Acoustic, mechanical, and microstructure data used in: Coda-Wave Based Monitoring of Pore-Pressure Depletion-driven Compaction of Slochteren Sandstone Samples from the Groningen Gas Field

  • R.D. (Reuben) Zotz-Wilson (Creator)



Pore-pressure depletion in sandstone reservoirs is well known to cause both elastic and inelastic compaction, often resulting in notable surface subsidence and induced seismicity. Recent studies indicate that in such cases inelastic strain, which is often neglected in geomechanical models, represents a significant proportion of the total strain throughout reservoir production. While there has been considerable effort to quantify the proportion of continuous inelastic deformation from the mechanical response of laboratory samples, there has been little focus to date on the associated acoustic response throughout compaction. With this in mind, we employ three coda-wave based processing methods for the active source monitoring of ultrasonic velocity, scattering power, and intrinsic/scattering attenuation during the pore-pressure depletion of core samples from the Slochteren sandstone reservoir in the Groningen gas field (the Netherlands). Our results corroborate previous studies suggesting that initially, inelastic deformation occurs primarily along intergranular boundaries, with intergranular cracking developing towards the end of depletion and particularly for the highest porosity samples. Furthermore, analysis of Biot type intrinsic attenuation indicates that this compaction occurs in several stages of predominately intergranular closure, transitioning into primarily intergranular slip/cracking, and eventually porosity-dependent intragranular cracking. We demonstrate how this segmentation of pore-pressure driven compaction can be used to characterise differences in sample properties, and monitor the evolution of microstructural inelastic deformation throughout depletion. We further discuss the feasibility of in/cross-borehole monitoring of reservoir compaction, for both improved geo-mechanical modelling and early warning detection of induced seismicity.
Date made available8 Jul 2019
PublisherTU Delft - 4TU.ResearchData
Date of data production2019
Geographical coverageGroningen gas field

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