Estimation Microporosity Value of Fontanebleau Sandstone Using Digital Rock Physics Approach

Authors

  • Reza Rizki Geophysical Engineering, Institut Teknologi Sumatera, South Lampung, Indonesia
  • Handoyo Handoyo Geophysical Engineering, Institut Teknologi Sumatera, South Lampung, Indonesia

DOI:

https://doi.org/10.24273/jgeet.2018.3.2.1544

Keywords:

Digital Rock Physics, Image Sample, Microporosity

Abstract

The technology of digital rock physics (DRP) allowed to predict the physical properties in core data sample, for example to predict value of porosity of data sample. This research applied the digital rock physics technique to predict the microporosity in sandstone sample: Fontanebleau Sandstone. The data are digital images from Fontanebleau Sandstone with high resolution scanned from micro tomography CT-Scan processing. The result of image processing shown in 2D and 3D image. From the data, the value of microporosity Fontanebleau Sandstone are beetwen 6% - 7%. This result confirmed by the quartz cemented sample of Fontanebleau Sandstone. The scale and sub-cube give the different value of microporosity which is indicated the scale influence to value of porosity value. So the simplest and best way is to average the all result from sub-cubes.

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References

Andrä, H., Combaret, N., Dvorkin, J., Glatt, E., Han, J., Kabel, M., Keehm, Y., Krzikalla, F., 376 Lee, M., Madonna, C., Marsh, M., Mukerji, T., Saenger, E.H., Sain, R., Saxena, N., Ricker, 377 S., Wiegmann, A., Zhan, X., 2013a. Digital rock physics benchmarks—Part I: imaging and 378 segmentation. Comp. Geosci. 50, 25–32.

Arns, C.H., Knackstedt, M.A., Pinczewski, W.V., Garboczi, E. G., 2002. Computation of linear elastic properties from microtomographic images: methodology and agreement between theory and experiment. Geophysics, 67, 1396-1405.

Bourbié, T., Coussy, O., and Zinszner, B., 1987, Acoustics of Porous Media. Houston, TX: Gulf Publishing Co.

Dvorkin, J., Nur, A., and Yin, H., 1994, Effective Properties of Cemented Granular Materials, Mechanics of Materials, 18, 351-366. Dvorkin, J., and Nur, A., 1996, Elasticity of high porosity Sandstones: Theory for Two North Sea Datasets, Geophysics, 61, 1363-1370.

Fourier, D.E.L., 2014. Analysis of Permeability and Tortuosity of Fontainebleau Sandstone and its Models Using Digital Rock Physics Approach. Physics of Earth and Complex System, Faculty of Mathematics and Natural Sciences, Bandung Institute of Technology, Indonesia.

Gomez, C., 2009, Reservoir characterization combining elastic velocities and electrical resistivity measurements. Ph.D. dissertation, Stanford University.

Han, D., 1986, Effects of porosity and clay content on acoustic properties of sandstones and unconsolidated sediments: Ph.D. dissertation, Stanford University.

Handoyo., Fatkhan., Fourier, D.E.L., 2014. Digital Rock Physics Application: Structure Parameters Characterization, Materials Identification, Fluid Modeling, and Elastic Properties Estimation of Saturated Sandstones, HAGI Proceeding 2014 Solo, Bandung Institute of Technology, Indonesia.

Mavko, G., and Nur, A., 2009, The Rock Physics Handbook, Second Edition Tools for Seismic Analysis of Porous Media. Cambridge University Press The Edinburgh Building, Cambridge CB2 8RU, UK

Saxena, Nishank, Day-Stirrat, Ruari J., 2017. Effect of image segmentation & voxel size on micro-CT computed effective transport & elastic properties. Marine and Petroleum Geology Article. USA.

Wiegman, et all. 2012. Predicting Effective Elastic Properties with Elastodict. Fraunhofer ITW. Germany.

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Published

2018-06-01