Quantification of pore structure and its effect on sonic velocity and permeability in carbonates

Weger, Ralf J.; Eberli, Gregor P.; Baechle, Gregor; Massaferro, José Luis; Sun, Yue Feng

doi:10.1306/05270909001

Cited by 247 publications

(215 citation statements)

References 42 publications

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“…The influence of pore space and its geometry on acoustic properties has been explored by many authors (Rafavich et al, 1984;Anselmetti and Eberli, 1999;Assefa et al, 2003;Saleh and Castagna, 2004;Weger et al, 2009;Lima Neto et al, 2013). Although these papers consider relationships between simple pore shape, size, and acoustic properties, there is no consensus as to the influence of more complex pore types.…”

Section: Discussionmentioning

confidence: 99%

“…Weger et al (2009) conducted a multilinear regression to assess the combined impact of multiple pore-shape parameters on V p . They found that by taking consideration of AR and porosity the correlation was poor, with R 2 equal to 0.549 and increasing to 0.639 after inclusion of g (defined in two dimensions), whereas the best R 2 (0.845) used these parameters, f m , and DomSize.…”

Section: Discussionmentioning

confidence: 99%

“…Carbonate rocks are highly prone to postdepositional alteration, such as dissolution and cementation, and these processes modify the pore structure, creating or destroying porosity and changing permeability and acoustic properties (Rafavich et al, 1984;Anselmetti et al, 1998;Eberli et al, 2003;Weger et al, 2009;Hollis et al, 2010;Castro and Rocha, 2013). Eberli et al (2003) showed that total porosity and pore type have nearly the same impact on the acoustic behavior of carbonate rocks and that the most used velocity-porosity empirical relations-for example, Gardner (Raymer et al, 1980) and Wyllie (Wyllie et al, 1958)-do not predict velocity with a high coefficient of determination (R 2 ).…”

Section: Introductionmentioning

confidence: 99%

“…Importantly, the most widely used algorithms for seismic inversion and log interpretation do not consider pore-shape factors, and, consequently, they can significantly over-or underestimate hydrocarbon volumes. Weger et al (2009) introduced the digital image analysis (DIA) method to improve the prediction of velocity and permeability. The study used two-dimensional (2-D) images from thin section, and a good improvement in velocity prediction was observed, with the R 2 increasing from 0.542 to 0.845.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Permeability and acoustic velocity controlling factors determined from x-ray tomography images of carbonate rocks

Archilha¹,

Misságia²,

Hollis³

et al. 2016

Bulletin

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A B S T R A C TCarbonate reservoir rocks exhibit a great variability in texture that directly impacts petrophysical parameters. Many exhibit bi-and multimodal pore networks, with pores ranging from less than 1 mm to several millimeters in diameter. Furthermore, many pore systems are too large to be captured by routine core analysis, and well logs average total porosity over different volumes. Consequently, prediction of carbonate properties from seismic data and log interpretation is still a challenge. In particular, amplitude versus offset classification systems developed for clastic rocks, which are dominated by connected, intergranular, unimodal pore networks, are not applicable to carbonate rocks.Pore geometrical parameters derived from digital image analysis (DIA) of thin sections were recently used to improve the coefficient of determination of velocity and permeability versus porosity. Although this substantially improved the coefficient of determination, no spatial information of the pore space was considered, because DIA parameters were obtained from twodimensional analyses. Here, we propose a methodology to link local and global pore-space parameters, obtained from threedimensional (3-D) images, to experimental physical properties of carbonate rocks to improve P-wave velocity and permeability predictions. Results show that applying a combination of porosity, microporosity, and 3-D geometrical parameters to P-wave velocity significantly improves the adjusted coefficient of determination from 0.490 to 0.962. A substantial improvement

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Permeability and acoustic velocity controlling factors determined from x-ray tomography images of carbonate rocks

Archilha¹,

Misságia²,

Hollis³

et al. 2016

Bulletin

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show abstract

“…The petrophysical impact of this porosity inversion has been widely described, since the poor connectivity of oo-mouldic pores means there is potential to underpredict pore volumes from velocity data, including during seismic inversion, and to overestimate permeability from porosity data (eg. Eberli et al, 2003;Weger et al, 2009). The mechanism for forming such porosity is not well understood, however, even though this is critical to prediction of the spatial and temporal distribution of pore type and connectivity.…”

Section: Introductionmentioning

confidence: 99%

Controls on porosity preservation within a Jurassic oolitic reservoir complex, UAE

Hollis¹,

Lawrence

Perière³

et al. 2017

Marine and Petroleum Geology

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Acoustic and reservoir properties of microporous carbonate rocks: Implication of micrite particle size and morphology

et al. 2015

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This integrated study provides significant insight into parameters controlling the acoustic and reservoir properties of microporous limestones, improving the knowledge of the relationships among petrophysic and microstructural content. Petrophysical properties measured from laboratory and logging tools (porosity, permeability, electrical conductivity, and acoustic properties) have been coupled with thin section and scanning electron microscope observations on the EST205 borehole from the Oxfordian limestone aquifer of the eastern part of the Paris Basin. A major achievement is the establishment of the link between micrite microtexture types (particle morphology and nature of intercrystal contacts) and the physical response, introducing a new effective and interesting rock-typing approach for microporous reservoirs. Fluid-flow properties are enhanced by the progressive augmentation of intercrystalline microporosity and associated pore throat diameter, as the coalescence of micrite particles decreases. Concerning acoustic properties, the slow increase of P wave velocity can be seen as a reflection of crystal size and growing contact cementation leading to a more cohesive and stiffer micrite microtexture. By applying poroelasticity theory on our samples, we show that velocity dispersion can be a very useful tool for data discrimination in carbonates. This dispersion analysis highlights the presence of microcracks in the rocks, and their overall effect on acoustic and transport properties. The presence of microcracks is also confirmed with observations and permeability measurements under high confining pressure. Finally, a possible origin of high porous levels in neritic limestones is a mineralogical transformation of carbonates through freshwater-related diagenesis during subaerial exposure time. Finally, by applying poroelasticity theory on our samples, we show that velocity dispersion can be a very useful tool for data discrimination in carbonates.

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Quantification of pore structure and its effect on sonic velocity and permeability in carbonates

Cited by 247 publications

References 42 publications

Permeability and acoustic velocity controlling factors determined from x-ray tomography images of carbonate rocks

Permeability and acoustic velocity controlling factors determined from x-ray tomography images of carbonate rocks

Controls on porosity preservation within a Jurassic oolitic reservoir complex, UAE

Acoustic and reservoir properties of microporous carbonate rocks: Implication of micrite particle size and morphology

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