873 resultados para Multi-scale modelling
Resumo:
This paper studies how to more effectively invert seismic data and predict reservoir under complicated sedimentary environment, complex rock physical relationships and fewer drills in offshore areas of China. Based on rock physical and seismic amplitude-preserving process, and according to depositional system and laws of hydrocarbon reservoir, in the light of feature of seismic inversion methods present applied, series methods were studied. A joint inversion technology for complex geological condition had been presented, at the same time the process and method system for reservoir prediction had been established. This method consists four key parts. 1)We presented the new conception called generalized wave impedance, established corresponding inversion process, and provided technical means for joint inversion lithology and petrophysical on complex geological condition. 2)At the aspect of high-resolution nonlinear seismic wave impedance joint inversion, this method used a multistage nonlinear seismic convolution model rather than conventional primary structure Robinson seismic convolution model, and used Caianiello neural network implement inversion. Based on the definition of multistage positive and negative wavelet, it adopted both deterministic and statistical physical mechanism, direct inversion and indirect inversion. It integrated geological knowledge, rock physical theory, well data, and seismic data, and improved the resolution and anti-noise ability of wave impedence inversion. 3)At the aspect of high-resolution nonlinear reservoir physical property joint inversion, this method used nonlinear rock physical model which introduced convolution model into the relationship between wave impedance and porosity/clay. Through multistage decomposition, it handles separately the large- and small-scale components of the impedance-porosity/clay relationships to achieve more accurate rock physical relationships. By means of bidirectional edge detection with wavelets, it uses the Caianiello neural network to finish statistical inversion with combined applications of model-based and deconvolution-based methods. The resulted joint inversion scheme can integrate seismic data, well data, rock physical theory, and geological knowledge for estimation of high-resolution petrophysical parameters. 4)At the aspect of risk assessment of lateral reservoir prediction, this method integrated the seismic lithology identification, petrophysical prediction, multi-scale decomposition of petrophysical parameters, P- and H-spectra, and the match relationship of data got from seismics, well logging and geology. It could describe the complexity of medium preferably. Through applications of the joint inversion of seismic data for lithologic and petrophysical parameters in several selected target areas, the resulted high-resolution lithologic and petrophysical sections(impedance, porosity, clay) show that the joint inversion can significantly improve the spatial description of reservoirs in data sets involving complex deposits. It proved the validity and practicality of this method adequately.
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Offshore seismic exploration is full of high investment and risk. And there are many problems, such as multiple. The technology of high resolution and high S/N ratio on marine seismic data processing is becoming an important project. In this paper, the technology of multi-scale decomposition on both prestack and poststack seismic data based on wavelet and Hilbert-Huang transform and the theory of phase deconvolution is proposed by analysis of marine seismic exploration, investigation and study of literatures, and integration of current mainstream and emerging technology. Related algorithms are studied. The Pyramid algorithm of decomposition and reconstruction had been given by the Mallat algorithm of discrete wavelet transform In this paper, it is introduced into seismic data processing, the validity is shown by test with field data. The main idea of Hilbert-Huang transform is the empirical mode decomposition with which any complicated data set can be decomposed into a finite and often small number of intrinsic mode functions that admit well-behaved Hilbert transform. After the decomposition, a analytical signal is constructed by Hilbert transform, from which the instantaneous frequency and amplitude can be obtained. And then, Hilbert spectrum. This decomposition method is adaptive and highly efficient. Since the decomposition is based on the local characteristics of the time scale of data, it is applicable to nonlinear and non-stationary processes. The phenomenons of fitting overshoot and undershoot and end swings are analyzed in Hilbert-Huang transform. And these phenomenons are eliminated by effective method which is studied in the paper. The technology of multi-scale decomposition on both prestack and poststack seismic data can realize the amplitude preserved processing, enhance the seismic data resolution greatly, and overcome the problem that different frequency components can not restore amplitude properly uniformly in the conventional method. The method of phase deconvolution, which has overcome the minimum phase limitation in traditional deconvolution, approached the base fact well that the seismic wavelet is phase mixed in practical application. And a more reliable result will be given by this method. In the applied research, the high resolution relative amplitude preserved processing result has been obtained by careful analysis and research with the application of the methods mentioned above in seismic data processing in four different target areas of China Sea. Finally, a set of processing flow and method system was formed in the paper, which has been carried on in the application in the actual production process and has made the good progress and the huge economic benefit.
