bluuebunny/crossref_metadata_2025_split huggingface dataset:
Analysis of Enhancement Shale Gas Recovery by CO2 Storage
Authors: Tang L.. , Sun S.. , Mi L.. , Wang L.. , Qi H.. , Yu R.. , Bai F.. , Chaoyang J.. 
Published: May 2016

Abstract
In order to enhance shale gas recovery and store CO2 geologically, a development model of EGR by CO2 flooding in shale was proposed based on the thought of CO2 flooding oil. In order to investigate the potential of EGR by CO2 flooding, experiments in house and simulations of well pattern were carried out. Specifically, In-house study included experiments of adsorption isothermal between CH4 and CO2 and experiments of displacement seepage CH4 by CO2. The results of above experiments show that, adsorption capacity for CO2 was about three to five times than that for methane in shale formation at the same condition of pressure and temperature. In addition, gas recovery for adsorbed gas would be promoted more than 20% just because of CO2 flooding CH4 during displacement experiments in question. What was more, it was found that two main mechanisms for CO2 EGR in shale gas were concluded as molecular replacement by CO2 and keep of formation pressure by CO2 injection. Based on the results of experiments, considering difficulty of CO2 injection due to poor property of shale formation, this paper proposed a solution of CO2 injection in one well and production shale gas in two wells nearby based on the ideas from well pattern of water flooding oil in oil field. Distance between injection and recovery can be calculated by theory calculation, providing references for carbon dioxide flooding in the field.
Data Driven Production Forecasting Using Machine Learning
Authors: Cao Q.. , Banerjee R.. , Gupta S.. , Li J.. , Zhou W.. , Jeyachandra B.. 
Published: May 2016

Abstract
Forecasting of production in unconventional prospects has gained a lot of attention in the recent years. The key challenges in unconventional reservoirs have been the requirement to put online a) a large number of wells in a short period of time, b) well productivity significantly driven by completion characteristics and that c) the physics of fluid flow in these prospects still remain uncertain. In this paper, machine learning algorithms are used to forecast production for existing and new wells in unconventional assets using inputs like geological maps, production history, pressure data and operational constraints. One of the most popular Machine Learning methods – Artificial Neural Network (ANN) is employed for this purpose. ANN can learn from large volume of data points without assuming a predetermined model and can adapt to newer data as and when it becomes available. The workflow involves using these data sets to train and optimize the ANN model which, subsequently, is used to predict the well production performance of both existing wells using their own history and new wells by using the history of nearby wells which were drilled in analogous geological locations. The proposed technique requires users to do less data conditioning and model building and focus more on analyzing what-if scenarios and determining the well performance.
Enhancing Well Performance via In-Stage Diversion in Unconventional Wells: Physics and Case Studies
Authors: Fragachán F. E. , Shahri M. Pordel , Arnold D. M. , Babey A. G. , Smith C. S. 
Published: May 2016

Abstract
Production rates in unconventional plays can decline dramatically, up to 70% in the first year. Refracturing—by today's understanding—is a remedial production operation often done because original fracturing failed to contribute any significant amount of flow, performance of the initial completion has degraded over time to below operationally or economically acceptable limits, or significant unfractured pay exists in the well.
Developments in nondamaging, degradable diverters with outstanding plugging efficiency have opened new opportunities for protecting existing fractures by plugging them and then fracturing zones that were previously bypassed because of inefficient zone coverage or refracturing zones that were inefficiently fractured initially. In fact, these new diverters enable zonal isolation for horizontal wells with multiple perforation clusters and for temporarily plugging perforations for re-stimulation treatments instead of squeezing the perforations and sealing them off. With multistage operations becoming the industry norm, operators need easily deployable diversion technologies that will protect previously stimulated perforations and enable adding new ones to untreated perforations or bypassed zones.
This paper reviews in-stage Diversion, including a brief discussion of diverter candidate selection in terms of production and risk assessment to ensure return on investment. Also included is an explanation of underlying mechanisms controlling the diversion process and the use of advanced modeling techniques to enhance efficiency of diversion operations. Then a case study is discussed to highlight how temporary and degradable chemistry can be used to enhance zone coverage, to provide temporary isolation between zones in shale fracturing operations, and to achieve multiple effective fracture treatments within the same stage. These degradable chemical diverting agents form a solid impermeable barrier or seal that in time will break or degrade to liquid form, leaving the existing zone that was diverted open to permit flow.
Multi-Well Stimulation Optimization in Shale Formation: Modeling and Application
Authors: Xu Ben , Li Yanchao 
Published: May 2016

