Petrophysical Characterization

Full Pore System Petrophysical Characterization Technology for Complex Carbonate Reservoirs – Results from Saudi Arabia
Phillips, E. C., Buiting, J. M., Clerke, E. A. – Saudi Aramco, Dhahran, Saudi Arabia

Extended Abstract We have developed new, petrophysical characterization technology for complex carbonate reservoirs using Petrophysical Rock Types (PRT). This technology has been proven inthe largest carbonate reservoirs in the world in Saudi Arabia. PRTs are derived from the Thomeer analyses of nearly 2,000 high pressure mercury injection capillary pressure (MICP) curves that are used as calibration data. The Thomeer parameters for each core plug sample are determined by applying a closure correction and fitting the Thomeer hyperbola to the capillary pressure data obtaining a nearexact fit (Figures 1 and 2).

Figure 1) Three Thomeer parameters per pore system (G, Pd and BV) can be used to replicate a capillary pressure curve

Thomeer parameters (initial displacement pressure – Pd, geometric factor – G, and fractional bulk volume mercury injected - BV) are determined for each sample resulting in a characterization of the pore space architecture. This is particularlyimportant in our complex, multimodal carbonates where the best reservoir rocks consist of both intergranular macroporosity and intraparticle microporosity. With our large hydrocarbon columns, oil easily enters the common second pore system’s intraparticle Type 1 microporosity once hydrocarbon column heights exceed 200 feet. The bulk of the Arab D oil is stored in bimodal limestone with a PRTclassification of M_1, i.e. a macroporous rock with Type 1 micro porosity (Figure 3).

Figure 2) Assuming a dual porosity system in this case, the Matlab optimization results in a near exact fit of the fitted data (blue dashed line) to the actual capillary pressure curve (green curve). The Thomeer parameters used to match the capillary pressure data are shown on the figure for both pore systems.Figure 3a Figure 3b Figure 3) Rosetta Stone calibration data set with 484 HPMI capillary pressure samples classified by four porositons on the left (3a). Three common PRTs from four porositons are shown in the photomicrographs; a bimodal M_1, a monomodal Type 1 and a micritic Type 2-3 micro porosity sample. The bimodal M_1 PRT, a Macro with a Type 1 micro component, is the most dominant PRT in theArab D of Saudi Arabia. The figure on the right shows the vertical distribution of the PRTs on a type well.

The PRT classification is obtained by querying our Thomeer parameter databases (Figure 3). Moreover, the databases provide rock properties, correlations and statistics for each reservoir. Clerke 1 has defined PRTs as clusters in the three dimensional space of Thomeer parameters (Figure 4).Figure 4) 3D cross plot of the Thomeer parameters, Pd1, G1 and BV1 for the 484 sample database

Using “Map Inversion Rock Typing” (MIRT), we exploit the ordered distribution of Thomeer parameters and PRTs on a two dimensional (porosity-permeability) petrophysical map (Figure 5). Thomeer parameter information is obtained by querying this petrophysical map using core-calibrated well-logpredictions of porosity and permeability.

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Clerke, E. A., Mueller III, H. W., Phillips, E. C., Eyvazzadeh, R. Y., Jones, D. H., Ramamoorthy, R.,

Srivastava, A., (2008) “Application of Thomeer Hyperbolas to decode the pore systems, facies and reservoir properties of the the Upper Jurassic Arab D Limestone, Ghawar field, Saudi Arabia: A Rosetta Stone approach”, GeoArabia, Vol. 13, No. 4, p.113-160, October.

Buiting, J.J.M, (2007), ‘Fully Upscaled Saturation Height Functions for Reservoir Modeling based on Thomeer’s Method for Analyzing Capillary Pressure Measurements’, SPE 105139.

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Figure 5) Cross plot of Porosity vs. Permeability with PRT’s on Z axis for calibration data

The query returns PRT classifications (and their probabilities) with associated Thomeer parameters...