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Most of the fields in China are in the middle-late development phase or are mature fields. It becomes more and more difficult to develop the remaining oil/gas. Therefore, it is import to enhance oil/gas recovery in order to maintain the production. Fine scale modeling is a key to improve the recovery. Incorporation of geological, seismic and well log data to 3D earth modeling is essential to build such models. In Ken71 field, well log, cross-well seismic and 3D seismic data are available. A key issue is to build 3D earth model with these multi-scales data for oil field development.In this dissertation, studies on sequential Gaussian-Bayesian simulation have been conducted. Its comparison with cokriging and sequential Gaussian simulation has been performed. The realizations generated by sequential Gaussian-Bayesian simulation have higher vertical resolution than those generated by other methods. Less differences between these realization and true case are observed. With field data, it is proved that incorporating well log, cross-well seismic and 3D seismic into 3D fine scale model is reliable. In addition, the advantages of sequential Gaussian-Bayesian simulation and conditions for input data are demonstrated. In Ken71 field, the impedance difference between sandstone and shale is small. It would be difficult to identify sandstone in the reservoir with traditional impedance inversion. After comparisons of different inversion techniques, stochastic hillclimbing inversion was applied. With this method, shale content inversion is performed using 3D seismic data. Then, the inverted results of shale content and well log data are incorporated into 3D models. This demonstrates a procedure to build fine scale models using multi scale seismic data, especially 3D seismic amplitude volume.The models generated through sequential Gaussian-Bayesian simulation have several advantages including: (1) higher vertical resolution compared with 3D inverted acoustic impedance (AI); (2) consistency of lateral variation as 3D inverted AI; (3) more reliability due to integration cross-well seismic data. It is observed that the precision of the model depends on the 3D inversion.
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Application of long-term exploration for oil and gas shows that the reservoir technology of prediction is one of the most valuable methods. Quantitative analysis of reservoir complexity is also a key technology of reservoir prediction. The current reservoir technologies of prediction are based on the linear assumption of various physical relationships. Therefore, these technologies cannot handle complex reservoirs with thin sands, high heterogeneities in lithological composition and strong varieties in petrophysical properties. Based on the above-mentioned complex reservoir, this paper conducts a series of researches. Both the comprehending and the quantitative analysis of reservoir heterogeneities have been implemented using statistical and non-linear theories of geophysics. At the beginning, the research of random media theories about reservoir heterogeneities was researched in this thesis. One-dimensional (1-D) and two-dimensional (2-D) random medium models were constructed. The autocorrelation lengths of random medium described the mean scale of heterogeneous anomaly in horizontal and deep directions, respectively. The characteristic of random medium models were analyzed. We also studied the corresponding relationship between the reservoir heterogeneities and autocorrelation lengths. Because heterogeneity of reservoir has fractal nature, we described heterogeneity of reservoir by fractal theory based on analyzing of the one-dimensional (1-D) and two-dimensional (2-D) random medium models. We simulated two-dimensional (2-D) random fluctuation medium in different parameters. From the simulated results, we can know that the main features of the two-dimensional (2-D) random medium mode. With autocorrelation lengths becoming larger, scales of heterogeneous geologic bodies in models became bigger. In addition, with the autocorrelation lengths becoming very larger, the layer characteristic of the models is very obvious. It would be difficult to identify sandstone such as gritstone, clay, dense sandstone and gas sandstone and so on in the reservoir with traditional impedance inversion. According to the obvious difference between different lithologic and petrophysical impedance, we studied multi-scale reservoir heterogeneities and developed new technologies. The distribution features of reservoir lithological and petrophysical heterogeneities along vertical and transverse directions were described quantitatively using multi-scale power spectrum and heterogeneity spectrum methods in this paper. Power spectrum (P spectrum) describes the manner of the vertical distribution of reservoir lithologic and petrophysical parameters and the large-scale and small-scale heterogeneities along vertical direction. Heterogeneity spectrum (H spectrum) describes the structure of the reservoir lithologic and petrophysical parameters mainly, that is to say, proportional composition of each lithological and petrophysical heterogeneities are calculated in this formation. The method is more reasonable to describe the degree of transverse multi-scale heterogeneities in reservoir lithological and petrophysical parameters. Using information of sonic logs in Sulige oil field, two spectral methods have been applied to the oil field, and good analytic results have been obtained. In order to contrast the former researches, the last part is the multi-scale character analysis of reservoir based on the transmission character of wave using the wavelet transform. We discussed the method applied to demarcate sequence stratigraphy and also analyzed the reservoir interlayer heterogeneity.
