2015 Issue №10

Algorithms for constructing three-dimensional models of microseismic activity fields are described. The first approach is based on voxel models and involves the construction of polygonal surfaces of interpolated parameters of microseismic events. The second approach uses a triangulation algorithm based on the Delaunay criterion and α-shapes method. Software developed on the basis of the proposed algorithms, offers advanced graphical tools for the analysis and interpretation of microseismic multiparameter data

Results of passive microseismic monitoring of water injection into one of the wells of the carbonate deposits are presented. The maps of the spatial distribution of sources have prepared and the analysis of the dynamic parameters of microseismic events together with graphs of pressure and injection volumes has done. The possibility of operational control of the process of flooding is shown on the example of Northern Truva.

The structure of Vendian sediments and overlying usolskaya formation sediments of the Lower Cambrian is described. The Vendian sediment (oskobinskaya formation) contaisn gas condensate deposit. The  sediments of vanavarskaya formation, carbonate Vendian and osinskiy horizon are perspective to search for hydrocarbons in the Ilbokichskiy license area. Therefore, learning the structure of Vendian and osinskiy horizon sediments is one of the most important factors in hydrocarbon deposits prediction.

One of the problems of interpretation of seismic data is that they are often measured on an irregular grid with large distances between the sources and receivers, which affects the outcome of processing. The article discusses the possibility of using the procedure RTD (Reverse Time Datuming) [1-4] to ob-tain the wave field with a dense and regular geometry of sources and receivers at some depth. The results of numerical testing are presented.

A Fast Iterative Method (FIM) for eikonal equations [1] are convenient and optimal in two-dimensional and small three-dimensional models. But it takes a lot of time and random access memory for big three-dimensional models. This article describes the time and memory optimization of this method for big 3d models. The results of simulations are presented

A technique for recognition of shapes of bodies in a 3D point cloud is de-scribed. At the first step cloud clustering is conducted using the criterion of maximum distance between the points to identify the bodies being determined. Then proceeding to voxel presentation is being done. Existence of a tetrahe-dron with its points in cloud points and size-limited sides for which the voxel being tested is internal is treated as a criterion of belongment of voxel to a body. A fast algorithm for voxel tetrahedron filling is developed and used for optimization. The work is a part of software for micro-seismic monitoring data processing.