Abstract: Drilling rig operations may be monitored using a variety of sensors and/or other data sources. Erroneous, faulty, and/or missing data may be cleansed prior to using the data for modeling and/or monitoring drilling operations. Erroneous, faulty, and/or missing data may be identified by comparing received data to anticipated values based on historical operations, other physically related sensor readings, and known operating ranges. Cleansing may comprise replacing erroneous, faulty, and/or missing data with a modeled value or omitting a reading entirely.

Abstract: Systems and methods for monitoring slide drilling operations and providing advisory information includes a Bayesian network having a slide drilling dysfunction output node and six input nodes including: a downhole mechanical specific energy (MSE) trend node; a downhole bit aggressiveness trend node; a differential pressure trend node; a minimum buckling load node; a downhole weight on bit (DWOB) vs surface weight on bit (SWOB) ratio node, and a toolface efficiency index node. When one or more dysfunctions are detected based on the information provided to one or more nodes, the system sends out one or more alerts and provides one or more corrective actions to return to efficient drilling.

Abstract: Drilling operations may be monitored to detect and quantify potential drilling dysfunctions. Using a Bayesian network, potential improvements to drilling operation may be made depending upon the type of dysfunction detected. Suggestions for improved drilling performance may comprise increasing, decreasing, or maintaining one or both of RPM and weight on bit. Suggestions may be presented to an operator as a cone having an apex at the current RPM and weight on bit drilling parameters, with suggestions for modifications to one or both of the RPM and weight on bit corresponding to a cone extending from that apex.

Abstract: A method for estimating the efficiency of hole cleaning of a well-bore during drilling operations includes (a) selecting at least one feature of the drilling operation for monitoring; (b) receiving, from a sensor, data regarding the at least one feature; (c) comparing the data to a predetermined condition for the at least one feature; (d) defining an event when the data meets the predetermined condition; (e) assigning a weight to the event based on a duration of the event; and (f) estimating an efficiency of the hole cleaning based on the event and the weight of the event. The at least one feature being selected from the list consisting of: hole angle, circulation, tight spot, static hole, and bit hydraulics.

Abstract: A method for estimating the efficiency of hole cleaning of a well-bore during drilling operations includes (a) selecting at least one feature of the drilling operation for monitoring; (b) receiving, from a sensor, data regarding the at least one feature; (c) comparing the data to a predetermined condition for the at least one feature; (d) defining an event when the data meets the predetermined condition; (e) assigning a weight to the event based on a duration of the event; and (f) estimating an efficiency of the hole cleaning based on the event and the weight of the event. The at least one feature being selected from the list consisting of: hole angle, circulation, tight spot, static hole, and bit hydraulics.

Abstract: Drilling rig operations may be monitored using a variety of sensors and/or other data sources. Erroneous, faulty, and/or missing data may be cleansed prior to using the data for modeling and/or monitoring drilling operations. Erroneous, faulty, and/or missing data may be identified by comparing received data to anticipated values based on historical operations, other physically related sensor readings, and known operating ranges. Cleansing may comprise replacing erroneous, faulty, and/or missing data with a modeled value or omitting a reading entirely.

Abstract: Drilling operations may be monitored to detect and quantify potential drilling dysfunctions. Using a Bayesian network, potential improvements to drilling operation may be made depending upon the type of dysfunction detected. Suggestions for improved drilling performance may comprise increasing, decreasing, or maintaining one or both of RPM and weight on bit. Suggestions may be presented to an operator as a cone having an apex at the current RPM and weight on bit drilling parameters, with suggestions for modifications to one or both of the RPM and weight on bit corresponding to a cone extending from that apex.

Abstract: A method, computer program product and system for presenting attributes of interest. A decision surface is created using process maps. The process maps are representative of system operational data from a plurality of sensors. A current operating point is identified including a location and a movement characteristic of the operating point. The location and the movement characteristic of the operating point are used to identify an attribute with a final probabilistic value assigned to the attribute. If the final probabilistic value for the attribute crosses a previously-defined threshold, an alarm is generated. The decision surfaces, the process maps, the current operating point, the predicted movement of the operating point, the attributes, and the alarms are visually represented in a data handling system to assist the operator in the real time monitoring and operation of the physical system.