Abstract

Multi-mineral model based upon statistical inverse modelling of well log data is best suited for complex reservoirs which contain an appreciable amount of basement rock fragments apart from the sand, silt, clay, feldspar, mica etc. The rock fragments are not pure minerals but a combination of various minerals like quartz, feldspar, mica, chlorite etc in varying proportions. Hence, it becomes very difficult to assign processing parameters for rock fragments in a multi-mineral model. In the present study, an innovative technique for selection of processing parameters of rock fragments in Panna formation of main Heera field, Mumbai offshore, has been evolved. These parameters have been selected from in-situ log data acquired against the weathered basement section of wells drilled on the crestal part of main Heera field i.e the source of rock fragments. The approach has been successfully applied for data processing of 16 wells of Heera field out of which the results for three wells from different parts of the field are presented in the paper. The results of the study corroborated well with the core data and initial production testing data. The developed methodology will be helpful in realistic formation evaluation during future exploration and development of Panna formation in Heera field. The study can be extended to other similar reservoirs of interest also.