keywords: Jupyter notebook, Crossplot, Hydrocarbon, Reservoirs Characterization
Python language was used on Jupyter note book to cross plot rock properties for lithology and fluid discrimination by engaging well datasets from a given Niger Delta oil field. The data used for the analysis consist of suites of one well which included gamma ray logs, velocity log, resistivity and caliper log and some derived logs. Sand lithology showed low gamma ray, high resistivity and low acoustic impedance. After the cross plotting was carried out, the plots with the most outstanding results were λρ Versus Vp/Vs, μρ against Density and λρ versus μρ. For the oil well considered, one reservoir was observed at a depth of 2774 meters to 2835 meters (9100 ft. to 9300 ft.). Crossplotting of rock properties discriminated the lithology into sand and shale, which is typical of Niger Delta Region in South-South Nigeria. The crossplot also discriminated the fluids into gas, brine and oil. This study has been able to show that an open source program (Python) which is easily available and accessible online, can be engaged in carrying out hydrocarbon reservoirs characterization study, in lieu of the proprietary software that are popularly used in the industries but often difficult to access by academic researchers.