Skip to main content

Pre-stack Seismic Inversion for Potential Reservoirs’ Characterization in Oued Mya Basin, Algeria

  • Conference paper
  • First Online:
Selected Studies in Geophysics, Tectonics and Petroleum Geosciences (CAJG 2020)

Abstract

The main objective of this study is to characterize the potential reservoirs situated in Oued Mya basin in Algeria by using pre-stack seismic inversion data. In fact, rock physics has been used to estimate shear waves and their densities from the compressional wave velocities at six wells, and then, cross-plots were exploited to establish a mathematical relation between the petrophysical and acoustic parameters of the rocks. After that, the lithological classification has been iteratively generalized for the whole seismic volume. The final model, obtained with a correlation ratio of 75%, allowed the classification of the dominant facies in the reservoir. Furthermore, the Petrophysical volumes obtained using these mathematical relations provided the horizontal distribution of the different existing reservoirs with a focus on the potential ones. The obtained results in this case study have highlighted the crucial role played by the seismic inversion in the characterization of the oil reservoirs in the Oued Mya Basin. It also permitted to provide lateral variations of petrophysical parameters of the reservoir; thus, it eliminates the problem of punctuality of the information provided by logging data. This characterization step is very important for determining the positions of new exploration drillings in order to optimize exploration strategy with minimal uncertainties; therefore, exploration costs can be optimized. The main novelty of this paper is that the obtained model was very reliable and its correlations with six wells in the basin were high; hence, it has been used to characterize the reservoirs and to identify new areas with hydrocarbons potentials where highly probable discoveries were identified.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 229.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 299.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  • Bacetti A., Doghmane M. Z. (2020). A practical workflow using seismic attributes to enhance sub seismic geological structures and natural fractures correlation. In Conference proceedings, first EAGE digitalization conference and exhibition (pp 1–5)

    Google Scholar 

  • Contreras, A., Torres-Verdin, C., Kvien, K., et al. (2005). AVA stochastic inversion of pre-stack seismic data and well logs for 3D reservoir modeling. In Conference proceedings, 67th EAGE conference and exhibition, cp-1–00310

    Google Scholar 

  • Doghmane, M. Z., Belahcene, B., & Kidouche, M. (2019). Application of improved artificial neural network algorithm in hydrocarbons’ reservoir evaluation. In M. Hatti (Eds.), Renewable energy for smart and sustainable cities. ICAIRES 2018. Lecture notes in networks and systems 62. Springer, Cham

    Google Scholar 

  • Doghmane, M. Z., & Belahcene, B. (2019). Design of new model (ANNSVM) compensator for saturation calculation based on logging curves for low resistivity phenomenon. In Conference proceedings, EAGE/ALNAFT geoscience workshop (pp 1–5)

    Google Scholar 

  • Eladj, S., Lounissi, T. K., Doghmane, M. Z., & Djeddi, M. (2020). Lithological characterization by simultaneous seismic inversion in Algerian South Eastern field. Engineering, Technology and Applied Science Research, 10(01), 5251–5258.

    Article  Google Scholar 

  • Hampson, D. P., Russell, B. H., & Bankhead, B. (2005). Simultaneous inversion of pre-stack seismic data. SEG Technical Program Expanded Abstracts, 17, 1633–1637.

    Article  Google Scholar 

  • James, J., Carrazzone, D., Chang, C., et al. (1994). Method for deriving reservoir lithology and fluid content from pre-stack inversion of seismic data. US Patent US5583825A

    Google Scholar 

  • Shuanghe, D., Zhigang, C., Jingbo, Y., et al. (2010). Application of the fluid mobility attribute technique in the reservoir characterization of KG Oilfield, Algeria. Petroleum Exploration and Development, 14, P619.

    Google Scholar 

  • Stolt, R. H., & Weglein, A. B. (1985). Migration and inversion of seismic data. Geophysics, 50(12), 2458–2472.

    Article  Google Scholar 

  • Thierry, C., Fabien, A., Bornard, R., et al. (2005). Petrophysical seismic inversion. SEG Technical Program Expanded Abstracts, 14, 1355–1358.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Said Eladj .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2024 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Eladj, S., Benabid, M., Doghmane, M.Z. (2024). Pre-stack Seismic Inversion for Potential Reservoirs’ Characterization in Oued Mya Basin, Algeria. In: Khomsi, S., et al. Selected Studies in Geophysics, Tectonics and Petroleum Geosciences. CAJG 2020. Advances in Science, Technology & Innovation. Springer, Cham. https://doi.org/10.1007/978-3-031-43807-3_16

Download citation

Publish with us

Policies and ethics