海相页岩TOC地震定量预测技术及其应用——以四川盆地焦石坝地区为例

总有机碳含量(TOC)是评价页岩生烃能力和页岩油气藏的一个重要指标,目前国内外利用地震资料直接定量预测TOC的报道很少,因此,有必要对地震预测TOC的方法作进一步的研究。为此,以四川盆地焦石坝地区为例,从岩心实测TOC出发,通过TOC与地球物理参数交会分析,寻找到TOC敏感地球物理参数——密度,并建立密度与TOC之间的最佳拟合方程,得到计算总有机碳含量的经验公式;结合叠前地震反演获得的密度体便可计算出TOC数据体,从而达到定量预测页岩TOC的目的。将改进的预测方法应用于四川盆地焦石坝地区海相页岩气勘探,结果表明:①利用叠前同时反演直接求得的密度体避免了累计误差,稳定性好,多解性少,结果可靠,为精细定量预测TOC提供了基础保证;②预测的TOC与实测结果吻合程度高,相对误差较小。结论认为,该技术在四川盆地海相页岩气勘探中具有广阔的应用前景。     

Perturbation sensitivity analysis of azimuth estimation of the acoustic source for the planar microphone array

Aiming at the requirements of quantitative analysis of the array scheme and positioning performance of a practical compact acoustic detection node system, the upper bound of the far-field azimuth estimation error for an arbitrary small-size planar array is derived and the four elements of the corresponding perturbation sensitivity factor with explicit physical significance are determined. It is proved that the perturbation sensitivity of the source direction-finding algorithm to the time difference of arrival (TDOA) estimates between microphones can be lowered obviously by means of increasing the number of distinct microphone pairs as well as employing spatially uniform distribution of array elements. Simulation results demonstrate that this study provides a quantitative approach to evaluating and comparing the azimuth estimation performance of different planar arrays.     

LDPE装置循环水节约实例研究

文中详细介绍了在高压低密度聚乙烯（LDPE）装置中用热水罐外排污水替代紧急放空塔循环水溢流的做法,探索了节水降耗、清洁生产的经验。     

A novel automatic suspicious mass regions identification using Havrda & Charvat entropy and Otsu's N thresholding

Mass detection is a very important process for breast cancer diagnosis and computer aided systems. It can be very complex when the mass is small or invisible because of dense breast tissue. Therefore, the extraction of suspicious mass region can be very challenging. This paper proposes a novel segmentation algorithm to identify mass candidate regions in mammograms. The proposed system includes three parts: breast region and pectoral muscle segmentation, image enhancement and suspicious mass regions identification. The first two parts have been examined in previous studies. In this study, we focused on suspicious mass regions identification using a combination of Havrda & Charvat entropy method and Otsu's N thresholding method. An open access Mammographic Image Analysis Society (MIAS) database, which contains 59 masses, was used for the study. The proposed system obtained a 93% sensitivity rate for suspicious mass regions identification in 56 abnormal and 40 normal images.     

Tensor-based methods for blind spatial signature estimation under arbitrary and unknown source covariance structure

Spatial signature estimation is a problem encountered in several applications in signal processing such as mobile communications, sonar, radar, astronomy and seismology. In this paper, we propose higher-order tensor methods to solve the blind spatial signature estimation problem using planar arrays. By assuming that sources' powers vary between successive time blocks, we recast the spatial and spatiotemporal covariance models for the received data as third-order PARATUCK2 and fourth-order Tucker4 tensor decompositions, respectively. Firstly, by exploiting the multilinear algebraic structure of the proposed tensor models, new iterative algorithms are formulated to blindly estimate the spatial signatures. Secondly, in order to achieve a better spatial resolution, we propose an expanded form of spatial smoothing that returns extra spatial dimensions in comparison with the traditional approaches. Additionally, by exploiting the higher-order structure of the resulting expanded tensor model, a multilinear noise reduction preprocessing step is proposed via higher-order singular value decomposition. We show that the increase on the tensor order provides a more efficient denoising, and consequently a better performance compared to existing spatial smoothing techniques. Finally, a solution based on a multi-stage Khatri–Rao factorization procedure is incorporated as the final stage of our proposed estimators. Our results demonstrate that the proposed tensor methods yield more accurate spatial signature estimates than competing approaches while operating in a challenging scenario where the source covariance structure is unknown and arbitrary (non-diagonal), which is actually the case when sample covariances are computed from a limited number of snapshots.     

A novel method of blind signal detection using the distribution of the bin values of the power spectrum density and the moving average

Signal detection in additive white Gaussian noise (AWGN) is one of the long-term developments driving the evolution of many different fields of science and technology, with important applications in telecommunications, medicine and astronomy. In this paper, we propose a novel method of blind signal detection that does not require knowledge of the noise variance. This method uses the distribution of the bin values of the power spectrum density of the received signal and the moving average (MAV). The simulation results for radio pulses show that the spectrum sensing performance is significantly improved under the proposed scheme compared to that of known blind signal detection methods.     

Energetic distribution of interface states extracted from photo-conductance of organic thin film transistors

In this paper, a new method is introduced to obtain the energetic distribution of the interface states (density of states; DOS) extracted from the photo-conductance of organic thin film transistors (OTFTs) which exhibit varied transfer characteristics under illumination with different photon energies. The method was applied to pentacene OTFTs, and the results were compared with existing data. The major findings were not only the existence of the well-known peaks of DOS at 1.82 eV (free exciton of pentacene), and at 1.49 eV (extrinsic exciton due to dihydropentacene) but also new peaks were found at 1.25 eV, 1.29 eV, 1.31 eV, and 1.35 eV in the mid-gap. The new peaks were strongly enhanced under exposure to oxygen, and thus seem to be related to the defects associated with the presence of oxygen.     

A probabilistic framework for next best view estimation in a cluttered environment

In this article, we present an information gain-based variant of the next best view problem for occluded environment. Our proposed method utilizes a belief model of the unobserved space to estimate the expected information gain of each possible viewpoint. More precise, this belief model allows a more precise estimation of the visibility of occluded space and with that a more accurate prediction of the potential information gain of new viewing positions. We present experimental evaluation on a robotic platform for active data acquisition, however due to the generality of our approach it also applies to a wide variety of 3D reconstruction problems. With the evaluation done in simulation and on a real robotic platform, exploring and acquiring data from different environments we demonstrate the generality and usefulness of our approach for next best view estimation and autonomous data acquisition.     

Rib stability:A way forward for safe coal extraction in India

Ensuring rib stability during pillar extraction is of prime importance in bord and pillar(BP) method of underground coal mining with caving. Rib stability has been assessed here by way of assessing factor of safety(FOS), a ratio of the strength of rib to stress on it. Earlier formulations for rib stability when applied to case studies gave very low FOS value suggesting significant ground control problems, which were contrary to the field observations. This has necessitated the need to revisit the concept of rib stability. The stress coming on the rib is estimated with the use of numerical modeling technique using the FLAC~(3D) software. The methodology of assessing rib-stability with the help of suggested rib-strength formulation has been validated at eight Indian coal mines. The outcome of this study finds relevance and importance in ensuring underground coal liquidation with improved safety and conservation.