Research Article | | Peer-Reviewed

Reservoir Characterization of KD Field Located Onshore of Akwa-Ibom State, Niger Delta, Nigeria Using Well Logs Property Comparison to Seismic Amplitude Analysis

Received: 7 February 2024     Accepted: 29 February 2024     Published: 17 April 2024
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Abstract

Characterization of reservoirs defines how well they can generate and store hydrocarbon, reservoir parameters are used to determine the behavior of reservoir fluids under various conditions and to identify the best production practices that can optimize hydrocarbon production, the objective is to identify and map reservoir sand zones using basic logs, provide information about the reservoir depth and thickness using well log data, interpret faults and sealing system using the seismic data and generate amplitude maps and model basic reservoir facies, the method applied was sectioned into three distinct parts that encompasses qualitative well log analysis, seismic interpretation and cross plotting of basic well logs versus amplitude for reservoir characterization, the well data analyzed shows well number 5, 6 and 8 have incomplete GR logs resulting in missing lithology while well 10 have some missing logs, such as, density (DEN) log, neutron porosity (NEU) log and porosity (POR) log, five logs needed for this study were available in the remaining complete wells. These logs include gamma ray (GR) log, resistivity (RES) log, density (DEN) log, neutron porosity (NEU) log, and porosity (POR) log. This study looks at a possible change in log signal due to an increase or decrease in seismic amplitude in characterizing a reservoir sand and how logs are influence with Amplitude peaks and trough.

Published in International Journal of Oil, Gas and Coal Engineering (Volume 12, Issue 2)
DOI 10.11648/j.ogce.20241202.12
Page(s) 57-62
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Reservoir, Seismic Interpretation, Well Logs, Hydrocarbon

1. Introduction
Reservoir characterization is the process of assessing a reservoir's capacity to produce and hold hydrocarbons . Reservoir characteristics are utilized to ascertain how reservoir fluids behave under different circumstances and to pinpoint the most effective production techniques for maximizing hydrocarbon output . Characterizing the reservoir is the first step towards quantifying reservoirs with a lower risk of uncertainty, which is connected to geological models of various exploration and production of interest . Applications of well-log measurements include the evaluation of the porosity and saturation of reservoir rocks as well as depth correlations .
The need of log information records for a thorough understanding of geology is becoming increasingly apparent. In fact, geologists have discovered that well logs may be to rocks what optical and geological devices are to surface outcrop . Through logging, we recorded several parameters related to the petrophysical and geological properties of the accessible strata; these properties are usually studied with the use of rock samples . Moreover, logs display the fluids found in the pores of reservoir rocks (Hampson & Russell, 2012). The distinct picture that logs offer is sometimes distorted or lacking, but it is always permanent, unwavering, and unbiased .
As a consequence of the physical, chemical, and biological circumstances that existed during deposition as well as the evolution of the rock throughout geological time, the morphological traits represented by log data are comparable to the "signature" of the rock .
2. Study Area
In the Nigerian Niger Delta's Akwa-Ibom State, the field is known as KR field. It is in the southern section of OML 138, around 55 kilometers south of Abia. It is located in the Niger Delta depobelt's coastal marsh region (Figure 1). Numerous writers have written on the well-known Niger Delta's geology
Figure 1. Map of Niger Delta showing the study area.
The Niger Delta clastic wedge originated about the late Jurassic plate fracturing of South America and Africa, and it developed within a futile sector of an aulacogen triple linked system

2.1. Aim and Objectives of the Study

This research is aimed at comparatively analyzing log properties and seismic amplitudes to provide a more reasonable and dependable data for reservoir characterization. The objectives are to identify lithology and thickness of rock strata using well logs data, identify and Map reservoir sand zones using basic logs, provide information about the reservoir depth and thickness using well log data, interpret Faults and sealing systems using the seismic data, generate amplitude maps and model basic reservoir facies, and cross-plot well logs with seismic amplitude to provide reservoir characteristics.

