Porosity Prediction, Prior to Drilling, in Sandstones of the Kekiktuk Formation (Mississippian), North Slope of Alaska (1)

Bloch, Salman; McGowen, J. H.; Duncan, John R.; Brizzolara, D. W.

doi:10.1306/0c9b24cf-1710-11d7-8645000102c1865d

Cited by 10 publications

(2 citation statements)

References 19 publications

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“…Because each simulation starts at the beginning of a deposit event and layers are added to the top only, the initial conditions are already determined by the top boundary conditions given in (10):…”

Section: Initial Conditionsmentioning

confidence: 99%

“…Usually, mechanical compaction is the dominating phenomenon in the upper layers of the basin, while chemical compaction dominates in the lower layers. The depth transition between mechanically and chemically dominated layers depends on lithology, varying from 0.1 km for carbonates [8,9] to 1.5 km for sandstone [10][11][12][13]. In the present work, we neglect chemical compaction so that our model is best suited, but not limited, to upper layers.…”

Section: Introductionmentioning

confidence: 99%

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A simplified vertical and horizontal geomechanical model for compaction in sedimentary basins

Saverio Patacchini,

Cacas-Stentz,

Maurand

et al. 2023

STET

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In the context of mechanical compaction in sedimentary basins, we introduce a simple model including lateral deformations with the goal to improve the results obtained under oedometric conditions (i.e., neglecting horizontal strains) without losing much computational time. The model is based on a modified vertical porosity-stress law where horizontal strains are inserted and on an elastic stress-strain law with stress-dependent Young modulus. Though it is not three-dimensional and does not involve plasticity, we manage to validate the model on a geometrically and lithologically complex test case by comparing our results with those obtained on the same case using a full-dimensional finite-element simulator. We conclude that our model offers a significant improvement in accuracy against an oedometric model, with little loss in computational time, and so provides a useful tool to users who want a quick insight into results before running longer and more accurate simulations.

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Section: Initial Conditionsmentioning

confidence: 99%