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Scale matching method means adjusting information with different scale to the same level. This thesis focuses on scale unification of information with different frequency bandwidth. Well-seismic cooperate inversion is an important component of reservoir geophysics; multiple prediction & subtraction is a development of multiple attenuation in recent years. The common ground of these two methods is that they both related to different frequency bandwidth unification. Well log、cross-hole seismic、VSP、3D seismic and geological information have different spatial resolution, we can decrease multi-solution of reservoir inversion and enhance the vertical and lateral resolution of the geological object by integrate those information together; Compare the predicted multiple generated by SRME with the real multiple, we find the predicted multiple convolutes at least one wavelet more, which brings frequency bandwidth difference between them. So the subtraction method also relates to multi-scale information unification. This thesis gives a method of well constrained seismic high resolution processing basing on auto gain control modulation. It uses base function method which utilizes original well-seismic match result as initial condition and processed seismic trace as initial model to extrapolate the high frequency information of the well logs to the seismic profiles. In this way we can broaden the bandwidth of the seismic and make the high frequency gain geological meaning. In this thesis we introduce the revised base function method to adaptive subtraction and verify the validity of the method using models. Key words: high frequency reconstruction, scale matching, base function, multiple, SRME prediction & subtraction
Resumo:
Pre-stack seismic inversion has become the emphasis and hotspot owing to the exploration & exploitation of oil field and the development of seismic technology. Pre-stack seismic inversion has the strongpoint of making the most of amplitude versus offset compared with the post-stack method. In this dissertation, the three parameters were discussed from multi-angle reflectance of P-wave data based on Zoeppritz’s and Aki & Richard’s equation, include P-wave velocity, S-wave velocity, and density. The three parameters are inversed synchronously from the pre-stack multi-angle P-wave data, based on rockphysics model and aimed at the least remnant difference between model simulation and practical data. In order to improve the stability of inversion and resolution to thin bed, several techniques were employed, such as the wavelet transform with multi-scale function, adding the Bayesian soft constraint and hard constraints (the horizon, structure and so on) to the inversion process. Being the result, the uncertainty of the resolution is reduced, the reliability and precision are improved, the significance of parameters becomes clearer. Meeting to the fundamental requirement of pre-stack inversion, some research in rockphysics are carried out which covered the simulation and inversion of S-wave velocity, the influence of pore fluids to geophysical parameters, and the slecting and analyzing of sensitive parameters. The difference between elastic wave equation modeling and Zoeppritz equation method is also compared. A series of key techniques of pre-stack seismic inversion and description were developed, such as attributes optimization, fluid factors, etc. All the techniques mentioned above are assembled to form a technique sets and process of synchronous pre-stack seismic inversion method of the three parameters based on rock physics and model simulation. The new method and technology were applied in many areas with various reservoirs, obtained both geological and economic significance, which proved to be valid and rational. This study will promote the pre-stack inversion technology and it’s application in hidden reservoirs exploration, face good prospects for development and application.
