Application of Simple Smart Logic for Waterflooding Reservoir Management

A simple smart logic for controlling inflow control valves (ICV) in waterflooding reservoir management is implemented and analyzed, with the final objective of improving the long term financial return of a petroleum reservoir. Such a control is based in a reactive simple logic that responds to the watercut measured in the ICV. Basically, when the watercut increases, the ICV is set to close proportionally. For comparison purposes, four strategies are presented: base case scenario with conventional control, the best completion configuration found by trial-and-error, the reactive control, and a deterministic optimal control based on Nonlinear Gradient Method with adjoint-gradient formulation is shown for comparison purposes. Finally, all four strategies are tested again in different reservoir realizations in order to mimic the geological uncertainties. Two different synthetic reservoir models were studied. First, a simple cube with a five-spot well configuration, in which the permeability field has a horizontal pattern defined by lognormal distributions. The second model is a benchmark proposed by the Dutch university, TU delft, with 101 channelized permeability fields representing river patterns. For the first model, no significant relative gain is found neither in the variable control nor in the optimal control. Manly because of the high homogeneity of the reservoir models. Therefore, no intelligent completion is recommended. On the other hand, for the second and more complex case, the results indicate an expressive relative gain in the use of simple reactive logic. Besides, this type of control achieves results nearly as good as the optimal control. The test in different realizations, however, shows that reservoir characterization is still a key part of any attempt to improve production. Although the variable reactive control is semi-independent, with action being taken based on measurements, some parameters need a priori model to be tuned

Application of Simple Smart Logic for Waterflooding Reservoir Management

A simple smart logic for controlling inflow control valves (ICV) in waterflooding reservoir management is implemented and analyzed, with the final objective of improving the long term financial return of a petroleum reservoir. Such a control is based in a reactive simple logic that responds to the watercut measured in the ICV. Basically, when the watercut increases, the ICV is set to close proportionally. For comparison purposes, four strategies are presented: base case scenario with conventional control, the best completion configuration found by trial-and-error, the reactive control, and a deterministic optimal control based on Nonlinear Gradient Method with adjoint-gradient formulation is shown for comparison purposes. Finally, all four strategies are tested again in different reservoir realizations in order to mimic the geological uncertainties. Two different synthetic reservoir models were studied. First, a simple cube with a five-spot well configuration, in which the permeability field has a horizontal pattern defined by lognormal distributions. The second model is a benchmark proposed by the Dutch university, TU delft, with 101 channelized permeability fields representing river patterns. For the first model, no significant relative gain is found neither in the variable control nor in the optimal control. Manly because of the high homogeneity of the reservoir models. Therefore, no intelligent completion is recommended. On the other hand, for the second and more complex case, the results indicate an expressive relative gain in the use of simple reactive logic. Besides, this type of control achieves results nearly as good as the optimal control. The test in different realizations, however, shows that reservoir characterization is still a key part of any attempt to improve production. Although the variable reactive control is semi-independent, with action being taken based on measurements, some parameters need a priori model to be tuned

An Online Model-Free Adaptive Tracking Controller for Cable-Driven Medical Continuum Manipulators

Continuum manipulators have demonstrated promising potential for flexible access and complicated operation and thus have been emerging and introduced in robot-assisted flexible endoscopy. However, due to their inherent structural compliance and strong nonlinearities, developing an accurate and robust control framework remains challenging. This paper proposes a model-free control method based on the Model-Free Adaptive Control (MFAC) algorithm to accomplish the trajectory tracking for two kinds of continuum manipulators by solely utilizing the robotic system’s real-time input/output data. The presented controller discretizes and dynamically linearizes the motion process of the continuum actuator to obtain a dynamic linearization data (DLD) model. This DLD model can be derived from a pseudo-partial derivative (PPD) matrix updated based on the I/O measurement data for the iterative operation. The stability of the presented MFAC controller can be mathematically guaranteed in theory to provide generality, and the control framework demonstrates a low computational cost and real-time control capability. The superior performance of the presented controller is firstly validated in MATLAB simulations and then compared with the other two controllers. Through experimental validation on two kinds of continuum manipulators, the model-free control framework shows high tracking accuracy and good robustness against the system uncertainty and external disturbances, as well as high transferability

Wearable exoskeleton systems based-on pneumatic soft actuators and controlled by parallel processing

Human assistance innovation is essential in an increasingly aging society and one technology that may be applicable is exoskeletons. However, traditional rigid exoskeletons have many drawbacks. This research includes the design and implementation of upper-limb power assist and rehabilitation exoskeletons based on pneumatic soft actuators. A novel extensor-contractor pneumatic muscle has been designed and constructed. This new actuator has bidirectional action, allowing it to both extend and contract, as well as create force in both directions. A mathematical model has been developed for the new novel actuator which depicts the output force of the actuator. Another new design has been used to create a novel bending pneumatic muscle, based on an extending McKibben muscle and modelled mathematically according to its geometric parameters. This novel bending muscle design has been used to create two versions of power augmentation gloves. These exoskeletons are controlled by adaptive controllers using human intention. For finger rehabilitation a glove has been developed to bend the fingers (full bending) by using our novel bending muscles. Inspired by the zero position (straight fingers) problem for post-stroke patients, a new controllable stiffness bending actuator has been developed with a novel prototype. To control this new rehabilitation exoskeleton, online and offline controller systems have been designed for the hand exoskeleton and the results have been assessed experimentally. Another new design of variable stiffness actuator, which controls the bending segment, has been developed to create a new version of hand exoskeletons in order to achieve more rehabilitation movements in the same single glove. For Forearm rehabilitation, a rehabilitation exoskeleton has been developed for pronation and supination movements by using the novel extensor-contractor pneumatic muscle. For the Elbow rehabilitation an elbow rehabilitation exoskeleton was designed which relies on novel two-directional bending actuators with online and offline feedback controllers. Lastly for upper-limb joint is the wrist, we designed a novel all-directional bending actuator by using the moulding bladder to develop the wrist rehabilitation exoskeleton by a single all-directional bending muscle. Finally, a totally portable, power assistive and rehabilitative prototype has been developed using a parallel processing intelligent control chip