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In the process of transforming seismic data into vital information about subsurface rock and fluid properties, seismic inversion is a crucial tool. This motivates researchers to develop several seismic inversion methods and software. Since the seismic data are band-limited, seismic inversion is ill-posed, and the results are not unique, each method tries to use initial information and assumes expected conditions for the results. Satisfying a general low-frequency trend and having a smooth model or step-wise results are some of the assumptions that these methods add as constraints to the inversion process. Well-logs, geological studies, and models from other geophysical methods can add important insight into the seismic inversion results. We introduce an objective function that applies the clustering properties of the prior information as a constraint to the seismic inversion process as well as other common constraints. An optimal solution to the objective function is explained. We applied the Gustafson-Kessel fuzzy C-means as one of the possible clustering methods for clustering term. Numerical synthetic and real data examples show the efficiency of the proposed method in the inversion of seismic data. In addition to the acoustic impedance model, the proposed seismic inversion method creates reliable deconvolved and denoised versions of the input seismic data. Additionally, the membership section output from the inversion process shows high potential in the seismic interpretation. Further research on selecting an optimum fuzziness, updating wavelet, and the potential of the membership sections to track horizons, distinguish sequences and layers, identify possible contents of the layers, and other possible applications are recommended. [ABSTRACT FROM AUTHOR]

The pixel vertex detector (PXD) is an essential part of the Belle II detector recording particle positions. Data from the PXD and other sensors allow us to reconstruct particle tracks and decay vertices. The effiect of background hits on track reconstruction is simulated by adding measured or simulated background hit patterns to the hits produced by simulated signal particles. This model requires a large set of statistically independent PXD background noise samples to avoid a systematic bias of reconstructed tracks. However, data from the fine-grained PXD requires a substantial amount of storage. As an efficient way of producing background noise, we explore the idea of an on-demand PXD background generator using conditional Generative Adversarial Networks (GANs), adapted by the number of PXD sensors in order to both increase the image fidelity and produce sensor-dependent PXD hitmaps.

To match the statistical precision due to the large dataset that Belle II is expected to collect, simulations that accurately describe real data are required. The effect of beam background must be considered and can be taken into account with overlaying random trigger data, but its large size is a technical challenge. This problem can be mitigated by generating beam background data with generative adversarial networks. A proof of principle is shown for the background data recorded by the pixel vertex detector.

The current paper deals with a new use of fuzzy logic in the domain of seismic zonation methodologies with a case study in Meybod, Iran. Determining the risk function of an earthquake is an important issue and for the complete solution, the seismic specialist shall necessarily find the soil response and present an appropriate zonation output to the civil engineer. For tackling this problem, a fuzzy clustering method has been applied in acquiring microtremor data more specifically in the city of Meybod. Dataset is divided into four subsets based on its intrinsic complexity by GK fuzzy clustering. Features in this classification practice are including the coordinates, the output dominant frequency of H/V method and the related amplitudes. Euclidian distance matrix norm is constructed to detect hyper ellipsoidal clusters with different orientations (shape and size) in the dataset. The cluster means are then refreshed in an iterative manner so as to identify the uniform seismic answer into the isolated gatherings. We used this method to determine the four divided seismicity regions with different range of frequencies. In addition, various type of soil structures in Meybod city with high and weak risky area have been cleared and can be applied in hazard and earthquake engineering projects. This approach was significantly well matched with clay and silt dominant on soil observed in the boreholes. Finally zonation maps based on this new method is provided. [ABSTRACT FROM AUTHOR]

Sequence stratigraphy is a key step in interpretation of the seismic reflection data. It was originally developed by seismic specialists, and then the usage of high-resolution well logs and core data was taken into consideration in its implementation. The current paper aims in performing sequence stratigraphy using three-dimensional seismic data, well logs (gamma ray, sonic, porosity, density, water saturation and resistivity) on Hendijan oil field located in the northwest part of Persian Gulf., Depth interval of the study that covered from Asmari formation to Kajhdumi formation was determined by using well markers. Based on the depositional sequence model that consists of four systems tracts and with the help of Wheeler diagram, observed patterns have been used in seismic reflection terminations to identify sequence boundaries, systems tracts and internal stratigraphic surfaces in the sequences. Additionally, well logs were interpreted for two objectives. Firstly, variation patterns of well logs were used to validate sequences, their components and internal sequence stratigraphic surfaces. Secondly, the well log data was used for characterization of systems tracts with the log values. This paper addresses the constraints patterns for such stratigraphic problems in seismic interpretation with the aim of achieving better chrono-stratigraphic reasoning system with previous studies in Iran. [ABSTRACT FROM AUTHOR]