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In modem signal Processing,non-linear,non-Gaussian and non-stable signals are usually the analyzed and Processed objects,especially non-stable signals. The convention always to analyze and Process non-stable signals are: short time Fourier transform,Wigner-Ville distribution,wavelet Transform and so on. But the above three algorithms are all based on Fourier Transform,so they all have the shortcoming of Fourier Analysis and cannot get rid of the localization of it. Hilbert-Huang Transform is a new non-stable signal processing technology,proposed by N. E. Huang in 1998. It is composed of Empirical Mode Decomposition (referred to as EMD) and Hilbert Spectral Analysis (referred to as HSA). After EMD Processing,any non-stable signal will be decomposed to a series of data sequences with different scales. Each sequence is called an Intrinsic Mode Function (referred to as IMF). And then the energy distribution plots of the original non-stable signal can be found by summing all the Hilbert spectrums of each IMF. In essence,this algorithm makes the non-stable signals become stable and decomposes the fluctuations and tendencies of different scales by degrees and at last describes the frequency components with instantaneous frequency and energy instead of the total frequency and energy in Fourier Spectral Analysis. In this case,the shortcoming of using many fake harmonic waves to describe non-linear and non-stable signals in Fourier Transform can be avoided. This Paper researches in the following parts: Firstly,This paper introduce the history and development of HHT,subsequently the characters and main issues of HHT. This paper briefly introduced the basic realization principles and algorithms of Hilbert-Huang transformation and confirms its validity by simulations. Secondly, This paper discuss on some shortcoming of HHT. By using FFT interpolation, we solve the problem of IMF instability and instantaneous frequency undulate which are caused by the insufficiency of sampling rate. As to the bound effect caused by the limitation of envelop algorithm of HHT, we use the wave characteristic matching method, and have good result. Thirdly, This paper do some deeply research on the application of HHT in electromagnetism signals processing. Based on the analysis of actual data examples, we discussed its application in electromagnetism signals processing and noise suppression. Using empirical mode decomposition method and multi-scale filter characteristics can effectively analyze the noise distribution of electromagnetism signal and suppress interference processing and information interpretability. It has been founded that selecting electromagnetism signal sessions using Hilbert time-frequency energy spectrum is helpful to improve signal quality and enhance the quality of data.
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Study of 3D visualization technology of engineering geology and its application to engineering is a cross subject which includes geosciences, computer, software and information technology. Being an important part of the secondary theme of National Basic Research Program of China (973 Program) whose name is Study of Multi-Scale Structure and Occurrence Environment of Complicated Geological Engineering Mass(No.2002CB412701), the dissertation involves the studies of key problems of 3D geological modeling, integrated applications of multi-format geological data, effective modeling methods of complex approximately layered geological mass as well as applications of 3D virtual reality information management technology.The main research findings are listed below:Integrated application method of multi-format geological data is proposed,which has solved the integrated application of drill holes, engineering geology plandrawings, sectional drawings and cutting drawings as well as exploratory trenchsketch. Its application can provide as more as possible fundamental data for 3Dgeological modeling.A 3D surface construction method combined Laplace interpolation points withoriginal points is proposed, so the deformation of 3D model and the crossing error ofupper and lower surface of model resulted from lack of data when constructing alaminated stratum can be eliminated.3D modeling method of approximately layered geological mass is proposed,which has solved the problems of general modeling method based on the sections or points and faces when constructing terrain and concordant strata.The 3D geological model of VII dam site of Xiangjiaba hydropower stationhas been constructed. The applications of 3D geological model to the auto-plotting ofsectional drawing and the converting of numerical analysis model are also discussed.3D virtual reality information integrated platform is developed, whose mostimportant character is that it is a software platform having the functions of 3D virtualreality flying and multi-format data management simultaneously. Therefore, theplatform can load different 3D model so as to satisfy the different engineeringdemands.The relics of Aigong Cave of Longyou Stone Caves are recovered. Thereinforcement plans of 1# and 2# cave in phoenix hill also be expressed. The intuitiveexpression provided decision makers and designers a very good environment.The basic framework and specific functions of 3D geological informationsystem are proposed.The main research findings in the dissertation have been successfully applied to some important engineering such as Xiangjiaba hydropower station, a military airport and Longyou Stone Caves etc.
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This thesis describes a new representation for two-dimensional round regions called Local Rotational Symmetries. Local Rotational Symmetries are intended as a companion to Brady's Smoothed Local Symmetry Representation for elongated shapes. An algorithm for computing Local Rotational Symmetry representations at multiple scales of resolution has been implemented and results of this implementation are presented. These results suggest that Local Rotational Symmetries provide a more robustly computable and perceptually accurate description of round regions than previous proposed representations. In the course of developing this representation, it has been necessary to modify the way both Smoothed Local Symmetries and Local Rotational Symmetries are computed. First, grey-scale image smoothing proves to be better than boundary smoothing for creating representations at multiple scales of resolution, because it is more robust and it allows qualitative changes in representations between scales. Secondly, it is proposed that shape representations at different scales of resolution be explicitly related, so that information can be passed between scales and computation at each scale can be kept local. Such a model for multi-scale computation is desirable both to allow efficient computation and to accurately model human perceptions.
