Nonlinear Model Predictive Pressure Control during Drilling Operations

Abstract

Drilling into mature, depleted fields is often difficult because of tight pressure margins. Increasing the pressure control will enable wells that previously were considered undrillable, to be drilled. Enabling drilling and increased oil recovery from depleted fields would most likely lead to a substantial increase in profit margains. A better pressure control will also increase the safety of the drilling crew, because the risk of unwanted situations such as a kick or a blow-out is decreased, also reducing the risk of unwanted environmental influence, e.g. oil spill. To compensate for the lack of a continuous measurement of the bottomhole pressure during drilling operations, an adpative observer of the bottomhole pressure is implemented. The observer implemented is tested, and shows promising results in estimating both the bottomhole pressure and the friction coefficient in the well during a pipe connection procedure. To control the pressure in the well, a low-order nonlinear model predicitve controller is developed, and it has been tested to perform well during the pipe connection procedure, where it maintains the pressure within the predefined boundaries. In this thesis both the obsever and the controller will be tested against an artificial well; simulated by a commercial software.