Mathematical model using machine learning boosts output offshore China
World Oil(2010)
Abstract
The resulting differential equations represent the process well enough to predict the status of the pumps up to four weeks in advance, allowing preventative maintenance to be performed. Each pump can be influenced via two major control variables: choke diameter and pump frequency. At the platform in Dagang Field, these parameters were controlled manually by operators. Observation results showed oscillations of parameters in a rough 8-hr pattern, corresponding to operator shifts, which supports the argument that a fluctuation in the knowledge and experience of human operators may lead to a fluctuation in decision making and, thus, in operation of the platform. The model does not allow us to understand the process inside the black box, but it does allow us to compute the output of the black box given a sample input. There are random and structured errors associated with the measurement process, and physical sensors drift with age and environmental effects.
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