Abstract:
Techniques for predicting a failure metric of a physical system using a semiparametric model, including providing raw data representative of the physical system, to identify a set of units at risk in the physical system, a set of times of treatment corresponding to a event of at least one unit in the set of units, and an index- set of the at least one unit for which a event has occurred. A parametric and a nonparametric component of the semiparametric model are estimated and a hazard rate is predicted at a given time with the semiparametric model.
Abstract:
Systems and methods for allocating resources within an infrastructure, such as an electrical grid, in response to changes to inputs and output demands on the infrastructure, such as energy sources and sinks. A disclosed system includes one or more processors, each having respective communication interfaces to receive data from the infrastructure, the data comprising infrastructure network data, one or more software applications, operatively coupled to and at least partially controlling the one or more processors, to process and characterize the infrastructure network data; and a display, coupled to aid one or more processors, for visually presenting a depiction of at least a portion of the infrastructure including any changes in condition thereof, and one or more controllers in communication with the one or more processors, to manage processing of the resource, wherein the resource is obtained and/or distributed based on the characterization of said real time infrastructure data.
Abstract:
The invention utilizes 3-D and 4-D seismic surveys as a means of deriving information useful in petroleum exploration and reservoir management. The methods use both single seismic surveys (3-D) and multiple seismic surveys separated in time (4-D) of a region of interest to determine large scale migration pathways within sedimentary basins, and fine scale drainage structure and oil-water-gas regions within individual petroleum producing reservoirs. Such structure is identified using pattern recognition tools which define the regions of interest. The 4-D seismic data sets may be used for data completion for large scale structure where time intervals between surveys do not allow for dynamic evolution. The 4-D seismic data sets also may be used to find variations over time of small scale structure within individual reservoirs which may be used to identify petroleum drainage pathways, oil-water-gas regions and, hence, attractive drilling targets. After spatial orientation, and amplitude and frequency matching of the multiple seismic data sets, High Amplitude Event (HAE) regions consistent with the presence of petroleum are identified using seismic attribute analysis. High Amplitude Regions are grown and interconnected to establish plumbing networks on the large scale and reservoir structure on the small scale. Small scale variations over time between seismic surveys within individual reservoirs are identified and used to identify drainage patterns and bypassed petroleum to be recovered. The location of such drainage patterns and bypassed petroleum may be used to site wells.
Abstract:
A system for evaluating the accuracy of a predicted effectiveness of an Improvement to an infrastructure based on data collected from the infrastructure during a first time period before a change to an infrastructure has been implemented and a second time period after the change to the infrastructure has been implemented.
Abstract:
A machine learning system creates failure-susceptibility rankings for feeder cables in a utility's electrical distribution system. The machine learning system employs martingale boosting algorithms and Support Vector Machine (SVM) algorithms to generate a feeder failure prediction model, which is trained on static and dynamic feeder attribute data. Feeders are dynamically ranked by failure susceptibility and the rankings displayed to utility operators and engineers so that they can proactively service the distribution system to prevent local power outages. The feeder rankings may be used to redirect power flows and to prioritize repairs. A feedback loop is established to evaluate the responses of the electrical distribution system to field actions taken to optimize preventive maintenance programs.
Abstract:
Oil and gas horizons in a wellbore are located by establishing from thermal logs (T) thermal gradients (G) for successive intervals free of drilling-induced thermal disturbances, identifying the mineral abundances surrounding the wellbore at each of said intervals, establishing ideal thermal conductivities (TC) for said mineral abundances based on assumptions that sand-rich formations have high thermal conductivities and are water-bearing and that shale-rich formations have low thermal conductivities, determining an ideal heat flow (HF) at each interval by multiplying the thermal gradients (G) at such interval by the ideal thermal conductivity (TC) of the mineral abundances at the interval, determining the average ideal heat flow for all of the intervals, and identifying the zones of the wellbore exhibiting anomalous ideal heat flows that are higher than the average heat flow (AHF).
Abstract:
Techniques for managing one or more buildings, including collecting historical building data, real-time building data, historical exogenous data, and real-time exogenous data and receiving the collected data at an adaptive stochastic controller. The adaptive stochastic controller can generate at least one predicted condition with a predictive model. The adaptive stochastic controller can generate one or more executable recommendations based on at least the predicted conditions and one or more performance measurements corresponding to the executable recommendations.
Abstract:
Techniques for managing one or more buildings, including collecting historical building data, real-time building data, historical exogenous data, and real-time exogenous data and receiving the collected data at an adaptive stochastic controller. The adaptive stochastic controller can generate at least one predicted condition with a predictive model. The adaptive stochastic controller can generate one or more executable recommendations based on at least the predicted conditions and one or more performance measurements corresponding to the executable recommendations.
Abstract:
Techniques for generating a dynamic treatment control policy for a cyber- physical system having one or more components, including a data collector for collecting data representative of the cyber-physical system, and adaptive stochastic controller including one or more models for generating a predicted value corresponding to available actions based on an objective function, and an approximate dynamic programming element configured to receive actual operation metrics corresponding to the available actions. The approximate dynamic programming element can learn a state-action map and generate a dynamic treatment control policy using the one or more models.
Abstract:
A capital asset planning system for selecting assets for improvement within an infrastructure that includes data sources descriptive of the infrastructure, databases coupled to the one or more data sources, to compile the one or more data sources, processors coupled to and having respective communication interfaces to receive data from the databases The processor includes a predictor to generate a first metric of estimated infrastructure effectiveness based upon a current status of the infrastructure, a second metric of estimated infrastructure effectiveness based upon a user-selected, proposed changed configuration of the infrastructure, and a net metric of infrastructure effectiveness based upon said first metric and said second metric The system also includes a display, coupled to have the processors, for visually presenting the net metric of infrastructure effectiveness, in which the assets for improvement are selected based upon the net metric of infrastructure effectiveness