#TITLE_ALTERNATIVE#
In evaluating reservoir production prediction, sometimes a method is needed that can predict while considering the availability of time and resources, reliability and application of prediction. The capacitance-resistance model (CRM) came out as a rapid predictive model to study reservoir performance...
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| Format: | Final Project |
| Language: | Indonesia |
| Online Access: | https://digilib.itb.ac.id/gdl/view/26609 |
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| Institution: | Institut Teknologi Bandung |
| Language: | Indonesia |
| Summary: | In evaluating reservoir production prediction, sometimes a method is needed that can predict while considering the availability of time and resources, reliability and application of prediction. The capacitance-resistance model (CRM) came out as a rapid predictive model to study reservoir performance. In this study, the application of CRM is used as predictive model and evaluate waterflood performance. <br />
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CRM relies upon injection and production rate which are considered as input and output signals as well as CRM parameters such as inter-well connectivity and the effects of injection rates on production rates to develop a simple model for the reservoir. Solving history production/injection data will provide CRM parameters of inter-well connectivity and time constant. Implementation of solving the parameters is using generalized reduced gradient (GRG) nonlinear solver. We used a CRM calibrated with historical production/injection data. Thereafter, the model is used to optimize oil produced by reallocating water injection rates. <br />
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In this study, the application of CRM for oil production optimization are demonstrated in one synthetic field and two West Indonesia oilfield case studies. The result shows that the method is able to predict and moreover optimize oil produced by reallocating water injection rate. This work would demonstrate CRM using GRG nonlinear solver. |
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