Estimating density and vertical stress magnitudes using hydrocarbon exploration data in the onshore Northern Niger Delta Basin, Nigeria: Implication for overpressure prediction

E. O. Adewole*, D. I M Macdonald, D. Healy

*Corresponding author for this work

Research output: Contribution to journalArticle

6 Citations (Scopus)

Abstract

Different techniques for predicting density have been driven by the generally poor resolution with depth, and the lack of good quality density data for quantitative formation evaluation studies. The accuracy of most empirical methods is sometimes affected by the methodological uncertainty, but mainly influenced by the reliability of the input data. The benefits of using different methods in density prediction were demonstrated on the basis of a pore pressure prediction study from the Northern Niger Delta Basin (NNDB). The assessment of three density prediction methods (Wyllie, Gardner and Bellotti & Giacca) shows that the Wyllie's method is the preferred choice for the density prediction in the study area because it has the lowest Least Squares Misfit (LSM) error of 0.0019. The vertical stress gradients (constrained from densities) vary vertically with depth from 19 MPa/km (near the surface) to 25.7 MPa/km (at 4 km depth) and laterally between wells, particularly at the top of high magnitude overpressures (at 3.5 km) from 23.6 MPa/km to 25.0 MPa/km. The differences in the vertical stress gradients are consistent with the density variations observed in the area, and they have implications for the predicted pore pressures. We found there to be an increase in pressure gradient from the top to the bottom of wells, which is consistent with data from 87 wells in the area of study. We have therefore been able to identify three main pressure magnitudes in the area of study: (i) low pressure (close to hydrostatic pressure), (ii) abnormal pressure (a little above hydrostatic) and (iii) high pressure (far above hydrostatic).

Original languageEnglish
Pages (from-to)294-308
Number of pages15
JournalJournal of African Earth Sciences
Volume123
Early online date4 Aug 2016
DOIs
Publication statusPublished - 1 Nov 2016

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hydrocarbon exploration
overpressure
prediction
basin
hydrostatics
well
pore pressure
hydrostatic pressure
pressure gradient
low pressure
method

Keywords

  • Density prediction
  • Niger delta
  • Overpressure
  • Pressure prediction
  • Vertical stress
  • Vertical stress gradient

ASJC Scopus subject areas

  • Geology
  • Earth-Surface Processes

Cite this

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title = "Estimating density and vertical stress magnitudes using hydrocarbon exploration data in the onshore Northern Niger Delta Basin, Nigeria: Implication for overpressure prediction",
abstract = "Different techniques for predicting density have been driven by the generally poor resolution with depth, and the lack of good quality density data for quantitative formation evaluation studies. The accuracy of most empirical methods is sometimes affected by the methodological uncertainty, but mainly influenced by the reliability of the input data. The benefits of using different methods in density prediction were demonstrated on the basis of a pore pressure prediction study from the Northern Niger Delta Basin (NNDB). The assessment of three density prediction methods (Wyllie, Gardner and Bellotti & Giacca) shows that the Wyllie's method is the preferred choice for the density prediction in the study area because it has the lowest Least Squares Misfit (LSM) error of 0.0019. The vertical stress gradients (constrained from densities) vary vertically with depth from 19 MPa/km (near the surface) to 25.7 MPa/km (at 4 km depth) and laterally between wells, particularly at the top of high magnitude overpressures (at 3.5 km) from 23.6 MPa/km to 25.0 MPa/km. The differences in the vertical stress gradients are consistent with the density variations observed in the area, and they have implications for the predicted pore pressures. We found there to be an increase in pressure gradient from the top to the bottom of wells, which is consistent with data from 87 wells in the area of study. We have therefore been able to identify three main pressure magnitudes in the area of study: (i) low pressure (close to hydrostatic pressure), (ii) abnormal pressure (a little above hydrostatic) and (iii) high pressure (far above hydrostatic).",
keywords = "Density prediction, Niger delta, Overpressure, Pressure prediction, Vertical stress, Vertical stress gradient",
author = "Adewole, {E. O.} and Macdonald, {D. I M} and D. Healy",
note = "The authors wish to thank the Ministry of Petroleum Resources (MPR), Nigeria for giving authority to access the data for this study. We are indeed very grateful to Mark Tingay, formerly of the University of Adelaide, now at Chevron (Australia). The careful reviews and helpful comments on the Ph.D. thesis of E.O.A. by Clare Bond are also gratefully acknowledged. We also appreciate Andrew Hurst, Judith Christie, John Still, and Jim Marr at the Department of Geology and Petroleum Geology (University of Aberdeen, Aberdeen) for their technical support, discussion and advice. This study is a part of a wider research on the development of petroleum industries in Nigeria. The Niger Delta Development Commission (NDDC), Nigeria is acknowledged for funding E.O.A.’s Ph.D. scholarship. Our work has been aided by the provision of software to the University of Aberdeen by Halliburton, Badleys, Ikon, and CGG Veritas, which we gratefully acknowledged. We thank the editor of this journal, Damien Delvaux, and the two anonymous reviewers for their comments and suggestions that paved the way for the overall improvement of the final manuscript.",
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T1 - Estimating density and vertical stress magnitudes using hydrocarbon exploration data in the onshore Northern Niger Delta Basin, Nigeria

T2 - Implication for overpressure prediction

AU - Adewole, E. O.

