An Improved Method of Clay-Induced Rock Typing Derived from Log Data in Modelling Low Salinity Water Injection: A Case Study on an Oil Field in Indonesia

Low salinity water injection (LSWI) is an emerging way to improve waterflood performance through chemical processes. The presence of clay minerals one the required parameters successfully implement LSWI in sandstone formations. ability clays exchange cations, represented by cation capacity (CEC), leads oil detachment from rock surface and changes formation wettability toward water-wet. There are still limited studies that discuss implementation specific CEC models field-scale reservoir simulation. This paper attempts propose improved method clay-induced typing can be representatively implemented for scope this study a field Indonesia. considered light, contains main minerals, including kaolinite illite, trace chlorite was also found XRD evaluation. derived log data, while type estimated data using artificial neural network method. finding combination those variables, i.e., properties, CEC, results characterize classify into three types associated with conventional types. classification obtained utilized as input advanced modeling, which expected provide more robust results. Furthermore, dispersed has strong influence on magnitude rather than laminar structural clays.