Применение онтологий для решения задач геофизики

The paper covers an intelligent support system that allows to describe and construct solutions to various scientific problems. In this study, in particular, we consider geophysical problems. This system is being developed at the Institute of Computational Mathematics and Mathematical Geophysics of the Russian Academy of Sciences (ICMMG SB RAS) and Institute of Informatics System of the Russian Academy of Sciences (IIS SB RAS). The system contains a knowledge base, the core of which is a set of several interconnected ontologies such as the ontology of supercomputer architectures, the ontology of algorithms and methods. Ontology can be viewed as a set of concepts and how those concepts are linked. As the result, the authors present an ontological description of two geophysical problems via the means of the intelligent support system: 1) the seismic wavefield simulation and 2) the reconstruction of a seismic image through pre-stack time or depth migration. For a better visual understanding of the system described and the results obtained, the paper also contains several schematic diagrams and images. В статье рассматривается система интеллектуальной поддержки, позволяющая описывать и выстраивать решения различных научных задач. В данной работе рассматриваются геофизические задачи. Система разрабатывается в Институте вычислительной математики и математической геофизики Российской академии наук (ИВМГ СО РАН) и Институте систем информатики Российской академии наук (ИИС СО РАН). Система содержит базу знаний, ядром которой является набор из нескольких взаимосвязанных онтологий, таких как онтология суперкомпьютерных архитектур, онтология алгоритмов и методов. Онтологию можно рассматривать как набор концепций и связей между ними. В результате авторы представляют онтологическое описание двух геофизических задач с помощью средств системы интеллектуальной поддержки: 1) моделирование сейсмического волнового поля и 2) реконструкция сейсмического изображения посредством временной или глубинной миграции до суммирования. Для лучшего визуального понимания описанной системы и полученных результатов в работе также есть несколько схематических диаграмм и изображений.

An optimised one-way wave migration method for complex media with arbitrarily varying velocity based on eigen-decomposition

The classical one-way generalised screen propagator (GSP) and Fourier finite-difference (FFD) schemes have limitations in imaging large angles in complex media with substantial lateral variations in wave velocity. Some improvements to the classical one-way wave scheme have been proposed with optimised methods. However, the performance of these methods in imaging complex media remains unsatisfying. To overcome this issue, a new strategy for wavefield extrapolation based on the eigenvalue and eigenvector decomposition of the Helmholtz operator is presented herein. In this method, the square root operator is calculated after the decomposition of the Helmholtz operator at the product of the eigenvalues and eigenvectors. Then, Euler transformation is applied using the best polynomial approximation of the trigonometric function based on the infinite norm, and the propagator for one-way wave migration is calculated. According to this scheme, a one-way operator can be computed more accurately with a lower-order expansion. The imaging performance of this scheme was compared with that of the classical GSP, FFD and the recently developed full-wave-equation depth migration (FWDM) schemes. The impulse responses in media with arbitrary velocity inhomogeneity demonstrate that the proposed migration scheme performs better at large angles than the classical GSP scheme. The wavefronts calculated in the dipping and salt dome models illustrate that this scheme can provide a precise wavefield calculation. The applications of the Marmousi model further demonstrate that the proposed approach can achieve better-migrated results in imaging small-scale and complex structures, especially in media with steep-dipping faults.

3D reflection seismic imaging of the iron-oxide deposits in the Ludvika mining area (Sweden) using a focusing pre-stack depth migration approach

We present the pre-stack depth imaging results for a case study of 3D reflection seismic exploration at the Blötberget iron-oxide mining site belonging to the Bergslagen mineral district in central Sweden. The goal of this case study is to directly image the ore-bearing units and to map its possible extension down to greater depths than known from existing boreholes. Therefore, we applied a tailored pre-processing workflow as well as two different seismic imaging approaches, Kirchhoff pre-stack depth migration and Fresnel Volume Migration (FVM). Both imaging techniques deliver a well resolved 3D image of the deposit and its host rock, where the FVM image yields a significantly better image quality compared to the KPSDM image. We were able to unravel distinct reflection horizons, which are linked to known mineralisation and provide insights on lateral and depth extent of the deposits beyond their known extension from borehole data. A comparison of the known mineralization and the image show a good agreement of the position and the shape of the imaged reflectors caused by the mineralization. Furthermore, the images show a reflector, which is interpreted to be a fault intersecting the mineralisation and which can be linked to the surface geology. The depth imaging results can serve as the basis for further investigations, drillings and follow-up mine planning at the Blötberget mining site.

Case Study: Improving the quality of the seismic reflection image for a Fujian mineral exploration data set with offset-domain common-image gathers

Seismic reflection is a proven and effective method commonly used during the exploration of deep mineral deposits in Fujian, China. In seismic data processing, rugged depth migration based on wave-equation migration can play a key role in handling surface fluctuations and complex underground structures. Because wave-equation migration in the shot domain cannot output offset-domain common-image gathers in a straightforward way, the use of traditional tools for updating the velocity model and improving image quality can be quite challenging. To overcome this problem, we employed the attribute migration method. This worked by sorting the migrated stack results for every single-shot gather into the offset gathers. The value of the offset that corresponded to each image point was obtained from the ratio of the original migration results to the offset-modulated shot-data migration results. A Gaussian function was proposed to map every image point to a certain range of offsets. This helped improve the signal-to-noise ratio, which was especially important in handing low quality seismic data obtained during mineral exploration. Residual velocity analysis was applied to these gathers to update the velocity model and improve image quality. The offset-domain common-image gathers were also used directly for real mineral exploration seismic data with rugged depth migration. After several iterations of migration and updating the velocity, the proposed procedure achieved an image quality better than the one obtained with the initial velocity model. The results can help with the interpretation of thrust faults and deep deposit exploration.