEOLOGY………………………………………………………………..26

CHAPTER THREE: DATA LOADING AND ANALYSIS

3.1 DATA LOADING AND ASSESSMENT (WELL DATA)………………………………………..30

3.2 DELINEATION OF LITHOFACIES, SEQUENCE AND GENETIC UNITS………………... 32

3.2.1 LITHOLOGIC IDENTIFICATION……………………………………………………………………….32

3.2.2 SEQUENCE STRATIGRAPHIC AND REGIONAL SURFACES CORRELATION………...33

3.2.3 RESERVOIR DIFFERENTIATION AND DEPOSIONAL ENVIRONMENT………………..36

3.3 FLUID TYPE…………………………………………………..………………………………………….…..38

3.4 REFLECTIVITY ANALYSIS……………………………………………………………………………….40

3.5 SEISMIC TO WELL TIE……………………………………………………………………………………42

CHAPTER FOUR: GEOPGHYSICAL – PETROPHYSICAL EVALUATION AND RESULTS

4.1.1 SEISMIC DATA LOADING, CONDITIONING AND INTERPRETATION………………….44

4.1.2 FAULTS/STRUCTURAL INTERPRETATION…………………………………………………….....46

4.2 HORIZON INTERPRETATION…………………………………………………………………………….49

4.2.1 D2000 HORIZON…………………………………………………………………………………………….49

4.2.2 D4000 HORIZON…………………………………………………………………………………………….50

ix

4.2.3 D5000 HORIZON……………………………………………………………………………………………50

4.2.4 D7000 HORIZON………………………………………………..…………………………………………50

4.3 PETROPHYSICAL INTERPRETATION AND RESULTS DISCUSSION…………………………51

4.3.1 DATA AVAILABILITY AND QUALITY…………………………………………………………………..52

4.3.2 DATA PREPERATION……………………………………………………………………………..………..54

4.3.3 EVALUATION PARAMETERS……………………………………………………………………………..56

4.4 RESERVOIR PROPERTIES ESTIMATION……………………………………………………………….56

4.4.1 SHALE VOLUME CALCULATION…………………………………………………………………………56

4.4.2 POROSITY EVALUATION………………………………………………………………………………….58

4.4.3 HYDROCARBON SATURATION EVALUATION……………………………………………………59

4.4.4 SATURATION HEIGHT FUNCTION…………………………………………………………………….59

4.5 PETROPHYSICAL RESULTS AND FLUID DISTRIBUTION…………………………………………..61

CHAPTER FIVE: GEOPGHYSICAL – RESERVOIR GEOLOGIC INTERPRETATION, FLUID DISTRIBUTION

ANALYSIS AND RESULTS

5.1.1 DATA AVAILABILITY AND QUALITY………………………………………………………………….64

5.2 RESERVOIR DESCRIPTION OF THE ‘’D-SANDS’’……………………………………………………65

5.2.1 D2000 RESERVOIR DESCRIPTION………………………………………………………………………65

5.2.2 D2000 RESERVOIR CORRELATION……………………………………………………………….....66

5.2.3 D3000 RESERVOIR DESCRIPTION…………………………………………………………………….69

5.2.4 D3000 RESERVOIR CORRELATION…………………………………………………………………..71

5.2.5 RESERVOIR SUBDIVISION AND FLOW UNITS DEFINITION……………………………..72

x

5.2.6 D4000 RESERVOIR DESCRIPTION…………………………………………………………………..73

5.2.7 D5000 AND D5200 RESERVOIRS DESCRIPTION………………………………………………74

5.2.8 D5000-D5200 RESERVOIR SUB-UNITS…………………………………………………………….75

5.2.9 D7000 RESERVOIR DESCRIPTION……………………………………………………………………77

5.3 CORRELATION ANALYSIS………………………………………………………………………………..80

5.4 WELL CORRELATION RESULTS FOR THE D- RESERVOIRS………………………………….83

5.5 FACIES AND PROPERTY EVALUATION………………………………………………………….....89

5.6 POROSITY POPULATION………………………………………………………………………………….90

5.7 FLUID DISTRIBUTION ANALYSIS…………………………………………..…………………………..92

CHAPTER SIX: SUMMARY AND CONCLUSION

6.1 SUMMARY…………………………………………..………………………………………………………….94

6.2 CONCLUSION…………………………………………………………………………………………………..94

REFERENCES…………………………………………………………………………………………………… 96

xi

LIST OF FIGURES

fig. 1-1. Map of Niger-delta showing the Field Location……………………..……..………………5

Fig. 2-1. Map of the Niger Delta Showing Province Outline………………………..................8

Fig. 2-2. Location Map of the Niger Delta showing the main sedimentary basins and tectonic Features……………………………………………………………..……………….…….…...9

Fig. 2-3. Schematic of a seismic section from the Niger Delta Continental Slope/rise showing the results of internal gravity tectonics on the sediments at the distal portion of the depobelt……………………………………………………………………..10

Fig. 2-4. Example of Niger Delta oil field structure and associated trap types. Modified

from Doust and Omatsola………………………………………………………..………….…..…13

Fig. 2-5. Niger Delta Depobelts……………………………………………………….………………..………15

Fig. 2-6. Niger Delta Regional cross-section; showing structural belts……………………….16

Fig. 2-7. Stratigraphy and Ages of the Niger Delta.......................................................19

Fig. 2-8. Schematic showing the location of Lobes of early Niger Delta, prolific oil

centres and Shale prone areas……………………………….…………………….…..…..….26

Fig. 2-9. Sequence Stratigraphic Model for the central portion of the Niger Delta

showing the relation of Source Rock, Migration Pathways and Hydrocarbon

traps related to Growth Faults……….…………………………………………………..……..28

Fig. 3-1. Lithologic differentiation based on GR logs……………………………………….….…..31

Fig. 3-2. The Niger Delta Cenozoic Chronostratigraphic Chart (SPDC)…………………....33

Fig. 3-3. Shows the correlation panel across dip showing the key surfaces…………..…34

xii

Fig. 3-4. Illustration of GR, Resistivity, neutron and density readings, in well 1, 10

and.…………………………………………………………………………………………………..………35

Fig. 3-5. Representative gamma ray pattern observed in the study……………………….37

Fig. 3-6. Well section across strike with marker tops, bases and fluid contacts at

the D-reservoirs and E-reservoirs……………………………………………………………..38

Fig. 3-7. Reflectivity analysis for well 1 at D2000, D6000, D7000 and D8000…………39

Fig. 3-8. Figure3-8: mapping strategy for well 1.......................................................40

Fig. 3-9. Initially tie for well 6 showing the major hydrocarbon reservoirs…………....42

Fig. 3-10. Final Well-to-seismic match for well 6 showing ………………….…………………..42

Fig. 4-1. Comparison of the two seismic data sets received for the study……………..43

Fig. 4-2. Shows the major faults, synthetic fault and collapsed crest interpreted in

the seismic volume from the PSDM Seismic volume…………………………………..45

Fig. 4-3. Shows fault frame work building for the interpreted faults……………………..46

Fig. 4-4. Interpretations from the new PSDM Seismic volume showing the major

boundary fault and some wells in the field. (in-line 11348)……………………47

Fig. 4-5. Seismic random line crossing the field and showing the D2000, D4000,

and D7000 horizons......................................................................................48

Fig. 4-6. Seismic section (Inline 11268) showing interpreted D2000, D4000, D5000

and D7000 horizons and well locations……………………………………………………...50

Fig.4-7. Logs, editing, depth shift and normalization, Well 2 …………………………………....54

Fig. 4-8. Shale distribution type in D7 reservoir………………………………………………….…..57

Fig. 4-9. D7000 Reservoir Sand Unit……………………………………………………………………..….59

Fig. 5-1. D2000 Reservoir Description…………………………………………………………………..65

xiii

Fig. 5-2. Correlation of D2000 reservoirs along dip………………………………………………..66

Fig. 5-3. D2000 Reservoir average VCL Map at various well locations…………………….67

Fig. 5-4. PHIT-VCL cross plot for D2000 reservoir using raw log data (blue) and

log data averaged values (red) shown with the best fit

line.................................68

Fig. 5-5. D3000 reservoir log

section…………………………...............................................69

Fig. 5-6. D3000 reservoir correlation for well 6, 7 and 4………………………………..………70

Fig. 5-7. Correlation panel showing D3000 reservoir sub-units across well 6 & 4……71

Fig. 5-8. D4000 Reservoir Description…………………………………………………………………...73

Fig. 5-9. D5000 reservoir description…………………………………………………….……………….74

Fig. 5-10. Well correlation panel showing D5000 and D5200 reservoir sub-units……..76

Fig. 5-11. Well 7 showing D7 reservoir sub-units........................................................ 77

Fig. 5-12. Well correlation panel showing D7 reservoir sub-units…………………..……….78

Fig. 5-13. D7000 intra-reservoir zones (N-S cross

section)...........................................79

Fig. 5-14. Stratigraphic layers (D7)…………………………………………….…………………………….82

Fig. 5-15. Well correlation between well 2, 3and 4, showing missing reservoir…83

Fig. 5-17. Porosity vs. VCL cross plot..................................................................90

Fig. 5-18. Histogram porosity distribution plots for upscale logs (green bars) and

raw logs (red

bars)............................................................................................... 91

Fig. 5-19. 4W-E cross section of the 3D porosity property distribution…………………92

xiv

Fig. 5-19. Type log (well 6) of the D7000 reservoir shows that the lower sand

member is poorly developed and has high water saturation exhibiting a

lower resistivity response than the upper

member................................................93

xv

LIST OF TABLES

Table 3-1: List of available and unavailable well logs……………………………………….……....29

Table 3-2: List of wells with check shots and bio data…………………………………………..….30

Table 3-3: Showing MFS confirmed by faunal abundance……………………………………….…32

Table 4-1: Seismic data

information..............................................................................44

Table 4-2: List of available and unavailable logs for Petrophysical evaluation……………52

Table 4-3: List of wells with check shots and bio data……………………………………………….53

xvi

Table 4-4: Fluid distribution table for D2000 reservoir. All depth in ft

tvdss.................60

Table 4-5: Fluid distribution table for D3000 reservoir. All depth in ft

tvdss.................60

Table 4-6: Fluid distribution table for D4000 reservoir. All depth in ft

tvdss..................61

Table 4-7: Fluid distribution table for D5000 reservoir. All depth in ft

tvdss..................61

Table 4-8: Fluid distribution table for D7000 reservoir. All depth in ft

tvdss..................62

Table 5-1: Available data for D

reservoirs.......................................................................64

Table 5-2: Layering inside D7

zones................................................................................80

