An Experimental and Numerical Investigation into Permeability and Injectivity Changes during CO2 Storage in Saline Aquifers

CO2 storage appears as one of the best solutions to effectively decrease carbon emissions into the atmosphere in the short to medium term. CO2 can be stored in different types of geological formations. Among the various storing options, deep saline aquifers have the greatest capacity. As supercritical CO2 is injected in the aquifers, a number of strongly coupled chemical and physical processes occur. Among these various mechanisms, dissolution and precipitation of minerals, in particular carbonates, and halite deposition due to vapourisation of water require particular attention as they can lead to significant reduction in injectivity. This research investigated the mechanisms involved in injectivity losses through experimental and theoretical methods. The impact on injectivity of permeability changes occurring at various distances from the wellbore was studied using an idealised 1-D CO2 injection well flow model. A new experimental set-up was used to investigate the effect on dissolution/precipitation mechanisms of the pressure and temperature changes that the fluid is subjected to as it advances from the wellbore. Additional CO2 core flooding experiments were conducted on limestone and sandstone cores saturated with saline water in order to study the effects of water vapourisation. These vapourisation experiments aimed to provide a relationship between porosity changes and resulting permeability variations representing the effect of salt precipitation due to vapourisation. Such relationship was used to obtain more accurate results from a 2-D radial CO2 injection well flow model studying the effect of salt precipitation on the field. Numerical modelling of the injection wellbore have shown that changes in the petrophysical properties of the reservoir several metres away from the wellbore can still have a significant impact on injectivity. As indicated by the experimental research carried out, pressure and temperature gradients that exist inside the reservoirs may lead to re-precipitation in the far field, however no significant permeability and porosity changes were detected to suggest major losses of injectivity due to these effects. The results of vapourisation experiments have shown that small reduction in porosity can induce significant impairments in permeability. Results of the 2-D model showed that without appropriate injection strategies the technical and economical feasibility of CO2 storage projects can be compromised due to this effect. The numerical study also highlighted the possibility of the progressive formation of a layer of halite scaling in the interface between host-rock and cap-rock which would work as an extra sealing protection in the near wellbore area

Understanding Game Theory via Wireless Power Control

In this lecture note, we introduce the basic concepts of game theory (GT), a branch of mathematics traditionally studied and applied in the areas of economics, political science, and biology, which has emerged in the last fifteen years as an effective framework for communications, networking, and signal processing (SP). The real catalyzer has been the blooming of all issues related to distributed networks, in which the nodes can be modeled as players in a game competing for system resources. Some relevant notions of GT are introduced by elaborating on a simple application in the context of wireless communications, notably the power control in an interference channel (IC) with two transmitters and two receivers.Comment: Accepted for publication as lecture note in IEEE Signal Processing Magazine, 13 pages, 4 figures. The results can be reproduced using the following Matlab code: https://github.com/lucasanguinetti/ ln-game-theor

Distributed Power Control Techniques Based on Game Theory for Wideband Wireless Networks

This thesis describes a theoretical framework for the design and the analysis of distributed (decentralized) power control algorithms for high-throughput wireless networks using ultrawideband (UWB) technologies. The tools of game theory are shown to be expedient for deriving scalable, energy-efficient, distributed power control schemes to be applied to a population of battery-operated user terminals in a rich multipath environment. In particular, the power control issue is modeled as a noncooperative game in which each user chooses its transmit power so as to maximize its own utility, which is defined as the ratio of throughput to transmit power. Although distributed (noncooperative) control is known to be suboptimal with respect to the optimal centralized (cooperative) solution, it is shown via large-system analysis that the game-theoretic distributed algorithm based on Nash equilibrium exhibits negligible performance degradation with respect to the centralized socially optimal configuration. The framework described here is general enough to also encompass the analysis of code division multiple access (CDMA) systems and to show that UWB slightly outperforms CDMA in terms of achieved utility at the Nash equilibrium

Energy-Aware Competitive Power Allocation for Heterogeneous Networks Under QoS Constraints

This work proposes a distributed power allocation scheme for maximizing energy efficiency in the uplink of orthogonal frequency-division multiple access (OFDMA)-based heterogeneous networks (HetNets). The user equipment (UEs) in the network are modeled as rational agents that engage in a non-cooperative game where each UE allocates its available transmit power over the set of assigned subcarriers so as to maximize its individual utility (defined as the user's throughput per Watt of transmit power) subject to minimum-rate constraints. In this framework, the relevant solution concept is that of Debreu equilibrium, a generalization of Nash equilibrium which accounts for the case where an agent's set of possible actions depends on the actions of its opponents. Since the problem at hand might not be feasible, Debreu equilibria do not always exist. However, using techniques from fractional programming, we provide a characterization of equilibrial power allocation profiles when they do exist. In particular, Debreu equilibria are found to be the fixed points of a water-filling best response operator whose water level is a function of minimum rate constraints and circuit power. Moreover, we also describe a set of sufficient conditions for the existence and uniqueness of Debreu equilibria exploiting the contraction properties of the best response operator. This analysis provides the necessary tools to derive a power allocation scheme that steers the network to equilibrium in an iterative and distributed manner without the need for any centralized processing. Numerical simulations are then used to validate the analysis and assess the performance of the proposed algorithm as a function of the system parameters.Comment: 37 pages, 12 figures, to appear IEEE Trans. Wireless Commu

