Skip to main content
SpringerLink
Log in

Static Reservoir Modeling of the Eocene Clastic Reservoirs in the Q-Field, Niger Delta, Nigeria

  • Original Paper
  • Published:
Natural Resources Research Aims and scope Submit manuscript

Abstract

This work integrates seismic and well log data to establish a 3D reservoir model of the Q-Field, which is a prolific onshore hydrocarbon field situated in the Central Swamp Depobelt of Nigeria. The subsurface modeling focuses on the four principal clastic reservoir intervals of the Agbada Formation (D6200, D7000, D9000 and E2000), which was deposited in a deltaic to fluvio-deltaic system during Eocene. The seismic-based structural modeling inferred an extensional set-up dominated by NW–SE trending normal faults. Reservoirs are sand-dominated and laterally extensive, as interpreted from the 3D facies model. Well log-based petrophysical parameters were up-scaled and distributed stochastically using the Sequential Gaussian Simulation method to generate a 3D reservoir property model. Lateral and vertical heterogeneities of the reservoir properties were inferred from the 3D models. In general, the clastic reservoirs exhibit 18–22% porosity, 62–105 mD permeability, moderate to good net-gross thickness, and 36–74% water saturation. Hydrocarbon accumulation was primarily restricted within the anticlines. Gas-down-to exists in the upper three reservoirs (D6200, D7000 and D9000) at 10,577 ft (1 ft = 0.3048 m), 10,756 ft and 11,389 ft, respectively. Gas–oil and oil–water contacts in the E2000 reservoir were interpreted to be at 11,812 ft and 11,886 ft, respectively. Based on the hydrocarbon distribution, oil and gas-in-place volumes were estimated for all the reservoir intervals. The comprehensive 3D modeling work addressed the spatial distribution of the studied reservoir properties and can be directly useful for planning better the future wells for field development.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
Figure 7
Figure 8
Figure 9
Figure 10
Figure 11
Figure 12
Figure 13
Figure 14
Figure 15

Similar content being viewed by others

References

  • Abdel-Fattah, M., & Alrefaee, H. (2014). Diacritical seismic signatures for complex geological structures: Case studies from Shushan Basin (Egypt) and Arkoma Basin (USA). International Journal of Geophysics. https://doi.org/10.1155/2014/876180.

    Article  Google Scholar 

  • Abdel-Fattah, M., Dominik, W., Shendi, E., Gadallah, M., & Rashed, M. (2010). 3D integrated reservoir modelling for Upper Safa Gas Development in Obaiyed Field, Western Desert, Egypt. In 72nd EAGE Conference and Exhibition Incorporating SPE EUROPEC, Spain, June 2010. https://doi.org/10.3997/2214-4609.201401358

  • Abdel-Fattah, M., Gameel, M., Awad, S., & Ismaila, A. (2015). Seismic interpretation of the Aptian Alamein dolomite in the Razzak oil field, Western Desert, Egypt. Arabian Journal of Geosciences, 8(7), 4669–4684.

    Article  Google Scholar 

  • Abdel-Fattah, M. I., Metwalli, F. I., & El Sayed, I. M. (2018). Static reservoir modeling of the Bahariya reservoirs for the oilfields development in South Umbarka area, Western Desert, Egypt. Journal of African Earth Sciences, 138, 1–13.

    Article  Google Scholar 

  • Abdel-Fattah, M. I., & Tawfik, A. Y. (2015). 3D geometric modeling of the Abu Madi reservoirs and its implication on the gas development in Baltim area (Offshore Nile Delta, Egypt). International Journal of Geophysics. https://doi.org/10.1155/2015/369143

  • Adagunodo, T. A., Sunmonu, L. A., Adabanija, M. A., Oladejo, O. P., & Adenji, A. A. (2017). Analysis of fault zones for reservoir modeling in Taa field, Niger Delta, Nigeria. Petroleum and Coal, 59(3), 378–388.