Table 5-3: Well correlation result for well

1...................................................................82

Table 5-4: Well correlation result for well

2...................................................................82

Table 5-5: Well correlation result for well 4………………………………………………………….….83

Table 5-6: Well correlation result for well

6...................................................................84

Table 5-7: Well correlation result for well 7…………………………………………….……………….84

xvii

Table 5-8: Well correlation result for well

9.................................................................85

Table 5-9: Well correlation result for well

12...............................................................86

Table 5-10: Well correlation result for well

15..............................................................87

Table 5-11: Well correlation result for well

16..............................................................88

Table 5-12: Reservoir cut-off for the various rock

types...............................................89

xviii

Abstract

An integrated approach which honours all the available well log data, seismic and

geological information was employed for the evaluation of the D-Reservoirs of the Alpha

field, Coastal Swamp Niger Delta for better understanding of the reservoir properties

and fluid distribution. The depositional and tectonic settings of the area conform to the

typical Niger Delta sequence: sediment distribution is controlled by the fault activity

that generated a few roll-over anticlines and antithetic faults. The depositional model

was deduced from reservoir geologic interpretations and 3D seismic data which show

good events continuity and reflection termination against faults. The subtle variations in

the geometric properties show a good sand development from the proximal to the distal

part of the basin. Petrophysical evaluation carried out across all the D-reservoirs

suggests that shale volume estimation is uncertain in the thinly laminated sands due to

limitations in the tools logging vertical resolution but well defined in the main sand

intervals. The result from this analysis also shows that the sands have good reservoir

properties with porosity ranging from 20 to 30% while the formation water saturation in

the clean and permeable intervals is low ranging from 5 to 20% (e.g. in the D5200 for

example). The lower sand member is poorly developed and has water saturation

exhibiting a lower resistivity response than the upper member. A total of 16

hydrocarbon bearing reservoirs, labeled C to G has been identified within the down

thrown block of the field, and of these reservoirs, the D-sand are volumetrically the

most significant. The individual reservoirs and their sub-units are separated by thin

shales which are predominantly of marine origin while the D-sand sequence is capped

by thick extensive marine shale. Therefore, in order to obtain best results for reservoir

properties, one must design a multi-disciplinary workflow that integrates well log,

petrophysical and seismic information, the use of such a workflow would yield reliable

information of required to support the optimization of the development wells to be

drilled in the area.

1

CHAPTER ONE

INTRODUTION

It is critical to obtain an accurate description of the hydrocarbon reservoirs from

well control. An integrated approach applied to this study helps in understanding

the reservoir and lithologic variation within the reservoir units. The description of

the reservoir away from the well control is also determined from 3D seismic data

and Quantitative interpretation studies. The standard approach to incorporating

seismic information to reservoir evaluation involves;

I. Detailed sequence stratigraphic analysis of the reservoir units to determine

the depositional history, reservoir architecture and facies distribution.

II. Evaluation of reservoir flow units and fluid distribution analysis to

determine the variations in reservoir lithology, morphology and possible

connectivity between reservoirs.

Thus an integrated approach was employed to accurately map and identify the

hydrocarbon bearing units of the D- reservoirs and evaluate the major flow unit.

The exploration strategy for mapping and evaluation of the sandstone reservoirs

would be a step-wise process, involving the integration of petrophysical, seismic

information, fluid distribution analysis and quantitative interpretation studies.

2

1.2 TECHNICAL OBJECTIVE:

The objective of this work is:

I. To carry out stratigraphic correlations of the field using well logs,

biostratigraphic and seismic data; including detailed litho-stratigraphic

description of the hydrocarbon reservoirs in the area.

II. To carry out detailed seismic interpretation and geologic mapping of the

area.

III. To qualify the uncertainty in reservoir description by quantitatively

incorporating different data types which includes both the seismic and well

log.

IV. To generate petro-physical model ready for input to reservoir simulation.

1.3 METHODOLOGY:

The applied methodology used in this study, utilized tools such as Petrel software;

Stochastic Trap Analysis and Risking (STAR) module of Petrel software; Geo-frame

Software and the Shell NDi tool. The study involves;

Data gathering and loading of seismic volumes, well data, geologic

information etc.

Well log interpretation and correlation

Seismic data interpretation (faults and horizon interpretation).

Well to seismic ties and acoustic analysis

Petrophysical evaluation and well correlation of the D-Reservoirs

3

Interpretation of results.

1.4 DATA SET USED;

i. 3D Pre-Stack Seismic Data volume study area.

ii. Well data from 16wells; including gamma ray log, caliper, sonic log,

Resistivity (deep and shallow), Density, Neutron, and well picks.

iii. Biofacies Data - Plankton diversity and abundance, Foram diversity

and abundance. Core sample type, paleobathymetry, depositional

environments, Regional surfaces with ages and marker names.

4

1.5 WORKFLOW

Well Description

And correlation

Biostrat Data

Biofacies Data

Seismic

Well Logs

Reflectivity Pattern Analysis

Caliper, Gamma ray

Logs Density, Sonic Logs

Well to Seismic Tie, Reservoir

Mapping and Interpretation

Velocity Data

Reflectivity Results of

D-reservoirs

Petro-Physical Evaluation, Geo-reservoir

Evaluation, Results and interpretation

5

1.6. LOCATION OF THE STUDY AREA

Y-Field is located in south-west of Port-Harcourt within the Coastal Swamp

Depobelt of the Cenozoic Tertiary Niger Delta Basin. Sediment deposition in this

area started in early Miocene times. The Niger Delta is found at the southern end

of Nigeria bordering the Atlantic Ocean and extends from about longitude 30 - 90 E

and latitude 40251 – 50201 N (Figure 1-1).

Sediment deposition in this area started in early Miocene times and the

sedimentary package is comprised of the basal holomarine shales (Akata

Formation), the coastal plain sand-shale alternations (Agbada Formation), and

coastal plain sands (Benin Formation) being the youngest stratigraphic unit at the

shallower part of the basin. This succession is linked to the palaeo Niger and

Benue system (Allen, 1965). The area is also characterized by basinward dipping

regional and counter-regional faults which are products of the regions tectonic

history as documented by several authors. A total of seven (16) Wells are located

in the Field. (Well -002, Well -003, Well 004, Well -005, Well -006, Well -007, Well

-008,….).

6

Figure 1-1: Map of Niger Delta showing the study location marked as AOI

LEGEND: AOI: Area of interest (Study Area).

7

CHAPTER TWO

LITERATURE REVIEW

2.1 NIGER-DELTA MORPHOLOGY (REGIONAL GEOLOGY)

The Tertiary Niger Data is situated in the Gulf of Guinea and extends throughout

the Niger Delta province as defined by Kulke (1995). It is one of the largest delta

systems in the world, and forms one of its important hydrocarbon provinces. The

development of the delta has been dependent on the balance between the rate

of sedimentation and the rate of subsidence. This balance and the resulting

sedimentary patterns appear to have been influenced by the structural

configuration and tectonics of the basement. From the Eocene to the present, the

delta has prograded southwestwards, forming depobelts that represent the most

active portions of the delta at each stage of its development (Doust and

Omatsola, 1990).

The onshore portion of the Niger Delta Province is delineated by the geology of

southern Nigeria and southwestern Cameroon. The northern boundary is the

Benin flank-an east-northeast trending hinge line south of the West Africa

basement massif. The northeastern boundary is defined by outcrops of the

Cretaceous on the Abakiliki High and further east-south-east by the Calabar flank-

a hinge line bordering the adjacent Precambrian (Figure 2-1).

8

Figure 1 Map of the Niger Delta Showing Province Outline (Maximum petroleum system bounding

structural features, minimum petroleum system as defined by oil and gas field center points (Petro

consult, 1996).

9

2.2 LOCATION AND REGIONAL SETTING

The Niger- Delta Basin is located on the West African continental margin where

the east trending equatorial coast turns south towards the Equator. It underlies

the coastal plain, the continental shelf and slope of Nigeria and western

Cameroun, and the northern territorial waters of equatorial Guinea, West of

Bioko Island. Its southern margin is marked by seafloor escarpments, which lie

over oceanic crust. . The Niger Delta basin covers approximately 211,000km² and

developed south-westwards out of the Anambra Basin and the Benue Trough.

The Niger Delta basin is located within the perioceanic section of the Abakaliki-

Benue suture zone of the much larger southern Nigerian basin. On the west it is

separated from the Dahomey (or Benin) basin by the Okitipupa basement high,

and on the east is bounded by the Cameroun volcanic line. The Benin flank, which

is the subsurface continuation of the West African shield, marks the north-

western rim of the basin. To the north of the Cenozoic basin lie the Senonian

Abakaliki Uplift and the Post-Abakaliki Anambra Basin (Murat, 1972)

10

Figure 2 Location Map of the Niger Delta showing the main sedimentary basins

and tectonic features. (Whiteman, 1982).

11

2.3 STRUCTURAL EVOLUTION AND TECTONICS

Along the west coast of equatorial Africa, the tectonic framework of the

continental margin along the West Coast of equatorial Africa is controlled by

Cretaceous fracture zones expressed as trenches and ridges in the deep Atlantic.

The fracture zone ridges subdivide the margin into individual basins, and, in

Nigeria, form the boundary faults of the Cretaceous Benue-Abakaliki trough,

which cuts far into the West African shield. The trough represents a failed arm of

a rift triple junction associated with the opening of the South Atlantic. In this

region, rifting started in the Late Jurassic and persisted into the Middle

Cretaceous (Lehner and De Ruiter, 1977). In the region of the Niger Delta, rifting

diminished altogether in the Late Cretaceous (Michele et al., 1999).

After rifting ceased, gravity tectonism became the primary deformational process.

Shale mobility induced internal deformation and occurred in response to two

processes (Kulke, 1995). First, shale diapers formed from loading of poorly

compacted, over-pressured, prodelta and delta-slope clays (Akata Formation.) by

the higher density delta-front sands (Agbada Formation). Second, slope instability

occurred due to lack of lateral, basinward, support for the under-compacted

delta-slope clays (Akata Formation).

For any given depobelt, gravity tectonics were completed before deposition of

the Benin Formation and are expressed in complex structures, including shale

diapers, roll-over anticlines, collapsed growth fault crest, back-to-back features,

and steeply dipping, closely spaced flank faults (Evamy et al, 1978).

12

Figure 3 Schematic of a seismic section from the Niger Delta Continental

Slope/rise showing the results of internal gravity tectonics on the

sediments at the distal portion of the depobelt (Stacher, 1995

13

These faults mostly offset different parts of the Agbada Formation and flatten

into detachment planes near the top of the Akata Formation.

In summary, the structural styles in the Niger Delta, both on a regional scale and

on a field scale can simply be described by the influence of sedimentation ratio to

subsidence rates. Thus the following can exist.

(i) Faulted rollover anticlines with multiple growth or anticlinal faults

(ii) Simple unfaulted anticlinal rollover structures

(iii) Complicated collapsed crest structures

(iv) Sub-parallel growth faults (K-block structure)

(v) Structural closures along the back of major growth faults.

Most of the largest fields in the Niger Delta are of the collapsed crest type about

half of the structures of this type are prominent fields. The second best fields are

the faulted rollover anticlines while third are the unfaulted rollover structures.

Among all other types, only the structures in the upthrown blocks of major

growth faults occur with some frequency and appreciable reserves.

2.3.1 GROWTH FAULTS:

Weber and Daukoro described this as a result of rapid sand deposition along the

delta edge on top of under-compacted clay which leads to the development of a

large number of synsedimentary gravitational faults (Fig 2-4).

14

The spacing between successive growth faults decreases with an increase of

depositional slope or an increase in the rate of deposition over the rate of

subsidence. Growth faults tend to envelop local depocenters at their time of

formation.