AbstractIn order to increase production rate, reduce treatment period, and solve some special problems, multi-well completion has been proposed, especially in mountain areas with limited well pads. Simultaneous fracturing and zipper fracturing are two new fracturing patterns in multi-well completion, which can increase fracture network complexity and stimulated reservoir volume (SRV) because of the interference of wells or fractures. However, unlike multi-frac treatments of a single well, interference between multi-wells also increases difficulties on hydraulic fracturing design.In the previous papers, we have shown that natural fractures impacted the direction of hydraulic fracture propagation and mechanical properties of reservoir formations, which increases the complexity of fracture network complexity. As known, hydraulic fracture propagation is a complicated process influenced by frac spacing, hydraulic fracture length, mechanical properties of natural fractures, and in-situ stress. Especially, in-situ stress and natural fractures play more complex roles in multi-well completions.In this paper, we presented one numerical model to better understand the process of hydraulic fracture propagation in multi-well completions, which includes influences of in-situ stress changes and interactions between hydraulic fracture and natural fractures. The numerical results show that in addition to hydraulic fracture propagating, natural fracture opening also changes in-situ stress, which makes hydraulic fracture network more complex. The model has been validated in a zipper fracturing case, and the optimization of well spacing, frac spacing and treatment volume has been proposed to enhance stimulated reservoir volume (SRV) and increase shale gas production.The simulation results of this paper provide some guidelines for hydraulic fracturing design in multi-well completions, which contains optimum well spacing, frac spacing, and treatment volume. The results of this paper may also help deal with limited well pad area and increase gas production, and ultimately it should lead to improved well economics.
Hydraulic Fractures Behavior Evaluation in Vaca Muerta Formation, Case Studies
Authors: Moreyra J. D. 
Published: May 2016

Abstract
The objective of this work is to show that the estimated stimulate reservoir volume (SRV) from micro seismic analysis under dynamic conditions not always represents the SRV acting as hydrocarbon collector and need to be calibrated with total organic content (TOC), vertical and areal distribution. Furthermore, unlike conventional reservoirs, the potential leakoff damage caused during the fracturing and the SRV generation process, are not detectable by pressure transient analysis (PTA), but us a change on SRV transmissibility.
Integrating PTA, net pressure behavior during fracture treatment and micro seismic analysis results, allow us to better understand the reason that seismic events from one or more monitoring wells, might conduct us to wrong interpretation of the active SRV. Field cases show how PTA conventional technique helps to identify the existence or absence of an effective SRV connected to each individual hydraulic fracture stage and its associated best quality TOC thickness.
Results confirm that active SRV, generated by hydraulic fracture treatment in lower Vaca Muerta, where the seismic events practically are no detected, PTA analysis has an excellent infinite conductivity fracture behavior on the best TOC thickness. Production potential depends on different factors, net pay with TOC percentage greater than 2.5 %, vertical and areal distribution associated to rock porosity, natural fissured and SRV are the most important parameters. It is critical to understand the system deliverability potential, it must be evaluated under production conditions and the active SRV adjusted with TOC percentage and distribution, taking into account the effects caused by SRV pore pressure drop. Network of natural fissures originally in place and changes generated around the main fracture, combine to enhance the quality system.
An improvement of active SRV transmissibility was detected after the buildup period, increasing from 20 to 80 % oil production and more than three times the initial production. As in conventional reservoirs, where pressure test results are related to formation transmissibility, in unconventional reservoir pressure test results are related to SRV transmissibility and TOC percentage.
It can be concluded that the best zones to be fractured are determined by PTA associating to logging and cutting geochemistry analysis. PTA evaluation will determine only chocked fracture damage and not surface fracture damage.
PTA allows us to improve well completions efficiency and amount of fractures. Vertical wells production performance and best zones knowledge, will allow a better choice of zones to be developed thru drilling horizontal wells. In spite of industry belief, PTA analysis can give us a better understanding of SRV behavior in contact with the generated primary fracture.
Conventional Fracturing vs. Complex Fracturing Network in Tight Turbidite Oil Deposits in Mexico
Authors: Murillo G. Gutierrez , Salguero Javier 
Published: May 2016