AU - Macdonald, D. I M

AU - Healy, D.

N1 - The authors wish to thank the Ministry of Petroleum Resources (MPR), Nigeria for giving authority to access the data for this study. We are indeed very grateful to Mark Tingay, formerly of the University of Adelaide, now at Chevron (Australia). The careful reviews and helpful comments on the Ph.D. thesis of E.O.A. by Clare Bond are also gratefully acknowledged. We also appreciate Andrew Hurst, Judith Christie, John Still, and Jim Marr at the Department of Geology and Petroleum Geology (University of Aberdeen, Aberdeen) for their technical support, discussion and advice. This study is a part of a wider research on the development of petroleum industries in Nigeria. The Niger Delta Development Commission (NDDC), Nigeria is acknowledged for funding E.O.A.’s Ph.D. scholarship. Our work has been aided by the provision of software to the University of Aberdeen by Halliburton, Badleys, Ikon, and CGG Veritas, which we gratefully acknowledged. We thank the editor of this journal, Damien Delvaux, and the two anonymous reviewers for their comments and suggestions that paved the way for the overall improvement of the final manuscript.

PY - 2016/11/1

Y1 - 2016/11/1

N2 - Different techniques for predicting density have been driven by the generally poor resolution with depth, and the lack of good quality density data for quantitative formation evaluation studies. The accuracy of most empirical methods is sometimes affected by the methodological uncertainty, but mainly influenced by the reliability of the input data. The benefits of using different methods in density prediction were demonstrated on the basis of a pore pressure prediction study from the Northern Niger Delta Basin (NNDB). The assessment of three density prediction methods (Wyllie, Gardner and Bellotti & Giacca) shows that the Wyllie's method is the preferred choice for the density prediction in the study area because it has the lowest Least Squares Misfit (LSM) error of 0.0019. The vertical stress gradients (constrained from densities) vary vertically with depth from 19 MPa/km (near the surface) to 25.7 MPa/km (at 4 km depth) and laterally between wells, particularly at the top of high magnitude overpressures (at 3.5 km) from 23.6 MPa/km to 25.0 MPa/km. The differences in the vertical stress gradients are consistent with the density variations observed in the area, and they have implications for the predicted pore pressures. We found there to be an increase in pressure gradient from the top to the bottom of wells, which is consistent with data from 87 wells in the area of study. We have therefore been able to identify three main pressure magnitudes in the area of study: (i) low pressure (close to hydrostatic pressure), (ii) abnormal pressure (a little above hydrostatic) and (iii) high pressure (far above hydrostatic).

AB - Different techniques for predicting density have been driven by the generally poor resolution with depth, and the lack of good quality density data for quantitative formation evaluation studies. The accuracy of most empirical methods is sometimes affected by the methodological uncertainty, but mainly influenced by the reliability of the input data. The benefits of using different methods in density prediction were demonstrated on the basis of a pore pressure prediction study from the Northern Niger Delta Basin (NNDB). The assessment of three density prediction methods (Wyllie, Gardner and Bellotti & Giacca) shows that the Wyllie's method is the preferred choice for the density prediction in the study area because it has the lowest Least Squares Misfit (LSM) error of 0.0019. The vertical stress gradients (constrained from densities) vary vertically with depth from 19 MPa/km (near the surface) to 25.7 MPa/km (at 4 km depth) and laterally between wells, particularly at the top of high magnitude overpressures (at 3.5 km) from 23.6 MPa/km to 25.0 MPa/km. The differences in the vertical stress gradients are consistent with the density variations observed in the area, and they have implications for the predicted pore pressures. We found there to be an increase in pressure gradient from the top to the bottom of wells, which is consistent with data from 87 wells in the area of study. We have therefore been able to identify three main pressure magnitudes in the area of study: (i) low pressure (close to hydrostatic pressure), (ii) abnormal pressure (a little above hydrostatic) and (iii) high pressure (far above hydrostatic).

KW - Density prediction

KW - Niger delta

KW - Overpressure

KW - Pressure prediction

KW - Vertical stress

KW - Vertical stress gradient

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