    Google Scholar 

  • Adelu, A. O., Aderemi, A. A., Akanij, A. O., Sanuade, O. A., Kaka, S. I., Afolabi, O., et al. (2019). Application of 3D static modeling for optimal reservoir characterization. Journal of African Earth Sciences, 152, 184–196.

    Article  Google Scholar 

  • Adeoti, L., Onyekachi, N., Olatinsu, O., Fatoba, J., & Bello, M. (2014). Static reservoir modeling using well log and 3-D seismic data in a KN Field, Offshore Niger Delta, Nigeria. International Journal of Geosciences, 5, 93–106.

    Article  Google Scholar 

  • Adesoji, O. A., Oluseun, A. S., SanLinn, I. K., & Isaac, D. B. (2018). Integration of 3D seismic and well log data for the exploration of Kini Field, Offshore Niger Delta. Petroleum and Coal, 60(4), 752–761.

    Google Scholar 

  • Adiela, U. P. (2018). Reservoir modeling using seismic attributes and well log analysis: A Case study of Niger Delta, Nigeria. In: AAPG International Conference and Exhibition, Cape Town, South Africa, Nov 4–11. AAPG Search and Discovery Article # 90332

  • Agbasi, O. E., Igboekwe, M. U., Chukwu, G. U., & Sunday, E. E. (2018). Discrimination of pore fluid and lithology of a well in X Field, Niger Delta, Nigeria. Arabian Journal of Geosciences, 11, 274. https://doi.org/10.1007/s12517-018-3610-7.

    Article  Google Scholar 

  • Agbasi, O. E., Sen, S., Inyang, N. J., & Etuk, S. E. (2020). Assessment of pore pressure, wellbore failure and reservoir stability in the Gabo field, Niger Delta, Nigeria-implications for drilling and reservoir management. Journal of African Earth Sciences, 173, 104038.

    Article  Google Scholar 

  • Ahmed, H., Nyeche, M., Engel, S., Nworie, E., & De Mooij, H. (2011). 3D reservoir simulation of X field onshore Niger Delta, Nigeria: The power of multiple iterations. In: SPE Nigeria International Conference and Exhibition, Abuja, Nigeria, July 30–Aug 3. SPE-150730-MS. https://doi.org/10.2118/150730-MS

  • Aigbadon, G. O., Okoro, A. U., Una, C. O., & Ocheli, A. (2017). Depositional facies model and reservoir characterization of USANI field 1, Niger Delta Basin, Nigeria. International Journal of Advanced Geosciences, 5(2), 57–68.

    Article  Google Scholar 

  • Alao, P. A., Olabode, S. O., & Opeloye, S. A. (2013). Integration of seismic and petrophysics to characterize reservoirs in ‘“ALA”’ Oil Field, Niger Delta. The Scientific World Journal. https://doi.org/10.1155/2013/421720.

    Article  Google Scholar 

  • Ali, M., Abdelhady, A., Abdelmaksoud, A., Darwish, M., & Essa, M. A. (2020). 3D Static modeling and petrographic aspects of the Albian/Cenomanian Reservoir, Komombo Basin, Upper Egypt. Natural Resources Research, 29, 1259–1281.

    Article  Google Scholar 

  • Burke, K. (1972). Longshore drift, submarine canyons, and submarine fans in development of Niger Delta. American Association of Petroleum Geologists, 56, 1975–1983.

    Google Scholar 

  • Deutsch, C. V., & Journel, A. G. (1998). Geostatistical software library (GSLIB) (2nd ed., p. 369). Oxford: Oxford University Press.

    Google Scholar 

  • Doust, H., & Omatsola, E. (1990). Niger Delta. In: Edwards, J.D., Santogrossi, P.A. (eds.) Divergent/passive margin basins (vol. 48, pp. 239–248). AAPG Memoir.