The term “growth fault” derives from the fact that after its formation, the faults

remains active and thereby allowing faster sedimentation in the down thrown

fault block relative to the up-thrown side. The thickness ratio of a given

stratigraphic unit in the up-thrown block is known as the “growth index” which in

Nigeria can be as high as 2.5m. Basically, growth faults are listric normal faults

and thus tend to die out with depth thereby forming bedding plane.

The fault thrown at the level of the Akata Formation is often as large as several

thousand feet. The enhanced sedimentation along the growth fault causes a

rotational movement. This tilts the beds towards the fault thereby forming the

“rollover anticlines”. Almost all the oil fields discovered in the Niger Delta so far

are associated with the rollover anticlines. An important characteristic of Nigerian

rollover anticlines is the shift of the crestal position with depth. The Agbada

Formation is the most affected by growth faulting in the Niger Delta. The faults of

the Niger Delta die out at the upper part of the massive marine Akata shale

Formation.

2.3.2 Shale Ridges and Salt Diapirs:

The shale upheaval ridges occurring in Nigeria are of three different kinds (Weber

and Daukoru, 1975). The first are the zones behind major growth faults. Secondly,

15

shale bulges in front of growth faults are often observed and these bulges can

sometimes act as positive elements, causing collapsed crest structures and

unconformities. The third type, are those along the continental slope shale bodies

were extruded in a seaward direction as a result of different loading on the plastic

marine shale. With continued sedimentation, these offshore clay upheaval ridges

are buried but like salt domes, their growth can continue. Finally, the clay ridges

may develop into true diapiric structures.

16

Figure 1.10.2: Example of Niger Delta oil field structure and associated trap types. Modified from

Doust and Omatsola (1990) and Stacher (1995).

17

From the Eocene to the present, the delta has prograded southwestward, forming

depobelts that represent the most active portion of the delta at each stage of its

development (Doust and Omatsola, 1990). Thus, today the Niger Delta represents

a coarsening upward regressive sequence of Tertiary clastics that prograded over

a passive continental margin sequence of mainly Cretaceous sediments.

2.4 THE NIGER DELTA DEPO-BELTS

Deposition of the three formations occurred in each of the five offlapping

siliciclastic sedimentation cycles that comprise the Niger Delta. These cycles

(depobelts) are 30-60 kilometers wide, prograde southwestward 250 kilometers

over oceanic crust into the Gulf of Guinea (Stacher, 1995), and are defined by

synsedimentary faulting that occurred in response to variable rates of subsidence

and sediment supply rates resulted in deposition of discrete depobelts—when

further crustal subsidence of the basin could no longer be accommodated, the

focus of sediment deposition shifted seaward, forming a new depobelt (Doust and

Omatsola, 1990). Each depobelt is a separate unit that corresponds to a break in

regional dip o f the delta and is bounded landward by growth faults and seaward

by large counter-regional faults or the growth fault of the next seaward belt

(Evamy and others, 1978; Doust and Omatsola, 1990). Five major depobelts are

generally recognized, each with its own sedimentation, deformation, and

petroleum history.

Doust and Omatsola (1990) describe three depobelt provinces based on structure.

The northern delta province, which overlies relatively shallow basement, has the

18

oldest growth faults that are generally rotational, evenly spaced, and increases

their steepness seaward. The central delta province has depobelts with well-

defined structures such as successively deeper rollover crests that shift seaward

for any given growth fault. Lastly, the distal delta province is the most structurally

complex due to internal gravity tectonics on the modern continental slope.

Classic integrated geological studies have shown that several different depobelts

abound in the Niger delta Basin (Figure 2-5). These depobelts are;

Northern

Greater Ughelli Onshore

Central swamp

Coastal Swamp

Shallow Offshore continental Shelf (Not more than 200 isobaths)

Deep/Ultra Offshore 200 to 300 isobaths

19

FIG. 2-5: Niger Delta Depobelts (DPR, 2006)

20

while three (3) categories of structural styles are common in the Niger Delta

Onshore, continental Shelf and Deepwater terrains (Figure 2-6).

Extensional Zone – Growth Faults

Translational Zone – Diapirs

Compression Zone – Toe thrust

21

Figure 2-6: Niger Delta Depobelts and Niger Delta Regional cross-section;

Showing structural belts. (Adopted from Hooper et al. 200

22

2.5.0 SEDIMENTATION AND STRATIGRAPHY OF THE NIGER- DELTA

2.5.1 Sedimentation

Deltaic sedimentation is seen as a function of the rate of deposition (Rd) and the

rate of subsidence (Rs). Depending on this function, the delta builds out or

progrades (Rd>Rs), remains stationary and builds up (RdRs) or retreats (Rd<Rs)

(Michele et al., 1999).

In Lower Tertiary times, the sea transgressed the whole of southern Nigeria,

terminating the advance of a Cretaceous Niger Delta. The Tertiary Niger Delta

began its seaward advance in Eocene time (Short and Stauble, 1967). The net

result of these events was the formation of a sediment body, greater than 5000m

thick, which contain a great number of trangressive/regressive depositional

sequences.

From the Campanian through the Paleocene, the shoreline was concave into the

Anambra basin (Hospers, 1965), resulting in convergent longshore drift cells that

produced tide-dominated deltaic sedimentation during transgression and river-

dominated deltaic sedimentation during regression (Reijers, 1996). In the

Paleocene, a major transgression (referred to as the Sokoto transgression by

Reijers, 1996) began with the Imo Shale being deposited in the Anambra basin to

the northeast and the Akata Shale in the Niger Delta basin area to the southwest.

In the Eocene, the coastline shape became convexly curvilinear, the longshore

drift cells switched to divergent, and sedimentation changed to being wave-

dominated (Reijers et al., 1996). At this time, deposition of paralic sediments

began in the Niger Delta basin proper and, as the sediments prograded south; the

coastline became progressively more convex seaward.

23

The shale ridges at the distal ends of the long, regional south flanks are thought to

be the product of a strongly diachronous southward facies to purely marine shale,

developed when RdRs. The Akata Formation formed during lowstands when

terrestrial organic matter and clays were transported to deep-water areas

characterized by low energy conditions and oxygen deficiency (Stacher, 1995).

The formation is typically overpressured and estimated to be up to 7000m thick

(Doust and Omatsola, 1990).

2.5.2 STRATIGRAPHY

Short and Stauble (1967), defined three stratigraphic unit in the tertiary Niger

Delta based on the dominant environmental influence. The main sedimentary

environments are the continental environment, the transitional environment, and

the marine environment. These are stratigraphically superimposed; the basal

parts of the stratigaphic sequence are represented by inter-bedded shallow

marine and fluvial sands, silt and clays which are typical of parallic setting. The

sequence is capped by a section of massive continental sands.

Based on the history or relative unbroken progradation throughout the Tertiary,

these depositional lithofacies are readily identified despite local facies variations,

as the three regional and diachronons formations ranging from Eocene to Recent

age. The three formations are locally designated (from the bottom) as Akata

Formation, Agbada Formation and Benin Formation respectively (figure below).

Of these three Formations, the Agbada Formation constitutes the main reservoirs

24

of hydrocarbons in the Niger Delta while the Agbada shales mainly constitute the

seals. The stratigraphy of Niger Delta outlined below is based on the work of

(Short and Stauble 1967; Weber 1971; Weber and Daukoru 1975).

Figure 2.3- Stratigraphy and Ages of the Niger Delta (After Doust and Omatsola, 1990).

25

2.5.2.1 AKATA FORMATION:

The basal marine pro-delta megafacies Akata Formation is predominantly shale

sequence with occasional turbidite sandstones (potential reservoirs in deep

water) and minor amounts of clay and silt. Beginning in the Paleocene and

through the Recent, the Akata Formation formed during low lowstands when

terrestrial organic matter and clays were transported to deep water areas

characterized by low energy conditions and oxygen deficiency. The formation

underlies the entire delta, and is typically over-pressured. Turbidity currents likely

deposited deep sea fan sands within the upper Akata Formation during

development of the delta.

The formation consists of dark grey uniform shale, especially in the upper part. In

some areas, it is sandy or silty in the upper part of the formation where it grades

into the Agbada Formation.

As defined by paleontological evidence mainly planktonic foraminifera, the

marine shale of the Akata Formation range from Paleocene to Holocene in age

and are over pressured.

Source rocks of the Niger delta hydrocarbon have been a subject of some

controversy. Some researchers have proposed the shales of the paralic sequence

(i.e. Agbada Formation) as the source rock, while others argue that in most parts

of the delta, the Agbada Formation is immature and suggested the source rocks

to be the ature shales of Akata Formation that are more mature. Drilling activities

26

have not penetrated the base of Akata Formation probably because of its highly

compacted and over-pressured nature.

2.5.2.2 AGBADA FORMATION

Deposition of the overlying Agbada Formation, the major petroleum-bearing unit,

began in the Eocene (in the North) and continues into the recent (in the South) at

the present day surface though varies. The formation consists of alternating

sandstones and shales of over 3700 meters thick and represents the actual deltaic

portion of the sequence deposited at interface between the lower deltaic plain

and marine of the continental shelf fronting the delta. It consists of numerous

offlap rhythmic, the sand parts of which constitute the main petroleum reservoirs

in the Niger Delta oil fields. The shales constitute seals to reservoirs. The clastics

accumulated in delta-front, delta-topset, and fluvio-deltaic environments. In the

lower Agbada Formation, shale and sandstone beds were deposited in equal

proportions, however, the upper portion is mostly sand with only minor shale

interbeds.

The alternations of sandy and argillaceous sediments are the result of differential

subsidence, variation in the sediment supply and shift in the depositional lobs of

the delta. Generally the upper part is sandier than the lower part, indicating a

general seaward advancing of the delta. The thickest section of the Agbada is

about 10,000ft to 15,000ft. Obviously thickness will vary from place to place

27

dependent on structural and depositional and depositional position. The Agbada

Formation is overlain by the cyclic sedimentation and physiographic Units.

The vertical sequence of sediments in the shallow core holes in the Recent and in

the deep boreholes in the Tertiary paralic deposits of the Niger Delta shows

clearly the characteristic cyclic nature of the sedimentation. The Tertiary paralic

sediments are composed of a large number of depositional cycles with a thickness

ranging from 15 to 100metres (Weber, 1971).

A complete cycle generally consists of thin fossiliferous transgressive marine

sands followed by an offlap sequence which commences with marine shale and

continues with laminated fluviomarine sediments. Barrier-bar and/or fluviatile

sediments may follow before another transgression terminates the cycle. The

physiographic units associated with the formation of the Niger Delta are discussed

below.

I. Onlap Sands

Most cycles begin with the erosion of the underlying sand unit and the deposition

of thin fossiliferous transgressive marine sand. These sands can be recognized by

their relatively high resistivity because their pores are partly filled with carbonate

cement. Often the gamma radiation emitted by the transgressive sands is also

high due to high percentage of the potassium-rich glauconite. The sands are

mainly derived from reworking and winnowing of the eroded beds. Burrowing

extending into the underlying offlap sand is common. This type of transgressive

sand is probably associated with a regional transgression, which pushed the

28

shoreline back over a considerable distance (Weber, 1971). The presence of

abundant glauconite is indicative of shallow marine deposition.

