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Journal : Journal of Geoscience, Engineering, Environment, and Technology

Rock Physics Modeling and Seismic Interpretation to Estimate Shally Cemented Zone in Carbonate Reservoir Rock Handoyo Handoyo; M Rizki Sudarsana; Restu Almiati
Journal of Geoscience, Engineering, Environment, and Technology Vol. 1 No. 1 (2016): JGEET Vol 01 No 01 : December (2016)
Publisher : UIR PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (564.18 KB) | DOI: 10.24273/jgeet.2016.11.6

Abstract

Carbonate rock are important hydrocarbon reservoir rocks with complex texture and petrophysical properties (porosity and permeability). These complexities make the prediction reservoir characteristics (e.g. porosity and permeability) from their seismic properties more difficult. The goal of this paper are to understanding the relationship of physical properties and to see the signature carbonate initial rock and shally-carbonate rock from the reservoir. To understand the relationship between the seismic, petrophysical and geological properties, we used rock physics modeling from ultrasonic P- and S- wave velocity that measured from log data. The measurements obtained from carbonate reservoir field (gas production). X-ray diffraction and scanning electron microscope studies shown the reservoir rock are contain wackestone-packstone content. Effective medium theory to rock physics modeling are using Voigt, Reuss, and Hill. It is shown the elastic moduly proposionally decrease with increasing porosity. Elastic properties and wave velocity are decreasing proporsionally with increasing porosity and shally cemented on the carbonate rock give higher elastic properties than initial carbonate non-cemented. Rock physics modeling can separated zones which rich of shale and less of shale.
Estimation Microporosity Value of Fontanebleau Sandstone Using Digital Rock Physics Approach Reza Rizki; Handoyo Handoyo
Journal of Geoscience, Engineering, Environment, and Technology Vol. 3 No. 2 (2018): JGEET Vol 03 No 02 : June (2018)
Publisher : UIR PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (502.29 KB) | DOI: 10.24273/jgeet.2018.3.2.1544

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.
Rock Physics Formula and RMS Stacking Velocity Calculation to Assist Acoustic Impedance Inversion that Constrain Well Data Handoyo; Mochammad Puput Erlangga; Paul Young
Journal of Geoscience, Engineering, Environment, and Technology Vol. 5 No. 2 (2020): JGEET Vol 05 No 02 : June (2020)
Publisher : UIR PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (711.717 KB) | DOI: 10.25299/jgeet.2020.5.2.3089

Abstract

This research ilustrate the generation of acoustic impedance inversion in the absence of well log using stacking velocity input in Salawati Basin, Papua, Indonesia using data obtained from seismic lines and stacking velocity section. Initial acoustic impedance modelswere first before the inversion process and were created by spreading the value of well log data to the all seismic CDP. The calculated acoustic impedance logs from standard sonic and density logs were used to build the initial model of acoustic impedance.First, the stacking velocities was first interpolated on a grid that has the same size as the seismic data using by means of Polynomial algorithm. This was closely followed by the conversion of the stacking velocities to interval velocities using Dix’s equation. The matrix densities were estimated by simple rock physics approach i.e. Gardner’s equation as a velocity function. The initial model of acoustic impedance was calculated by multiplying the densities section and interval velocities section. The resulting initial model of acoustic impedance was inverted to obtain the best of acoustic impedance section based on reflectivity.