Abstract: Methods for interpreting pressure transient tests and predicting future production for a well are provided. In one embodiment, a method for predicting future production includes beginning a pressure transient test within a well at a wellsite and obtaining pressure measurements of well fluid during the pressure transient test. The method can also include using the obtained pressure measurements to determine probabilistic estimates of input parameters of a pressure transient reservoir model while continuing the pressure transient test. Future production from the well can then be estimated based on the probabilistic estimates of the input parameters. Other methods and systems are also disclosed.

Abstract: Methods for interpreting pressure transient tests and predicting future production for a well are provided. In one embodiment, a method for predicting future production includes beginning a pressure transient test within a well at a wellsite and obtaining pressure measurements of well fluid during the pressure transient test. The method can also include using the obtained pressure measurements to determine probabilistic estimates of input parameters of a pressure transient reservoir model while continuing the pressure transient test. Future production from the well can then be estimated based on the probabilistic estimates of the input parameters. Other methods and systems are also disclosed.

Abstract: A system and method to automate data acquisition in a wireless telemetry network optimizes data acquisition to best match a target data set that the user desires given the performance limitations of the telemetry network. The user defines the target data set by providing inputs regarding a target quality of the target data set relative to a data set that has been produced and stored by a communication node in the network. The performance limitations of the network are defined in a system operating envelope. A data acquisition cycle is then automatically initiated and propagated in the network to acquire an actual data set that is an optimal match for the user's target given the system operating envelope.

Abstract: A system and method to automate data acquisition in a wireless telemetry network optimizes data acquisition to best match a target data set that the user desires given the performance limitations of the telemetry network. The user defines the target data set by providing inputs regarding a target quality of the target data set relative to a data set that has been produced and stored by a communication node in the network. The performance limitations of the network are defined in a system operating envelope. A data acquisition cycle is then automatically initiated and propagated in the network to acquire an actual data set that is an optimal match for the user's target given the system operating envelope.

Abstract: A system and method to automate data acquisition in a wireless telemetry network optimizes data acquisition to best match a target data set that the user desires given the performance limitations of the telemetry network. The user defines the target data set by providing inputs regarding a target quality of the target data set relative to a data set that has been produced and stored by a communication node in the network. The performance limitations of the network are defined in a system operating envelope. A data acquisition cycle is then automatically initiated and propagated in the network to acquire an actual data set that is an optimal match for the user's target given the system operating envelope.

Abstract: A system and method to automate data acquisition in a wireless telemetry network optimizes data acquisition to best match a target data set that the user desires given the performance limitations of the telemetry network. The user defines the target data set by providing inputs regarding a target quality of the target data set relative to a data set that has been produced and stored by a communication node in the network. The performance limitations of the network are defined in a system operating envelope. A data acquisition cycle is then automatically initiated and propagated in the network to acquire an actual data set that is an optimal match for the user's target given the system operating envelope.

Abstract: Techniques for modelling a production forecast for a well are described. In one embodiment, a method includes calibrating a geological reservoir model by analyzing pressure transient well tests, fitting the geological reservoir model to pressure data to estimate model parameters, and building a simulated history of bottom hole pressure based on the model and measured transient flow data. The calibrating may further include fitting the model to flow rate data, using measured and simulated pressure data as input, to estimate model parameters, and then building a simulated history of downhole flow rate based on the model and change in measured pressure data. The calibrated model can be used to forecast future well production. Additional methods, systems, and devices are also disclosed.

Abstract: Methods for interpreting pressure transient tests and predicting future production for a well are provided. In one embodiment, a method for predicting future production includes beginning a pressure transient test within a well at a wellsite and obtaining pressure measurements of well fluid during the pressure transient test. The method can also include using the obtained pressure measurements to determine probabilistic estimates of input parameters of a pressure transient reservoir model while continuing the pressure transient test. Future production from the well can then be estimated based on the probabilistic estimates of the input parameters. Other methods and systems are also disclosed.

Abstract: Techniques for modelling a production forecast for a well are described. In one embodiment, a method includes calibrating a geological reservoir model by analyzing pressure transient well tests, fitting the geological reservoir model to pressure data to estimate model parameters, and building a simulated history of bottom hole pressure based on the model and measured transient flow data. The calibrating may further include fitting the model to flow rate data, using measured and simulated pressure data as input, to estimate model parameters, and then building a simulated history of downhole flow rate based on the model and change in measured pressure data. The calibrated model can be used to forecast future well production. Additional methods, systems, and devices are also disclosed.