Onlap deposits with thicknesses up to 10 meters seem to have taken place more

gradually and the onlap sands have the character of fluviomarine sediments.

Streaks of coarse grains and glauconite and clay intercalations are common, and

they may be associated with strong growth-fault activity in a limited area.

II. Offlap Sediments

Marine clay: The marine clay overlying the onlap sands quite silty and sandy.

Streaks and lenses of very fine sand to silt occur throughout; clay and plant

remains indicate that the clays were deposited in the inner to middle neritic

zones. It contains significant amounts of montmorillonite, which is finer than

kaolinite and thus transported further, and can form the seal over a reservoir.

III. Fluviomarine (Delta Fringe) and Barrier-Foot Deposits

Towards the top, the marine clay becomes sandier and gradually changes to

laminated clay/silt/fine sand. Because of the rapid sedimentation the layers are

little disturbed by burrowing (Weber, 1971). Plant remains are very common in

the fluviomarine sands and occasionally accumulate in thin lignitic streaks. This

forms the proximal fluviomarine frontal part of coastal barriers and is termed

“barrier foot”. Its remarkable feature is the high gamma radiation commonly

29

associated with these beds. An analysis of the sidewall samples from a high

radiation zone of this kind in the Olomoro field indicates the presence of silt size

zircon (Weber, 1971).

IV. Barrier Bar

The higher energy beach and washover sands often overlie the barrier foot. The

cleaner and coarser sands deposited in the zone where wave action takes place

are termed “barrier bars” deposits. The sands are fine with an average grain size

of 250-60 microns. The ratio of the maximum to average grain size in the fluviatile

sediments of the Niger Delta is always higher than 3.

The main part of the barrier bars is usually parallel bedded with occasional small-

scale cross bedding in the lower part and a limited number of burrows, with silty

clay breaks and lignite beds are common. The length of the barriers parallel to the

coast is very large (5-37km with an average of 18km in the recent delta). Thus the

barrier bars have the character of widespread sheet sands. Because longshore

currents and wave action control their formation, they can be correlated over all

or most of a field’s area.

It is fairly common to find a series of barrier-bar sands on top of each other with

only very thin marine clay and/or thin interval of barrier-foot sediments in

between the clean sands.

30

V. Tidal Channels

Tidal channel-fills often consist of a series of thin cross-bedded sequences fining

upwards with a clay pebble or gravel lag deposit at the base, and separated by

thin clay beds. The maximum width of the tidal channels is 2700m with a depth of

20m. Clay breaks between these sequences give the channel-fills a serrated

character on the SP and gamma ray logs (Weber, 1971).

Distributary channel-fills are very similar in grain-size distribution and internal

structure to point bar sands formed further away from the coast. In the channel,

the upward fining grain-size distribution is often pronounced in the upper part of

the fills, which are commonly composed of, laminated wavy-bedded clay and silty

and often followed by kaolinitic root-marked clay. Plant remains and clay pebbles

are common. Around the fills are found, the natural-levee deposits of clayey fine

sand and crevasse sands interbedded with the backswamp and lagoonal

sediments.

2.5.2.3 BENIN FORMATION:

Benin Formation, which is a continental, latest Eocene to Recent deposit of

alluvial and super coastal plain sands that are up to 2000m thick (Avbovbo, 1978).

Formation has been described as “Coastal plain Sand” and the sediments

represent upper deltaic plain deposits. The formation lacks faunal content and

this makes it uneasy to date although an Oligocene-Recent age is generally

accepted.

31

Till today, very little oil has been found in the Benin Formation (mainly minor oil

show), and the formation is generally water bearing. It is the main source of

portable ground water in the Niger Delta area.

2.6 NIGER DELTA PETROLEUM GEOLOGY

The prolific Cenozonic Niger Delta has enormous petroleum reserves estimated at

about 30 billion barrels of oil and 260 trillion cubic feet of natural gas. Worldwide

ranking marks the Niger delta as the seventh richest petroleum production with

an average of about 1.8 million bbl of oil per day. Nearly 1 billion barrels of oil and

condensate have been discovered in the Rio Del Rey section in Cameroon and 45

million barrels occur in the Equator-Guinea sector of the delta.

Petroleum occurs throughout the Agbada Formation of the Niger delta however,

several directional trends form an “oil-rich belt” having the largest field and

lowest gas:oil ratio (Ejedawe, 1984; Evamy and others; 1978; Doust and

Omatsola, 1990). From the northwest offshore are to the southeast offshore and

along a number of north-south trends in the area of Port Harcourt (figure 2-8).

32

Figure2-7 Schematic showing the location of Lobes of early Niger Delta, prolific oil centres and Shale

prone areas ( Tuttle et al 1999).

33

This hydrocarbon distribution was originally attributed to timing of trap formation

relative to petroleum migration (earlier landward structures trapped earlier

migrating oil). Evamy and others (1978), however, showed that in many rollovers,

movement on the structure-building fault and resulting growth continued and

was relayed progressively southward into the younger part of the section by

successive crestal faults, concluding that there was no relation between growth

along a fault and distribution of petroleum. Ejedawe (1981) relates the position of

the oil-rich areas within the belt to five delta lobes fed by four different rivers. He

states that the two controlling factors are an increase in geothermal gradient

relative to the minimum gradient in the delta center and the generally greater age

of sediments within the belt relative to those further seaward. Together these

factors gave the sediments within the belt the highest “maturity per unit depth.”

Weber (1971) indicates that the oil-rich belt (“golden lane”) coincides with a

concentration of rollover structures across depobelts having short southern flanks

and little paralic sequence to the south. Doust and Omatsola (1990) suggest that

the distribution of petroleum is likely related to heterogeneity of source rock type

(greater contribution from paralic sequences in the west) and/or segregation due

to remigration. Haack et al (1997) relate the position of the oil-rich belt to oil-

prone marine source rocks deposited adjacent to the delta lobes, and suggest that

the accumulation of these source rocks was controlled by pre-Tertiary structural

sub-basins related to basement structures.

Outside of the “oil-rich belt” (central, easternmost, and northernmost parts of the

delta), the gas:oil ratios (GOR) are high. The GOR within each depobelt increases

seaward and along strike away from depositional centers. Causes for the

distribution of GOR’s are speculative and include remigration induced by tilting

34

during the latter history of deposition within the downdip portion of the

depobeflt, updip flushing of accumulations by gas generated at higher maturity,

and/or heterogeneity of source rock type (Doust and Omatsola, 1990). Stacher

(1995), using sequence stratigraphy, developed a hydrocarbon habitat model for

the Niger delta (Figure 2-9).

The model was constructed for the central portion of the delta, including some of

the oil-rich belt, and relates deposition of the Akata Formation (the assumed

source rock) and the sand/shale units in the Agbada Formation (the reservoirs

and seals) to sea level. Pre-Miocene Akata shale was deposited in deep water

during lowstands and is overlain by Miocene Agbada sequence system tracts. The

Agbada Formation in the central portion of the delta fits a shallow ramp model

with mainly highstand (hydrocarbon-bearing sands) and trangressive (sealing

shale) system tracts--third order lowstand system tracts were not formed.

Faulting in the Agbada Formation provided pathways for petroleum migration and

formed structural traps that, together with stratigraphic traps, accumulated

petroleum. The shale in the transgressive system tract provided an excellent seal

above the sands as well as enhancing clay smearing within faults. (Stacher, 1995).

35

Figure 2-9: Sequence Stratigraphic Model for the central portion of the Niger Delta showing the

relation of Source Rock, Migration Pathways and Hydrocarbon traps related to Growth Faults

(Stacher, 1995).

36

CHAPTER THREE

3.0 DATA LOADING AND ASSESSMENT (WELL DATA)

Well logs 15 wells were imported and used for the lithologic identification and to

quality check the different fluid types and contacts. The key logs used for the

lithologic discrimination were gamma ray, resistivity, compensated neutron

porosity and bulk density logs. Details of available log data are as follows;

TABLE 3-1: LIST OF AVAILABLE AND UNAVAILABLE LOGS

37

TABLE 3-2: LIST OF WELLS WITH CHECK SHOTS AND BIO DATA

38

39

3.2 DELINEATION OF LITHOFACIES, SEQUENCES AND GENETIC UNITS

3.2.1 LITHOLOGIC IDENTIFICATION

The identification and differentiation of reservoir and non-reservoir units (sands

and shales) is usually done with gamma ray logs.

The log character is applied in the classification of lithofacies or depositional

environment and well correlation. It is also the key parameter for determination

of gross reservoir thickness. At the deeper sections where GR log values poorly

differentiate the reservoirs from the non reservoirs, we integrated it with sonic,

density and resistivity logs, and the raw porosity log for better lithology definition.

For example, our well logs show that at some deep seated intervals in deeper

depths of this field, the gamma ray values predicts shale (>80-90 API), whereas

other porosity logs and resistivity logs suggests otherwise at such depths. Some of

the key hydrocarbon rich intervals especially at greater depths actually show very

high GR values.(see figure below).

40

Figure 3-1: lithologic differentiation based on GR logs.

41

3.2.2 SEQUENCE STRATIGRAPHIC AND REGIONAL SURFACES CORRELATION

Genetically related strata are bounded by surfaces of erosion or non deposition,

or their correlative conformities. The key surfaces of division recognized here

includes; sequence boundary (SB), maximum flooding surfaces (MFS), and the

transgressive or flooding surfaces.

Based on biostratigraphic data, three major depositional cycles with associated

MFS have been interpreted within the P770, P780 and P820 P zones.

TABLE 3-3: SHOWING MFS CONFIRMED BY FAUNAL ABUNDANCE

Dodo Shale (11.5 Ma) E1000 Base Shales

Nonion-4 (10.4Ma) D5 Base Shale

Uvigerina-8 TAF Shale

Key flooding surfaces were picked on the basis of density, neutron, resistivity log

responses and biostratigraphic data from wells. To mitigate the impact of

spurious log across shales on account of washout effects, density and neutron

logs were used.

Also, biofacies data; planktonia and fogram diversity and abundance (PDIV,

PPOPN, FDIV, and FPOPN), paleobathymetry, P-F zones from Niger Delta

42

chronostratigraphic chart (Shown in the figure below) were used as a guide to a

good correlation.

The Chronostratigraphic chart is a table showing the Nigeria delta Cenozoic

sequence stratigraphic and geological data table. The ages of the maximum

flooding surfaces and the sequences boundaries in this chart prepared by SPDC

using the P and F zones established from biostratigraphic data.

Marker fossils for specific age were also integrated in delineating the key flooding

surfaces.

Based on biostatigraphic data, three major depositional cycles with associated

MFS have been interpreted within the P770, P780 and P820 P-zones.

Key flooding surfaces were picked on the bases of density, neutron and resistivity

log responses and biostratigraphic data from wells. To mitigate the impact of

spurious log response across shales on account of washout effects, density and

neutron logs were used. The figure below shows the correlation panel across dip

showing the key surfaces encountered.

43

Figure 2.4. The Niger Delta Cenozoic Chronostratigraphic Chart (SPDC)

44

Figure 3-3: Shows the correlation panel across dip

45

The key surfaces; sequences boundary (SB) and maximum flooding surfaces (MFS)

was marked and identified. The sequence boundary (SB) is always identified on

the zone of minimum gamma ray, progradational-retrogredational boundary,

zones of lowest faunal diversity and abundance. While the MFS is identified at

maximum neutron and density separation, retrogradational to progradational and

maximum water depth.