  • Edwin, E. V., Jose, L. P., Carlos, A. M., & María, C. H. (2011). High resolution stratigraphic controls on rock properties distribution and fluid flow pathways in reservoir rocks of the Upper Caballos Formation, San Francisco Field, Upper Magdalena Valley, Colombia. In South American Oil and Gas Congress, SPE Western Venezuela Section, Maracaibo, Venezuela, Oct 18–21. SPE WVS 095.

  • Egbe, T., Ugwu, S. A., & Ideozu, R. U. (2019). Reservoir characterization of Buma Field Reservoirs, Niger Delta using Seismic and Well Log Data. Petroleum and Chemical Industry International, 2(4), 1–11.

    Google Scholar 

  • Ejedavwe, J., Fatumbi, A., Ladipo, K., & Stone, K. (2002). Pan—Nigeria exploration well look—back (Post-Drill Well Analysis). Shell Petroleum Development Company of Nigeria Exploration Report 2002.

  • Farouk, I. M., El-Arabi, H. S., & Mohamed, S. F. (2017). Reservoir petrophysical modeling and risk analysis in reserve estimation: A Case Study from Qasr Field, North Western Desert, Egypt. Journal of Applied Geology and Geophysics (IOSR-JAGG), 5(2), 41–52.

    Article  Google Scholar 

  • Geboy, N. J., Olea, R. A., Engle, M. A., & Martín-Fernández, J. A. (2013). Using simulated maps to interpret the geochemistry, formation and quality of the blue gem coal bed, Kentucky, USA. International Journal of Coal Geology, 112, 26–35.

    Article  Google Scholar 

  • Godwill, P. A., & Waburoko, J. (2016). Application of 3D reservoir modeling on Zao 21 Oil Block of Zilaitun Oil Field. Journal of Petroleum Environmental and Biotechnology, 7, 262. https://doi.org/10.4172/2157-7463.1000262.

    Article  Google Scholar 

  • Haque, A. K. M. E., Islam, M. A., & Shalaby, M. R. (2016). Structural modeling of the Maui Gas Field, Taranaki Basin, New Zealand. Petroleum Exploration Development, 43(6), 883–892.

    Article  Google Scholar 

  • Inyang, N. J., Akpabio, O. I., & Agbasi, O. E. (2018). Shale volume and permeability of the Miocene unconsolidated Turbidite sand of Bonga Oil Field, Niger Delta, Nigeria. International Journal of Advanced Geoscience, 5(1), 37–45.

    Google Scholar 

  • Ismail, A., Raza, A., Gholami, R., & Reza, R. (2020). Reservoir characterization for sweet spot detection using color transformation overlay scheme. Journal of Petroleum Exploration and Production Technology, 10, 2313–2334.

    Article  Google Scholar 

  • Jika, H. T., Onuoha, K. M., & Dim, C. I. P. (2019). Application of geostatistics in facies modeling of Reservoir-E, “Hatch Field” offshore Niger Delta Basin, Nigeria. Journal of Petroleum Exploration and Production Technology, 10, 769–781.

    Article  Google Scholar 

  • Jika, H. T., Onuoha, M. K., Okeugo, C. G., & Eze, M. O. (2020). Application of sequential indicator simulation, sequential Gaussian simulation and flow zone indicator in reservoir-E modelling; Hatch Field Niger Delta Basin, Nigeria. Arabian Journal of Geosciences, 13, 410.

  • Journel, A. (1982). The indicator approach to estimation of spatial distributions. In 17th APCOM Symposium Proceedings. Society of Mining Engineers (pp. 793–806).

  • Kalu, C. G., Obiadi, I. I., Amaechi, P. O., & Ndeze, C. K. (2020). petrophysical analysis and reservoir characterization of emerald field, Niger Delta Basin, Nigeria. Asian Journal of Earth Sciences, 13, 21–36.

    Article  Google Scholar 

  • Koledoye, A. B., & Aydin, A. A. (2000). Three-dimensional visualization of normal faults segmentation and its implication for faults growth. The Leading Edge, 19(7), 692.

