Abstract: Membranes used in membrane separation technologies change over time due to changes in physical characteristics of the membrane. Predicting remaining useful lifetime of a membrane is performed by fitting an evolution model of the membrane to real-time performance characteristics recorded for the membrane and by comparing later performance characteristics of the membrane to the evolution model. Updating an evolution model during membrane operation improves estimates of remaining useful membrane lifetime and allows for accurate estimates of estimated membrane end-of-life.

Abstract: Bayesian recursive estimation is used to analyze performance parameters of a membrane separation system based on historical operational data of a membrane system. Bayesian estimation considers historical data over prior time intervals to predict future membrane separation performance to avoid unexpected downtime and unanticipated maintenance. A set of state variables used for modeling performance is used with a degradation model of to anticipate performance changes and maintenance based on measured properties of permeate, non-permeate, and feed flows.

Abstract: A method is described herein, comprising registering an event at a first processing unit of a processing facility comprising a plurality of processing units, using a coincidence probability array and an event probability to identify a second processing unit of the plurality of processing units based on the event, determining whether the second processing unit experienced a coincident event, if the second processing unit experienced a coincident event, remediating a condition of the second processing unit that caused the coincident event, and updating the coincidence probability array based on the event.

Abstract: Systems and methods presented herein generally relate to greenhouse gas emission management and, more particularly, to greenhouse gas emission management systems and methods for performing greenhouse gas detection sensor placement planning, leakage source tracing, and quantification of leakage source detections for oil and gas production facilities.

Abstract: A method is described herein, comprising registering an event at a first processing unit of a processing facility comprising a plurality of processing units, using a coincidence probability array and an event probability to identify a second processing unit of the plurality of processing units based on the event, determining whether the second processing unit experienced a coincident event, if the second processing unit experienced a coincident event, remediating a condition of the second processing unit that caused the coincident event, and updating the coincidence probability array based on the event.

Abstract: Methods of operating membrane processes, such as seawater purification processes, are described herein. The methods generally include flowing seawater into a membrane purification process; recovering purified seawater and concentrated seawater from the membrane purification process; sensing operating parameters of the membrane purification process; determining a state of the membrane purification process from the operating parameters using a physical model; using a statistical model to resolve a time dependence of the state of the membrane purification process; using a recursive statistical process to update the statistical model; using the updated statistical model to predict a future state of the membrane purification process; comparing the predicted future state of the membrane purification process to a threshold state; and predicting a remaining time before the membrane purification process reaches the threshold state.

Abstract: Membranes used in membrane separation technologies change over time due to changes in physical characteristics of the membrane. Predicting remaining useful lifetime of a membrane is performed by fitting an evolution model of the membrane to real-time performance characteristics recorded for the membrane and by comparing later performance characteristics of the membrane to the evolution model. Updating an evolution model during membrane operation improves estimates of remaining useful membrane lifetime and allows for accurate estimates of estimated membrane end-of-life.

Abstract: Bayesian recursive estimation is used to analyze performance parameters of a membrane separation system based on historical operational data of a membrane system. Bayesian estimation considers historical data over prior time intervals to predict future membrane separation performance to avoid unexpected downtime and unanticipated maintenance. A set of state variables used for modeling performance is used with a degradation model of to anticipate performance changes and maintenance based on measured properties of permeate, non-permeate, and feed flows.