Quality Assurance of Carbonate Rock Special Core Analysis - Lesson Learnt from a Multi-Year Research Project

Abstract

Abstract Core data has historically been used as the ground truth in many upstream applications, such as formation evaluation, geological modeling, and reservoir simulation. The importance bestowed upon the data requires that core analysis programs are properly designed and the data is thoroughly quality controlled. Otherwise, a high percentage of the data, especially from special core analysis (SCAL), may not be usable. To design a fit-for-purpose program and produce quality results, potential issues related to the analysis of the targeted reservoir rock and fluids need to be fully understood and taken into account. Many lessons have been learnt from a multi-year project studying drainage and imbibition electrical properties in carbonate rocks, chief among them are related to rock cleaning, porous plate preparation, and test equilibrium conditions. Results generated in this study show that conventional cleaning may be sufficient for a porosity measurement provided that rock is not extremely heterogeneous. Specially designed cleaning procedures and solvents should be applied for wettability restoration as demonstrated from various wettability measurements. In using porous plate for resistivity index (RI) tests, the main challenges are to prepare the porous discs to oil-wet and flow crude oil through them. Special procedures have been developed to address these challenges successfully. In performing equilibrium RI tests, data shows that a test cycle may last for many months, or even years, and often may be terminated prematurely due to equipment/ sample failures. This issue can only be resolved by adopting a non-equilibrium method with in-situ saturation monitoring and/or numerical simulation algorithms. Findings from this study can help others to better understand some of the key issues in dealing with carbonate rocks in the core analysis laboratory, thus design a proper SCAL program to produce quality SCAL data.