    Article  Google Scholar 

  • Ma, Y. Z., & Pointe, P. L. (2011). Uncertainty analysis and reservoir modeling: Developing and managing assets in an uncertain world. In: Y. Z. Ma & P. L. Pointe (Eds.), AAPG Memoir (vol. 96).

  • Maleki Tehrani, M. A., Asghari, O., & Emery, X. (2012). Simulation of mineral grades and classification of mineral resources by using hard and soft conditioning data: application to Sungun porphyry copper deposit. Arabian Journal of Geosciences, 6, 3773–3781.

    Article  Google Scholar 

  • Ndip, E. A., Agyingyi, C. M., Nton, M. E., & Oladunjoye, M. A. (2018). Seismic stratigraphic and petrophysical characterization of reservoirs of the Agbada Formation in the Vicinity of ‘Well M’, Offshore Eastern Niger Delta Basin, Nigeria. Journal of Geology and Geophysics, 7, 331. https://doi.org/10.4172/2381-8719.1000331.

    Article  Google Scholar 

  • Okpogo, E. U., Abbey, C. P., & Atueyi, I. O. (2018). Reservoir characterization and volumetric estimation of Orok Field, Niger Delta hydrocarbon province. Egyptian Journal of Petroleum, 27(4), 1087–1094.

    Article  Google Scholar 

  • Olubunmi, C. A., & Olawale, O. A. (2018). Structural interpretation, trapping styles and hydrocarbon potential of Block-X, Northern Depobelt, Onshore Niger Delta. In: AAPG Annual Convention and Exhibition, Salt Lake City, Utah, May 20–23. AAPG Search and Discovery Article # 11099.

  • Oluwadare, O. A., Osunrinde, O. T., Abe, S. J., & Ojo, B. T. (2017). 3-D geostatistical model and volumetric estimation of ‘Del’ Field, Niger Delta. Journal of Geology and Geophysics, 6, 291. https://doi.org/10.4172/2381-8719.1000291.

    Article  Google Scholar 

  • Omoja, U. C., & Obiekezie, T. N. (2018). Application of 3D seismic attribute analyses for hydrocarbon prospectivity in Uzot-Field, Onshore Niger Delta Basin, Nigeria. International Journal of Geophysics. https://doi.org/10.1155/2019/1706416.

    Article  Google Scholar 

  • Oyeyemi, K. D., Olowokere, M. T., & Aizebeokhai, A. P. (2018). Hydrocarbon resource evaluation using combined petrophysical analysis and seismically derived reservoir characterization, offshore Niger Delta. Journal of Petroleum Exploration and Production Technology, 8, 99–115.

    Article  Google Scholar 

  • Remy, N., Boucher, A., & Wu, J. B. (2009). Applied geostatistics with SGeMS (p. 264). Cambridge: Cambridge University Press.

    Book  Google Scholar 

  • Seyyedattar, M., Zendehbiudi, S., & Butt, S. (2020). Technical and non-technical challenges of development of offshore petroleum reservoirs: Characterization and production. Natural Resources Research, 29, 2147–2189.

    Article  Google Scholar 

  • Tuttle, M. L., Charpentier, R. R., & Brownfield, M. E. (1999). The Niger Delta petroleum system; Niger Delta Province, Nigeria, Cameroon, and Equatorial Guinea, Africa. United States Geological Survey (USGS) Open-File Report 99-50-H. https://doi.org/10.3133/ofr9950H

  • Victor, C. N., Kingsley, C. E., & Tuoyo, A. E. (2019). Evaluation of hydrocarbon reserves using integrated petrophysical analysis and seismic interpretation: A case study of TIM field at southwestern offshore Niger Delta oil Province, Nigeria. Egyptian Journal of Petroleum, 28(3), 273–280.

