Penerapan Sistem Analitik Untuk Data Bawah Permukaan Sebagai Penentu Kualitas Reservoir

Abstract

Oil and gas reserves in Indonesia have an important role in the lives of their people. Therefore, data on oil and gas reserves in Indonesia are very necessary. In addition, the quality of the reserves itself determines the development of the oil and gas industry going forward. Since the government has aggressively encourage the use of natural gas and at present the government does not yet have data on Indonesia's gas reserves efficiently, this study presents a concept so that the government can easily see the quality of gas reserves. In this study, data management was carried out by grouping raw data according to each category. The data calculated using the Bayesian statistical method. This statistical assessment is a prediction model or percentage of data quality trust and definition of limits in grouping data quality. The percentage number of the prediction model appears based on suggestions according to the user's perspective. Data quality prediction models determine the quality of the reservoir. The role of reservoir quality is very large in determining future business. The results of research conducted by researchers labeling the classification of well status of On Production produces a high average accuracy with 81% precision, 98% recall, and 89% f-measured.