International Business Machines Corporation

Pacific Northwest Division Batelle Memorial Institute

John Baxter Rollins

Frederick Davis Busche

Harold J Noyes

James G Bush

Curtis Richard Hale

James R Kraemer

Robert R Friedlander

Richard D Hennessy

Ramasubbu Venkatesh

Jo Arao Ramos

David Giddens Wilhite

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 system, method, and program product for interpreting, optimizing, and customizing data mining models through the use of statistical techniques that utilize diagnostic measures and statistical significance testing. A data processing system is disclosed that includes a data mining system for mining data from a data warehouse in accordance with a data model, wherein the data model defines how data groups can be partitioned; and a data group analysis system that calculates a set of diagnostic measures and performs statistical significance tests for a defined data group.

Data mining model interpretation, optimization, and customization using statistical techniques

An initial set of prospects in a customer database is identified, by data mining, as initially identified prospects based on predetermined selection criteria. The number of initially identified prospects is compared to a target number of prospects. When the number of initially identified prospects matches the target number of prospects, the initially identified prospects are utilized as the final selection of prospects. When the number of initially identified prospects mismatches the target number of prospects, the final selection of prospects is determined by performing a culling process or an augmenting process to reduce or increase, respectively, the initial set of prospects using a heuristic measure H, until the number of prospects in the initial set of prospects matches the target number of prospects.

Process and heuristic statistic for prospect selection through data mining

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

Methods and apparatus, including computer program products, implementing and using techniques for populating a data cache on a server. Data requests received by the server are collected in a repository. A data mining algorithm is applied to the collected data requests to predict a set of data that is likely to be requested during an upcoming time period. It is determined whether the complete set of predicted data exists in the data cache. If the complete set of predicted data does not exist in the data cache, the missing data is retrieved from a database and added to the data cache.

Smart data caching using data mining

A computer implemented method, apparatus, and computer usable program code for automatically selecting an optimal control cohort. Attributes are selected based on patient data. Treatment cohort records are clustered to form clustered treatment cohorts. Control cohort records are scored to form potential control cohort members. The optimal control cohort is selected by minimizing differences between the potential control cohort members and the clustered treatment cohorts.

System and method to optimize control cohorts using clustering algorithms

Method, system, and article of manufacture for selecting prospects for a product promotion though data mining. An initial set of prospects in a customer database is identified, by data mining, as initially identified prospects based on predetermined selection criteria. The number of initially identified prospects is compared to a target number of prospects. When the number of initially identified prospects matches the target number of prospects, the initially identified prospects are utilized as the final selection of prospects. When the number of initially identified prospects mismatches the target number of prospects, the final selection of prospects is determined by performing a culling process or an augmenting process to reduce or increase, respectively, the initial set of prospects using a heuristic measure H, until the number of prospects in the initial set of prospects matches the target number of prospects.

A method, apparatus, and computer instructions for direct linkage of relational database table to a data preparation tool for data preparation. In a preferred embodiment, the mechanism of the present invention allows data to be read directly from one or more relational database tables to a data preparation tool into datasets without generating output flat files. Multiple datasets from different relational database table are merged into one dataset if more than one relational database table is read. Upon completion of necessary data preparation on the dataset by the data preparation tool, the present invention creates a new relational database table and loads resulting data from the prepared dataset into the new relational database table.

Growing community of inventors

Southlake, TX, United States of America

John Baxter Rollins