Predicting the Dynamometer Card of a Rod Pump

A rod pump is a simple device that is used the world over to pump for oil on land, see figures 1 and 2. Basically, we drill a hole into the ground and cement the hole (with a well casing)so that a nice vertical cavity results. Into this cavity a rod is inserted that is going to move up and down using a mechanical device that is called the rod pump. Attached to the bottom of the rod is a plunger that is a cylindrical “bottle” used to transport the oil. On the downward stroke, the plunger is allowed to be filled with oil, and on the upward stroke this oil is transported to the top where it is extracted and put into barrels.

For complete details on this case study, go to: Predicting the Dynamometer Card of a Rod Pump

Identifying and Predicting the Failure of Valves

A chemical plant has a particular unit that is meant to combine several chemicals from a variety of input sources in order to provide a gaseous output (called “tailgas”) with a composition that is as constant as possible. In our particular case, this task is run by an assembly of 40 valves that are controlled by a computer that opens and closes them according to a well-balanced schedule. If the valves do not open and close according to schedule, or if they are either too fast or slow, or if they leak, then the tailgas composition is not constant and causes problems later on in the process. In this study, we demonstrate how to predict future problems and to identify the valves responsible for recurring problems in the composition of the tailgas.

For complete details on this case study, go to: Identifying and Predicting the Failure of Valves

Predicting Vibration Crises in Nuclear Power Plants

In a nuclear power plant, if the vibration of the turbine axle exceeds a certain limit, we speak of a vibration crisis. It does not represent a real damage but it could, if left unchecked, lead to a major failure. The exact cause of the problem is not precisely identified at present but it always occurs during the same conditions of vacuum pressure and power, two essential measurements on the plant.

This study concerns itself with the prediction of future vibration crises and not with determining the mechanism that causes such vibrations. If one could know hours in advance that a crisis will happen, this would help operators to alleviate it: The plant can be regulated into a state more conducive to controlling the impending crisis.

For complete details on this case study, go to: Predicting Vibration Crises in Nuclear Power Plants

Catalytic Reactors in Chemistry and Petrochemistry

In a catalytic reactor, at least two substances are brought into contact with each other. One is a substance that we would like to change in some chemical way; and the other substance is the catalyst that is supposed to bring this change about. The two substances are mixed and heated to provide the energy for the change. It is also necessary to provide the plumbing for the substances to enter the reactor and for the end product to leave the reactor. Some parts that are not converted have to be re-cycled back for a second round (and possibly third and more rounds) through the reactor until all of the original substance has finally been transformed. One example for this process is the breaking down of the long molecular chains of crude oil in the effort to make gasoline.

As already indicated, the catalyst performs its work upon the substance and brings about a change. However, by doing so, it ages over time and thereby exhausts its potential to cause the change. This degradation of the catalyst is the primary problem in operating such a reactor continuously over the long term. The catalyst must therefore be re-activated in some fashion and at some time.

For complete details on this case study, go to: Catalytic Reactors in Chemistry and Petrochemistry

Wind Power Plant Failure Prediction

Wind power plants sometimes shut down due to diverse failure mechanisms and must therefore be maintained. These maintenance activities are costly due to logistics and delay-especially in the offshore sector.

It is possible to model dynamic evolving mechanisms of aging in a mathematical form so that a reliable prediction of a future failure can be computed. For example, we can say that a bearing will fail within 59 hours from now because the vibration will then exceed the allowed limits. This information allows a maintenance activity to be planned in advance and thus saves collateral damage and a longer outage.

For complete details on this case study, go to: Failures of Wind Power Plants

Prediction of Turbine Failure

It is possible to predict a turbine failure using historical data. On a particular turbine, a blade tore off and completely damaged the turbine, requiring extensive and expensive repair and replacement. After the event, the question was raised, whether or not this failure could have been predicted and localized to a specific place inside the turbine.

For complete details on this case study, go to: Prediction of Turbine Failure

Optimizing Chemical Processes

A chemical plants efficiency and profitability can be optimized using mathematical modeling. The optimization tells the plant operators which set-points should be modified in order to obtain maximum profitability. This method requires no engineering changes to be made to the plant whatsoever. In this case study we show that a profitability increase of approximately 6% was possible in a specific chemical plant producing silanes, with an overall yield increase o 5.1% and an increase o 2.9% or the most profitable end product.

For complete details on this case study, go to: Optimizing Chemical Processes

Increase of Oil Production Yield

Sometimes offshore oil wells break down and need repair such as when a pump fails. If spare parts are not readily available, this can cause unwanted downtime that is expensive in terms of yield failure and repair costs.We show how costs can be minimized by predicting the status of pumps up to four weeks in advance– allowing preventive maintenance to be performed. This is made possible by using a mathematical model of the pumping operation using automated machine learning methods. This method was applied to shallow-water offshore oil wells in the Dagang oilfield covering 34,629 km2in China. We consider data for 5 oil-wells of a shallow water oil-rig in Dagang operated by PetroChina.

For complete details on this case study, go to: Increase in Oil Production Yield

Reducing the Internal Demand of a Power Plant

A power plant uses up some of the electricity it produces for its own operations. In particular the pumps in the cooling system and the fans in the cooling tower use up significant amounts of electricity. It will increase the effective efficiency of the power plant if this internal electricity demand can be reduced.

For complete details on this case study, go to: Power Plant Demand Reduction