Abstract: The invention relates to downhole motors for rotating drill bits. The downhole motors may comprise stators, turbines or the like. The drilling motor may comprise a drilling apparatus comprising a drill bit connected to a rotor rotatably housed within a stator (or a turbine rotor in a housing), the rotor comprising at least one magnetic field source or magnetic field detector, and the stator comprising at least one magnetic field source if the rotor comprises a magnetic field detector or comprising at least one magnetic field detector if the rotor comprises a magnetic field source, thereby allowing the rotation speed of the rotor relative to the stator to be measured.

Abstract: Optimising the operation of a hydraulically powered rotor and stator driven drill as it drills a wellbore into the earth is described. Drilling optimization is provided measuring a first set of rotor and stator operating parameters including the speed of rotation of the rotor and rotor torque for a first period of time, generating a first set of relationships from the first set of operating parameters to enable the rotor speed and rotor torque to be predicted over a range of operating parameter values, determining from the relationships a first more optimal mode of operation, and changing at least one operating parameter to move the operation of the rotor and stator towards the more optimal mode of operation.

Abstract: A method can include proposing a new well; accessing data associated with at least one other well where at least a portion of the data includes indicia of uncertainty; performing a geostatistical analysis of the accessed data for an issue for drilling of the new well to provide a probability of occurrence for the issue and an uncertainty for the accessed data; and rendering to a display a graphical representation of the well, the probability of occurrence for the issue and the uncertainty for the accessed data as a function of depth. Various other apparatuses, systems, methods, etc., are also disclosed.

Abstract: Embodiments of the present invention provide methods of using General Bayesian Networks to automate oilfield operations. In certain aspects, a Monte-Carlo method is used to propagate probability density functions for root-variables to continuous-valued hidden variables reflecting some oilfield operation properties. Evidence in the form of observed properties are used to weight samples used in the Monte-Carlo process thereby propagating the observed values onto other variables. The inferred probability distributions are provided to an oilfield control system or monitoring system.

Abstract: Systems, methods, and devices are provided for compressing a variety of signals, such as measured signals from a hydrocarbon operation, that may be stored and/or transmitted in compressed form. Segmentation tools and techniques are used to compress the signals. Segmentation techniques include breaking a signal into segments and representing the data samples of the signal as segment boundary points, which may reflect where changes occur in the signal, and segment parameters, which may be utilized to model the segmented data. Embodiments can be used in real-time or in batch modes. New data samples can influence previous segment boundary points and/or segment parameters in some cases. Systems may modify what has already been stored or displayed as a result in revising segmentation information based on analysis utilizing the new data samples. Embodiments may utilize different Bayesian analysis techniques including the use of prior probability distributions and maximum a posteriori analyses.

Abstract: A drill string suitable for use in directional drilling of a borehole, comprising a rotatable shaft at the leading end of which is a drill bit, and wherein the shaft comprises a variable friction inducing member, which provides rotational friction by physical contact with an inside face of the borehole, the friction inducing member being arranged to exert a first rotational frictional force when the shaft in the vicinity of the member is substantially rotating and a second rotational frictional force when the shaft in the vicinity of the member is substantially not rotating, wherein the first rotational frictional force is less than the second rotational frictional force.

Abstract: A method and system is disclosed for automatically correcting for depth errors in measurements taken from a drillstring during the drilling phase of the construction of a hydrocarbon wellbore. The correction is based on a stress profile which in turn is based on the states of the drilling rig, drill string description length spec, borehole description trajectory, friction factor and weight on bit.

Abstract: Embodiments of the present invention provide methods of using General Bayesian Networks to automate oilfield operations. In certain aspects, a Monte-Carlo method is used to propagate probability density functions for root-variables to continuous-valued hidden variables reflecting some oilfield operation properties. Evidence in the form of observed properties are used to weight samples used in the Monte-Carlo process thereby propagating the observed values onto other variables. The inferred probability distributions are provided to an oilfield control system or monitoring system.

Abstract: A method and system is disclosed for automatically correcting for depth errors in measurements taken from a drill-string during the drilling phase of the construction of a hydrocarbon wellbore. The correction is based on a stress profile which in turn is based on the states of the drilling rig, drill string description length spec, borehole description trajectory, friction factor and weight on bit.