Modeling of CO2-brine interfacial tension: Application to enhanced oil recovery

Development of reliable and accurate models to estimate carbon dioxide–brine interfacial tension (IFT) is necessary, since its experimental measurement is time-consuming and requires expensive experimental apparatus as well as complicated interpretation procedure. In the current study, feed forward artificial neural network is used for estimation of CO₂–brine IFT based on data from published literature which consists of a number of carbon dioxide–brine interfacial tension data covering broad ranges of temperature, total salinity, mole fractions of impure components and pressure. Trial-and-error method is utilized to optimize the artificial neural network topology in order to enhance its capability of generalization. The results showed that there is good agreement between experimental values and modeling results. Comparison of the empirical correlations with the proposed model suggests that the current model can predict the CO₂–brine IFT more accurately and robustly.     

Applying FCM-ANFIS algorithm as a novel computational method for prediction of viscosity of bitumen and heavy alkane mixture

Recently the studies expressed that the noticeable number of oil reservoirs in all over the world are heavy oil and bitumen reservoirs. So the importance of enhancement of oil recovery (EOR) processes for heavy oil and bitumen reservoirs is highlighted. The Dilution of the reservoir fluid by solvents such as tetradecane is one of well-known methods for these types of reservoirs which effects oil recovery by decreasing viscosity. In the present study, Fuzzy c-means (FCM) algorithm was coupled with Adaptive neuro-fuzzy inference system (ANFIS) to predict viscosity of bitumen and tetradecane in terms of temperature, pressure and weight percent of tetradecane. The coefficients of determination for training and testing steps were calculated such as 0.9914 and 0.9613. The comparison of results and experimental data expressed that FCM-ANFIS algorithm has great potential for estimation of viscosity of bitumen and tetradecane.     

The impact of geological uncertainty on primary production from a fluvial reservoir

Deposition of fluvial sandbodies is controlled mainly by characteristics of the system, such as the rate of avulsion and aggradation of the fluvial channels and their geometry. The impact and the interaction of these parameters have not received adequate attention. In this paper, the impact of geological uncertainty resulting from the interpretation of the fluvial geometry, maximum depth of channels, and their avulsion rates on primary production is studied for fluvial reservoirs. Several meandering reservoirs were generated using a process-mimicking package by varying several controlling factors. Simulation results indicate that geometrical parameters of the fluvial channels impact cumulative production during primary production more significantly than their avulsion rate. The most significant factor appears to be the maximum depth of fluvial channels. The overall net-to-gross ratio is closely correlated with the cumulative oil production of the field, but cumulative production values for individual wells do not appear to be correlated with the local net-to-gross ratio calculated in the vicinity of each well. Connectedness of the sandbodies to each well, defined based on the minimum time-of-flight from each block to the well, appears to be a more reliable indicator of well-scale production.     

Enhanced oil recovery from carbonate reservoirs by spontaneous imbibition of low salinity water

An experimental study was performed to investigate the impact of low salinity water on wettability alteration in carbonate core samples from southern Iranian reservoirs by spontaneous imbibition. In this paper, the effect of temperature, salinity, permeability and connate water were investigated by comparing the produced hydrocarbon curves. Contact angle measurements were taken to confirm the alteration of surface wettability of porous media. Oil recovery was enhanced by increasing the dilution ratio of sea water, and there existed an optimum dilution ratio at which the highest oil recovery was achieved. In addition, temperature had a very significant impact on oil recovery from carbonate rocks. Furthermore, oil recovery from a spontaneous imbibition process was directly proportional to the permeability of the core samples. The presence of connate water saturation inside the porous media facilitated oil production significantly. Also, the oil recovery from porous media was highly dependent on ion repulsion/attraction activity of the rock surface which directly impacts on the wettability conditions. Finally, the highest ion attraction percentage was measured for sodium while there was no significant change in pH for all experiments.     