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A novel method that combines shape-based object recognition and image segmentation is proposed for shape retrieval from images. Given a shape prior represented in a multi-scale curvature form, the proposed method identifies the target objects in images by grouping oversegmented image regions. The problem is formulated in a unified probabilistic framework and solved by a stochastic Markov Chain Monte Carlo (MCMC) mechanism. By this means, object segmentation and recognition are accomplished simultaneously. Within each sampling move during the simulation process,probabilistic region grouping operations are influenced by both the image information and the shape similarity constraint. The latter constraint is measured by a partial shape matching process. A generalized parallel algorithm by Barbu and Zhu,combined with a large sampling jump and other implementation improvements, greatly speeds up the overall stochastic process. The proposed method supports the segmentation and recognition of multiple occluded objects in images. Experimental results are provided for both synthetic and real images.
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CONFIGR (CONtour FIgure GRound) is a computational model based on principles of biological vision that completes sparse and noisy image figures. Within an integrated vision/recognition system, CONFIGR posits an initial recognition stage which identifies figure pixels from spatially local input information. The resulting, and typically incomplete, figure is fed back to the “early vision” stage for long-range completion via filling-in. The reconstructed image is then re-presented to the recognition system for global functions such as object recognition. In the CONFIGR algorithm, the smallest independent image unit is the visible pixel, whose size defines a computational spatial scale. Once pixel size is fixed, the entire algorithm is fully determined, with no additional parameter choices. Multi-scale simulations illustrate the vision/recognition system. Open-source CONFIGR code is available online, but all examples can be derived analytically, and the design principles applied at each step are transparent. The model balances filling-in as figure against complementary filling-in as ground, which blocks spurious figure completions. Lobe computations occur on a subpixel spatial scale. Originally designed to fill-in missing contours in an incomplete image such as a dashed line, the same CONFIGR system connects and segments sparse dots, and unifies occluded objects from pieces locally identified as figure in the initial recognition stage. The model self-scales its completion distances, filling-in across gaps of any length, where unimpeded, while limiting connections among dense image-figure pixel groups that already have intrinsic form. Long-range image completion promises to play an important role in adaptive processors that reconstruct images from highly compressed video and still camera images.
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To investigate women’s help seeking behavior (HSB) following self discovery of a breast symptom and determine the associated influencing factors. A descriptive correlation design was used to ascertain the help seeking behavior (HSB) and the associated influencing factors of a sample of women (n = 449) with self discovered breast symptoms. The study was guided by the ‘Help Seeking Behaviour and Influencing Factors” conceptual framework (Facione et al., 2002; Meechan et al., 2003, 2002; Leventhal, Brissette and Leventhal, 2003 and O’Mahony and Hegarty, 2009b). Data was collected using a researcher developed multi-scale questionnaire package to ascertain women’s help seeking behavior on self discovery of a breast symptom and determine the factors most associated with HSB. Factors examined include: socio-demographics, knowledge and beliefs (regarding breast symptom; breast changes associated with breast cancer; use of alternative help seeking behaviours and presence or absence of a family history of breast cancer),emotional responses, social factors, health seeking habits and health service system utilization and help seeking behavior. A convenience sample (n = 449 was obtained by the researcher from amongst women attending the breast clinics of two large urban hospitals within the Republic of Ireland. All participants had self-discovered breast symptoms and no previous history of breast cancer. The study identified that while the majority of women (69.9%; n=314) sought help within one month, 30.1% (n=135) delayed help seeking for more than one month following self discovery of their breast symptom. The factors most significantly associated with HSB were the presenting symptom of ‘nipple indrawn/changes’ (p = 0.005), ‘ignoring the symptom and hoping it would go away’ (p < 0.001), the emotional response of being ‘afraid@ on symptom discovery (p = 0.005) and the perception/belief in longer symptom duration (p = 0.023). It was found that women who presented with an indrawn/changed nipple were more likely to delay (OR = 4.81) as were women who ‘ignored the symptoms and hoped it would go away’ (OR = 10.717). Additionally, the longer women perceived that their symptom would last, they more likely they were to delay (OR = 1.18). Conversely, being afraid following symptom discovery was associated with less delay (OR = 0.37; p=0.005). This study provides further insight into the HSB of women who self discovered breast symptoms. It highlights the complexity of the help seeking process, indicating that is not a linear event but is influenced by multiple factors which can have a significant impact on the outcomes in terms of whether women delay or seek help promptly. The study further demonstrates that delayed HSB persists amongst women with self discovered breast symptoms. This has important implications for continued emphasis on the promotion of breast awareness, prompt help seeking for self discovered breast symptoms and early detection and treatment of breast cancer, amongst women of all ages.
