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A.R. Dudaev (NSU, IPGG SB RAS), A.Y. Sobolev (IPGG SB RAS, NSU, NSTU), V.N. Glinskikh* (IPGG SB RAS, NSU, NSTU) SUMMARYWe have developed a prototype of cloud computing software for logging-while-drilling and geosteering. For the first time ever, during the development of software for addressing the problems of petroleum geophysics, we apply software solutions based on state-of-the-art IT-technologies in the field of cloud computing, namely, cross-platform scalable distributed computing. We have created a client-server application written in JavaScript, which stores all user data in MongoDB. The application allows a user to send input data through message queues for processing by means of computing applications that run in a virtual environment. Processing results are displayed on a web page. We have tested the software under discussion on real practical data from the interval of a subhorizontal well from one of the Latitude Priob oil fields. When drilling highly deviated boreholes, an effective well targeting in the productive part of a reservoir is essential. Successful Russian experience of studying oil and gas wells is demonstrated by using the first Russian telemetry system for logging-while-drilling, intended for drilling wells with horizontal completions. At the present time, it is necessary to develop a multifunctional automated computer system for processing, visualization and interpretation of the data obtained with the complex under consideration.

Accuracy of the horizontal well placement in the target reservoir becomes essential for efficient oilfield development. Geosteering of a well with a complex trajectory is performed using real-time geophysical data obtained while drilling. The presented work is devoted to the development of a new software for horizontal oil and gas wells geosteering. Algorithms based on logging data correlation and electromagnetic logging data numerical inversion methods are used for well placement. The developed application is based on web-technologies and has a client-server architecture. To optimize the resource-intensive calculations execution time, high-performance cloud computing is used.