2.2. Significance of the Study

In order to support well management and reservoir monitoring, the data from this study can be used to enhance research on reservoir features. Furthermore, this study will help eliminate false log responses caused by changes in temperature, pore fluid concentration and lithology contrast.
3. Methodology
The method applied in this research encompasses three distinct separate sections. The first section covers qualitative well-log analysis, also known as petrophysical analysis. Identifying the reservoir's top and base as well as delineating its lithology are the main objectives of the qualitative study. The second half of the study focuses on seismic interpretation, which involves facie modeling and the third section of this research project consists of cross-plots of basic well logs vs. amplitude for reservoir characterisation.
In this research, the sources of data were obtained from Total Energies EP Nigeria Limited which consist a set of well information and 3D post-stack seismic volume acquired from the Niger Delta. Total Energies EP Nigeria Limited also known as TEPNG is a subsidiary of Total Energies France which is an integrated energy company with its headquarters in Courbevoie, France, near Paris. More than 100,000 workers from various nations make up the company. The Data set consists of Ten (10) wells that cut across the Agbada formation and four (4) of the wells have incomplete information needed for this study. The well log suites consist of gamma ray log (GR), Resistivity (RES), Porosity (POR), Neutron (NEU) and Density (DEN) logs. The seismic volume comprises of in-lines ranging from 100 and 1600, X-lines (crosslines) 110 and 800. Then, certain software such as Word, Excel and Petrel 2014 version are used. Petrel is an open-source seismic determination system that is licenced from Schlumberger and can be used to visualize analyse, and interpret 2D, 3D, and 4D seismic data. For the interpretation of Geo-Radar, it is also widely used. All of the tools you would expect to find in a seismic interpretation system are supported by Petrel, including but not limited to: cross-plots, log viewers, well-tie module, Time-Depth Conversion, 3D bodies, Mapping (via GMT), modelling, and more. Horizon trackers (auto-tracking, manual, gridding, etc.) and fault interpretation (sticks and planes) are also supported.
4. Results and Discussion
From the results analyzed, Seismic data from KR Field, South-South, Niger Delta, reveals an intense amplitude horizon in the Agbada formation. Every well that was interpreted reached the reservoir's top.

4.1. Well Data

A total number of 10 Well data (Table 1) were provided for this research work From the data provided, well numbers 5, 6, and 8 have incomplete GR logs resulting in missing lithology while well 10 have some missing logs; density (DEN) log, neutron porosity (NEU) log, and porosity (POR) log. Five logs needed for this study were available in the remaining complete wells. These logs include gamma ray (GR) log, resistivity (RES) log, density (DEN) log, neutron porosity (NEU) log, and porosity (POR) log.

4.2. Petrophysical Evaluation

Qualitative Interpretation
The typical well log responses for all ten wells named KR-1, KR-2, KR-3, KR-4, KR-5, KR-6, KR-7, KR-8, KR-9 and KR-10 in discrimination of lithology and formation boundary is displayed in Figure 2 & 3 and discussed below.
Table 1. Summary of Results of well log Analysis of KR wells for zone 1 – 3.
The typical well log responses for all ten wells named KR-1, KR-2, KR-3, KR-4, KR-5, KR-6, KR-7, KR-8, KR-9 and KR-10 in discrimination of lithology and formation boundary is displayed in Figure 2 & 3 and discussed below.
Resistivity log play an important role in identifying a reservoir rock. In this study, the ten wells were correlated from north to south and the resistivity log of KR wells are displayed on track 3 alongside the Gamma ray log to identify lithology and sand zones.
One reservoir unit labelled HRA was identified at depths ranging from 3625 – 4700 m across all wells. Reservoir HRA consist of five (5) smaller zones that occurred in a paralic sequence. In well KR-1, Reservoir zone 1 consists of Shale unit and it was identified at a depths of 3575 – 3676 m with thickness of 101 m. Reservoir zone 2 consists of Shale unit and it was identified at a depths of 3676 – 3802 m with thickness of 126 m.
Table 2. Summary of Results of well log Analysis of KR wells for zone 4 – 5.

