Patents by Inventor Roberto Valerio Molina

Roberto Valerio Molina has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Method and system for predicting a drill string stuck pipe event
    Patent number: 8752648
    Abstract: Predicting a drill string stuck pipe event. At least some of the illustrative embodiments are methods including: receiving a plurality of drilling parameters from a drilling operation; applying the plurality of drilling parameters to an ensemble prediction model comprising at least three machine-learning algorithms operated in parallel, each machine-learning algorithm predicting a probability of occurrence of a future stuck pipe event based on at least one of the plurality of drilling parameters, the ensemble prediction model creates a combined probability based on the probability of occurrence of the future stuck pipe event of each machine-learning algorithm; and providing an indication of a likelihood of a future stuck pipe event to a drilling operator, the indication based on the combined probability.
    Type: Grant
    Filed: October 26, 2012
    Date of Patent: June 17, 2014
    Assignee: Landmark Graphics Corporation
    Inventors: Thomas Goebel, Roberto Valerio Molina, Ricardo Vilalta, Kinjal Dhar Gupta
  • METHOD AND SYSTEM FOR PREDICTING A DRILL STRING STUCK PIPE EVENT
    Publication number: 20140110167
    Abstract: Predicting a drill string stuck pipe event. At least some of the illustrative embodiments are methods including: receiving a plurality of drilling parameters from a drilling operation; applying the plurality of drilling parameters to an ensemble prediction model comprising at least three machine-learning algorithms operated in parallel, each machine-learning algorithm predicting a probability of occurrence of a future stuck pipe event based on at least one of the plurality of drilling parameters, the ensemble prediction model creates a combined probability based on the probability of occurrence of the future stuck pipe event of each machine-learning algorithm; and providing an indication of a likelihood of a future stuck pipe event to a drilling operator, the indication based on the combined probability.
    Type: Application
    Filed: October 26, 2012
    Publication date: April 24, 2014
    Applicant: LANDMARK GRAPHICS CORPORATION
    Inventors: Thomas Goebel, Roberto Valerio Molina, Ricardo Vilalta, Kinjal Dhar Gupta