Most macro rock typically has a dual porosity system where the Pore Throat Distribution (PTD) will have two modes as shown below. Interrogate the Well Log data and Rosetta Stone calibration data using standard Geolog layouts, cross plots and histograms and then use a python loglan featuring Altair, which is interactive software driven from a Geolog Module Launcher.Īltair Used to Interrogate the Well log data in Geolog:Īltair used to Interrogate the Rosetta Stone Thomeer Capillary Pressure curves and Petrophysical Rock Types (PRTs):. ![]() The workflow consists of the following steps: The following workflow and processing is suggested to interrogate, process, interpret and model the petrophysical properties of a typical Arab D carbonate reservoir using Clerke’s Arab D Rosetta Stone Carbonate database as calibration. For this Arab D reservoir, most PRTs have a dual-porosity system, and some PRTs have up to 3 pore systems. From these results (primarily Pd) Clerke defined his Petrophysical Rock Types (PRT). He then fit the capillary pressure curves using the Thomeer hyperbola (see Altair Plot of Capillary Pressure curves) created from the Initial Displacement Pressure (Pdi), Pc curvature term Gi that relates to the variability of pore throats and Bulk Volume Occupied (BVocci) that is related to the Pore Volume for each pore system 'i'. For each sample Clerke acquired High Pressure Mercury Injection (HPMI) data. ![]() The Rosetta Stone data cover the full range in poro-perm space and Petrophysical Rock Types (PRTs) observed in the Arab D reservoir. ![]() Clerke randomly selected the final calibration samples from 1,000’s of core plugs for the final dataset. This is a very special carbonate dataset. We are using Ed Clerke’s Rosetta Stone, Arab-D carbonate dataset from Ghawar field in Saudi Arabia as calibration data. Typically this static model would then be used to initialize the dynamic model in reservoir simulation. The final objective would be to use these well data results and create a 3D static model of porosity, permeability, Petrophysical Rock Types (PRT), capillary pressure parameters and saturations. In this example we are showing the results for just one well, but in the full-field reservoir characterization we would follow the same workflow and generate the same results for all wells. ![]() This will serves as the basis for a full-field reservoir characterization workflow for all wells throughout the entire field. Soon we will provide a complete Geolog project in GitHub with Geolog python loglans, data with one well to utilize our proven workflow to interrogate and characterize a typical Arab D carbonate reservoir on the project well. Permeability, Petrophysical Rock Types (PRT), Capillary Pressure and modeled saturations are all estimated or calculated within this workflow in order to characterize this complex carbonate reservoirs, and Clerke’s(2) Arab D Rosetta Stone core analysis database is used as the calibration data. This repository contains python Jupyter Notebooks to use as help and demonstration files to demonstrate a tried and proven workflow with the techniques as described by Phillips et al.(1) used in the characterization of most Arab D reservoirs in Saudi Arabia. Carbonate characterization workflow using Clerke’s carbonate Arab D Rosetta Stone calibration data to provide for a full pore system characterization with modeled saturations using Thomeer Capillary Pressure parameters for an Arab D complex carbonate reservoir.
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