CARBONATE RESERVOIR ROCKS AT GIANT OIL AND GAS FIELDS IN SW IRAN AND THE ADJACENT OFFSHORE: A REVIEW OF STRATIGRAPHIC OCCURRENCE AND PORO‐PERM CHARACTERISTICS

SW Iran and the adjacent offshore are prolific petroleum‐producing areas with very large proven oil and gas reserves and the potential for significant new discoveries. Most of the oil and gas so far discovered is present in carbonate reservoir rocks in the Dehram, Khami and Bangestan Groups and the Asmari Formation, with smaller volumes in the Dashtak, Neyriz, Najmeh, Gurpi, Pabdeh, Jahrum, Shahbazan, Razak and Mishan (Guri Member) Formations. The Permo‐Triassic Dehram Group carbonates produce non‐associated gas and condensate in Fars Province and the nearby offshore. The Jurassic – Lower Cretaceous Khami Group carbonates are an important producing reservoir at a number of offshore fields and in the southern Dezful Embayment, and are prospective for future exploration. Much of Iran's crude oil is produced from the Oligo‐Miocene Asmari Formation and the mid‐Cretaceous Sarvak Formation of the Bangestan Group in the Dezful Embayment. This review paper is based on data from 115 reservoir units at 60 oil‐ and gasfields in SW Iran and the adjacent offshore. It demonstrates that the main carbonate reservoir units vary from one‐another significantly, depending on the particular sedimentary and diagenetic history. Ooidal‐grainstones and rudist‐ and Lithocodium‐bearing carbonate facies form the most important reservoir facies, and producing units are commonly dolomitised, karstified and fractured. In general, reservoir rocks in the study area can be classified into six major types: grainstones; reefal carbonates; karstified, dolomitised and fractured carbonates; and sandstones. The stratigraphic distribution of these reservoir rocks was principally controlled by the palaeoclimatic conditions existing at the time of deposition. A comparative reservoir analysis based on core data shows that dolomitised and/or fractured, grain‐dominated carbonates in the Dehram Group, Lower Khami Group and Asmari Formation typically have better reservoir qualities than the Cretaceous limestones in the Upper Khami and Bangestan Groups.     

Fetal electrocardiogram modeling using hybrid evolutionary firefly algorithm and extreme learning machine

Multidimensional Systems and Signal Processing - Extraction of fetal electrocardiogram (FECG) from the abdominal region of the mother’s skin is challenge task due to the high overlapping of...     

Frequency selective millimeter‐wave channel estimation based on subspace enhancement algorithms

In millimeter wave (mmW) communication systems, hybrid architecture, including the analog‐digital precoder and combiner matrices, is employed to take advantage of the multistream transceiver. In practice, mmW channel is assumed to be frequency‐selective, since the signal bandwidth is larger than the coherence bandwidth. Hence, orthogonal frequency‐division multiplexing signaling can be remedial. So far, most of the previous works on the frequency‐selective channel estimation have focused on the single measurement vector (SMV) form, whereas finding and exploiting the proper multimeasurement vector (MMV) model can improve upon the estimation procedure based on compressive sensing (CS) concepts. In fact, the estimation procedure based on the MMV model has a faster convergence speed than the SMV method specially, when the training frames are small. In this paper, we first extract the MMV model of the channel. In this model, the rank‐deficiency occurs as the number of training frames is less or equal to the sparsity level. Thus, the conventional estimation methods fail to provide the desirable performance. To overcome this issue, we propose two rank‐aware algorithms based on the enhancement of the observed signal subspace. The first algorithm assumes to know the sparsity level, while the second faces to the lack of knowledge about the sparsity level. The simulation results corroborate the fact that the proposed methods outperform the conventional CS algorithms such as Simultaneous Orthogonal Matching Pursuit.     

Characterization and Investigation of Magnetic and Microwave Properties of Multiwalled Carbon Nanotube/SrFe10MnSn0.5Ti0.5O19 Nanocomposites

SrFe₁₀MnSn_0.5Ti_0.5O₁₉/multiwalled carbon nanotube (MWCNT) nanocomposites with different volume percentages of MWCNT content were synthesized by a sol–gel method. The results of x-ray diffraction, field-emission scanning electron microscopy, and Fourier-transform infrared spectrometry analyses demonstrated that the SrFe₁₀MnSn_0.5Ti_0.5O₁₉ nanoparticles were attached on the external surfaces of the MWCNTs. Mössbauer spectroscopy indicates that the substituted cations preferentially occupy the 12k sites. Magnetic properties were measured using a vibrating-sample magnetometer, and microwave absorption properties were investigated using a vector network analyzer. It was found that, with increasing volume percentage of MWCNT content, the saturation magnetization as well as the coercivity decrease, but the reflection loss widely increases. To investigate the effect of sample thickness on the absorption properties, different values of thickness (1.6 mm, 1.7 mm, 1.8 mm, 1.9 mm, and 2 mm) were selected. The results showed that, with increasing thickness of the absorber, the reflection loss and bandwidth broadly increase.     