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Thin film dielectrics based on titanium, zirconium or hafnium oxides are being introduced to increase the permittivity of insulating layers in transistors for micro/nanoelectronics and memory devices. Atomic layer deposition (ALD) is the process of choice for fabricating these films, as it allows for high control of composition and thickness in thin, conformal films which can be deposited on substrates with high aspect-ratio features. The success of this method depends crucially on the chemical properties of the precursor molecules. A successful ALD precursor should be volatile, stable in the gas-phase, but reactive on the substrate and growing surface, leading to inert by-products. In recent years, many different ALD precursors for metal oxides have been developed, but many of them suffer from low thermal stability. Much promise is shown by group 4 metal precursors that contain cyclopentadienyl (Cp = C5H5-xRx) ligands. One of the main advantages of Cp precursors is their thermal stability. In this work ab initio calculations were carried out at the level of density functional theory (DFT) on a range of heteroleptic metallocenes [M(Cp)4-n(L)n], M = Hf/Zr/Ti, L = Me and OMe, in order to find mechanistic reasons for their observed behaviour during ALD. Based on optimized monomer structures, reactivity is analyzed with respect to ligand elimination. The order in which different ligands are eliminated during ALD follows their energetics which was in agreement with experimental measurements. Titanocene-derived precursors, TiCp*(OMe)3, do not yield TiO2 films in atomic layer deposition (ALD) with water, while Ti(OMe)4 does. DFT was used to model the ALD reaction sequence and find the reason for the difference in growth behaviour. Both precursors adsorb initially via hydrogen-bonding. The simulations reveal that the Cp* ligand of TiCp*(OMe)3 lowers the Lewis acidity of the Ti centre and prevents its coordination to surface O (densification) during both of the ALD pulses. Blocking this step hindered further ALD reactions and for that reason no ALD growth is observed from TiCp*(OMe)3 and water. The thermal stability in the gas phase of Ti, Zr and Hf precursors that contain cyclopentadienyl ligands was also considered. The reaction that was found using DFT is an intramolecular α-H transfer that produces an alkylidene complex. The analysis shows that thermal stabilities of complexes of the type MCp2(CH3)2 increase down group 4 (M = Ti, Zr and Hf) due to an increase in the HOMO-LUMO band gap of the reactants, which itself increases with the electrophilicity of the metal. The reverse reaction of α-hydrogen abstraction in ZrCp2Me2 is 1,2-addition reaction of a C-H bond to a Zr=C bond. The same mechanism is investigated to determine if it operates for 1,2 addition of the tBu C-H across Hf=N in a corresponding Hf dimer complex. The aim of this work is to understand orbital interactions, how bonds break and how new bonds form, and in what state hydrogen is transferred during the reaction. Calculations reveal two synchronous and concerted electron transfers within a four-membered cyclic transition state in the plane between the cyclopentadienyl rings, one π(M=X)-to-σ(M-C) involving metal d orbitals and the other σ(C-H)-to-σ(X-H) mediating the transfer of neutral H, where X = C or N. The reaction of the hafnium dimer complex with CO that was studied for the purpose of understanding C-H bond activation has another interesting application, namely the cleavage of an N-N bond and resulting N-C bond formation. Analysis of the orbital plots reveals repulsion between the occupied orbitals on CO and the N-N unit where CO approaches along the N-N axis. The repulsions along the N-N axis are minimized by instead forming an asymmetrical intermediate in which CO first coordinates to one Hf and then to N. This breaks the symmetry of the N-N unit and the resultant mixing of MOs allows σ(NN) to be polarized, localizing electrons on the more distant N. This allowed σ(CO) and π(CO) donation to N and back-donation of π*(Hf2N2) to CO. Improved understanding of the chemistry of metal complexes can be gained from atomic-scale modelling and this provides valuable information for the design of new ALD precursors. The information gained from the model decomposition pathway can be additionally used to understand the chemistry of molecules in the ALD process as well as in catalytic systems.