AbstractOver the past decade the hydraulic fracturing industry has been working to increase oil production from low-permeability or "tight" sands formations by applying the experience and techniques gained from shale oil and gas well completions. The shale-based completion approach calls for the creation of complex but short-length fracture networks via the use of low-viscosity fluid systems combined with pumping at higher rates than a conventional stimulation. This paper is a case study of an oil-producing basin in Mexico. It evaluates the impact on cumulative production from stimulations assumed to have a greater fractured length compared to stimulations of the complex fracture network type with their associated shorter fractures. This paper uses data from a 13-year period (2003 to 2016) comparing wells in two tight sands fields with varying characteristics such as well design, vertical and horizontal configuration, fracture fluid systems and completion techniques.Due to the studied fields' petrophysical characteristics, hydraulic fracturing was necessary in all cases to economically produce hydrocarbons. Beyond this common characteristic, key properties varied across fields, with high heterogeneity due to the characteristics of the turbidite reservoirs. Natural fractures were not always present, permeability varied from 0.3 to 5 mD, while average porosity was 15% with low changes in vertical stress. Microseismic data acquired in the Basin provided information critical to understanding fracture behavior and, when combined with fracture simulation software, estimating propped geometry.Among the central observations of this study is that the stimulated reservoir volume (SRV) has certain limitations when oil-bearing compact turbidites are being stimulated. This was especially observed in lateral wells where the minimum horizontal stress (Shmin) increased gradually towards the heel of the well, making it more difficult to generate a complex fracture.The study area's stimulated wells showed a strong correlation between fracture half-length and cumulative hydrocarbon production. This proved true even among wells with complex fracture networks that typically had higher initial production. The critical conclusion of this study is that an oil well in low-permeability compact turbidites with greater fractured length can generate cumulative production up to 60% greater than a well with a complex but shorter half-length fracture network.
Performance of Sampling/Resampling-based Particle Filters Applied to Non-Linear Problems
Authors: Ly-Tu Nga , Le-Tien Thuong , Tran-Hoang-Thi Oanh , Huynh-Kha Tu , Mai Linh 
Published: May 2016

In this work, we propose a wireless body area sensor network (WBASN) to monitor patient position. Localization and tracking are enhanced by improving the effect of the received signal strength (RSS) variation. First, we propose a modified particle filter (PF) that adjusts resampling parameters for the Kullback-Leibler distance (KLD)-resampling algorithm to ameliorate the effect of RSS variation by generating a sample set near the high-likelihood region. The key issue of this method is to use a resampling parameter lower bound for reducing both the root mean square error (RMSE) and the mean number of particles used. To determine this lower bound, an optimal algorithm is proposed based on the maximum RMSE between the proposed algorithm and the KLD-resampling algorithm or based on the maximum mean number of particles used of these algorithms. Finally, PFs based on KLD-sampling and KLD-resampling are proposed to minimize the efficient number of particles and to reduce the estimation error compared to traditional algorithms.
Design and Simulation of Measurement-Based Correlation Models for Shadow Fading
Authors: Pätzold Matthias , Avazov Nurilla , Nguyen Van Duc 
Published: May 2016

This paper deals with the design of measurement-based correlation models for shadow fading. Based on the correlation model, we design a simulation model using the sum-of-sinusoids (SOS) method to enable the simulation of spatial lognormal processes characterizing real-world shadow fading scenarios. The model parameters of the simulation model are computed by applying the Lp-norm method (LPNM). This method facilitates an excellent fitting of the simulation model’s autocorrelation function (ACF) to that of measured channels. Our study includes an evaluation of all important statistical quantities of the proposed measurement-based simulation model, such as the probability density function (PDF), spatial ACF, decorrelation and coherence distance, as well as the level-crossing rate (LCR) and the average duration of fades (ADF). A comparison with the Gudmundson correlation model shows that the developed measurement-based correlation model outperforms the former one by far in terms of the goodness of fit to the measured data. The proposed measurement-based simulation model allows to study the effects of long-term fading on the performance of mobile communication systems under real-world shadow fading conditions.
Quantization Error Correction Schemes for Lattice-Reduction Aided MIMO Detectors
Authors: Nguyen Tien Duc , Fujino Tadashi , Tran Xuan Nam 
Published: May 2016

Lattice reduction aided (LRA) linear detectors have been known to achieve near optimal performance at low complexity. However, one weakness of LRA detector is that the quantization step in LRA detector is not optimal. Based on simulation results, we show that most of detection errors in LRA linear detectors are due to quantization errors. We then propose two methods to correct the quantization errors. In the first method, sphere detectors are introduced to correct quantization errors at low additional complexity. As a second approach, we propose a list quantization scheme which can generate a list of candidate symbols from the original LRA estimated symbols. From these listed symbols, decisions are made according to the minimum Euclidean distance between the received and estimated points. It is shown by simulations that both methods provide significant BER performance improvements with only a small additional complexity.
Gram-Schmidt Combined LLL Lattice-Reduction Aided Detection in MIMO Systems
Authors: Fujino Tadashi 
Published: May 2016

