digilib@itb.ac.id +62 812 2508 8800

An electrical submersible pump (ESP) is one of the artificial lift methods that is commonly used in mature oil fields. Considering its smaller surface footprint and ability to support higher production rates with higher water cuts than other artificial lift methods, this equipment is often selected for an artificial lift for the oil wells at some point in its life cycle. However, costs related to pump failure and workover are expected to be millions of dollars annually if it happens. It has become crucial to monitor the pump in real-time to prevent the impending failure of the pumps. The ammeter chart is the earliest diagnostic tool for ESP performance. After that, the downhole measurements were utilized to get more precise downhole conditions. Furthermore, for more robust diagnostics tools, the operator often combines an ammeter chart, downhole sensor data, and well-test data. However, it has a lot of information to be evaluated for one pump at one time. For one pump, seven parameters must be evaluated which are average ampere, flow rate, motor temperature, intake temperature, discharge pressure, intake pressure, and vibration. If one pump is required to evaluate seven parameters, then for a whole field, let’s say 300 wells, it is required to evaluate 2100 parameters at a single time. In this study, an algorithm is built to generate a single parameter that could be used to detect the operating condition of the pump which is normal or not. The seven parameters the pump used as input to the algorithm, then the algorithm generates a single parameter at a single time. Therefore, to monitor a field with 300 wells, it is only required to evaluate 300 parameters, seven times less than conventional way. This study used fourteen datasets from fourteen different wells in one of the fields in Indonesia. The model was verified by real pump conditions, then the model results are compared with ammeter chart and downhole sensor. At the end of the study, real-time electrical submersible pump monitoring dashboard is simulated with one of the datasets. This study concludes that the new parameter is as sensitive as downhole sensor but simple to monitor as well as ammeter chart.