International Business Machines Corporation

Pacific Northwest Division Batelle Memorial Institute

Frederick Davis Busche

John Baxter Rollins

Harold J Noyes

Alexander Darius Zekulin

James G Bush

Bhooshan Prafulla Kelkar

Jeffrey D Kish

Kirk A Boothe

William D Calkins

Shahinaz Nabih Carson

Scott L Swain

In one embodiment, the invention provides a system including at least one computing device for enhancing the recovery of heavy oil in an underground, near-surface crude oil extraction environment by performing a method comprising sampling and identifying microbial species (bacteria and/or fungi) that reside in the underground, near-surface crude oil extraction environment; collecting rock and fluid property data from the underground, near-surface crude oil extraction environment; collecting nutrient data from the underground, near-surface crude oil extraction environment; identifying a preferred microbial species from the underground, near-surface crude oil extraction environment that can transform the heavy oil into a lighter oil; identifying a nutrient from the underground, near-surface crude oil extraction environment that promotes a proliferation of the preferred microbial species; and introducing the nutrient into the underground, near-surface crude oil extraction environment.

Preparing near-surface heavy oil for extraction using microbial degradation

A supercomputer processing system is provided that is configured to execute a plurality of simulations through transaction processing. The supercomputer processing system includes a supercomputer configured to execute a first simulation of the plurality of simulations and generate an output based upon execution of the first simulation, and a transaction hub. The transaction hub includes a relational database configured to store the output of the first simulation, and an application server having a service-oriented architecture (SOA) that supports an event triggering service. The event triggering service is configured to detect the output of the first simulation and automatically trigger the supercomputer to execute a second simulation of the plurality of simulations using the output of the first simulation stored in the relational database.

Method and apparatus for executing multiple simulations on a supercomputer

A system and method for interpreting electrocardiogram data. A system is provided that clusters raw electrocardiogram (EKG) data into clusters of EKG data; generates a predictive model for each cluster of EKG data; compares inputted patient EKG data with the clusters of EKG data to identify a matching cluster of EKG data; applies the predictive model associated with the matching cluster of EKG data to the inputted patient EKG data; and outputs diagnostic data.

System and method for interpreting electrocardiograms

A system and method for enhancing the recovery of heavy oil in an oil extraction environment by feeding nutrients to a preferred microbial species (bacteria and/or fungi). A method is described that includes the steps of: sampling and identifying microbial species that reside in the oil extraction environment; collecting fluid property data from the oil extraction environment; collecting nutrient data from the oil extraction environment; identifying a preferred microbial species from the oil extraction environment that can transform the heavy oil into a lighter oil; identifying a nutrient from the oil extraction environment that promotes a proliferation of the preferred microbial species; and introducing the nutrient into the oil extraction environment.

System and method for preparing near-surface heavy oil for extraction using microbial degradation

A method and system for predicting customer behavior based on the geography of a data network are provided. Furthermore, a method and system for evaluating the training of a predictive algorithm to determine if the algorithm does not adequately take into consideration the influences of data network geography are also provided. The method and system generate frequency distributions of a customer database data set, training data set and testing data set and compare the frequency distributions of data network geographical characteristics to determine if there are discrepancies. If the discrepancies are above a predetermined tolerance, one or more of the data sets may not be representative of the customer database taking into account data network geographical influences on customer behavior. Thus, recommendations for improving the training data set and/or testing data set are then provided such that the data set is more representative of the data network geographical influences. Once trained, the predictive algorithm may be utilized to predict customer behavior taking into account the influences of data network geography.

Method and system for predicting customer behavior based on data network geography

A method and system for sample data selection to test and train predictive algorithm of customer behavior are provided. The method and system generate frequency distributions of a customer database data set, training data set and testing data set and compare the frequency distributions of geographical characteristics to determine if there are discrepancies. If the discrepancies are above a predetermined tolerance, one or more of the data sets may not be representative of the customer database taking into account geographical influences on customer behavior. Thus, recommendations for improving the training data set and/or testing data set are then provided such that the data set is more representative of the customer database. In this way, 'nuggeting' of customers is accounted for in the training and/or testing data sets.

Method and system for sample data selection to test and train predictive algorithms of customer behavior

An enhanced concern indicator failure prediction system is provided to predict possible product failures with automatic notification of people as well as systems. The system integrates data mining, spatial analysis, linear programming, narrowcasting, data warehousing, visualization, and text mining. As a result, failure conditions, attributes, complaints, locations, consequences, and sequence of events are analyzed using data mining technologies. This data is fed into an optimization module that assesses the efficiency of the failure process such that failures can be assessed as to their priority. These priorities are then used to feed a triggering engine that triggers notification of systems and individuals using narrowcasting technology. This system is one that allows early warning of potential problems to occur and integrates data from call centers, legacy systems, retailers, manufacturers, vendor supplied parts, and transportation of parts.

Enhanced concern indicator failure prediction system

A method and system for integrating spatial analysis, data mining analysis, and scheduling to efficiently schedule and monitor infrastructure maintenance is provided. The physical locations within a region of infrastructure repairs are identified and data values for characteristics of the infrastructure repairs are compiled and stored. Data mining algorithms are used to generate input data for the formulation of a set of spatial relationships. The locations of the infrastructure repairs within the region are associated with the locations of other infrastructure elements to form a set of spatial relationships. Spatial analysis techniques are used to provide understanding of this set of spatial relationships and how they relate to the location of infrastructure elements that are likely to require maintenance.

Method and system for integrating spatial analysis, and scheduling to efficiently schedule and monitor infrastructure maintenance

A method and system for ascertaining warranty issues associated with transportation products is provided. Transportation products are manufactured at a factory, and as the products are made, historical information concerning significant events related to the manufacturing process may be stored. As the transportation product is delivered to a retail outlet, other significant event information may be stored. Locations are determined within a region for warranty claims related to the servicing of selected transportation products. Product history information for the selected transportation products may be retrieved from one or more databases. Data mining algorithms may be employed to generate input data for forming a set of spatial relationships. The locations of products within the region are then associated with the product history information to form a set of spatial relationships. Product history information may include such information as purchaser address information, information related to manufacture of the selected transportation products, information related to transportation of the selected transportation products from a manufacturing site to a retail outlet, etc.

Method and system for integrating spatial analysis and data mining analysis to ascertain warranty issues associated with transportation products

A method and system for ascertaining relationships between collected geological samples and remotely sensed geological data within a region is provided. The locations of physical samples and the locations of data points associated with remotely sensed data are identified and stored. The locations within the region are determined using a position identifying system, such as the global positioning system. The collected physical samples are analyzed to obtain data values for physical and chemical properties of the collected samples. Data mining algorithms are used to generate input data for the formulation of a set of spatial relationships. The locations of the physical samples within the region are associated with the locations of the remotely sensed data to form a set of spatial relationships. Spatial analysis techniques are used to provide understanding of this set of spatial relationships and how they relate to the location of either an economically viable mineral resource or the position of hidden subsurface contaminants and the understanding of their potential migration paths.

Method and system for integrating spatial analysis and data mining analysis to ascertain relationships between collected samples and geology with remotely sensed data

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Highland Village, TX, United States of America

Frederick Davis Busche