This paper proposes an improved lattice-reduction aided (LRA) MMSE detection scheme, based on the Gram-Schmidt (GS) procedure. The proposed scheme reduces the column vectors of the MIMO channel matrix, by using the LLL algorithm followed by the GS procedure in order to transform the channel matrix into a new one which has mutually purely orthogonal column vectors. Compared to the conventional LRA MMSE detector, the proposed detector achieves a very good BER performance, almost equivalent to those using the ML detector in the 4 × 4 MIMO system at the cost of a slightly larger computational complexity.
An Efficient Architecture of Forward Transforms and Quantization for H.264/AVC Codecs
Authors: Tran Xuan-Tu , Tran Van-Huan 
Published: May 2016

Thanks to many novel coding tools, H.264/AVC has become the most efficient video compression standard providing much better performance than previous standards. However, this standard comes with an extraordinary computational complexity and a huge memory access requirement, which make the hardware architecture design much more difficult and costly, especially for realtime applications. In the framework of H.264 codec hardware architecture project, this paper presents an efficient architecture of Forward Transform and Quantization (FTQ) for H.264/AVC codecs in mobile applications. To reduce the hardware implementation overhead, the proposed design uses only one unified architecture of 1-D transform engine to perform all required transform processes, including discrete cosine transform and Walsh Hadamard transform. This design also enables to share the common parts among multipliers that have the same multiplicands. The performance of the design is taken into consideration and improved by using a fast architecture of the multiplier in the quantizer, the most critical component in the design. Experimental results show that our architecture can completely finish transform and quantization processes for a 4:2:0 macroblock in 228 clock cycles and the achieved throughput is 445Msamples/s at 250MHz operating frequency while the area overhead is very small, 147755μm2 (approximate 15KGates), with the 130nm TSMC CMOS technology.
Dual Band-Notched UWB Antenna based on Electromagnetic Band Gap Structures
Authors: Trinh-Van Son , Dao-Ngoc Chien 
Published: May 2016

A printed ultra-wideband (UWB) antenna with dual band-notched characteristics based on electromagnetic band-gap (EBG) structure is presented. To produce dual-band rejection, the microstrip feed line is placed between two pairs of EBG cells which are designed to act as stop-band filters. The final design of the antenna satisfies the voltage standing wave ratio (VSWR) requirement of less than 2.0 in a bandwidth spreading from 2.275 GHz to 10.835 GHz, which entirely covers UWB frequency band allocated from 3.1 to 10.6 GHz. The antenna also shows dual band-notched performance at the frequency bands of 3.375 − 3.875 GHz for WiMAX and 5.325 − 6.150 GHz for WLAN, while possessing omni-directional characteristic in the whole operating frequency band. The results show good agreement between simulation and measurement.
Asynchronous Sampling Rate Conversions in Digital Communications Systems
Authors: Duong Quang X. , Pelet Eric R. , Salt J. Eric , Nguyen Ha H. 
Published: May 2016

The problem of resampling digital signals at an output sampling rate that is incommensurate with the input sampling rate is the topic of this paper. This problem is often encountered in practice, as for example in the multiplexing of video signals from different sources for the purpose of distribution. There are basically two approaches to resample the signals. Both approaches are thoroughly described and practical circuits for hardware implementation are provided. A comparison of the two circuits presented in the paper shows that one circuit requires a division to compute the new sampling times. This time scaling operation adds complexity to the implementation with no performance advantage over the other circuit, and makes the “division free” circuit the preferred one for resampling.
A Novel Multi-Dimensional Spectrum Estimation Technique using Antenna Array Displacement
Authors: Pham Viet-Ha , Grenier Dominic , Chouinard Jean-Yves 
Published: May 2016

Conventionally, in multi-dimensional spectral estimation techniques, each data snapshot in space is captured simultaneously. All antenna elements or sensors being used to collect data are sampled at the same time. By doing so, the size of the antenna array is proportional to the area of interest in space. The antenna array is prohibitively huge if the area that we want to cover is large. In this paper, in order to reduce the number of antenna elements in use, we propose a novel multi-dimensional spectrum estimation technique based on displacing small antenna arrays along predefined paths. It includes a data measurement technique which sequentially collects data samples within each snapshot in space according to a predefined order, and a spectral estimation technique which is based on the Discrete Fourier Transform (DFT) of the collected data. The key idea is to create a large synthetic antenna aperture by displacing a small antenna array along a predefined trajectory. Impinging waves are assumed uniform plane waves. The performance of the proposed technique is evaluated by simulation. The applications of the proposed technique include synthetic aperture radar, radar image processing and sonar systems.