Zones

4

5

Depth (m)

Thickness

Lithology

Depth (m)

Thickness

Lithology

Top

Base

Top

Base

KR-1

4000

4151

151

Sandstone

4151

4325

174

Clean sand

KR-2

3899

3975

76

Clean

3975

4100

125

Clean sand

sand

KR-3

4000

4150

150

Sandstone

4150

4300

150

Clean sand

KR-4

3910

4010

100

Clean

4010

4125

115

Sandstone

sand

KR-5

-

-

-

NA

-

-

-

NA

KR-6

-

-

-

NA

-

-

-

NA

KR-7

4110

4290

180

Sandstone

4290

4410

120

Sandstone

KR-8

-

-

-

NA

-

-

-

NA

KR-9

3950

4175

225

Sandstone

4175

4362

187

Sandstone

KR-10

4200

4375

175

Clean

4375

4550

175

Clean sand

Sand

Reservoir zone 3 consists of Sand stone unit and it was identified at a depths of 3802 – 4000 m with thickness of 198 m. Reservoir zone 4 also consists of Sand stone unit and it was identified at a depths of 4000 – 4151 m with thickness of 151 m. Reservoir zone 5 consists of clean sand unit and it was identified at a depths of 4151 – 4325 m with thickness of 174 m.
In well KR-2, Reservoir zone 1 consists of Sand Stone unit and it was identified at a depths of 3575 – 3699 m with thickness of 124 m. Reservoir zone 2 consists of Shale unit and it was identified at a depths of 3699 – 3803 m with thickness of 104 m. Reservoir zone 3 consists of Shale unit and it was identified at a depths of 3803 – 3899 m with thickness of 96 m. Reservoir zone 4 also consists of Clean Sand unit and it was identified at a depths of 3899 – 3975 m with thickness of 76 m. Reservoir zone 5 consists of clean sand unit and it was identified at a depths of 3975 – 4100 m with thickness of 125 m.
Figure 2. Correlation of KR wells from north to south.
Figure 3. Correlation of KR wells from north to south cont’d.
5. Conclusions
Accurate evaluation of the formation is essential to access the economic viability of reservoir wells in the Niger Delta oilfield. Reflection amplitude plays a vital role in reservoir characterization and its importance cannot be over-emphasized. Over the Years, reservoir characterization has taken diverse forms and shapes and each result has proven to be very effective. Using an innovative method, this study has effectively evaluated and characterised reservoir sand. The data showed some trends, but the majority of cross plots showed only a broad trend and weak correlation.
Abbreviations
OML: Oil Mining Lease
GR: Gamma Ray Log
RES: Resistivity
POR: Porosity
NEU: Neutron
DEN: Density Logs
KR: Oil Field or Well
Acknowledgments
I want to sincerely appreciate all the lecturers and students in the department of geology, Niger Delta University for their endless encouragement and support throughout this programme.
Conflicts of Interest
The authors declare no conflict of interest.
References
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    Oborie, E., Adimie, E. O., Macdonald, I. (2024). Reservoir Characterization of KD Field Located Onshore of Akwa-Ibom State, Niger Delta, Nigeria Using Well Logs Property Comparison to Seismic Amplitude Analysis. International Journal of Oil, Gas and Coal Engineering, 12(2), 57-62. https://doi.org/10.11648/j.ogce.20241202.12

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    Oborie, E.; Adimie, E. O.; Macdonald, I. Reservoir Characterization of KD Field Located Onshore of Akwa-Ibom State, Niger Delta, Nigeria Using Well Logs Property Comparison to Seismic Amplitude Analysis. Int. J. Oil Gas Coal Eng. 2024, 12(2), 57-62. doi: 10.11648/j.ogce.20241202.12