ATM cell encryption and key update synchronization

This paper presents a data compaction/randomization based approach as a mode of block encryption for ATM (Asynchronous Transfer Mode) cells. The presented approach converts a plaintext into pseudo‐random plaintext before ciphering to conceal patterns in the plaintext. The underlying idea behind this scheme is the Shannon's principles of “confusion” and “diffusion” which involve breaking dependencies and introducing as much randomness as possible into the ciphertext. In this scheme, confusion and diffusion are introduced into the system by first compressing the ATM cell payload and then spreading a continuously changing random data over the entire content of the cell. As a mode of operation for block ciphering, this scheme offers the following attractive features:(i) plaintext patterns are pseudo‐randomized and chained with ciphertext (thereby, preventing against “dictionary”, “known plaintext”, and “statistical analysis” attacks), (ii) it is self‐synchronizing, (iii) cell loss has no additional negative effect, (iv) no IV (Initialization Vector) storage is required, (v) it is encryption‐algorithm independent, (vi) there is no cell‐to‐cell dependency (no feedback from previous cells), and (vii) it is highly scalable (i.e., cells from the same stream can be ciphered and deciphered in parallel). This paper also presents a secure mechanism for in‐band synchronization of encryption/decryption key updates using a “marker‐cell” that is carried within the data channel. An important aspect of both the above mechanisms is that they do not require any changes to the ATM cell header or ATM infrastructure. This revised version was published online in June 2006 with corrections to the Cover Date.     

Label‐QoS switching protocol for quality of service assurance in dynamic swarm robot local network

This paper presents the modeling and analysis of a proposed label–quality of service (QoS) switching protocol for heterogeneous robot in a swarm. Establishing the data communication and network in multirobot task allocation is an important aspect in robot collaboration. Instead of passing the data through the cloud network, each robot can be configured as a node in its swarm for intercommunication. This research was conducted to model and propose aggregation and classification methods in a swarm robot network inspired from multiprotocol label switching, namely, label‐QoS switching protocol. Each packet of data is forwarded with a proposed 2‐side label values that are concerned with addressing and QoS. This proposed protocol was applied in each of the node's routing, and it was set up with forwarding information table. The simulation and analysis were conducted in 2 situations: (1) with a constant n–label switch mobile robot and a number of packet data increasing with time and (2) with a constant number of packet and varying n–label switch mobile robot by time. With reference to the network parameter performances, it shows that the anomaly treatment by the proposed protocol is able to prioritize the data forwarding between the robots at the edge of the swarm with class of service although the robot community at the center is increasing or getting crowded.     

Locality‐Conscious Nested‐Loops Parallelization

To speed up data‐intensive programs, two complementary techniques, namely nested loops parallelization and data locality optimization, should be considered. Effective parallelization techniques distribute the computation and necessary data across different processors, whereas data locality places data on the same processor. Therefore, locality and parallelization may demand different loop transformations. As such, an integrated approach that combines these two can generate much better results than each individual approach. This paper proposes a unified approach that integrates these two techniques to obtain an appropriate loop transformation. Applying this transformation results in coarse grain parallelism through exploiting the largest possible groups of outer permutable loops in addition to data locality through dependence satisfaction at inner loops. These groups can be further tiled to improve data locality through exploiting data reuse in multiple dimensions.     

High resolution target localization using rotating linear array radar

In this paper, an algorithm is proposed for detection and joint estimation of parameters of multiple targets using rotating antenna array. This paper is sequel to our previous work addressing a two element antenna array only. Joint estimation of number of targets, the targets’ range, Doppler and their directions of arrivals is carried while the effects of antenna rotation are compensated for a multi element linear array. The effectiveness of the algorithm is verified by the simulation results carried out for an eight element array. The proposed algorithm is able to resolve targets with same range and Doppler. The computations of the proposed algorithm are calculated and comparison is also given with other algorithms.

     

Radiation pattern design of photonic crystal LED optimized by using multi-objective grey wolf optimizer

Photonic Network Communications - This paper proposes an effective method for shaping the radiation pattern intensity of photonic crystal (PhC) light-emitting diode (LED). In this method, the...     

Improving the Reliability of Software-Defined Networks with Distributed Controllers Through Leader Election Algorithm and Colored Petri-Net

Wireless Personal Communications - Software-Defined Networks (SDNs) are developed to compensate the complicated function of the controlling parts of the given network elements and making the...