3.2.3 RESERVOIR DIFFERENTIATION AND DEPOSIONAL ENVIRONMENT

Basically, gamma ray values are used for differentiation of reservoir and non –

reservoir units. On the other hand, its motifs and character is applied for

lithofacies or depositional environment and well correlation. It is also the key

parameter for determination of gross reservoir thickness. Gamma ray log was

integrated with sonic, density and resistivity logs and porosity logs for better

lithologic definition and correlation for well 1, 10 and 11.

46

Figure 3-4: Illustration of GR, Resistivity, neuron and density readings, in well 1, 10 and 11.

47

The delineation of depositional environments using conventional GR, and SP log

signatures (motifs) has its challenges. First, the method is quite subjective

because there are cases where similar log motifs have been recorded for

lithologic intervals belonging to two or more different depositional settings.

Secondly, the issue of scale for the motifs is also a major concern to geologist.

This raises questions on how much we should rely on the use of log motifs for

facies identification and interpretation of depositional environments (Genetic

units). According to some authors, the definition of genetic units using a

combination of log motifs with sidewall sample descriptions and reservoir quality

index (RQl) is most likely to give better results. The reservoir quality index is a

parameter used to quantitatively characterize reservoirs and separate them into

hydraulic units of same flow index (Uguru et al., 2005) for this project, we used

integration of the fluid zone index (FZI) which is derived from the RQl, log motifs

and sidewall descriptions for better definition of the sedimentary facies belonging

to distinct depositional environments (genetic units). The different log motifs

usually reflect the vertical behavior of Gamma and SP logs in sediments of

different grain sizes. These shapes as used to deduce paleoenvironments and

other depositional -conditions has been documented by several authors (Paul

Lane, 2002; Klett, et al., 2002; Iwegbu and Arochukwu, 2003; Jinder, et al., 2005;

Olo-Buraimo, et al., 2010).

(a) Bell-shaped GR/resistivity – channels

(b) Funnel-shaped GR/resistivity – (i) Shoreface (>20m thick, glauconite +

shell debris), (ii) Crevasse splay (<8m + carbonaceous detritus), (iii) Lower

shoreface (thin sand, thicker marine mud, lower FZI). (Jinder, et al., 2005).

48

(c) Cylindrical – (i) Tidal channels (glauconite - shell debris, serrated), (ii)

Foreshore.

One importance of the use of this integrated method is the achievement of better

resolution and genetic unit discrimination.

49

Figure 3-5: Representative gamma ray pattern observed in the study area (After Rider, 1996)

3.3 Fluid Type

The different fluid contacts were given for some of the wells. However, a quality

check was done using the resistivity and neutron-density log readings to confirm

50

the stated contents. This is based on the principle that high resistivity sands are

indicative of hydrocarbon presence while water is inferred where very low values

are recorded. Secondly, neutron and density readings are used for gas-oil or gas-

water contacts, and for discriminating between However, there are low resistivity

pay zones at deeper intervals in some wells. These are intervals characterized by

very thin sands with low resistivity values (and high GR values). It also noted that

the use of neutron-density cross-over for separating gas-oil or gas-water contacts

were unreliable at such intervals. Also, almost all the wells do not have porosity

logs so petrophysical evaluation was carried-out to re-validate the given well

markers.

51

Figure 3-6: well section across strike with marker tops, bases and fluid contacts at D-reservoirs and E-

reservoirs.

LEGEND:

Brown = D1000 and E1000 reservoirs and contactsGreen = D2000 and D3000

reservoirs and contacts

Purple =D4000 and D5000 reservoirs and contacts

52

3.4 REFLECTIVITY PATTERN ANALYSIS:

This analysis was carried-out before tying the seismic to the well in order to

validate the amplitude conformance on structure, infer the continuity of events

and lateral extent.

This was carried-out with wells that have density and sonic logs in order to

generate the acoustic impedance and synthetic. 3 wells were used for this

analysis. (Well 1)

Analysis for well one:

The pattern below shows that the top of D-5000 above has a very high resistivity

and high gamma ray (an indication of radioactive sands).

53

Figure 3-7: Reflectivity analysis for well 1 @ D2000, D6000, D7000 and D8000 l

54

Figure 3-8: mapping strategy for well 1

55

Here, the correct reservoir tops is inferred from the reflectivity analysis followed

by well tie.

3.5 SEISMIC TO WELL TIE

Well tie was carried-out to connect geology observed/interpreted log data with

seismic events (i.e. correlation of formation tops and seismic reflectors). This was

done to establish/optimize mapping and DHI detection strategy. Correct and

reliable well tie adds tremendous value to seismic interpretation. Seismic wiggles

or ‘loops’ become geologic interfaces with lithologic and stratigraphic meaning.

Conversely, petrophysical and stratigraphic observations based on log data can be

analyzed at seismic scale – log interfaces and makers can be interpreted as

seismic loops.

The seismic to well calibration has been achieved using check shot data from 3

wells. Wavelet has been extracted from the seismic and convolved with the

acoustic impedance to obtain the synthetic trace along the well bore. This has

been displayed along the well path with normal polarity to match with the

seismic. These synthetics were matched with seismic and integrated with gamma-

ray log, well 6 exhibited a very good match at all the levels to about 2000ms with

about 5ms shift (figure below).

56

Figure 3-9: initial tie for well 6 showing the major hydrocarbon reservoirs

57

Figure 3-10: final well –to-seismic match for well 6 showing (reservoirs D2000, D3000, D4000 and

D7000)

The tie conforms to the general reflectivity analysis for the wells.

58

CHAPTER FOUR

4.1 GEOPHYSICAL AND PETROPHYSICAL EVALUATION AND RESULTS.

4.1.1 SEISMIC DATA LOADING, CONDITIONING AND INTERPRETATION.

Two different seismic survey data have been provided during the course of this

study work. The more recent was used and has been based on the PSDM (Pre-

stack depth migration) processed survey. This recent dataset is of better seismic

quality than the old dataset and has been used for this study. The figure below

compares the same Inline at well 6 locations between the previous seismic data

and the PSDM.

The entire dataset from the first to the last Inline as well as XY co-ordinates for

the entire survey area has been loaded into petrel database. However, to

optimize the display time and memory usage, parts of the dataset has been

cropped resulting in a more manageable Region on interest (ROI). Subsequently

the survey has been ‘’realized’’ to 8 bits from 16 bits. Realization is a process of

creating a physical copy of the seismic volume in a petrel’s internal binary. It has

not been necessary to use scaling or clipping. The seismic data set used is in the

SEG-Y format and the seismic data was loaded into Petrel data base To get the

best out of the seismic data, there is the need to use some technique to improve

on the data quality before interpretation. Improvement of the seismic data

quality is important in order to aid in fault and horizon picking. This was carried

out using the structural smoothening option under the volume attributes in

petrel. Applying smoothening will enhance the signal to noise ratio.

59

Figure 4-1: Comparison of the two seismic data received for the study

60

The PSDM data shows good reflectivity, clarity of events and fault definition

suitable for further detailed interpretation of the horizon.

Table 4-1: seismic data information

61

4.1.2 FAULTS / STRUCTURAL INTERPRETATION:

Faults and structural interpretations were carried in a Pre-stack Time Migration

Seismic data using Petrel software. The faults were interpreted in the seismic in-

lines. A 10 by 10 milliseconds pacing was used in the fault mapping while areas of

fault connections and truncations were confirmed using narrower pacing so as to

capture faults relationship; which is paramount for a realistic and reliable

structural framework building. The interpreted faults and structures include

growth faults, synthetic faults, antithetic faults, faulted anticlines, and collapsed

crest structures within the Field.

62

Figure 4-2: shows the major faults, synthetic faults and collapsed crest interpreted in the seismic

volume from the PSDM seismic volume.

63

Figure4-3: shows fault frame work building for the interpreted faults.

64

Remarks:

The 3D seismic data quality is moderate to good, showing good events continuity

and reflection termination against faults. There are some stack channels,

erosional surfaces and shale plugs in the area visible on seismic sections. These

are, however, limited and have not hindered the definition of structural style of

the D2000, D4000, D5000 and D7000 reservoirs.

Seismic variance cube were generated using 3x3 traces in a window of 250 ms to

reveal features, enhance discontinuity in the seismic data and accurately define

the structural framework of the area.

A consistent fault framework has been extracted from the seismic variance

attribute. The field is situated in the footwall wall block of a major growth fault.

65

Figure 4-4: interpretations from the new PSDM Seismic volume illustrating seismic quality and

showing the major boundary fault in the north and the display of some wells within the field. (In-line

11348)

66

4.2 HORIZON INTERPRETATION

Horizons have been picked for mapping by integrating the well marker ties on the

correlation panel with the results of the synthetic seismogram match. Consistent

with SPDC approach, the closest soft-kick maximum positive amplitudes events

have been mapped.

Figure 4-5: Seismic random line crossing the field and showing the D2000, D4000, and

D7000 horizons.

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4.2.1 D2000 HORIZON

The D2000 horizon was interpreted on a tight grid of every 8th inline and cross

line, and where necessary every 4th inline and cross line, especially in highly

faulted zones. Due to the quality of the loop corresponding to the D2000 horizon,

the grid spacing was considered to be adequate. The seismic reflector

corresponding to the D2000 level was easily identified and followed on the

seismic.

The seismic response of the reservoir is resolved as a black maximum amplitude

loop (normal SEG polarity). A seed grid of every 8th inline and cross line was

interpreted. Seeded auto-grid was used were the amplitude of the loop is well

defined.

4.2.2 D4000 HORIZON

D4000 horizon interpretation was carried out using a similar seed grid with the

D2000 horizon. The seismic response was resolved as a maximum amplitude black

loop (normal SEG polarity) which represents a change from hard to soft. The

seismic loop response of the D4000 sand in the field is determined by the acoustic

impedance contrast between the upper part of the sand and the overlying

regional shale marker.

68

4.2.3 D5000 HORIZON

The loop was easily identified and followed. Interpretation was carried out on 8x8

and the auto seeded gridding was used to fill up areas of low degree of

confidence. The loop continuity of D5000 horizon is good to fair.

4.2.4 D7000 HORIZON

The D7000 horizon has been picked as soft-kick positive maximum amplitude. It is

a good reflector with considerable reflection strength. The top of D7000 horizon

is resolved as the first strong (positive) black loop beneath the D5000 loop. Over

most of the mapped area, it is very continuous strong loop, a characteristic which

has made it useful in defining the structural and stratigraphic framework of the

field.

69

Figure 4-6: Seismic section (Inline 11268) showing interpreted D2000, D4000, D5000 and D7000

horizons and well locations.

Remarks: (Structural Uncertainty)

The quality of the seismic is moderate to good, the horizons are continuous and it

has been possible to have a good interpretation of the top D-reservoirs.

4.3 PETROPHYSICAL INTERPRETATION AND RESULTS DISCUSSION

D2.0

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The petrophysical interpretation was carried out after checking and making

possible corrections (depth matching, splicing, editing and normalization.

