987 research outputs found
PORE-NETWORK MODELING AND ANALYSIS OF LABORATORY INDUCED HYDRAULIC FRACTURES
Well stimulation is undertaken to reduce the restriction to flow in a reservoir. Among all the well stimulation techniques, hydraulic fracturing is one of the most widely employed techniques due to the development of shale and tight sand resources. The present study focuses on two problems relevant to hydraulic fracturing; predicting the transport properties enhancement as a function of recorded acoustic emission (AE) events during hydraulic fracturing and predicting the breakdown pressures in cyclic fracturing.
To study the first problem, I initiate pore-scale modeling of acoustic emission (AE) events based on percolation theory. The primary objective is to predict the permeability enhancement by accounting for the number of AE events. I first develop a physically representative model of the intact pore space of the matrix of Tennessee sandstone at the core scale based on petrophysical measurements, which are porosity, permeability, and capillary pressure. A block-scale sample of the formation is then hydraulically fractured, where piezoelectric sensors record the events generated during stimulation. I predict the permeability enhancement of the formation at the core scale by accounting for the number of AE events per unit volume. Independent petrophysical measurements corroborate the predicted results based on percolation theory. The proposed model has significant implications for characterizing the transport properties of the stimulated reservoir volume.
The second problem is relevant to predicting the breakdown pressure in hydraulic fracturing. In conventional fracturing, the fluid pressure is increased monotonically to reach failure in a single cycle. The breakdown pressure can be reduced if we increase and decrease the fluid pressure cyclically (cyclic fracturing). This phenomenon has been tested in other fields, but it is not yet possible to predict the breakdown pressure and cycle in petroleum engineering in the context of hydraulic fracturing. The present study proposes a workflow based on a modified Paris law to predict the breakdown pressure and cycle of cyclic fracturing. The modified Paris law is based on linear elastic fracture mechanics (LEFM), which treats the solid domain as an isotropic and linear elastic medium. I use the data available in the literature for dry Tennessee sandstones. The samples were hydraulically fractured under triaxial stress, two with conventional and two with cyclic methods. The results show that the tuned Paris law can predict the breakdown pressure and cycle with reasonable accuracy. The tuned model can help us to design an optimum scenario that is fundamentally different from the conventional method for formation stimulation
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Scalable Array Transceivers with Wide Frequency Tuning Range for Next Generation Radios
Scalable array transceivers with wide frequency tuning range are attractive for next-generationradios. Key challenges for such radios include generation of LO signals with widefrequency tuning range, scalable synchronization between multiple array unit cells andtolerance to in-band and out-of-band interferers. This thesis presents approaches toaddress these challenges in commercial CMOS technologies.The first part focuses on a series resonant mode-switching VCO architecture thatachieves both state-of-art area and power efficiency with an octave frequency tuningrange from 6.4-14 GHz achieved 186-dB-188-dB Figure-of-Merit (FoM) in 65 nm CMOStechnology. The scalability of this approach towards achieving even larger FTR is alsodemonstrated by a triple-mode 2.2 GHz to 8.7 GHz (119% FTR) CMOS VCO.In the second part a scalable, single-wire coupled-PLL architecture for RF mm-wavearrays is presented. The proposed architecture preserves the simplicity of a daisy-chained LO distribution, compensates for phase offset due to interconnect, and provides phasenoise improvement commensurate to the number of coupled PLLs. Measurements on a28 GHz CMOS prototype demonstrate the feasibility of this scheme.The third part of this thesis presents filtering techniques for in-band blocker suppression.A spatial spectral notch filter design for MIMO digital beam forming arrays is proposedto relax the ADC dynamic range requirement. Orthogonal properties of Walsh functionsincorporated into passive N-path approach enables reconfigurable notches at multiplefrequencies and angles-of-incidence. A 0.3 GHz-1.4 GHz four-element array prototypeimplemented in 65 nm CMOS achieves > 15-dB notch filtering at RF input for twoblockers while causing < 3-dB NF degradation.Finally, a code-domain N-path receiver (RX) is proposed based on pseudo-random(PN) code-modulated LO pulses for simultaneous transmission and reception (STAR)applications. A combination of Walsh-Function and PN sequence is proposed to createcode-domain matched filter at the RF frontend which reflects unknown in-band blockersand rejects known in-band TX self-interference (SI) by using orthogonal codes at RXinput thereby maximizing the SNR of the received signals. The resulting prototype in65 nm is functional from 0.3 GHz-1.4 GHz with 35 dB gain and concurrently receivestwo code-modulated signals. Proposed transmitter (TX) SI mitigation approach resultsin 38.5 dB rejection for -11.8 dBm 1.46 Mb s QPSK modulated SI at RX input. TheRX achieves 23.7 dBm OP1dB for in-band SI, while consuming ∼35 mW and occupies0.31 mm2Keywords: Passive Mixers, dual band, TX self-Interferer, synchronisation, STAR, Code domain N-path receiver, mode switching, notch filter, Phase locked loops, Octave tuning range, CMOS, phase noise, VCO, large-scale 5G mm-wave arrays, resonator, Simultaneous transmit and receive, resonator band-switching, LO distribution, scalable coupled-PLL, N-path passive mixers, MIMO arrays, digital beamforming, CDMA, phased arrays, wide tuning range, Walsh Functio
"When and Where?": Behavior Dominant Location Forecasting with Micro-blog Streams
The proliferation of smartphones and wearable devices has increased the
availability of large amounts of geospatial streams to provide significant
automated discovery of knowledge in pervasive environments, but most prominent
information related to altering interests have not yet adequately capitalized.
In this paper, we provide a novel algorithm to exploit the dynamic fluctuations
in user's point-of-interest while forecasting the future place of visit with
fine granularity. Our proposed algorithm is based on the dynamic formation of
collective personality communities using different languages, opinions,
geographical and temporal distributions for finding out optimized equivalent
content. We performed extensive empirical experiments involving, real-time
streams derived from 0.6 million stream tuples of micro-blog comprising 1945
social person fusion with graph algorithm and feed-forward neural network model
as a predictive classification model. Lastly, The framework achieves 62.10%
mean average precision on 1,20,000 embeddings on unlabeled users and
surprisingly 85.92% increment on the state-of-the-art approach.Comment: Accepted as a full paper in the 2nd International Workshop on Social
Computing co-located with ICDM, 2018 Singapor
Parameterized Complexity of Perfectly Matched Sets
For an undirected graph G, a pair of vertex disjoint subsets (A, B) is a pair of perfectly matched sets if each vertex in A (resp. B) has exactly one neighbor in B (resp. A). In the above, the size of the pair is |A| (= |B|). Given a graph G and a positive integer k, the Perfectly Matched Sets problem asks whether there exists a pair of perfectly matched sets of size at least k in G. This problem is known to be NP-hard on planar graphs and W[1]-hard on general graphs, when parameterized by k. However, little is known about the parameterized complexity of the problem in restricted graph classes. In this work, we study the problem parameterized by k, and design FPT algorithms for: i) apex-minor-free graphs running in time 2^O(?k)? n^O(1), and ii) K_{b,b}-free graphs. We obtain a linear kernel for planar graphs and k^?(d)-sized kernel for d-degenerate graphs. It is known that the problem is W[1]-hard on chordal graphs, in fact on split graphs, parameterized by k. We complement this hardness result by designing a polynomial-time algorithm for interval graphs
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