The conventional approach of calibrating and updating well models is time consuming. Because of the dependency of the field optimization software on updated well models, the conventional approach reduces the frequency of implementing the optimizer's recommendations.
To operate their fields at their maximum deliverability, taking into consideration all the system constrains, a real-time software/workflow, Intelligent Daily Operation (IDO) was proposed and implemented to monitor, automatically calibrate and update well models.
The question is will IDO and other tools be able to address all these?
The objective of this work was to evaluate IDO and other real-time optimization (RTO) tools that are present in the company, and to identify effective ways of optimizing production using these applications. The workflow is as follows:
Identify critical steps in the current workflow that can be improved by switching over to real time mode. Review the tools that are available for real time performance surveillance and optimization. Identify the scope and limitations of IDO. Suggest ways of using field data source to monitor/validate result of IDO. Identify gaps and suggest ways of closing the optimization cycle.
The study reveals; average monthly savings of 380 engineering hours, achievement of daily update of well models as a result of implementation of RTO tools and after full implementation of RTO applications, monthly implementation of optimizer's recommendation will also be attained.
Certain limitations of the RTO were also identified, it includes inability of the models to match field operating conditions, possibility of erroneous readings from the multiphase meters, on which the production allocation function of the RTO applications depend.
The work further makes suggestions on how to use to the RTO applications for early detection of unhealthy wells, which improves efficiency.
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