4.4 Article

High-resolution lithofacies and porosity modeling of the mixed siliciclastic-carbonate deposits of the Burdigalian Dam Formation, Eastern Saudi Arabia

Journal

INTERNATIONAL JOURNAL OF EARTH SCIENCES
Volume 108, Issue 1, Pages 155-172

Publisher

SPRINGER
DOI: 10.1007/s00531-018-1647-1

Keywords

Dam Formation; Burdigalian; Lithofacies model; Porosity model; Saudi Arabia

Funding

  1. Geosciences Department of King Fahd University of Petroleum and Minerals (KFUPM)
  2. Centre for Integrative Petroleum Research of King Fahd University of Petroleum and Minerals (KFUPM)

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Conventional subsurface models of reservoir bodies are limited with respect to the good understanding of small-scale heterogeneities at inter-well spacing. Uncertainties associated with data limitation of such large-scale models can be enhanced by information from small-scale modeling. These high-resolution models may provide a realistic three-dimensional insight into their relevant subsurface reservoir setting. In this context, outcrop studies are frequently used to produce high-resolution models. In this paper, the Burdigalian Dam Formation outcrop in eastern Saudi Arabia was targeted to construct high-resolution models of lithofacies and porosity variations. These models were used to identify small-scale heterogeneities in lithofacies and porosity distribution using geostatistical modeling. Ten different lithofacies were identified and modeled. Indicator semivariogram analysis of the lithofacies showed good continuity in NW-SE direction but less continuity in NE-SW. The porosity model showed differing porosity distributions in different carbonate lithofacies. Several realizations of lithofacies and porosity models were generated and ranked against the input data set. Furthermore, the porosity variation was investigated through detailed petrography and SEM analyses for each of the studied lithofacies. The models demonstrated the presence of patterns of lithofacies and porosity variation at a small scale that cannot be obtained from conventional subsurface models. The study indicated the importance of such models in reducing the uncertainty associated with subsurface modeling as a result of data limitation.

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