Abstract: A method of probabilistically estimating a velocity of a plunger of a beam pump may comprise continuously monitoring well acoustics using a plurality of passive acoustic sensors attached to external structures of the beam pump; digitizing outputs of the plurality of passive acoustic sensors and sending the digitized outputs to a computing device for storage and processing; and using the digitized outputs of the plurality of passive acoustic sensors, estimating a probability of the velocity of the plunger using a hidden Markov model (HMM) to represent a probability of a position and the probability of the velocity of the plunger, the HMM comprising a state space model and an observational model.

Abstract: A method of probabilistically estimating a velocity of a plunger of a beam pump may comprise continuously monitoring well acoustics using a plurality of passive acoustic sensors attached to external structures of the beam pump; digitizing outputs of the plurality of passive acoustic sensors and sending the digitized outputs to a computing device for storage and processing; and using the digitized outputs of the plurality of passive acoustic sensors, estimating a probability of the velocity of the plunger using a hidden Markov model (HMM) to represent a probability of a position and the probability of the velocity of the plunger, the HMM comprising a state space model and an observational model.

Abstract: A method of probabilistically estimating a velocity of a plunger of a beam pump may comprise continuously monitoring well acoustics using a plurality of passive acoustic sensors attached to external structures of the beam pump; digitizing outputs of the plurality of passive acoustic sensors and sending the digitized outputs to a computing device for storage and processing; and using the digitized outputs of the plurality of passive acoustic sensors, estimating a probability of the velocity of the plunger using a hidden Markov model (HMM) to represent a probability of a position and the probability of the velocity of the plunger, the HMM comprising a state space model and an observational model.

Abstract: A computer-implemented method may comprise attaching a plurality of wireless sensors to a pump jack; receiving time-stamped data from at least some of the plurality of wireless sensors attached to the pump jack, at least one of the plurality of wireless sensors comprising an accelerometer and a gyroscope and being attached to a crank arm of the pump jack; synchronizing the received time-stamped data; from the synchronized time-stamped data, calculating and generating information related to: a downhole load versus polished rod position of the pump jack; a relative balance of a counterweight of the pump jack relative to a horse head of the pump jack; deviations from a nominal acceleration profile of a bridle of the pump jack; and an angle of inclination of the bridle of the pump jack; and selectively generating, on a computing device, visualizations of the generated information.

Abstract: A computer-implemented method may comprise attaching a plurality of wireless sensors to a pump jack; receiving time-stamped data from at least some of the plurality of wireless sensors attached to the pump jack, at least one of the plurality of wireless sensors comprising an accelerometer and a gyroscope and being attached to a crank arm of the pump jack; synchronizing the received time-stamped data; from the synchronized time-stamped data, calculating and generating information related to: a downhole load versus polished rod position of the pump jack; a relative balance of a counterweight of the pump jack relative to a horse head of the pump jack; deviations from a nominal acceleration profile of a bridle of the pump jack; and an angle of inclination of the bridle of the pump jack; and selectively generating, on a computing device, visualizations of the generated information.

Abstract: A method of probabilistically estimating a velocity of a plunger of a beam pump may comprise continuously monitoring well acoustics using a plurality of passive acoustic sensors attached to external structures of the beam pump; digitizing outputs of the plurality of passive acoustic sensors and sending the digitized outputs to a computing device for storage and processing; and using the digitized outputs of the plurality of passive acoustic sensors, estimating a probability of the velocity of the plunger using a hidden Markov model (HMM) to represent a probability of a position and the probability of the velocity of the plunger, the HMM comprising a state space model and an observational model.

Abstract: A computer-implemented method may comprise attaching a plurality of wireless sensors to a pump jack; receiving time-stamped data from at least some of the plurality of wireless sensors attached to the pump jack, at least one of the plurality of wireless sensors comprising an accelerometer and a gyroscope and being attached to a crank arm of the pump jack; synchronizing the received time-stamped data; from the synchronized time-stamped data, calculating and generating information related to: a downhole load versus polished rod position of the pump jack; a relative balance of a counterweight of the pump jack relative to a horse head of the pump jack; deviations from a nominal acceleration profile of a bridle of the pump jack; and an angle of inclination of the bridle of the pump jack; and selectively generating, on a computing device, visualizations of the generated information.

Abstract: A computer-implemented method may comprise attaching a plurality of wireless sensors to a pump jack; receiving time-stamped data from at least some of the plurality of wireless sensors attached to the pump jack, at least one of the plurality of wireless sensors comprising an accelerometer and a gyroscope and being attached to a crank arm of the pump jack; synchronizing the received time-stamped data; from the synchronized time-stamped data, calculating and generating information related to: a downhole load versus polished rod position of the pump jack; a relative balance of a counterweight of the pump jack relative to a horse head of the pump jack; deviations from a nominal acceleration profile of a bridle of the pump jack; and an angle of inclination of the bridle of the pump jack; and selectively generating, on a computing device, visualizations of the generated information.