The petrophysical evaluation was carried out across all D reservoirs for a better

understanding of reservoir rock properties and fluid distribution. GeoFrame

package has been used to carry out the full petrophysical study. The shale volume

estimation is uncertain in the thinly laminated sand due to tools vertical

resolution limitation and well defined in the main sand intervals. The density

curve is a good porosity indicator; the combination of density neutron may be

used for porosity, shale and gas definition especially in well stable boreholes. The

shale volume within the sand beds is mainly of dispersed type and consequently

Waxman-Smiths equation has been used to determine formation water

saturation and to correct for shale effect on resistivity behavior. The D reservoirs

are mainly composed of good reservoir properties, the porosity in the clean sand

intervals ranged between 25% and more that 30%. The formation water

saturation in the hydrocarbon in the clean porous and permeable intervals is very

low ranging from 5% to 20% (reservoir D5200 for example), relative higher

formation water saturation was observed in the thin laminated sand intervals.

4.3.1 DATA AVAILABILITY/QUALITY

71

In general, the evaluated wells required at least a minimum suite of logs

(Resistivity/GR or SP, and a porosity log) in other to carry out petrophysical

evaluation; though some wells does not have the complete set of logs for the

evaluation. (View table below).

Eight wells were involved in the petrophysical study. Anomalies on resistivity

curves were observed especially between the Log normal and LN) and the Deep

Latero-log.

72

TABLE: 4-2: LIST OF AVAILABLE AND UNAVAILABLE LOGS FOR PETROPHYSICAL

EVALUATION

73

74

4.3.2 DATA PREPARATION

Data check and depth matching

Data preparation was part of a complete and full data review in all the wells from

top to bottom. The data was provided both in Ascii and LIS (DLIS) formats. The

Ascii files in most of the wells are truncated and covered only shallower intervals.

Available data was checked by comparing the behavior of similar logs (different

runs of resistivity logs- and GR) and the response of different logs to determine

data consistency and reliability mainly in front of shale and clean oil or water

bearing sands.

Special attention was paid to wash-out intervals mainly in the shallower reservoirs

of D-sands. Figure below illustrates an example of data editing, depth matching

and log normalization. Some spikes are manually edited and removed from the

density-neutron and sonic log.

In general, the wells are stable in the reservoirs (zones of interest) mainly in the

D-reservoir sands., and highly damaged in the shaly layers and the shallower

reservoirs D-sands (D2000,D3000,D4000) though was affected to some extent by

wash-out effects in some zones as can be seen from caliper log.

75

Figure 4-7: Logs, editing, depth shift and normalization, Well 2

Depth match

RT Normalization

Depth match

RT Normalization

76

Remarks:

Data normalization was performed in some of the wells to validate the logs

available.

The Deep resistivity LL9D was normalized to fit the global response of shale

and aquifer reading around 2 ohm.m.

The following formula was used for LL9D normalization:

Rt = LL9D/1.9

Where TR: Is the true formation resistivity in ohm.m

The Sonic may be used as porosity indicator with a co-efficient of

compaction equal to 0.75 using Wyllie and Rose equation.

4.3.3 EVALUATION PARAMETERS

The parameters used to complete the petrophysical evaluation include:

Shale parameters

The shale parameters were selected and adjusted for each well accordingly. The

combination of density/neutron and SP or GR was used to determine the best

possible value of shale volume The combination of Density Neutron gives

acceptable shale volume estimation for oil and water bearing zones especially in

calibrated boreholes.

77

4.4. RESERVOIR PROPERTIES ESTIMATED

4.4.1 SHALE VOLUME CALCULATION AND SHALE

DISTRIBUTION MODE

The shale volume is a key parameter in the petro-physical model and its

estimation is a very challenging task especially in case of complex reservoirs and

lack of adequate shale indicators logs.

Three shale indicators were combined in this study to estimate the shale volume

as the minimum obtained value:

- The GR log generally shows good sand discrimination in the main

distributary channels but has a poor response over the

thinly bedded sands due to limited vertical resolution. In addition

to that, the GR is less reliable in case of radioactive sands.

- The SP log differentiates permeable and no permeable zones;

hence this curve is not affected by the presence of radioactive

sands. However the resolution of the SP curve is very low

especially over the thinly laminated sands, very common in D

reservoirs. The SP curve is also affected by the contrast of RMF

and RW.

- The cross plot of Density/Neutron delineates sand shale with the

advantage of discriminating radioactive sand. However these

tools are affected by borehole conditions (wash-out and fluid

density) and also by gas and light hydrocarbon presence.

78

- The shale volume is highly defined in case of thick sand beds and

poorly defined in case of thin laminated sands.

The shale distribution made from Thomas- Steiber plot (porosity and shale

volume) in figure 4 shows a global laminar shale distribution with relative low

dispersed shale in the sand beds.

Thomas – Steiner plot is used to justify the use of Waxmas- Smits equation for SW

estimation.

79

Figure 4-8: Shale distribution type in D7 reservoir

Laminar Shale

Dispersed Shale

Laminar ShaleLaminar Shale

Dispersed Shale

80

4.4.2 POROSITY EVALUATION

The porosity estimation over the D sands reservoir was carried out using mainly

the density curve or in some cases based on the Density/Neutron cross plot.The

density curve seems to be the most adequate curve to estimate the total porosity

using the conventional equation.

However the results were used in the fluid distribution analysis.

4.4.3 HYDROCARBON SATURATIOM EVALUATION

The Waxman-Smith’s equation was used to estimate the formation water

saturation. This method compensate for the effect of shale content and

distribution in the sand based on the resistivity behavior.

The Waxman-Smith’s equation is given by the following equation’

)//1(/1**

SWQvBRwSWRt nm

Where;

Rt = True formation resistivity

SW = Total Formation water saturation

= Total porosity

B = parameter function of RW and temperature

Qv = CEC per unit of pore volume meg/ ml

81

Remark:

B and QV values are calculated from water-bearing method of Qv estimation in

preview Plus as a function of the resistivity of the formation water RW, RWB the

resistivity of the bound Water Rwb (Shale) and the temperature.

4.4.4 SATURATION HEIGHT FUNCTION

The D7.0 sand unit is composed of interbedded fine grained sand, silt and shale.

Permeability is expected to be low. The SW is relatively high within this sequence

(high capillary pressure).

A saturation height function derived for the D7.0 sand unit from logs.

Sw = 0.75 + 1/h

Where h = Height above contact

And Sw = Saturation function

82

Figure 0-1: D7000 Reservoir Sand Units

D7.0

D7.2

D7.4

D7.6

D7.8

D7.0

D7.2

D7.4

D7.6

D7.8

83

4.5 PETROPHYSICAL

4.6 RESULTS AND FLUID DISTRIBUTION

TABLE 4.4: FLUID DISTRIBUTION TABLE FOR D2000 RESERVOIR. ALL DEPTH IN FT

TVDSS

WELL GUT GDT GOC OUT ODT OWC WUT

Well 2 6590

Well 6 6540 6587

Well 7 6575 6580

Well 4 6527 65890

84

TABLE 4.5: FLUID DISTRIBUTION TABLE FOR D3000 RESERVOIR. ALL DEPTH IN FT

TVDSS

WELL GUT GDT GOC OUT ODT OWC WUT

Well 6 6623 6637

Well no

name

34,59,35

6538 6602

Well no

name

Well no

name

6618

Well 30 6588 6630

85

TABLE 4.6: FLUID DISTRIBUTION TABLE FOR D4000 RESERVOIR. ALL DEPTH IN FT

TVDSS

WELL GUT GDT GOC OUT ODT OWC WUT

Well 2 6863 6884

Well 6 6807 6870

Well 7 6858 6870

Well 4 6807 6868

Well 4 6807 6868

86

TABLE 4.7: FLUID DISTRIBUTION TABLE FOR D5000 RESERVOIR. ALL DEPTH IN FT

TVDSS

WELL GUT GDT GOC OUT ODT OWC WUT

Well 3

Well 12

Well 16 6968 6980

Well 9 7040

87

TABLE 4.8: FLUID DISTRIBUTION TABLE FOR D7000 RESERVOIR. ALL DEPTH IN FT

TVDSS

WELL GUT GDT GOC OUT ODT OWC WUT

Well 2 7552

Well 6 7399 7417

Well 7 7362 7415

Well 4 7269 7345

Where;

GUT = Gas up to

ODT = Oil down to

OUT = Oil up to

OWC = Oil water contact

GOC = Gas oil contact

88

CHAPTER FIVE

5.1 RESERVIOR GEOLOGIC INTERPRETATION, FLUID DISTRIBUTION ANALYSIS

AND RESULTS

A total 14 hydrocarbon-bearing reservoirs, labeled C1000 to G8000, have

been identified within the down-thrown block of the field. Of these

reservoirs, the D sands are volumetrically the most significant.

Reservoirs geological interpretations were made based on data from seismic

interpretation and well log analysis. The objective of this is to analyze and validate

the data for adequate reservoirs characterization and qualify the hydrocarbons in

place in the reservoirs.

The individual reservoirs and sub-units are separated by laterally extensive

shales which are predominantly marine origin.

The D sands sequence is capped by thick marine shale. The stacking pattern in the

D sands suggests a prograding pattern and overall coarsening and thickening of

the sand intervals from D9000 to the top of the D3000 and a gradual thinning and

fining from the top of D3000 to the top of the D sands. The shales in between the

D sand units are thin and grade into siltier and sandy deposits.

5.1.1 DATA AVAILABILITY AND QUALITY

5.1.2 Moderate to good quality well data and different suites of logs were made

available for the D reservoirs. All the wells and well logs data made available were

utilized in the study.

Table 5-1 describes the data available for the project.

89

TABLE 5-1: AVAILABLE DATA FOR D RESERVOIRS

Description Status Complete Quality

Petro-physical data Available Incomplete Fair

Well markers Available Complete Good

We Data, surface location &

deviation

Available Complete Good

90

5.2 RESERVOIR DESCRIPTION OF THE D-SAND

The D sand reservoir distribution, thickness and evaluation are as follows;

5.2.1 D2000 RESERVOIR DESCRIPTION

The D2000 sand is characterized by a serrated log profile and consists of

interbedded sands and thin shales organized into three distinct sedimentary

sequences as shown in Figure 5-1. The log profile suggests that the sequences

represent retrograding shore face/mouth bar sequences which are characterized

by the presence of thinly interbedded shales and sands. The overall net sand,

porosity and permeability in the D2000 sand decreases upwards. The increase in

thickness of the shale beds upwards in each sequence indicates an increasingly

distal depositional setting relative to source of sediments. If point bar deposits

were present, their lateral extent should be relatively limited in the strike

direction (west- east) which is not the case for the laterally well correlatable

sands of the D2000 sequences.

91

Figure 0-2: D2000 Reservoir Description

92

5.2.2 D2000 RESERVOIR CORRELATION

Correlation of the D sands across the field is relatively simple. Log correlation is

good and shows a general thinning and increased shaliness eastward in the field.

The well correlation panel below shows the correlation of D-2000 reservoirs across

the field (Figu5-2). Here, the correlation shows a more or less uniform thickness

across the wells for D2000.

93

Figure 5-2: Correlation of D2000 reservoirs along dip

94

An average VCL map has been generated for D2000 reservoir using log data

based average values.

