Learning Decentralized Linear Quadratic Regulator with T\sqrt{T} Regret

We study the problem of learning decentralized linear quadratic regulator when the system model is unknown a priori. We propose an online learning algorithm that adaptively designs a control policy as new data samples from a single system trajectory become available. Our algorithm design uses a disturbance-feedback representation of state-feedback controllers coupled with online convex optimization with memory and delayed feedback. We show that our controller enjoys an expected regret that scales as $\sqrt{T}$ with the time horizon $T$ for the case of partially nested information pattern. For more general information patterns, the optimal controller is unknown even if the system model is known. In this case, the regret of our controller is shown with respect to a linear sub-optimal controller. We validate our theoretical findings using numerical experiments

The Particle Swarm Optimization Algorithm with Adaptive Chaos Perturbation

Aiming at the two characteristics of premature convergence of particle swarm optimization that the particle velocity approaches 0 and particle swarm congregate, this paper learns from the annealing function of the simulated annealing algorithm and adaptively and dynamically adjusts inertia weights according to the velocity information of particles to avoid approaching 0 untimely. This paper uses the good uniformity of Anderson chaotic mapping and performs chaos perturbation to part of particles based on the information of variance of the population’s fitness to avoid the untimely aggregation of particle swarm. The numerical simulations of five test functions are performed and the results are compared with several swarm intelligence heuristic algorithms. The results shows that the modified algorithm can keep the population diversity well in the middle stage of the iterative process and it can improve the mean best of the algorithm and the success rate of search

Prediction of Pressure Gradient in Two and Three-phase Flows in Horizontal Pipes Using an Artificial Neural Network Model

Concurrent flow of gas with a mixture of oil and water in production equipment is common necessitating the need for additional investigations to gain more insight and development of more accurate correlations for prediction of flow characteristics including pressure drop. In this study, an experimental study was conducted using air-water and air-water-oil mixtures in a 0.075-m diameter pipe. Superficial gas and liquid velocities ranged from 0.03 to 0.13 m/s and 1.26 to 41.58 m/s respectively. Slug flow was the main flow pattern observed. In addition, transition to annular and annular flow were also observed. Due to the homogeneous nature of the oil-water-air mixture, the three-phase flow was evaluated as a pseudo-two-phase mixture. An Artificial Neural Network (ANN) model developed for the prediction of two- and three- phase pressure drop performed better than all models considered during the evaluation. Generally, it is found that the accuracies for pressure drop were considered adequate

Upward interfacial friction factor in gas and high-viscosity liquid flows in vertical pipes

In this study, experiments were carried out in a vertical 60-mm internal diameter pipe with air and oil (viscosities 100–330 mPa s) constituting the gas and liquid phases. Superficial air and oil velocity ranges used were 9.81–59.06 m/s and 0.024–0.165 m/s, respectively. Visual observations and change in slope of pressure drop–Vsg plot were used to identify flow pattern transition to annular flow. Using the experimental data as well as other reported data, a new correlation to predict interfacial friction factor in upward gas–viscous liquid annular flow regime was developed. Compared to the performance of 16 existing correlations using higher viscosity liquids, that of the new correlation was better. The performance of another correlation we derived for predictions at both low and higher low viscous showed good agreement with measurements. In addition, a neural network model to predict the interfacial friction factor involving both low and high viscous liquids was developed and it excellently described the experimental data

Experimental study of horizontal two- and three-phase flow characteristics at low to medium liquid loading conditions

Anexperimental study is conducted using a 0.075-m ID pipe to investigate characteristics of two-and three-phase stratified flow in a horizontal pipeline. Experiments are conducted under low to medium liquid loading conditions which is common in wet-gas andlongtransportation pipelines. The flow characteristics investigated include flow pattern, liquid holdup and pressure drop. The experimental range covers superficial gas Reynolds numbers from 6314 to 200,734, superficial liquid Reynolds numbers from 160 to4391andwater-cut values from 0 to90%.Differential pressure transducers, quick closing valves and a high-speed camera are utilized to obtain the relevant data and the trends investigated. The observed flow patterns are stratified smooth, stratified wavyandstratified-annular flow. The transitions between flow patterns vary as a function of water-cut. The effect of water-cut on liquid holdup and pressure drop were relatively negligible especially at low water-cut conditions and the fine mixing of the oilwater mixture may bepartially responsible for this. As a result, with the exception offlow pattern transitions, the performances of classical two-phase flow models (for the prediction of liquid holdup and pressure drop) appear unaffected when applied to airoil–water 3-phase flows especially at high water-cuts

Experimental Study, Characterization and Application of Starch-Graft-Acrylamide Gel for Plugging

