Open AccessDEVELOPMENT OF PRODUCTION RATE DECLINE-BASED SOFTWARE FOR RESERVOIR PERFORMANCE PREDICTION
Author(s) -
Innocent O. Oboh,
Anietie N. Okon,
Hocaha F. Enyi
Publication year - 2019
Publication title -
international journal of research - granthaalayah
Language(s) - English
Resource type - Journals
eISSN - 2394-3629
pISSN - 2350-0530
DOI - 10.29121/granthaalayah.v7.i6.2019.749
Subject(s) - software , software development , computer science , software sizing , production (economics) , inflow , reliability engineering , software construction , engineering , operating system , economics , macroeconomics , physics , mechanics
The need for predicting the performance of hydrocarbon reservoirs has led to the development of a number of software in the Petroleum industry. Lots of these available software handled virtually all tasks in reservoir engineering ranging from estimation, forecasting, history matching, among others. That notwithstanding, improvements on these software are still been made and newer versions are released to meet users’ requirements. In this work, software “ULTIMATE” was developed based on production rate decline analysis to predict reservoir performance. Also, the developed software “ULTIMATE” handles Inflow Performance Relationship (IPR) prediction. The developed software prediction based on data obtained from two wells were compared with another software MBAL 10.5 developed by petroleum Experts Limited. The results of the comparison indicated that the developed ULTIMATE software predictions were very close to the MBAL 10.5 predictions. Additionally, the incorporated parallel algorithm in the ULTIMATE software enables it to analyze more wells and with more speed than the other software (MBAL 10.5). Therefore, the developed ULTIMATE software can be use as quick tool for predicting reservoir performance based on production rate decline analysis. Furthermore, the developed software would be improved to handle reservoir performance predictions based on Materials Balance Equation (MBE), and other production rate-related predictions like coning parameters estimation.