Figure 5-3: D2000 Reservoir average VCL map

95

In order to assess how good the relationships between the different variables are,

cross-plotting is established. For instance, cross-plotting the volume of shale

(VCL) versus effective porosity (PIGN) has been used to QC and confirm a reverse

relationship between shaliness and porosity trends. To establish this cross-plot for

the D2000 reservoir, both raw and averaged values of well log data have been

used.A nice trend between the two variables is seen from this cross-plot.

96

Figure 5-4: PHIT-VCL cross plot for D2000 reservoir using raw log data (blue) and

log data averaged values (red) shown with the best fit line.

97

5.2.3 D3000 RESERVOIR DESCRIPTION

The stratigraphic framework of the D3000 reservoir was established in Petrel with

the aid of different correlation panels across the entire wells intersecting the

reservoir. D3000 reservoir was encountered between 6540ftss and 7060ftss. A

combination of log suites – GR/SP, Density/Neutron and Resistivity were used in

validating and re-defining the tops and bases of the sand unit.

The log profile show predominantly blocky or cleaning upwards GR trend while

the neutron density logs indicate an upward increase in sand content (figure). The

log character expressed on GR and neutron/density logs suggest a combination of

shoreface sands and distributary channel/mouthbar deposits. The overall trend

which reflects general thinning and increased shaliness southward and eastward

indicate a gradual change from proximal to distal mouth bar deposits and to

lower/middle shoreface deposits. The D3000 sands are bounded at the top and base

by distinct shale intervals which appear to have a field wide extent.

98

Figure 5-5: D3000 Réservoir Log Section

99

5.2.4 D3000 Reservoir Correlation

Figure below shows correlation panel for D3000 Reservoirs.

Figure 0-3: D3000 Reservoir Correlation For Well 6, 7 and 4

100

5.2.5 RESERVOIOR SUBDIVISION AND FLOW UNITS DEFINITION

Reservoir sub-units tops were picked primarily using GR, SP, neutron, density and

resistivity logs. Five intra-reservoir zones have been defined to delineate major

flow units within the D3000 reservoir level.

The zones consist of three major flow units separated by two thin shaly units. The

top of the zone is D3000_Top and the base of the zone is D3000_Base. The intra-

reservoir zonation defining the flow units are the D3000_1, D3000_2, D3000_3

and D3000_4 markers (Figure 5-7). The zones are ; D3000_zone1, D3000_zone2,

D3000_zone3, D3000_zone4 and D3000_zone5.

101

Figure 0-4: Correlation Panel showing D3000 Reservoir Sub-units across well 6 and 4

102

Zone 1 sand (D3000_Top to D3000_1) is characterized by a predominantly

thickening and cleaning upwards trend. It shows a good correlation across the

wells with mean gross reservoir thickness of 66.4ft.

Zone 2 (D3000_1to D3000_2) is characterized by thin but extensive intra-

reservoir shale that separates zone 1 sands from zone 3 sands. It has an average

thickness of 4.4ft.

Zone 3 sand (D3000_2-to D3000_3) shows a good correlation across the wells

with mean gross reservoir thickness of 34ft. This zone is thinner and shalier than

the other reservoir zones.

Zone 4 (D3000_3 to D3000_4) is characterized by thin laterally continues shale

that separates zone 3 sands from zone 5 sands. It has an average thickness of

4.6ft.

Zone 5 sand (D3000_4 to D3000_Base) is characterized by rapid changes in log

character as a distinct coarsening upward sequence with a sharp base can be

observed in the lower part while a fining upward sequence can be observed in the

upper part of the unit. It has a mean gross reservoir thickness of 50.2ft.

103

5.2.6 D4000 RESERVOIR DESCRIPTION

The D4000 sands can be subdivided into five correlatable sub-units, based

on the presence of shale markers (or their equivalents) between the sub-

units. The sub-units are generally fairly constant in thickness and, similar to

the overlying D2000 and D3000 units. The reservoir shows a trend of

thinning of sand beds and deterioration in reservoir quality to the

southeast. The D4000 sands are bounded at the top and base by field-wide

correlatable marine shales shows an upwards-cleaning and coarsening

trend in all the sub-units except the top most one. The thickness of the

D4000 ranges from 109 to 161ft as shown in the figure below.

104

Figure 0-5: D4000 Reservoir Description

105

5.2.7 D5000 AND 52000 RESERVOIRS DESCRIPTION

D5000 and D5200 Reservoirs

The D5000 reservoir is interpreted as highstand deposits comprising of stacked

highly serrated upward coarsening sequences, the lower sequence being shalier

than the upward sequence. The lower unit consists of interbedded fine sand, silts

and shales as shown in figure 5-9. This reservoir represents shoreface deposits.

Decrease in sand thickness is observed in the central area of the reservoir. The

D5000 reservoir ranges in thickness from 60 to 82ft.

D5200 Reservoir Description

The log character expressed in GR and neuron-density log suggests that the D5200

represents stacked distributary channel/mouthbar deposits. The D5200 reservoir

has a thickness range between 104 and 117 feet as shown below.

106

Figure 0-6: D5000 and D5200 reservoir

D5000_Top

D5000_Base

D5200_Top

D5200_Base

SSTVD

7050

7100

7150

7200

7250

7300

7350

7400

7441

70090.00 150.00GR 0.00 1.00VCL 0.0000 0.5000PIGN_00000

D5200_Top

D5200_Base

D5000_Base

D5000_Top

14 [SSTVD]

D5000_Top

D5000_Base

D5200_Top

D5200_Base

107

5.2.8 D5000 – D52000 RESERVOIR SUB-UNITS

The first zone comprises D5000_top to D5000_1. This zone comprises upward

coarsening sequence and subsequent shaling upward sequence. The unit

comprises mostly sand and minor silts. This zone is expected to have good

reservoir property. The next zone, D5000_1 to D5000_2 is mostly silty, reservoir

property is expected to be moderate in this zone. D5000_2 to D5000_3 comprises

stacked upward coarsening sequences; this implies that the base of this sequence

is silty to shaly while it’s sandy at the top. This implies better reservoir property is

expected to be low, and may constitute baffles to flow. The basal unit, D5000_4

to D5000_base also comprises upward coarsening silts that may constitute baffle

to flow.

D5200

Zone D5200-top to D5200-1 comprises clean sand with minor silts. Reservoir

property is expected to be good in this zone. Zone D52000-1 to D5200-2

comprises silts that may act as baffles to flow. Reservoir property is expected to

be poor in this zone. Zone D5200-2 to D5200- base comprises mostly clean sand

with minor silts. Reservoir property is expected to be good in the sandy interval

while silts are expected to have poor reservoir quality.

The well section below was taken to check the continuity of the D5000 and D5200

reservoir.

108

Figure 5-10: Well Correlation Panel Showing D5000 and D5200 reservoir sub-units

109

Flow unit definition

Intra-reservoir correlation was also carried out for the reservoirs to capture

variation in reservoir properties. The D5000 reservoir was defined to have five

flow zones as seen in the above figure, while the D5200 had three zones.

5.2.9 D7000 RESERVOIR DESCRIPTION

The D7000 reservoir sands have been inferred as lower shoreface marine

sand sequence inter-bedded with relatively thin shale lenses. It is composed

of three main sand reservoirs D7.2, D7.4 and D7.6 separated by shaly / silty

layers. Figure below shows the internal sub-units of D7000 reservoirs.

110

Figure 5-11: Well 7 Showing D7 reservoir Sub-units

D7.2 sand

D7.4 sand

D7.6 sand

111

The stratigraphic framework of the D7000 horizons was established in Petrel with

the aid of different correlation panels across four wells intersecting the D7000

horizon.

The intra-reservoir zonation defining the flow units in D7000 reservoirs are D7.2,

D7.3, D7.4, D7.5 and D7.6. as shown in the panel below.

112

Figure 5-12: Well Correlation panel showing D7000 Reservoir sub-units.

113

5.3 CORRELATION ANALYSIS

The stratigraphic framework of the D7000 horizons was established in Petrel and

the section is flattened on Top of D7000. The correlation of 4 wells that cuts across

D7000 is shown in the figure above.

The Gamma Ray, Effective Porosity, volume of clay (VCL) and SP logs have been

used to update the reservoir tops and intra reservoir zones were defined to delineate

the major flow units within the subject reservoirs.

The correlation study using Gamma Ray, Effective Porosity, volume of clay (VCL)

and SP logs identified 6 zones in the D7000 reservoir level. The zones consist of

three major flow units separated by two shaly units plus one shaly unit at the top.

The top of the zone is D7000_Top and the base of the zone is D7000_Base. The

intra-reservoir zonation defining the flow units are D7.2, D7.3, D7.4, D7.5 and

D7.6. (Figure below).

Figure 5-13: D7000 intra reservoir zones (N-S Cross Section)

114

The sand becomes thinner from West to East and the average gross thickness of

the reservoir ranges from 91 to 203 ft. The log signatures are serrated with bow

shape trending curves depicting aggrading system and possibly delta front

environment. There is better sand development inferred from well 2 and 6.

Flow zone definition for each reservoir is based on defined correlatable reservoir

units across the field. As previously discussed, 6 zones have been established in

the D7000 reservoir unit.

A layering scheme of approximately 2ft interval along the pillar has been adopted

in the sand units of the reservoir (D7.2 and D7.4) in order to guarantee adequate

representation of the inherent heterogeneity. A coarser layering has been applied

in the shaly zones (D7.0, D7.3 and D7.5) and in the water flooded sandy zones

(D7.6). Since only the tops of the subject reservoirs have been mapped on

seismic, proportional layering method have been applied to ensure that the infill

horizons are conformable to the respective reservoir tops. Table 5-2 below

Presents a summary of the zones and layering in each of the reservoirs while

Figure 5-14 illustrates a cross-sectional view of the layers.

115

TABLE 5-2: LAYERING INSIDE D7 ZONES

Sand unit Reservoir zone Layering Method Number of sub-layers

D7000

D7.0

Proportional

10

D7.2 30

D7.3 3

D7.4 15

D7.5 3

D7.6 6

116

Figure 5-14: Stratigraphic layers (D7000).

D7.0

D7.2

D7.3

D7.5 D7.6

D7.4

117

Figure 5-15: Well Correlation between well 2,3 and 4 showing missing reservoirs.

Here, D6000 and 7000 were missing in well 3 and may occur as aresult of faults

that cut across the well (shown in the panel above).