Energy-Efficient Power Control for Contention-Based Synchronization in OFDMA Systems with Discrete Powers and Limited Feedback

This work derives a distributed and iterative algorithm by which mobile terminals can selfishly control their transmit powers during the synchronization procedure specified by the IEEE 802.16m and the 3GPP-LTE standards for orthogonal frequency-division multiple-access technologies. The proposed solution aims at maximizing the energy efficiency of the network and is derived on the basis of a finite noncooperative game in which the players have discrete action sets of transmit powers. The set of Nash equilibria of the game is investigated, and a distributed power control algorithm is proposed to achieve synchronization in an energy-efficient manner under the assumption that the feedback from the base station is limited. Numerical results show that the proposed solution improves the energy efficiency as well as the timing estimation accuracy of the network compared to existing alternatives, while requiring a reasonable amount of information to be exchanged on the return channel

Energy-Efficient Power Control: A Look at 5G Wireless Technologies

This work develops power control algorithms for energy efficiency (EE) maximization (measured in bit/Joule) in wireless networks. Unlike previous related works, minimum-rate constraints are imposed and the signal-to-interference-plus-noise ratio takes a more general expression, which allows one to encompass some of the most promising 5G candidate technologies. Both network-centric and user-centric EE maximizations are considered. In the network-centric scenario, the maximization of the global EE and the minimum EE of the network are performed. Unlike previous contributions, we develop centralized algorithms that are guaranteed to converge, with affordable computational complexity, to a Karush-Kuhn-Tucker point of the considered non-convex optimization problems. Moreover, closed-form feasibility conditions are derived. In the user-centric scenario, game theory is used to study the equilibria of the network and to derive convergent power control algorithms, which can be implemented in a fully decentralized fashion. Both scenarios above are studied under the assumption that single or multiple resource blocks are employed for data transmission. Numerical results assess the performance of the proposed solutions, analyzing the impact of minimum-rate constraints, and comparing the network-centric and user-centric approaches.Comment: Accepted for Publication in the IEEE Transactions on Signal Processin

Energy-Efficient Power Control in Impulse Radio UWB Wireless Networks

In this paper, a game-theoretic model for studying power control for wireless data networks in frequency-selective multipath environments is analyzed. The uplink of an impulse-radio ultrawideband system is considered. The effects of self-interference and multiple-access interference on the performance of generic Rake receivers are investigated for synchronous systems. Focusing on energy efficiency, a noncooperative game is proposed in which users in the network are allowed to choose their transmit powers to maximize their own utilities, and the Nash equilibrium for the proposed game is derived. It is shown that, due to the frequency selective multipath, the noncooperative solution is achieved at different signal-to-interference-plus-noise ratios, depending on the channel realization and the type of Rake receiver employed. A large-system analysis is performed to derive explicit expressions for the achieved utilities. The Pareto-optimal (cooperative) solution is also discussed and compared with the noncooperative approach.Comment: Submitted to the IEEE Journal on Selected Topics in Signal Processing - Special issue on Performance Limits of Ultra-Wideband System

Energy-Efficient Power Control for Multiple-Relay Cooperative Networks Using Q-Learning

In this paper, we investigate the power control problem in a cooperative network with multiple wireless transmitters, multiple amplify-and-forward relays, and one destination. The relay communication can be either full duplex or half-duplex, and all source nodes interfere with each other at every intermediate relay node, and all active nodes (transmitters and relay nodes) interfere with each other at the base station. A game-theory-based power control algorithm is devised to allocate the powers among all active nodes. The source nodes aim at maximizing their energy efficiency (in bits per Joule per Hertz), whereas the relays aim at maximizing the network sum rate. We show that the proposed game admits multiple pure/mixed-strategy Nash equilibrium points. A Q-learning-based algorithm is then formulated to let the active players converge to the best Nash equilibrium point that combines good performance in terms of both energy efficiency and overall data rate. Numerical results show that the full-duplex scheme outperforms half-duplex configuration, Nash bargaining solution, the max-min fairness, and the max-rate optimization schemes in terms of energy efficiency, and outperforms the half-duplex mode, Nash bargaining system, and the max-min fairness scheme in terms of network sum rate

Distributed Energy-Efficient Power and Subcarrier Allocation for OFDMA-Based Small Cells

In this work, we derive a distributed resource allocation scheme for the uplink of an OFDMA-based small- cell network. The mobile terminals are modeled as utility-driven rational agents that aim at maximizing the number of bits correctly delivered at destination per unit of energy consumed, under minimum-rate constraints. The theoretical analysis of the underlying game equilibrium is exploited to derive an iterative and distributed algorithm that allows each terminal to select its optimal power allocation over subcarriers. Extensive simulations show that the proposed technique is able to properly allocate the resources across the network in a scalable and adaptive manner, while improving the performance of each user in terms of energy efficiency compared to an iterative waterfilling criterion