    Article  Google Scholar 

  • Yu, X. Y., Ma, Y. Z., Psaila, D., Pointe, P. L., Gomez, E., & Li, S. (2011). Reservoir characterization and modeling. In Y. Z. Ma & P. LaPointe (Eds.), Uncertainty analysis and reservoir modeling. A look back to see forward (vol. 96, pp. 289–309). AAPG Memoir.

Download references

Acknowledgment

We are grateful to John Carranza, Ph.D., Editor-in-Chief, Natural Resources Research and to the two reviewers for their critical suggestions and constructive reviews which benefited this manuscript. Authors acknowledge SPDC Nigeria for providing the data set. The authors extend their sincere appreciation to the Researchers Supporting Project number (RSP-2020/92), King Saud University, Riyadh, Saudi Arabia.

Author information

Authors and Affiliations

  1. School of Engineering, Geosciences, Infrastructure and Society, Heriot Watt University, Edinburgh, EH14 4AS, UK

    Austin E. Okoli

  2. Department of Geology, Federal University of Technology, Owerri, Imo State, Nigeria

    Austin E. Okoli

  3. Department of Physics, Michael Okpara University of Agriculture, Umudike, Abia State, Nigeria

    Okechukwu E. Agbasi

  4. Petroleum and Natural Gas Engineering Department, College of Engineering, King Saud University, P.O. Box 800, Riyadh, 11421, Saudi Arabia

    Aref A. Lashin

  5. Geologix Limited, Dynasty Building, Andheri Kurla Road, Andheri (E), Mumbai, 400059, Maharashtra, India

    Souvik Sen

Authors
  1. Austin E. Okoli
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Okechukwu E. Agbasi
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Aref A. Lashin
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Souvik Sen
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Okechukwu E. Agbasi.

Appendix

Appendix

Sequential Indicator Simulation (SIS)

SIS is used for a discrete or categorical variable. The algorithm for SIS depends on indicator kriging to infer the cumulative distribution function (CDF) of a discrete variable Z(u). It simulates in cases where data are not required to fit a normal distribution with the sequential paradigm (Remy et al. 2009). Through stochastic simulation, equally probable realizations of the distribution of an indicator variable are produced (Journel 1982; Deutsch and Journel 1998). The steps in SIS are as follows.

  1. (i)

    Select pixels where the lithotype is unknown.

  2. (ii)

    Identify neighboring node points with known lithotypes.

  3. (iii)

    Assign weights to the neighboring points.

  4. (iv)

    Construct a local (CDF) for lithotype probability from the neighbor lithotypes.

  5. (v)

    Extraction forms the CDF of a single lithotype to occupy the empty node points.

  6. (vi)

    Random selection of another empty node point.

  7. (vii)

    Proceed to Step 1 and repeat until estimations have been made at all the empty node points.

Sequential Gaussian Simulation (SGS)

SGS is a stochastic modeling technique that obtains multiple realizations based on the same input data (Maleki Tehrani et al. 2012; Geboy et al. 2013). The steps of SGS consist of the following.

  1. (i)

    Select a node point where the reservoir property under investigation is unknown.

  2. (ii)

    Recognize adjacent node points where the property is known.

  3. (iii)

    Then, allocate weights to the neighbors, depending on their observed relevance at empty node points.

  4. (iv)

    Construct a local probability distribution function (pdf) at the empty node points from the neighbor values.

  5. (v)

    Extraction forms the pdf of a single value to occupy the empty node points, a random selection of another empty node points.

  6. (vi)

    Proceed to Step 1 and repeat until estimations have been made at all empty node points.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Okoli, A.E., Agbasi, O.E., Lashin, A.A. et al. Static Reservoir Modeling of the Eocene Clastic Reservoirs in the Q-Field, Niger Delta, Nigeria. Nat Resour Res 30, 1411–1425 (2021). https://doi.org/10.1007/s11053-020-09804-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11053-020-09804-2

Keywords

Search

Navigation