During underbalance drilling, completion and workover wells, plugging channeling, blocking preformation and plugging formation water are inevitable problems. Gel is one of the most effective and convenient method to solve the problem. In this study, modified starch gel is synthesized, investigated experimentally and improved for efficient oil and gas field applications. The gel slurry is composed of starch (3.6 wt.%), initiator (0.02 wt.%), acrylamide (14.4 wt.%), cross-linking agent (4.7 wt.%), all of the components are mixed together with water at pH 10 – 11 which viscosity is as low as 35 – 82 mPa.s and desired to form gel. Here the effects of the components, reaction temperature and pH on gelation time and gel viscosity are systematically investigated, and the results showed that the gelation can be controlled in a wide range 30 – 120 min efficiently by pH and initiator. Fourier Transform Infrared Spectroscopy (FTIR) and Scanning Electron Microscope (SEM) are employed to study the molecular structure and microstructure of the gel, respectively. A compact three-dimensional network structure was formed in the gel, which contribute to a good adhesion. The gel has been successfully used in shale gas field which provides a reference for sealing other similar high formation pressure under unbalanced workover treatment. DOI: http://dx.doi.org/10.5755/j01.ms.24.4.18565</p

A two-fluid model for high-viscosity upward annular flow in vertical pipes

Proper selection and application of interfacial friction factor correlations has a significant impact on prediction of key flow characteristics in gas–liquid two-phase flows. In this study, experimental investigation of gas–liquid flow in a vertical pipeline with internal diameter of 0.060 m is presented. Air and oil (with viscosities ranging from 100–200 mPa s) were used as gas and liquid phases, respectively. Superficial velocities of air ranging from 22.37 to 59.06 m/s and oil ranging from 0.05 to 0.16 m/s were used as a test matrix during the experimental campaign. The influence of estimates obtained from nine interfacial friction factor models on the accuracy of predicting pressure gradient, film thickness and gas void fraction was investigated by utilising a two-fluid model. Results obtained indicate that at liquid viscosity of 100 mPa s, the interfacial friction factor correlation proposed by Belt et al. (2009) performed best for pressure gradient prediction while the Moeck (1970) correlation provided the best prediction of pressure gradient at the liquid viscosity of 200 mPa s. In general, these results indicate that the two-fluid model can accurately predict the flow characteristics for liquid viscosities used in this study when appropriate interfacial friction factor correlations are implemented

The Thermal Gelation Behavior and Performance Evaluation of High Molecular Weight Nonionic Polyacrylamide and Polyethyleneimine Mixtures for In-Depth Water Control in Mature Oilfields

A delayed crosslinked polymer gel was developed for in-depth water control in mature oilfields. The thermal gelation behavior of nonionic polyacrylamide (NPAM) and PEI was investigated, and sodium citrate (NaCit) was selected as a new retarder to prolong the gelation time. The gelation performance of NPAM/PEI gel system can be adjusted by varying NPAM or PEI concentration, and a quadratic model is developed by statistical analysis, which predicts the gelation time of NPAM/PEI gel system. The obtained model shows high significance and good reliability, as suggested by the F-ratio of 175.16 and high adjusted R-square value (0.9732). The addition of NaCit exhibits a good delayed gelation effect on the NPAM/PEI gel system, better than that of NaCl. The decrease of the initial pH value of the gelling solution leads to the weaker gel viscosity and longer gelation time due to the protonation of amine groups on the PEI chains. Increasing temperature results in higher gel viscosity but shorter gelation time. The gel system in the presence of NaCit exhibits good compatibility with injection and formation water. A dense three-dimensional structure was observed in matured NPAM/PEI/NaCit gel, and it could keep stable below 160 &deg;C. The gel system could effectively reduce the permeability (&gt;95%) and restricted the flow of water after matured in natural cores

Shale Gas Productivity Prediction Model Considering Time-Dependent Fracture Conductivity

Conventional shale gas productivity prediction techniques consider fracture conductivity to be a fixed value, but in actual production processes, conductivity changes with time. Therefore, this paper proposed a capacity prediction method that considers time-dependent conductivity and validates its accuracy using commercial simulators. First, relevant parameters were obtained by fitting the improved long-term conductivity test, and then the shale gas seepage model was established using the EDFM method. The laboratory test results showed that the order of significance affecting the conductivity retention rate was fracturing fluid viscosity &gt; sand concentration &gt; fracturing fluid retention time; the calculation results of the production prediction model show that the flow and the pressure curves that corresponded to constant conductivity and variable conductivity were to some extent different. In the presence of complex fractures and natural fractures, the increase in the variable conductivity production curve was smaller than that of the constant conductivity production curve. This study provides some guidance for field production