118

5.3 WELL CORRELATION RESULTS FOR THE D-RESERVOIRS

TABLE 5-3: WELL CORRELATION RESULT FOR WELL 1

Well Reservoir Depth (MD)

Well 1 D2000_top 6552.66

Well 1 D2000_Base 6633.50

Well 1 D3000_Top 6644.00

Well 1 D3000_Base 6799.00

Well 1 D4000_Top 6832.24

Well 1 D4000_Base 6965.10

Well 1 D5000_Top 7029.55

Well 1 D5000_Base 7117.03

Well 1 D5200_Top 7119.18

Well 1 D5200_Base 7205.97

Well 1 D7000_Top 7330.8

Well D7000_Base 7429.88

119

TABLE 5.4: WELL CORRELATION RESULT FOR WELL 2

Well Reservoir Depth (MD)

Well 2 D2000_Top 6674

Well 2 D2000_Base 6757

Well 2 D3000_Top 6766

Well 2 D3000_Base 6922

Well 2 D4000_Top 6955.03

Well 2 D4000_Base 7110.18

Well 2 D5000_Top 7178.24

Well 2 D5200_Base 7259.08

Well 2 D5200_Top 7261.72

Well 2 D5200_Base 7363.66

Well 2 D7000_Top 7471.18

Well 2 D7000_Base 7601.41

120

TABLE 5.5: WELL CORRELATION RESULT FOR WELL 4

Well Reservoir Depth (MD)

Well 4 D2000_Top 6628.00

Well 4 D2000_Base 6707.92

Well 4 D3000_Top 6718.71

Well 4 D3000_Base 6875.00

Well 4 D4000_Top 6901.00

Well 4 D4000_Base 7023.07

Well 4 D5000_Top 7102.36

Well 4 D5000_Base 7182.56

Well 4 D5200_Top 7184.54

Well 4 D5200_Base 7272.96

Well 4 D7000_Top 7400.82

Well 4 D7000_Base 7493.77

121

TABLE 5.6: WELL CORRELATION RESULT FOR WELL 6

Well Reservoir Depth (MD)

Well 6 D2000_Top 6630.00

Well 6 D2000_Base 6712.00

Well 6 D3000_Top 6721.00

Well 6 D3000_Base 6870.00

Well 6 D4000_Top 6896.00

Well 6 D4000_Base 7040.31

Well 6 D5000_Top 7113.33

Well 6 D5000_Base 7190.78

Well 6 D5200_Top 7193.13

Well 6 D5200_Base 7270.30

Well 6 D7000_Top 7389.25

Well 6 D7000_Base 7493.23

122

TABLE 5.7: WELL CORRELATION RESULT FOR WELL 7

Well Reservoir Depth (MD)

Well 7 D2000_Top 6666.00

Well 7 D2000_Base 6746.00

Well 7 D3000_Top 6760.00

Well 7 D3000_Base 6927.13

Well 7 D4000_Top 6951.00

Well 7 D4000_Base 7088.89

Well 7 D5000_Top 7165.34

Well 7 D5000_Base 7251.75

Well 7 D5200_Top 7254.50

Well 7 D5200_Base 7336.58

Well 7 D7000_Top 7477.88

Well 7 D7000_Base 7580.51

123

TABLE 5.8: WELL CORRELATION RESULT FOR WELL 9

Well Reservoir Depth (MD)

Well 9 D2000_Top 6897.88

Well 9 D2000_Base 6982.00

Well 9 D3000_Top 6995.00

Well 9 D3000_Base 7146.50

Well 9 D4000_Top 7176.00

Well 9 D4000_Base 7328.26

Well 9 D5000_Top 7406.93

Well 9 D5000_Base 7478.41

Well 9 D5200_Top 7481.34

Well 9 D5200_Base 7558.89

Well 9 D7000_Top 7680.61

124

TABLE 5.9: WELL CORRELATION RESULT FOR WELL 12

Well Reservoir Depth (MD)

Well 12 D2000_Top 7033.00

Well 12 D2000_Base 7123.00

Well 12 D3000_Top 7138.00

Well 12 D3000_Base 7316.00

Well 12 D4000_Top 7346.54

Well 12 D4000_Base 7514.73

Well 12 D5000_Top 7591.91

Well 12 D5000_Base 7691.67

Well 12 D5200_Top 7693.85

Well 12 D5200_Base 7799.34

Well 12 D7000_Top 7936.49

Well 12 D7000_Base 8071.67

125

TABLE 5.10: WELL CORRELATION RESULT FOR WELL 15

Well Reservoir Depth (MD)

Well 15 D3000_Top 6690

Well 15 D3000_Base 6828

126

TABLE 5.11: WELL CORRELATION RESULT FOR WELL 16

Well Reservoir Depth (MD)

Well 16 D2000_Top 6977.00

Well 16 D2000_Base 7064.00

Well 16 D3000_Top 7071.00

Well 16 D3000_Base 7248.00

Well 16 D4000_Top 7277.79

Well 16 D4000_Base 7423.08

Well 16 D5000_Top 7500.25

Well 16 D5000_Base 7585.80

Well 16 D5200_Top 7598.65

Well 16 D5200_Base 7684.14

Well 16 D7000_Top 7821.65

Well 16 D7000-Base 7927.72

127

5.5. FACIES AND PROPERTY EVALUATION

A proper representation of the dynamic behavior within a geological model

requires a consistent distribution of properties in the 3-D model. This was

achieved in this study by dividing the subject reservoirs into different rock types.

Rock types have been defined on geological concepts and validated against

reservoir correlation.

Using the effective porosity (PIGN) vs. volume of clay (VCL) cross plot, 3

different rock types have been identified (Fig. ). These rock types are: Sand,

Laminated Sand and Shale.

Table below also shows the cut-off for the different facies.

128

Figure 5-17 Porosity vs. VCL Cross plot

129

Table 5-12 Reservoir cut-off for the various rock types

Property modeling is the process of populating the grid cells with either discrete

property using the Sequential Indicator Simulation (SIS) or continuous property

using the Sequential Gaussian Simulation (SGS).

The properties that have been populated in the 3D static model include: porosity,

permeability, water saturation and net-to-gross.

The effective porosity logs for the wells that penetrated the reservoir were upscaled

into their respective 3-D grid cells. In both the subject reservoirs, the distribution

trends before and after the upscale are similar and this validates the averaging

techniques applied in the upscale process. The up-scaled porosity is consistent with

the well log data (Figure 5-18).

Reservoir Rock type definition Code Rock type description

D7000

VCL60.0 2 Shale

60.020.0 VCL 1 Laminated Sand

20.0VCL 0 sand

130

Figure 5-18: Histogram porosity distribution plots for upscale logs (green bars) and raw logs

(red bars)

131

The SGS algorithms have been used to populate the reservoir model with 3-D

porosity property. The resulting distribution shows a deteriorating

reservoir property towards the East as you transverse from the West to

the East suggesting probably enhanced sediment sorting towards the

West of the structure due to high energy of deposition which reduces

away from it. (figure 5-19).The view is in North direction.

Figure 5-19: W-E cross section of the 3D porosity property distribution

W E

W E

132

5.7 FLUID DISTRIBUTION ANALYSIS

The long transition zone presented by the ratty lower sand member of the sand

poses a significant uncertainty in defining the actual OWC in some wells. Observe

in figure 5-20 that the resistivity response grades downward with depth. In well 6,

the resistivity of ~ 600 ohm-m was considered to be water response. If the same

interpretation is applied here, then OWC should be at 7384 ftss. This poses a

significant fluid-in-place uncertainty. This analysis was carried-out in order to re-

evaluate the given reservoir marker and adjust some markers that does not conform

to the analysis. In performing this analysis, more hydrocarbon bearing intervals has

been evaluated.

133

Figure 5-20: Type log (well 6) of the D7000 reservoir shows that the lower sand

member is poorly developed and has high water saturation exhibiting a lower

resistivity response than the upper member.

134

CHAPTER SIX

6.0 SUMMARY

A detailed study of the reservoir sands located in (situated in OML 24) the coastal

swamp depo-belt of the Cenozoic Niger Delta revealed a total of 16 major

hydrocarbon bearing reservoirs and the D reservoirs are volumetrically the most

significant of these hydrocarbon bearing reservoirs. Here, an integrated approach

which includes; seismic interpretation, well correlation of the D reservoirs across

the wells in the field, petrophysical evaluation and fluid distribution analysis was

carried out.

In summary, the general analysis carried-out in the study area to better

understand the “D reservoir sand” and major flow units are summarized as

follows;

I. Geophysics- four horizons D2000, D4000, D5000 and D7000

interpreted (which are the major hydrocarbon bearing intervals).

II. The stratigraphic correlation and environments of deposition were

obtained based on available data from well logs, biofacies (P and F

zones) and core data. From this, five stratigraphic makers were

mapped. These include the 9.5Ma MFS (the Afam Clay); 10.35Ma SB,

10.4Ma MFS (Uvigerina-8) the 10.6Ma SB (which marks the base of

the continental, Benin Formation) and 11.5 Ma MFS.

135

III. Petrophysical evaluation was carried out across all D- Reservoirs using

the schlumberger Geo-Frame package. Interpretation was carried out

after some editing and corrections (depth matching, splicing, editing

and normalization) were done on the data to better refined and

establish the reservoir tops and major flow units. Here, the major

reservoirs of interest lie within the 10.35 SB.

The following analysis has also been performed:

Performed Fluid identification and contacts using density, neutron, and

sometimes sonic and resistivity logs to identify hydrocarbon reservoirs

and wet sands in the area.

Developed porosity model based on fluid types using density, neutron

and sonic logs.

The shale volume estimation was perfumed (though is uncertain in the

thinly laminated sand due to tools vertical resolution limitation and well

defined in the main sand intervals).

Hydrocarbon saturation evaluation was done using Waxman-Smiths’

models.

Developed saturation height function for the D7000 reservoir from logs.

136

6.2 CONCLUSION

Results from detailed reservoir evaluation, well to seismic tie, reflectivity analysis

helps in understanding the major flow units within these reservoir and associated

seismic attributes to constrain validation of subsequent hydrocarbon bearing

intervals and reservoir characterization. Without applying the right petro-physical

evaluation method for identifying and analysing the sands, there is high possibility

of underestimating the final hydrocarbon reserve. Thus; the net to gross, porosity

and saturation would be erroneously calculate. The perfumed fluid distribution

analysis helps in re-validating the reservoir markers and more hydrocarbon

bearing intervals has been established.

137

RECOMMENDATION

The following recommendations are proposed to improve the understanding and

evaluation of study of the radioactive sands and to ensure proper reserve

estimation:

(1) To avoid underestimation of reserve during prospect evaluation, it is

recommended that the geophysical processing be improved as regards

integrating the right velocity modeling for better results.

(2) Proper petro-physical log data should be obtained during and after

drilling so as to properly evaluate the petro-physical parameters, and

hence obtain the accurate net to gross and final reserve.

(3) Good quality data is required for quantitative interpretation and to

ascertain the results from fluid distribution analysis.

138

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Nomenclature

Porosity(-)

GDT Gas-down-to (ft)

GIIP Gas-initially-in-place (Bscf)

GOC Gas Oil contact (ft)

GOR Gas Oil Radio (Mscf/stb)

GRV Gross rock volume (acre ft)

GWC Gas-water contact (ft)

HM History-match

H,z Height (ft)

144

K

M Permeability (mD)

Cementation factor (-)

n Viscosity (cp)

n/a Saturation exponent (-)

Not applicable or Not available

ODT

OIIP Oil-down-to (ft)

OUT Oil-initially-in-place (MMstb)

OWC Oil-up-to (ft)

r Oil-water contact (ft)

R Radius (ft)

Ry Resistivity (m)

Region y (where X = 1,2,3,4 or 5)

Q

S Rate (bpd, MMscf/d)

T Saturation (-)

145

Temperature (0F)

Transmissibility (bpd/cp/psi)

WUT Water-up-to (ft)