APPLICATION ARTIFICIAL INTELLIGENCE TO EVALUATE GAS INITIAL IN PLACE ON RESERVOIR RGN
Fajar Putra Nugraha, Rini Setiati, Aqlyna Fattahanisa
Petroleum Engineering Departement, Faculty Of Earth Technology And Energy, Trisakti University, Jakarta
Abstract
Oil and gas industry is an industry with a high cost and high risk, artificial intelligence will help the work of humans to minimize the risk of accidents, reduce processing time and improve corporate profits. So the work becomes more efficient.The aims of the study give information that the artificial intelligence help the work to evaluate the initial gas in place on reservoir. Reservoir RGN has long produced, then it needs to be evaluated to find out how many initial gas in place is left in the reservoir. Additional research is needed to know the type of reservoir and drive mechanism.The method used is the research on reservoir RGN, the data used are based on real data in field.This research uses artificial intelligence MBAL and PVTP software, with the study of literature.Based on the research results obtained, this type of reservoir RGN is dry gas reservoir, with the drive mechanism is depletion drive. Initial gas reservoir RGN is 50,661.3 MMscf, with estimate ultimate recovery is 47,966.13 MMscf, recovery factor was 94.68% and the remaining reserve reservoir RGN in July 2018 is 10,850.386 MMscf or 10,85 Bscf.Artificial intelligence helps work, provides diverse outputs and the results obtained are more accurate and detailed
Keywords: original gas in place, artificial intelligence, PVTP, MBAL
Topic: Material Engineering