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    AMA Style

    Oborie E, Adimie EO, Macdonald I. Reservoir Characterization of KD Field Located Onshore of Akwa-Ibom State, Niger Delta, Nigeria Using Well Logs Property Comparison to Seismic Amplitude Analysis. Int J Oil Gas Coal Eng. 2024;12(2):57-62. doi: 10.11648/j.ogce.20241202.12

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  • @article{10.11648/j.ogce.20241202.12,
      author = {Ebiegberi Oborie and Elvis Ogede Adimie and Indighe Macdonald},
      title = {Reservoir Characterization of KD Field Located Onshore of Akwa-Ibom State, Niger Delta, Nigeria Using Well Logs Property Comparison to Seismic Amplitude Analysis
    },
      journal = {International Journal of Oil, Gas and Coal Engineering},
      volume = {12},
      number = {2},
      pages = {57-62},
      doi = {10.11648/j.ogce.20241202.12},
      url = {https://doi.org/10.11648/j.ogce.20241202.12},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ogce.20241202.12},
      abstract = {Characterization of reservoirs defines how well they can generate and store hydrocarbon, reservoir parameters are used to determine the behavior of reservoir fluids under various conditions and to identify the best production practices that can optimize hydrocarbon production, the objective is to identify and map reservoir sand zones using basic logs, provide information about the reservoir depth and thickness using well log data, interpret faults and sealing system using the seismic data and generate amplitude maps and model basic reservoir facies, the method applied was sectioned into three distinct parts that encompasses qualitative well log analysis, seismic interpretation and cross plotting of basic well logs versus amplitude for reservoir characterization, the well data analyzed shows well number 5, 6 and 8 have incomplete GR logs resulting in missing lithology while well 10 have some missing logs, such as, density (DEN) log, neutron porosity (NEU) log and porosity (POR) log, five logs needed for this study were available in the remaining complete wells. These logs include gamma ray (GR) log, resistivity (RES) log, density (DEN) log, neutron porosity (NEU) log, and porosity (POR) log. This study looks at a possible change in log signal due to an increase or decrease in seismic amplitude in characterizing a reservoir sand and how logs are influence with Amplitude peaks and trough.
    },
     year = {2024}
    }
    

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    T1  - Reservoir Characterization of KD Field Located Onshore of Akwa-Ibom State, Niger Delta, Nigeria Using Well Logs Property Comparison to Seismic Amplitude Analysis
    
    AU  - Ebiegberi Oborie
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    JF  - International Journal of Oil, Gas and Coal Engineering
    JO  - International Journal of Oil, Gas and Coal Engineering
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    PB  - Science Publishing Group
    SN  - 2376-7677
    UR  - https://doi.org/10.11648/j.ogce.20241202.12
    AB  - Characterization of reservoirs defines how well they can generate and store hydrocarbon, reservoir parameters are used to determine the behavior of reservoir fluids under various conditions and to identify the best production practices that can optimize hydrocarbon production, the objective is to identify and map reservoir sand zones using basic logs, provide information about the reservoir depth and thickness using well log data, interpret faults and sealing system using the seismic data and generate amplitude maps and model basic reservoir facies, the method applied was sectioned into three distinct parts that encompasses qualitative well log analysis, seismic interpretation and cross plotting of basic well logs versus amplitude for reservoir characterization, the well data analyzed shows well number 5, 6 and 8 have incomplete GR logs resulting in missing lithology while well 10 have some missing logs, such as, density (DEN) log, neutron porosity (NEU) log and porosity (POR) log, five logs needed for this study were available in the remaining complete wells. These logs include gamma ray (GR) log, resistivity (RES) log, density (DEN) log, neutron porosity (NEU) log, and porosity (POR) log. This study looks at a possible change in log signal due to an increase or decrease in seismic amplitude in characterizing a reservoir sand and how logs are influence with Amplitude peaks and trough.
    
    VL  - 12
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