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This study selected six geographically-similar villages with traditional and alternative cultivation methods (two groups of three, one traditional and two alternatives) in two counties of Henan Province, China—a representative area of the Huang-huai-hai Plain representing traditional rural China. Soil heavy metal concentrations, floral and faunal biodiversity, and socio-economic data were recorded. Heavy metal concentrations of surface soils from three sites in each village were analysed using Inductively Coupled Plasma Mass Spectrometry (ICP-MS, chromium, nickel, copper, cadmium, and lead) and Atomic Absorption Spectrophotometer (AAS, zinc). The floral biodiversity of four land-use types was recorded following the Braun-Blanquet coverage-abundance method using 0.5×0.5m quadrats. The faunal biodiversity of two representative farmland plots was recorded using 0.3×0.3m quadrats at four 0.1m layers. The socio-economic data were recorded through face-to-face interviews of one hundred randomly selected households at each village. Results demonstrate different cultivation methods lead to different impact on above variables. Traditional cultivation led to lower heavy metal concentrations; both alternative managements were associated with massive agrochemical input causing heavy metal pollution in farmlands. Floral distribution was significantly affected by village factors. Diverse cultivation supported high floral biodiversity through multi-scale heterogeneous landscapes containing niches and habitats. Faunal distribution was also significantly affected by village factor nested within soil depth. Different faunal groups responded differently, with Acari being taxonomically diverse and Collembola high in densities. Increase in manual labour and crop number in villages using alternative cultivation may positively affect biodiversity. The results point to the conservation potential of diverse cultivation methods in traditional rural China and other regions under social and political reforms, where traditional agriculture is changing to unified, large-scale mechanized agriculture. This study serves as a baseline for conservation in small-holding agricultural areas of China, and points to the necessity of further studies at larger and longer scales.
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Dilute bismide alloys, containing small fractions of bismuth (Bi), have recently attracted interest due to their potential for applications in a range of semiconductor devices. Experiments have revealed that dilute bismide alloys such as GaBixAs1−x, in which a small fraction x of the atoms in the III-V semiconductor GaAs are replaced by Bi, exhibit a number of unusual and unique properties. For example, the band gap energy (E g) decreases rapidly with increasing Bi composition x, by up to 90 meV per % Bi replacing As in the alloy. This band gap reduction is accompanied by a strong increase in the spin-orbit-splitting energy (ΔSO) with increasing x, and both E g and ΔSO are characterised by strong, composition-dependent bowing. The existence of a ΔSO > E g regime in the GaBixAs1−x alloy has been demonstrated for x ≳10%, a band structure condition which is promising for the development of highly efficient, temperature stable semiconductor lasers that could lead to large energy savings in future optical communication networks. In addition to their potential for specific applications, dilute bismide alloys have also attracted interest from a fundamental perspective due to their unique properties. In this thesis we develop the theory of the electronic and optical properties of dilute bismide alloys. By adopting a multi-scale approach encompassing atomistic calculations of the electronic structure using the semi-empirical tight-binding method, as well as continuum calculations based on the k•p method, we develop a fundamental understanding of this unusual class of semiconductor alloys and identify general material properties which are promising for applications in semiconductor optoelectronic and photovoltaic devices. By performing detailed supercell calculations on both ordered and disordered alloys we explicitly demonstrate that Bi atoms act as isovalent impurities when incorporated in dilute quantities in III-V (In)GaAs(P) materials, strongly perturbing the electronic structure of the valence band. We identify and quantify the causes and consequences of the unusual electronic properties of GaBixAs1−x and related alloys, and our analysis is reinforced throughout by a series of detailed comparisons to the results of experimental measurements. Our k•p models of the band structure of GaBixAs1−x and related alloys, which we derive directly from detailed atomistic calculations, are ideally suited to the study of dilute bismide-based devices. We focus in the latter part of the thesis on calculations of the electronic and optical properties of dilute bismide quantum well lasers. In addition to developing an understanding of the effects of Bi incorporation on the operational characteristics of semiconductor lasers, we also present calculations which have been used explicitly in designing and optimising the first generation of GaBixAs1−x-based devices.