Oil -Water Relative Permeability Data for Reservoir Simulation Input, Part-I: Systematic Quality Assessment and Consistency Evaluation

Abstract The relative permeability concept has been used extensively in reservoir engineering. As numerical reservoir simulation has become more popular as a tool for reservoir development, the role of relative permeability data became even more evident and important. Its key use is to control the advancement and mobility of different fluids simultaneously coexisting in the porous media, and hence controlling the recovery of the fluids. However, deriving a reliable relative permeability data set remained a major challenge. In reservoir engineering, this challenge has been present for many decades and might be so in the foreseeable future. Another challenge is to have a data set which is internally consistent and does not hinder the simulation performance. Optimistically, with the significant literature accumulated over the years in deriving and using relative permeability, some techniques can be extracted for data quality check, control and assurance. This paper covers the limitations of the conventional methods used for calculating relative permeability from displacement experiments. It also compiles all contemporary techniques in a systematic workflow for quality assessment and consistency evaluation. The workflow has been demonstrated with different synthetic and field examples. This paper will provide a reference for reservoir engineers who have an interest in investigating, checking the quality, and preparing relative permeability data set usable for reservoir simulation process. Introduction Special core analysis (SCAL) is the hub of the evaluation and management of hydrocarbon reservoirs. Relative permeability is one the main constituent of the SCAL which importance is widely recognized for the prediction of oil recovery during displacement by water. As any other piece of data, high quality and reliable relative permeability data set can reduce uncertainty in dynamic reservoir modelling and provide a sound foundation for reservoir engineering studies. Conversely, ppoor quality data can result in lost time due to rework and additional studies, inadequate development plans, and inefficient investment. Relative permeability curves can be generated from different sources such as mathematical models and experimental methods. However, experimental methods are more desirable for two reasons. First, they produce specific relative permeability relationships for specific reservoirs. Second, it is best available approach to resemble the flooding process in the field provided that the experiments performed on representative core samples and fluids from the reservoir under study. Therefore, our discussion will be restricted to relative permeability data are derived from laboratory experiments. The main challenge in the derivation process is how to obtain a reliable relative permeability data set. The term reliable will often be used in referring to relative permeability data set with is a good probability that the defined relationships are representative of the reservoir and inherently repeatable. Judgment regarding reliability will be made according to analysis of results that are judged to have been obtained using valid laboratory procedures. When the term valid is used in referring to laboratory measurements it will mean that none of the procedures used during the test are inconsistent with obtaining reliable results for the sample tested. For instance, the use of an extracted core plug with altered wettability other than the reservoir one would generally mean that the results are invalid. The source of unreliability may be attributed to the following reasons:The derived relative permeability data set are usually prone to excremental artefacts.The state of the experiment does not fit the model's assumptions used to derive the relative permeability data sets. In another word, the methods of calculating relative permeabilities from data obtained from displacement experiments don't describe all physical effects encountered in the experiment.