叠后地震数据的自相似分段和多重分形

地质分层是石油工程中的一项重要的基础工作。叠后地震数据和测井数据的时间序列能反映地下分层。由于地层的非均质性和不同成因特性,它们表现出具有复杂模式的多重分形特性。在多重分形结构中,序列中的任何部分都具有不同的赫斯特(Hurst)指数,可反映其性质,并可用于分区检测。时间序列是井眼附近的叠后地震道和测井数据。自相似自回归外生(SAE)模型是一种改进的方法,它可以将自相似的叠后地震和测井段置于具有相同岩性的地层之间,这样就可以通过SAE模型对地震数据进行分层识别。

Stresses induced by post-tensioned anchor in jointed rock mass

A new analytical study on stresses around a post-tensioned anchor in rocks with two perpendicular joint sets is presented. The assumptions of orthotropic elastic rock with plane strain conditions are made in derivation of the formulations. A tri-linear bond-slip constitutive law is used for modeling the tendon-grout interface behavior and debonding of this interface. The bearing plate width is also considered in the analysis. The obtained solutions are in the integral forms and numerical techniques that have been used for evaluation. In the illustrative example given, the major principal stress is compressive in the anchor free zone and compressive stress concentrations of 815 k Pa and 727 k Pa(for the anchor load of 300 k N) are observed under the bearing plate and the bond length proximal end, respectively. However, large values of tensile stresses with the maximum of-434 k Pa are formed at the bond length distal end. The results obtained using the proposed solution are compared very those of numerical method(FEM).

Thermo-hydro-mechanical modeling of fault discontinuities using zero-thickness interface element

In this paper,a coupled thermo-hydro-mechanical(THM)simulation in a faulted deformable porous medium is presented.This model involves solving the mass conservation,linear momentum balance,and energy balance equations which are derived from the Biot’s consolidation theory.Fluid pore pressure,solid displacement,and temperature are chosen as initial variables in these equations,and the finite element method in combination with the interface element is used for spatial discretization of continuous and discontinuities(fault)parts of the medium to solve the equations.The main purpose of this study is providing precise formulations,applicability,and ability of the triple-node zero-thickness interface element in THM modeling of faults.It should be noted that the system of equations is solved using a computer code written in Matlab program.In order to verify the developed method,simulations of index problems such as Mandel’s problem,and coupled modeling of a faulted porous medium and a faulted aquifer are presented.The modeling results obtained from the developed method show a very good agreement with those by other modeling methods,which indicates its accuracy.

Self-similar segmentation and multifractality of post-stack seismic data

Layering detection is an important step in petroleum engineering.Time series of post-stack seismic data and wire-line log data belong to subsurface layering.They exhibit multifractal properties with complex patterns because of the heterogeneity and different genetic properties in the earth layers.In a multifractal configuration,any piece of a series has a distinct Hurst exponent that reflects its nature and can be used for zone detection.Time series are post-stack seismic traces and wire-line log data near the well-bores.Self-similar Autoregressive Exogenous(SAE)model is a modified method which can place self-similar post-stack seismic and wire-line log segments across layers with the same lithology.The results satisfy the capability of layering identification from seismic data by SAE model.

SINGULAR SPECTRUM ANALYSIS:METHODOLOGY AND APPLICATION TO ECONOMICS DATA

This paper describes the methodology of singular spectrum analysis (SSA) and demonstratethat it is a powerful method of time series analysis and forecasting,particulary for economic time series.The authors consider the application of SSA to the analysis and forecasting of the Iranian nationalaccounts data as provided by the Central Bank of the Islamic Republic of Iran.

Banking with blockchain-ed big data

Blockchain is disrupting the banking industry and contributing to the increased big data in banking.However,there exists a gap in research and development into blockchain-ed big data in banking from an academic perspective,and this gap is expected to have a significant negative impact on the adoption and development of blockchain technology for banking.In hope of motivating more active engagement by academics,researchers and bankers alike,we present the most comprehensive review of the impact of blockchain in banking to date by summarizing the opportunities and challenges from a bankers perspective.In addition,we also discuss the impact that big data from blockchain will have on banking data analytics in future and show the increasing importance of filtering and signal extraction for the banking industry.Whilst there is evidence of selected banks adopting blockchain technology in isolation or small groups,we find the need for extensive research and development into several aspects of banking with blockchain to overcome the challenges which are currently hindering its adoption in banking across the globe.

rVlathematical approaches in studying bicoid gene

It is widely believed that in Drosophila melanogaster the pattern of Bicoid protein gradient plays a crucial role in the segmentation stage of embryo development. As a result of its fundamental role, modelling the Bicoid gradient has become increasingly popular for researchers from many different areas of study. The aim of this paper is to bring together the most prominent studies on this maternal gene and discuss how existing techniques for modelling this gradient have evolved over the years.

Bicoid Signal Extraction with a Selection of Parametric and Nonparametric Signal Processing Techniques

The maternal segmentation coordinate gene bicoid plays a significant role during Drosophila embryogenesis. The gradient of Bicoid, the protein encoded by this gene, determines most aspects of head and thorax development. This paper seeks to explore the applicability of a variety of signal processing techniques at extracting bicoid expression signal, and whether these methods can outperform the current model. We evaluate the use of six different powerful and widely-used models representing both parametric and nonparametric signal processing techniques to determine the most efficient method for signal extraetion in bicoid. The results are evaluated using both real and simulated data. Our findings show that the Singular Spectrum Analysis technique proposed in this paper outperforms the synthesis diffusion degradation model for filtering the noisy protein profile of bicoid whilst the exponential smoothing technique was found to be the next best alternative followed by the autoregressive integrated moving average.