The Impact of Model Based Offset Scaling Technique on the Amplitude Variation with Offset Responses from 3D Seismic Data Acquired from the Tano Basin, Offshore Ghana

Amplitudes have been found to be a function of incident angle and offset. Hence data required to test for amplitude variation with angle or offset needs to have its amplitudes for all offsets preserved and not stacked. Amplitude Variation with Offset (AVO)/Amplitude Variation with Angle (AVA) is necessary to account for information in the offset/angle parameter (mode converted S-wave and P-wave velocities). Since amplitudes are a function of the converted S- and P-waves, it is important to investigate the dependence of amplitudes on the elastic (P- and S-waves) parameters from the seismic data. By modelling these effects for different reservoir fluids via fluid substitution, various AVO geobody classes present along the well and in the entire seismic cube can be observed. AVO analysis was performed on one test well (Well_1) and 3D pre-stack angle gathers from the Tano Basin. The analysis involves creating a synthetic model to infer the effect of offset scaling techniques on amplitude responses in the Tano basin as compared to the effect of unscaled seismic data. The spectral balance process was performed to match the amplitude spectra of all angle stacks to that of the mid (26°) stack on the test lines. The process had an effect primarily on the far (34° - 40°) stacks. The frequency content of these stacks slightly increased to match that of the near and mid stacks. In offset scaling process, the root mean square (RMS) amplitude comparison between the synthetic and seismic suggests that the amplitude of the far traces should be reduced relative to the nears by up to 16%. However, the exact scaler values depend on the time window considered. This suggests that the amplitude scaling with offset delivered from seismic processing is only approximately correct and needs to be checked with well synthetics and adjusted accordingly prior to use for AVO studies. The AVO attribute volumes generated were better at resolving anomalies on spectrally balanced and offset scaled data than data delivered from conventional processing. A typical class II AVO anomaly is seen along the test well from the cross-plot analysis and AVO attribute cube which indicates an oil filled reservoir.

Nonparametric Statistical Feature Scaling Based Quadratic Regressive Convolution Deep Neural Network for Software Fault Prediction

The development of defect prediction plays a significant role in improving software quality. Such predictions are used to identify defective modules before the testing and to minimize the time and cost. The software with defects negatively impacts operational costs and finally affects customer satisfaction. Numerous approaches exist to predict software defects. However, the timely and accurate software bugs are the major challenging issues. To improve the timely and accurate software defect prediction, a novel technique called Nonparametric Statistical feature scaled QuAdratic regressive convolution Deep nEural Network (SQADEN) is introduced. The proposed SQADEN technique mainly includes two major processes namely metric or feature selection and classification. First, the SQADEN uses the nonparametric statistical Torgerson–Gower scaling technique for identifying the relevant software metrics by measuring the similarity using the dice coefficient. The feature selection process is used to minimize the time complexity of software fault prediction. With the selected metrics, software fault perdition with the help of the Quadratic Censored regressive convolution deep neural network-based classification. The deep learning classifier analyzes the training and testing samples using the contingency correlation coefficient. The softstep activation function is used to provide the final fault prediction results. To minimize the error, the Nelder–Mead method is applied to solve non-linear least-squares problems. Finally, accurate classification results with a minimum error are obtained at the output layer. Experimental evaluation is carried out with different quantitative metrics such as accuracy, precision, recall, F-measure, and time complexity. The analyzed results demonstrate the superior performance of our proposed SQADEN technique with maximum accuracy, sensitivity and specificity by 3%, 3%, 2% and 3% and minimum time and space by 13% and 15% when compared with the two state-of-the-art methods.

Progress on the Use of Stable Isotope Techniques in Catchment Hydrograph Separation: A Review

Hydrograph separation is a fundamental catchment descriptor,revealing information about sources of water in runoff generation processes. The water isotopes are ideal tracers in studying hydrological processes since the isotope fractionation produces a natural labeling effect within the hydrologic cycle. The water isotope technique has become one of effective means for investigating complex hydrologic system on a catchment scale. This paper reviews the progress on the use of stable water isotope techniques in catchment hydrograph separation in last decades. Also,the isotope mixing model for hydrograph separation and its uncertainties are explained in detail. In future research,there are three hot issues in the use of isotopic hydrograph separation（ IHS） ： integrating new approaches into IHS,calibration and verification of IHS model and IHS application in large river basins.

Maintenance of Tropical Cyclone Bill (1988) after Landfall

The mechanism for the maintenance of Tropical Cyclone Bill （1988） after landfall is investigated through a numerical simulation. The role of the large-scale environmental flow is examined using a scale separation technique, which isolates the tropical cyclone from the environmental flow. The results show that Bill was embedded in a deep easterly-southeasterly environmental flow to the north-northeast of a large-scale depression and to the southwest of the western Pacific subtropical high. The depression had a quasi-barotropic structure in the mid-lower troposphere and propagated northwestward with a speed similar to the northwestward movement of Bill. The moisture budgets associated with both the large-scale and the tropical cyclone scale motions indicate that persistent low-level easterly-southeasterly flow transported moisture into the inner core of the tropical cyclone. The low-level circulation of the tropical cyclone transported moisture into the eyewall to support eyewall convection, providing sufficient latent heating to counteract energy loss due to surface friction and causing the storm to weaken relatively slowly after landfall. Warming and a westward extension of the upper-level easterly flow led to westward propagation of the environmental flow in the mid-lower troposphere. As a result, Bill was persistently embedded in an environment of deep easterly flow with high humidity, weak vertical wind shear, convergence in the lower troposphere, and divergence in the upper troposphere. These conditions are favorable for both significant intensification prior to landfall and maintenance of the tropical cyclone after landfall.

THE SYMMETRIC POSITIVE SOLUTIONS OF 2n-ORDER BOUNDARY VALUE PROBLEMS ON TIME SCALES

In this paper, we are concerned with the symmetric positive solutions of a 2n-order boundary value problems on time scales. By using induction principle,the symmetric form of the Green＇s function is established. In order to construct a necessary and sufficient condition for the existence result, the method of iterative technique will be used. As an application, an example is given to illustrate our main result.