Sas Institute Inc.

James Duarte

David Pope

Moray L Laing

Keith R Holdaway

Thomas Dale Anderson

Milad Falahi

A computing device configured to determine an optimal value for a control of a drilling operation is provided. An event stream processing engine (ESPE) instantiated. The ESPE is instantiated to execute an objective function model determined using historical drilling data. The objective function model maximizes a rate of penetration for a previous drilling operation. The historical drilling data includes a plurality of values measured for each of a plurality of drilling control variables during the previous drilling operation. Measured drilling data that includes current drilling data values for a current drilling operation is received by the ESPE. The received, measured drilling data is processed through the ESPE instantiated to execute the objective function model to determine an optimal value for a control of the current drilling operation. The determined optimal value is output by the ESPE for the control of the current drilling operation.

Control variable determination to maximize a drilling rate of penetration

A computing device predicts a probability of a transformer failure. An analysis type indicator defined by a user is received. A worth value for each of a plurality of variables is computed. Highest worth variables from the plurality of variables are selected based on the computed worth values. A number of variables of the highest worth variables is limited to a predetermined number based on the received analysis type indicator. A first model and a second model are also selected based on the received analysis type indicator. Historical electrical system data is partitioned into a training dataset and a validation dataset that are used to train and validate, respectively, the first model and the second model. A probability of failure model is selected as the first model or the second model based on a comparison between a fit of each model.

Electrical transformer failure prediction

A method of determining an optimal value for a control of a drilling operation is provided. Drilling data from a drilling operation is received. The drilling data includes a plurality of values measured for each of a plurality of drilling control variables during the drilling operation. An objective function model is determined using the received drilling data. The objective function model maximizes a rate of penetration for the drilling operation. Measured drilling data is received that includes current drilling data values for a different drilling operation. An optimal value for a control of the different drilling operation is determined by executing the determined objective function model with the measured drilling data that includes the current drilling data values for the different drilling operation as an input. The determined optimal value for the control of the different drilling operation is output.

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Clermont, FL, United States of America

James Duarte