Features of the time evolution of localized quantum states in graphene

In the Heisenberg representation, the phenomena of the interference of quantum states of the conduction and valence bands of graphene, arising for localized electron wave packets are analyzed. The interference leads to temporal oscillations in the values of the average physical quantities.     

Moisture Sensitive Smart Yarns and Textiles from Self‐Balanced Silk Fiber Muscles

Smart textiles that sense, interact, and adapt to environmental stimuli have provided exciting new opportunities for a variety of applications. However, current advances have largely remained at the research stage due to the high cost, complexity of manufacturing, and uncomfortableness of environment‐sensitive materials. In contrast, natural textile materials are more attractive for smart textiles due to their merits in terms of low cost and comfortability. Here, water fog and humidity‐driven torsional and tensile actuation of thermally set twisted, coiled, plied silk fibers, and weave textiles from these silk fibers are reported. When exposed to water fog, the torsional silk fiber provides a fully reversible torsional stroke of 547° mm^?1. Coiled‐and‐thermoset silk yarns provide a 70% contraction when the relative humidity is changed from 20% to 80%. Such an excellent actuation behavior originates from water absorption‐induced loss of hydrogen bonds within the silk proteins and the associated structural transformation, which are corroborated by atomistic and macroscopic characterization of silk and molecular dynamics simulations. With its large abundance, cost‐effectiveness, and comfortability for wearing, the silk muscles will open up additional possibilities in industrial applications, such as smart textiles and soft robotics.     

ANNM: A New Method for Adding Noise Nodes Which are Used Recently in Anonymization Methods in Social Networks

Wireless Personal Communications - One of the main concerns at the time of production or share of information on social networking sites for scientific research and business analysis is privacy....     

The off‐grid frequency selective millimeter wave channel estimation

Broadband millimeter wave (mmW) systems are a promising pioneer of cellular communication for next generation which is utilizing the hybrid baseband/analog beamforming structures along with the miniature massive antenna arrays at both sides of the communication link. mmW channel with an available unlicensed spread spectrum is frequency selective because the signal bandwidth can be larger than the coherence bandwidth. Due to the sparse nature of mmW channel, extracting compressive sensing model of the system is preferable. In fact, exploiting the sparse structure will lead to the reduction of the computational complexity, because there is a reduction in the channel training length compared with the conventional methods such as least square estimation. Most of the prior works have considered on‐grid quantized departure/arrival angles in the input/output antennas to obtain a sparse virtual channel model. However, the sparse angles in the physical channel model are continuous where this continuity indicates a mismatch between the physical angles and the on‐grid angles. Such a mismatch will contribute to unwanted components in the virtual channel model. Given these extra components, the conventional compressive sensing tools are unable to recover the channel. In this paper, we propose two solutions for overcoming the problem caused by off‐grid angle selection. The first is based on the vector shaping, and the second one is based on the sparse total least square concepts. Simulation results demonstrate that the proposed methods both could obtain an adequate channel recovery and are preferable regarding computational complexity concerning the newly developed surrogate method.     

Interaction of α radiation with iron-doped n-type silicon

Deep-level transient spectroscopy (DLTS) measurements were carried out on low-doped n-silicon before and after irradiation with 5.48 MeV α particles at room temperature with a fluence of 10¹⁰ α particles/cm². The DLTS measurements on the samples identified three electron levels E₁, E₂ and E₃ before irradiation. The deep-levels characteristic studies include emission rate signatures, activation energies, defect concentrations and capture cross sections. It was found that all pre-existing defects decreased their amplitudes during irradiation. The decrease in activation energy of level E₃ and noticeable suppression of level E₁ was also observed after irradiation. It was clearly seen that the composite peak E₃ (combination of E₂ and E₃) was successfully resolved after irradiating with α particles. α-irradiation is seen to lead a significant suppression of the iron interstitial defect, and without causing any change in its room temperature annealing characteristics.