The process of scattering the acoustical wave on an obstacle at any moment of time may be considered as an interaction of two interconnected vectors: the particle velocity vector of the incident wave and generated by scattering the vector of the reflected or scattered wave. Mathematical method of the inversion the wave front in time, based on the first order differential equations allows investigating such interaction more carefully. Proposed Vector Pair Reverse Time Migration method demands large storage memory and high computer performance but provides the new opportunities for studying the environment. Presentation Date: Monday, October 15, 2018 Start Time: 1:50:00 PM Location: Poster Station 21 Presentation Type: Poster

Purpose: A new method for positioning a group of unmanned aerial vehicles (UAVs) that collect data from seismic modules via wireless communication is proposed. Design/methodology/approach: The developed method of positioning a group of UAVs includes five main stages: constructing a heat map of Wi-Fi signal propagation, identifying points of maximum signal strength on the heat map, optimal target distribution between UAVs in the group, constructing optimal trajectories considering the complexity of the terrain and resolving conflict situations. The proposed algorithms were implemented programmatically in the ROS2 system in C++, then their operation was simulated in the Gazebo simulation environment. Findings: Simulation of flights of a group of 4, 7 and 10 UAVs in areas of 5 × 5 and 10 × 10 sq km with the presence of 60 and 180 peaks respectively with a height from −50 to −63 dBm, using the developed method made it possible to solve the problem of collecting data from seismic sensors via a wireless communication channel in 34, 18 and 11 min for each group in 5 × 5 area and 83, 37, 32 min for 10 × 10 area. The comparison with other methods showed scalability and performance improvements by an average of 6–18%, depending on the number of UAVs in the group. Originality/value: The main advantage of this method is the formation of global reciprocating trajectories of a group of UAVs, covering the coordinates of all seismic sensors in the minimum possible time and the iterative construction of local reciprocating trajectories in the process of flying around each sensor.

A new method for predicting lithofacies, gas, fluid and brine zones, and zones with abnormally high reservoir pressure, as well as the petrophysical properties of rocks using artificial intelligence methods, based on a family of new seismic attributes of the RTH (reverse time holography) method and well drilling data is proposed. The main difference between RTH attributes and conventional ones obtained by migration transformation is their voxel nature and hyperattribution. This turned out to be a key advantage of the new approach to solving problems of geological prediction by artificial intelligence methods. The results of applying a new method for processing and interpreting modern 3D seismic data, as well as geological prediction based on it for the area of intense brine occurrence at the Kovykta gas condensate field, are presented.